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name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option value="msc_class">MSC classification</option><option value="report_num">Report number</option><option value="paper_id">arXiv identifier</option><option value="doi">DOI</option><option value="orcid">ORCID</option><option value="license">License (URI)</option><option value="author_id">arXiv author ID</option><option value="help">Help pages</option><option value="full_text">Full text</option></select> <input id="query" name="query" type="text" value="Akter, M"> <ul id="abstracts"><li><input checked id="abstracts-0" name="abstracts" type="radio" value="show"> <label for="abstracts-0">Show abstracts</label></li><li><input id="abstracts-1" name="abstracts" type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.13615">arXiv:2411.13615</a> <span> [<a href="https://arxiv.org/pdf/2411.13615">pdf</a>, <a href="https://arxiv.org/format/2411.13615">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Statistical Finance">q-fin.ST</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> A Deep Learning Approach to Predict the Fall [of Price] of Cryptocurrency Long Before its Actual Fall </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Meem%2C+A+T">Anika Tahsin Meem</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst. Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Depto%2C+D+S">Deponker Sarker Depto</a>, <a href="/search/cs?searchtype=author&query=Mahdy%2C+M+R+C">M. R. C. Mahdy</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.13615v1-abstract-short" style="display: inline;"> In modern times, the cryptocurrency market is one of the world's most rapidly rising financial markets. The cryptocurrency market is regarded to be more volatile and illiquid than traditional markets such as equities, foreign exchange, and commodities. The risk of this market creates an uncertain condition among the investors. The purpose of this research is to predict the magnitude of the risk fa… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13615v1-abstract-full').style.display = 'inline'; document.getElementById('2411.13615v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.13615v1-abstract-full" style="display: none;"> In modern times, the cryptocurrency market is one of the world's most rapidly rising financial markets. The cryptocurrency market is regarded to be more volatile and illiquid than traditional markets such as equities, foreign exchange, and commodities. The risk of this market creates an uncertain condition among the investors. The purpose of this research is to predict the magnitude of the risk factor of the cryptocurrency market. Risk factor is also called volatility. Our approach will assist people who invest in the cryptocurrency market by overcoming the problems and difficulties they experience. Our approach starts with calculating the risk factor of the cryptocurrency market from the existing parameters. In twenty elements of the cryptocurrency market, the risk factor has been predicted using different machine learning algorithms such as CNN, LSTM, BiLSTM, and GRU. All of the models have been applied to the calculated risk factor parameter. A new model has been developed to predict better than the existing models. Our proposed model gives the highest RMSE value of 1.3229 and the lowest RMSE value of 0.0089. Following our model, it will be easier for investors to trade in complicated and challenging financial assets like bitcoin, Ethereum, dogecoin, etc. Where the other existing models, the highest RMSE was 14.5092, and the lower was 0.02769. So, the proposed model performs much better than models with proper generalization. Using our approach, it will be easier for investors to trade in complicated and challenging financial assets like Bitcoin, Ethereum, and Dogecoin. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13615v1-abstract-full').style.display = 'none'; document.getElementById('2411.13615v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">22 pages, 3 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2410.16507">arXiv:2410.16507</a> <span> [<a href="https://arxiv.org/pdf/2410.16507">pdf</a>, <a href="https://arxiv.org/format/2410.16507">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> </div> </div> <p class="title is-5 mathjax"> How the Internet Facilitates Adverse Childhood Experiences for Youth Who Self-Identify as in Need of Services </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Oguine%2C+O+C">Ozioma C. Oguine</a>, <a href="/search/cs?searchtype=author&query=Park%2C+J+K">Jinkyung Katie Park</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Olesk%2C+J">Johanna Olesk</a>, <a href="/search/cs?searchtype=author&query=Alluhidan%2C+A">Abdulmalik Alluhidan</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a>, <a href="/search/cs?searchtype=author&query=Badillo-Urquiola%2C+K">Karla Badillo-Urquiola</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2410.16507v1-abstract-short" style="display: inline;"> Youth implicated in the child welfare and juvenile justice systems, as well as those with an incarcerated parent, are considered the most vulnerable Children in Need of Services (CHINS). We identified 1,160 of these at-risk youth (ages 13-17) who sought support via an online peer support platform to understand their adverse childhood experiences and explore how the internet played a role in provid… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.16507v1-abstract-full').style.display = 'inline'; document.getElementById('2410.16507v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2410.16507v1-abstract-full" style="display: none;"> Youth implicated in the child welfare and juvenile justice systems, as well as those with an incarcerated parent, are considered the most vulnerable Children in Need of Services (CHINS). We identified 1,160 of these at-risk youth (ages 13-17) who sought support via an online peer support platform to understand their adverse childhood experiences and explore how the internet played a role in providing an outlet for support, as well as potentially facilitating risks. We first analyzed posts from 1,160 youth who self-identified as CHINS while sharing about their adverse experiences. Then, we retrieved all 239,929 posts by these users to identify salient topics within their support-seeking posts: 1) Urges to self-harm due to social drama, 2) desire for social connection, 3) struggles with family, and 4) substance use and sexual risks. We found that the internet often helped facilitate these problems; for example, the desperation for social connection often led to meeting unsafe people online, causing additional trauma. Family members and other unsafe people used the internet to perpetrate cyberabuse, while CHINS themselves leveraged online channels to engage in illegal and risky behavior. Our study calls for tailored support systems that address the unique needs of CHINS to promote safe online spaces and foster resilience to break the cycle of adversity. Empowering CHINS requires amplifying their voices and acknowledging the challenges they face as a result of their adverse childhood experiences. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.16507v1-abstract-full').style.display = 'none'; document.getElementById('2410.16507v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2410.14536">arXiv:2410.14536</a> <span> [<a href="https://arxiv.org/pdf/2410.14536">pdf</a>, <a href="https://arxiv.org/format/2410.14536">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> A Hybrid Feature Fusion Deep Learning Framework for Leukemia Cancer Detection in Microscopic Blood Sample Using Gated Recurrent Unit and Uncertainty Quantification </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Maksuda Akter</a>, <a href="/search/cs?searchtype=author&query=Khatun%2C+R">Rabea Khatun</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+M+M">Md Manowarul Islam</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2410.14536v1-abstract-short" style="display: inline;"> Acute lymphoblastic leukemia (ALL) is the most malignant form of leukemia and the most common cancer in adults and children. Traditionally, leukemia is diagnosed by analyzing blood and bone marrow smears under a microscope, with additional cytochemical tests for confirmation. However, these methods are expensive, time consuming, and highly dependent on expert knowledge. In recent years, deep learn… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.14536v1-abstract-full').style.display = 'inline'; document.getElementById('2410.14536v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2410.14536v1-abstract-full" style="display: none;"> Acute lymphoblastic leukemia (ALL) is the most malignant form of leukemia and the most common cancer in adults and children. Traditionally, leukemia is diagnosed by analyzing blood and bone marrow smears under a microscope, with additional cytochemical tests for confirmation. However, these methods are expensive, time consuming, and highly dependent on expert knowledge. In recent years, deep learning, particularly Convolutional Neural Networks (CNNs), has provided advanced methods for classifying microscopic smear images, aiding in the detection of leukemic cells. These approaches are quick, cost effective, and not subject to human bias. However, most methods lack the ability to quantify uncertainty, which could lead to critical misdiagnoses. In this research, hybrid deep learning models (InceptionV3-GRU, EfficientNetB3-GRU, MobileNetV2-GRU) were implemented to classify ALL. Bayesian optimization was used to fine tune the model's hyperparameters and improve its performance. Additionally, Deep Ensemble uncertainty quantification was applied to address uncertainty during leukemia image classification. The proposed models were trained on the publicly available datasets ALL-IDB1 and ALL-IDB2. Their results were then aggregated at the score level using the sum rule. The parallel architecture used in these models offers a high level of confidence in differentiating between ALL and non-ALL cases. The proposed method achieved a remarkable detection accuracy rate of 100% on the ALL-IDB1 dataset, 98.07% on the ALL-IDB2 dataset, and 98.64% on the combined dataset, demonstrating its potential for accurate and reliable leukemia diagnosis. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.14536v1-abstract-full').style.display = 'none'; document.getElementById('2410.14536v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2410.14489">arXiv:2410.14489</a> <span> [<a href="https://arxiv.org/pdf/2410.14489">pdf</a>, <a href="https://arxiv.org/format/2410.14489">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> An Integrated Deep Learning Model for Skin Cancer Detection Using Hybrid Feature Fusion Technique </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Maksuda Akter</a>, <a href="/search/cs?searchtype=author&query=Khatun%2C+R">Rabea Khatun</a>, <a href="/search/cs?searchtype=author&query=Talukder%2C+M+A">Md. Alamin Talukder</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+M+M">Md. Manowarul Islam</a>, <a href="/search/cs?searchtype=author&query=Uddin%2C+M+A">Md. Ashraf Uddin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2410.14489v2-abstract-short" style="display: inline;"> Skin cancer is a serious and potentially fatal disease caused by DNA damage. Early detection significantly increases survival rates, making accurate diagnosis crucial. In this groundbreaking study, we present a hybrid framework based on Deep Learning (DL) that achieves precise classification of benign and malignant skin lesions. Our approach begins with dataset preprocessing to enhance classificat… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.14489v2-abstract-full').style.display = 'inline'; document.getElementById('2410.14489v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2410.14489v2-abstract-full" style="display: none;"> Skin cancer is a serious and potentially fatal disease caused by DNA damage. Early detection significantly increases survival rates, making accurate diagnosis crucial. In this groundbreaking study, we present a hybrid framework based on Deep Learning (DL) that achieves precise classification of benign and malignant skin lesions. Our approach begins with dataset preprocessing to enhance classification accuracy, followed by training two separate pre-trained DL models, InceptionV3 and DenseNet121. By fusing the results of each model using the weighted sum rule, our system achieves exceptional accuracy rates. Specifically, we achieve a 92.27% detection accuracy rate, 92.33% sensitivity, 92.22% specificity, 90.81% precision, and 91.57% F1-score, outperforming existing models and demonstrating the robustness and trustworthiness of our hybrid approach. Our study represents a significant advance in skin cancer diagnosis and provides a promising foundation for further research in the field. With the potential to save countless lives through earlier detection, our hybrid deep-learning approach is a game-changer in the fight against skin cancer. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.14489v2-abstract-full').style.display = 'none'; document.getElementById('2410.14489v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 29 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 18 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2410.14433">arXiv:2410.14433</a> <span> [<a href="https://arxiv.org/pdf/2410.14433">pdf</a>, <a href="https://arxiv.org/format/2410.14433">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Genomics">q-bio.GN</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> A Bioinformatic Approach Validated Utilizing Machine Learning Algorithms to Identify Relevant Biomarkers and Crucial Pathways in Gallbladder Cancer </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Khatun%2C+R">Rabea Khatun</a>, <a href="/search/cs?searchtype=author&query=Tasnim%2C+W">Wahia Tasnim</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Maksuda Akter</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+M+M">Md Manowarul Islam</a>, <a href="/search/cs?searchtype=author&query=Uddin%2C+M+A">Md. Ashraf Uddin</a>, <a href="/search/cs?searchtype=author&query=Mahmud%2C+M+Z">Md. Zulfiker Mahmud</a>, <a href="/search/cs?searchtype=author&query=Das%2C+S+C">Saurav Chandra Das</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2410.14433v1-abstract-short" style="display: inline;"> Gallbladder cancer (GBC) is the most frequent cause of disease among biliary tract neoplasms. Identifying the molecular mechanisms and biomarkers linked to GBC progression has been a significant challenge in scientific research. Few recent studies have explored the roles of biomarkers in GBC. Our study aimed to identify biomarkers in GBC using machine learning (ML) and bioinformatics techniques. W… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.14433v1-abstract-full').style.display = 'inline'; document.getElementById('2410.14433v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2410.14433v1-abstract-full" style="display: none;"> Gallbladder cancer (GBC) is the most frequent cause of disease among biliary tract neoplasms. Identifying the molecular mechanisms and biomarkers linked to GBC progression has been a significant challenge in scientific research. Few recent studies have explored the roles of biomarkers in GBC. Our study aimed to identify biomarkers in GBC using machine learning (ML) and bioinformatics techniques. We compared GBC tumor samples with normal samples to identify differentially expressed genes (DEGs) from two microarray datasets (GSE100363, GSE139682) obtained from the NCBI GEO database. A total of 146 DEGs were found, with 39 up-regulated and 107 down-regulated genes. Functional enrichment analysis of these DEGs was performed using Gene Ontology (GO) terms and REACTOME pathways through DAVID. The protein-protein interaction network was constructed using the STRING database. To identify hub genes, we applied three ranking algorithms: Degree, MNC, and Closeness Centrality. The intersection of hub genes from these algorithms yielded 11 hub genes. Simultaneously, two feature selection methods (Pearson correlation and recursive feature elimination) were used to identify significant gene subsets. We then developed ML models using SVM and RF on the GSE100363 dataset, with validation on GSE139682, to determine the gene subset that best distinguishes GBC samples. The hub genes outperformed the other gene subsets. Finally, NTRK2, COL14A1, SCN4B, ATP1A2, SLC17A7, SLIT3, COL7A1, CLDN4, CLEC3B, ADCYAP1R1, and MFAP4 were identified as crucial genes, with SLIT3, COL7A1, and CLDN4 being strongly linked to GBC development and prediction. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.14433v1-abstract-full').style.display = 'none'; document.getElementById('2410.14433v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.02364">arXiv:2409.02364</a> <span> [<a href="https://arxiv.org/pdf/2409.02364">pdf</a>, <a href="https://arxiv.org/format/2409.02364">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> Examining Caregiving Roles to Differentiate the Effects of Using a Mobile App for Community Oversight for Privacy and Security </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Kropczynski%2C+J">Jess Kropczynski</a>, <a href="/search/cs?searchtype=author&query=Lipford%2C+H">Heather Lipford</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2409.02364v1-abstract-short" style="display: inline;"> We conducted a 4-week field study with 101 smartphone users who self-organized into 22 small groups of family, friends, and neighbors to use ``CO-oPS,'' a mobile app for co-managing mobile privacy and security. We differentiated between those who provided oversight (i.e., caregivers) and those who did not (i.e., caregivees) to examine differential effects on their experiences and behaviors while u… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.02364v1-abstract-full').style.display = 'inline'; document.getElementById('2409.02364v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.02364v1-abstract-full" style="display: none;"> We conducted a 4-week field study with 101 smartphone users who self-organized into 22 small groups of family, friends, and neighbors to use ``CO-oPS,'' a mobile app for co-managing mobile privacy and security. We differentiated between those who provided oversight (i.e., caregivers) and those who did not (i.e., caregivees) to examine differential effects on their experiences and behaviors while using CO-oPS. Caregivers reported higher power use, community trust, belonging, collective efficacy, and self-efficacy than caregivees. Both groups' self-efficacy and collective efficacy for mobile privacy and security increased after using CO-oPS. However, this increase was significantly stronger for caregivees. Our research demonstrates how community-based approaches can benefit people who need additional help managing their digital privacy and security. We provide recommendations to support community-based oversight for managing privacy and security within communities of different roles and skills. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.02364v1-abstract-full').style.display = 'none'; document.getElementById('2409.02364v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Proceedings on Privacy Enhancing Technologies 2025 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.02358">arXiv:2409.02358</a> <span> [<a href="https://arxiv.org/pdf/2409.02358">pdf</a>, <a href="https://arxiv.org/format/2409.02358">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1145/3686961">10.1145/3686961 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Teen Talk: The Good, the Bad, and the Neutral of Adolescent Social Media Use </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Alluhidan%2C+A">Abdulmalik Alluhidan</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Alsoubai%2C+A">Ashwaq Alsoubai</a>, <a href="/search/cs?searchtype=author&query=Park%2C+J">Jinkyung Park</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2409.02358v1-abstract-short" style="display: inline;"> The debate on whether social media has a net positive or negative effect on youth is ongoing. Therefore, we conducted a thematic analysis on 2,061 posts made by 1,038 adolescents aged 15-17 on an online peer-support platform to investigate the ways in which these teens discussed popular social media platforms in their posts and to identify differences in their experiences across platforms. Our fin… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.02358v1-abstract-full').style.display = 'inline'; document.getElementById('2409.02358v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.02358v1-abstract-full" style="display: none;"> The debate on whether social media has a net positive or negative effect on youth is ongoing. Therefore, we conducted a thematic analysis on 2,061 posts made by 1,038 adolescents aged 15-17 on an online peer-support platform to investigate the ways in which these teens discussed popular social media platforms in their posts and to identify differences in their experiences across platforms. Our findings revealed four main emergent themes for the ways in which social media was discussed: 1) Sharing negative experiences or outcomes of social media use (58%, n = 1,095), 2) Attempts to connect with others (45%, n = 922), 3) Highlighting the positive side of social media use (20%, n = 409), and 4) Seeking information (20%, n = 491). Overall, while sharing about negative experiences was more prominent, teens also discussed balanced perspectives of connection-seeking, positive experiences, and information support on social media that should not be discounted. Moreover, we found statistical significance for how these experiences differed across social media platforms. For instance, teens were most likely to seek romantic relationships on Snapchat and self-promote on YouTube. Meanwhile, Instagram was mentioned most frequently for body shaming, and Facebook was the most commonly discussed platform for privacy violations (mostly from parents). The key takeaway from our study is that the benefits and drawbacks of teens' social media usage can co-exist and net effects (positive or negative) can vary across different teens across various contexts. As such, we advocate for mitigating the negative experiences and outcomes of social media use as voiced by teens, to improve, rather than limit or restrict, their overall social media experience. We do this by taking an affordance perspective that aims to promote the digital well-being and online safety of youth "by design." <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.02358v1-abstract-full').style.display = 'none'; document.getElementById('2409.02358v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">36 pages</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2406.07716">arXiv:2406.07716</a> <span> [<a href="https://arxiv.org/pdf/2406.07716">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Unleashing the Power of Transfer Learning Model for Sophisticated Insect Detection: Revolutionizing Insect Classification </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Hasan%2C+M+M">Md. Mahmudul Hasan</a>, <a href="/search/cs?searchtype=author&query=Shaqib%2C+S">SM Shaqib</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Ms. Sharmin Akter</a>, <a href="/search/cs?searchtype=author&query=Alam%2C+R">Rabiul Alam</a>, <a href="/search/cs?searchtype=author&query=Haque%2C+A+U">Afraz Ul Haque</a>, <a href="/search/cs?searchtype=author&query=khushbu%2C+S+a">Shahrun akter khushbu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2406.07716v1-abstract-short" style="display: inline;"> The purpose of the Insect Detection System for Crop and Plant Health is to keep an eye out for and identify insect infestations in farming areas. By utilizing cutting-edge technology like computer vision and machine learning, the system seeks to identify hazardous insects early and accurately. This would enable prompt response to save crops and maintain optimal plant health. The Method of this stu… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.07716v1-abstract-full').style.display = 'inline'; document.getElementById('2406.07716v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2406.07716v1-abstract-full" style="display: none;"> The purpose of the Insect Detection System for Crop and Plant Health is to keep an eye out for and identify insect infestations in farming areas. By utilizing cutting-edge technology like computer vision and machine learning, the system seeks to identify hazardous insects early and accurately. This would enable prompt response to save crops and maintain optimal plant health. The Method of this study includes Data Acquisition, Preprocessing, Data splitting, Model Implementation and Model evaluation. Different models like MobileNetV2, ResNet152V2, Xecption, Custom CNN was used in this study. In order to categorize insect photos, a Convolutional Neural Network (CNN) based on the ResNet152V2 architecture is constructed and evaluated in this work. Achieving 99% training accuracy and 97% testing accuracy, ResNet152V2 demonstrates superior performance among four implemented models. The results highlight its potential for real-world applications in insect classification and entomology studies, emphasizing efficiency and accuracy. To ensure food security and sustain agricultural output globally, finding insects is crucial. Cutting-edge technology, such as ResNet152V2 models, greatly influence automating and improving the accuracy of insect identification. Efficient insect detection not only minimizes crop losses but also enhances agricultural productivity, contributing to sustainable food production. This underscores the pivotal role of technology in addressing challenges related to global food security. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.07716v1-abstract-full').style.display = 'none'; document.getElementById('2406.07716v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2404.10258">arXiv:2404.10258</a> <span> [<a href="https://arxiv.org/pdf/2404.10258">pdf</a>, <a href="https://arxiv.org/format/2404.10258">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> CO-oPS: A Mobile App for Community Oversight of Privacy and Security </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Alghamdi%2C+L">Leena Alghamdi</a>, <a href="/search/cs?searchtype=author&query=Gillespie%2C+D">Dylan Gillespie</a>, <a href="/search/cs?searchtype=author&query=Miazi%2C+N">Nazmus Miazi</a>, <a href="/search/cs?searchtype=author&query=Kropczynski%2C+J">Jess Kropczynski</a>, <a href="/search/cs?searchtype=author&query=Lipford%2C+H">Heather Lipford</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2404.10258v1-abstract-short" style="display: inline;"> Smartphone users install numerous mobile apps that require access to different information from their devices. Much of this information is very sensitive, and users often struggle to manage these accesses due to their lack of tech expertise and knowledge regarding mobile privacy. Thus, they often seek help from others to make decisions regarding their mobile privacy and security. We embedded these… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.10258v1-abstract-full').style.display = 'inline'; document.getElementById('2404.10258v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2404.10258v1-abstract-full" style="display: none;"> Smartphone users install numerous mobile apps that require access to different information from their devices. Much of this information is very sensitive, and users often struggle to manage these accesses due to their lack of tech expertise and knowledge regarding mobile privacy. Thus, they often seek help from others to make decisions regarding their mobile privacy and security. We embedded these social processes in a mobile app titled "CO-oPS'' ("Community Oversight for Privacy and Security"). CO-oPS allows trusted community members to review one another's apps installed and permissions granted to those apps. Community members can provide feedback to one another regarding their privacy behaviors. Users are also allowed to hide some of their mobile apps that they do not like others to see, ensuring their personal privacy. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.10258v1-abstract-full').style.display = 'none'; document.getElementById('2404.10258v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2404.03165">arXiv:2404.03165</a> <span> [<a href="https://arxiv.org/pdf/2404.03165">pdf</a>, <a href="https://arxiv.org/ps/2404.03165">ps</a>, <a href="https://arxiv.org/format/2404.03165">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> Towards Collaborative Family-Centered Design for Online Safety, Privacy and Security </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Agha%2C+Z">Zainab Agha</a>, <a href="/search/cs?searchtype=author&query=Alsoubai%2C+A">Ashwaq Alsoubai</a>, <a href="/search/cs?searchtype=author&query=Ali%2C+N">Naima Ali</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2404.03165v2-abstract-short" style="display: inline;"> Traditional online safety technologies often overly restrict teens and invade their privacy, while parents often lack knowledge regarding their digital privacy. As such, prior researchers have called for more collaborative approaches on adolescent online safety and networked privacy. In this paper, we propose family-centered approaches to foster parent-teen collaboration in ensuring their mobile p… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.03165v2-abstract-full').style.display = 'inline'; document.getElementById('2404.03165v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2404.03165v2-abstract-full" style="display: none;"> Traditional online safety technologies often overly restrict teens and invade their privacy, while parents often lack knowledge regarding their digital privacy. As such, prior researchers have called for more collaborative approaches on adolescent online safety and networked privacy. In this paper, we propose family-centered approaches to foster parent-teen collaboration in ensuring their mobile privacy and online safety while respecting individual privacy, to enhance open discussion and teens' self-regulation. However, challenges such as power imbalances and conflicts with family values arise when implementing such approaches, making parent-teen collaboration difficult. Therefore, attending the family-centered design workshop will provide an invaluable opportunity for us to discuss these challenges and identify best research practices for the future of collaborative online safety and privacy within families. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.03165v2-abstract-full').style.display = 'none'; document.getElementById('2404.03165v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 3 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.17008">arXiv:2402.17008</a> <span> [<a href="https://arxiv.org/pdf/2402.17008">pdf</a>, <a href="https://arxiv.org/format/2402.17008">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> Benchmarking LLMs on the Semantic Overlap Summarization Task </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Salvador%2C+J">John Salvador</a>, <a href="/search/cs?searchtype=author&query=Bansal%2C+N">Naman Bansal</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mousumi Akter</a>, <a href="/search/cs?searchtype=author&query=Sarkar%2C+S">Souvika Sarkar</a>, <a href="/search/cs?searchtype=author&query=Das%2C+A">Anupam Das</a>, <a href="/search/cs?searchtype=author&query=Karmaker%2C+S+K">Shubhra Kanti Karmaker</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2402.17008v1-abstract-short" style="display: inline;"> Semantic Overlap Summarization (SOS) is a constrained multi-document summarization task, where the constraint is to capture the common/overlapping information between two alternative narratives. While recent advancements in Large Language Models (LLMs) have achieved superior performance in numerous summarization tasks, a benchmarking study of the SOS task using LLMs is yet to be performed. As LLMs… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.17008v1-abstract-full').style.display = 'inline'; document.getElementById('2402.17008v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.17008v1-abstract-full" style="display: none;"> Semantic Overlap Summarization (SOS) is a constrained multi-document summarization task, where the constraint is to capture the common/overlapping information between two alternative narratives. While recent advancements in Large Language Models (LLMs) have achieved superior performance in numerous summarization tasks, a benchmarking study of the SOS task using LLMs is yet to be performed. As LLMs' responses are sensitive to slight variations in prompt design, a major challenge in conducting such a benchmarking study is to systematically explore a variety of prompts before drawing a reliable conclusion. Fortunately, very recently, the TELeR taxonomy has been proposed which can be used to design and explore various prompts for LLMs. Using this TELeR taxonomy and 15 popular LLMs, this paper comprehensively evaluates LLMs on the SOS Task, assessing their ability to summarize overlapping information from multiple alternative narratives. For evaluation, we report well-established metrics like ROUGE, BERTscore, and SEM-F1$ on two different datasets of alternative narratives. We conclude the paper by analyzing the strengths and limitations of various LLMs in terms of their capabilities in capturing overlapping information The code and datasets used to conduct this study are available at https://anonymous.4open.science/r/llm_eval-E16D. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.17008v1-abstract-full').style.display = 'none'; document.getElementById('2402.17008v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 February, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.15589">arXiv:2402.15589</a> <span> [<a href="https://arxiv.org/pdf/2402.15589">pdf</a>, <a href="https://arxiv.org/format/2402.15589">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Neural and Evolutionary Computing">cs.NE</span> </div> </div> <p class="title is-5 mathjax"> Prompting LLMs to Compose Meta-Review Drafts from Peer-Review Narratives of Scholarly Manuscripts </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Santu%2C+S+K+K">Shubhra Kanti Karmaker Santu</a>, <a href="/search/cs?searchtype=author&query=Sinha%2C+S+K">Sanjeev Kumar Sinha</a>, <a href="/search/cs?searchtype=author&query=Bansal%2C+N">Naman Bansal</a>, <a href="/search/cs?searchtype=author&query=Knipper%2C+A">Alex Knipper</a>, <a href="/search/cs?searchtype=author&query=Sarkar%2C+S">Souvika Sarkar</a>, <a href="/search/cs?searchtype=author&query=Salvador%2C+J">John Salvador</a>, <a href="/search/cs?searchtype=author&query=Mahajan%2C+Y">Yash Mahajan</a>, <a href="/search/cs?searchtype=author&query=Guttikonda%2C+S">Sri Guttikonda</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mousumi Akter</a>, <a href="/search/cs?searchtype=author&query=Freestone%2C+M">Matthew Freestone</a>, <a href="/search/cs?searchtype=author&query=Williams%2C+M+C">Matthew C. Williams Jr</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2402.15589v1-abstract-short" style="display: inline;"> One of the most important yet onerous tasks in the academic peer-reviewing process is composing meta-reviews, which involves understanding the core contributions, strengths, and weaknesses of a scholarly manuscript based on peer-review narratives from multiple experts and then summarizing those multiple experts' perspectives into a concise holistic overview. Given the latest major developments in… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.15589v1-abstract-full').style.display = 'inline'; document.getElementById('2402.15589v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.15589v1-abstract-full" style="display: none;"> One of the most important yet onerous tasks in the academic peer-reviewing process is composing meta-reviews, which involves understanding the core contributions, strengths, and weaknesses of a scholarly manuscript based on peer-review narratives from multiple experts and then summarizing those multiple experts' perspectives into a concise holistic overview. Given the latest major developments in generative AI, especially Large Language Models (LLMs), it is very compelling to rigorously study the utility of LLMs in generating such meta-reviews in an academic peer-review setting. In this paper, we perform a case study with three popular LLMs, i.e., GPT-3.5, LLaMA2, and PaLM2, to automatically generate meta-reviews by prompting them with different types/levels of prompts based on the recently proposed TELeR taxonomy. Finally, we perform a detailed qualitative study of the meta-reviews generated by the LLMs and summarize our findings and recommendations for prompting LLMs for this complex task. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.15589v1-abstract-full').style.display = 'none'; document.getElementById('2402.15589v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 23 February, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> I.2.7 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.08974">arXiv:2402.08974</a> <span> [<a href="https://arxiv.org/pdf/2402.08974">pdf</a>, <a href="https://arxiv.org/format/2402.08974">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1145/3613904.3642509">10.1145/3613904.3642509 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Examining the Unique Online Risk Experiences and Mental Health Outcomes of LGBTQ+ versus Heterosexual Youth </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Tanni%2C+T">Tangila Tanni</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Anderson%2C+J">Joshua Anderson</a>, <a href="/search/cs?searchtype=author&query=Amon%2C+M">Mary Amon</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2402.08974v1-abstract-short" style="display: inline;"> We collected and analyzed Instagram direct messages (DMs) from 173 youth aged 13-21 (including 86 LGBTQ+ youth). We examined youth's risk-flagged social media trace data with their self-reported mental health outcomes to examine how the differing online experiences of LGBTQ+ youth compare with their heterosexual counterparts. We found that LGBTQ+ youth experienced significantly more high-risk onli… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.08974v1-abstract-full').style.display = 'inline'; document.getElementById('2402.08974v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.08974v1-abstract-full" style="display: none;"> We collected and analyzed Instagram direct messages (DMs) from 173 youth aged 13-21 (including 86 LGBTQ+ youth). We examined youth's risk-flagged social media trace data with their self-reported mental health outcomes to examine how the differing online experiences of LGBTQ+ youth compare with their heterosexual counterparts. We found that LGBTQ+ youth experienced significantly more high-risk online interactions compared to heterosexual youth. LGBTQ+ youth reported overall poorer mental health, with online harassment specifically amplifying Self-Harm and Injury. LGBTQ+ youth's mental well-being linked positively to sexual messages, unlike heterosexual youth. Qualitatively, we found that most of the risk-flagged messages of LGBTQ+ youth were sexually motivated; however, a silver lining was that they sought support for their sexual identity from peers on the platform. The study highlights the importance of tailored online safety and inclusive design for LGBTQ+ youth, with implications for CHI community advancements in fostering a supportive online environments. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.08974v1-abstract-full').style.display = 'none'; document.getElementById('2402.08974v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 February, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2311.16944">arXiv:2311.16944</a> <span> [<a href="https://arxiv.org/pdf/2311.16944">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> </div> </div> <p class="title is-5 mathjax"> Teaching DevOps Security Education with Hands-on Labware: Automated Detection of Security Weakness in Python </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Rodriguez-Cardenas%2C+J">Juanjose Rodriguez-Cardenas</a>, <a href="/search/cs?searchtype=author&query=Rahman%2C+M+M">Md Mostafizur Rahman</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Rahman%2C+A">Akond Rahman</a>, <a href="/search/cs?searchtype=author&query=Wu%2C+F">Fan Wu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2311.16944v2-abstract-short" style="display: inline;"> The field of DevOps security education necessitates innovative approaches to effectively address the ever-evolving challenges of cybersecurity. In adopting a student-centered ap-proach, there is the need for the design and development of a comprehensive set of hands-on learning modules. In this paper, we introduce hands-on learning modules that enable learners to be familiar with identifying known… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.16944v2-abstract-full').style.display = 'inline'; document.getElementById('2311.16944v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2311.16944v2-abstract-full" style="display: none;"> The field of DevOps security education necessitates innovative approaches to effectively address the ever-evolving challenges of cybersecurity. In adopting a student-centered ap-proach, there is the need for the design and development of a comprehensive set of hands-on learning modules. In this paper, we introduce hands-on learning modules that enable learners to be familiar with identifying known security weaknesses, based on taint tracking to accurately pinpoint vulnerable code. To cultivate an engaging and motivating learning environment, our hands-on approach includes a pre-lab, hands-on and post lab sections. They all provide introduction to specific DevOps topics and software security problems at hand, followed by practicing with real world code examples having security issues to detect them using tools. The initial evaluation results from a number of courses across multiple schools show that the hands-on modules are enhancing the interests among students on software security and cybersecurity, while preparing them to address DevOps security vulnerabilities. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.16944v2-abstract-full').style.display = 'none'; document.getElementById('2311.16944v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 14 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2309.04823">arXiv:2309.04823</a> <span> [<a href="https://arxiv.org/pdf/2309.04823">pdf</a>, <a href="https://arxiv.org/format/2309.04823">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> FaNS: a Facet-based Narrative Similarity Metric </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mousumi Akter</a>, <a href="/search/cs?searchtype=author&query=Santu%2C+S+K+K">Shubhra Kanti Karmaker Santu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2309.04823v2-abstract-short" style="display: inline;"> Similar Narrative Retrieval is a crucial task since narratives are essential for explaining and understanding events, and multiple related narratives often help to create a holistic view of the event of interest. To accurately identify semantically similar narratives, this paper proposes a novel narrative similarity metric called Facet-based Narrative Similarity (FaNS), based on the classic 5W1H f… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.04823v2-abstract-full').style.display = 'inline'; document.getElementById('2309.04823v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2309.04823v2-abstract-full" style="display: none;"> Similar Narrative Retrieval is a crucial task since narratives are essential for explaining and understanding events, and multiple related narratives often help to create a holistic view of the event of interest. To accurately identify semantically similar narratives, this paper proposes a novel narrative similarity metric called Facet-based Narrative Similarity (FaNS), based on the classic 5W1H facets (Who, What, When, Where, Why, and How), which are extracted by leveraging the state-of-the-art Large Language Models (LLMs). Unlike existing similarity metrics that only focus on overall lexical/semantic match, FaNS provides a more granular matching along six different facets independently and then combines them. To evaluate FaNS, we created a comprehensive dataset by collecting narratives from AllSides, a third-party news portal. Experimental results demonstrate that the FaNS metric exhibits a higher correlation (37\% higher) than traditional text similarity metrics that directly measure the lexical/semantic match between narratives, demonstrating its effectiveness in comparing the finer details between a pair of narratives. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.04823v2-abstract-full').style.display = 'none'; document.getElementById('2309.04823v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 March, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 9 September, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2308.09722">arXiv:2308.09722</a> <span> [<a href="https://arxiv.org/pdf/2308.09722">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Social and Information Networks">cs.SI</span> </div> </div> <p class="title is-5 mathjax"> A Trustable LSTM-Autoencoder Network for Cyberbullying Detection on Social Media Using Synthetic Data </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Cuzzocrea%2C+A">Alfredo Cuzzocrea</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2308.09722v1-abstract-short" style="display: inline;"> Social media cyberbullying has a detrimental effect on human life. As online social networking grows daily, the amount of hate speech also increases. Such terrible content can cause depression and actions related to suicide. This paper proposes a trustable LSTM-Autoencoder Network for cyberbullying detection on social media using synthetic data. We have demonstrated a cutting-edge method to addres… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.09722v1-abstract-full').style.display = 'inline'; document.getElementById('2308.09722v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2308.09722v1-abstract-full" style="display: none;"> Social media cyberbullying has a detrimental effect on human life. As online social networking grows daily, the amount of hate speech also increases. Such terrible content can cause depression and actions related to suicide. This paper proposes a trustable LSTM-Autoencoder Network for cyberbullying detection on social media using synthetic data. We have demonstrated a cutting-edge method to address data availability difficulties by producing machine-translated data. However, several languages such as Hindi and Bangla still lack adequate investigations due to a lack of datasets. We carried out experimental identification of aggressive comments on Hindi, Bangla, and English datasets using the proposed model and traditional models, including Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BiLSTM), LSTM-Autoencoder, Word2vec, Bidirectional Encoder Representations from Transformers (BERT), and Generative Pre-trained Transformer 2 (GPT-2) models. We employed evaluation metrics such as f1-score, accuracy, precision, and recall to assess the models performance. Our proposed model outperformed all the models on all datasets, achieving the highest accuracy of 95%. Our model achieves state-of-the-art results among all the previous works on the dataset we used in this paper. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.09722v1-abstract-full').style.display = 'none'; document.getElementById('2308.09722v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">arXiv admin note: text overlap with arXiv:2303.07484</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2308.02270">arXiv:2308.02270</a> <span> [<a href="https://arxiv.org/pdf/2308.02270">pdf</a>, <a href="https://arxiv.org/format/2308.02270">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> Redundancy Aware Multi-Reference Based Gainwise Evaluation of Extractive Summarization </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mousumi Akter</a>, <a href="/search/cs?searchtype=author&query=Karmaker%2C+S">Santu Karmaker</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2308.02270v2-abstract-short" style="display: inline;"> The ROUGE metric is commonly used to evaluate extractive summarization task, but it has been criticized for its lack of semantic awareness and its ignorance about the ranking quality of the extractive summarizer. Previous research has introduced a gain-based automated metric called Sem-nCG that addresses these issues, as it is both rank and semantic aware. However, it does not consider the amount… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.02270v2-abstract-full').style.display = 'inline'; document.getElementById('2308.02270v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2308.02270v2-abstract-full" style="display: none;"> The ROUGE metric is commonly used to evaluate extractive summarization task, but it has been criticized for its lack of semantic awareness and its ignorance about the ranking quality of the extractive summarizer. Previous research has introduced a gain-based automated metric called Sem-nCG that addresses these issues, as it is both rank and semantic aware. However, it does not consider the amount of redundancy present in a model summary and currently does not support evaluation with multiple reference summaries. It is essential to have a model summary that balances importance and diversity, but finding a metric that captures both of these aspects is challenging. In this paper, we propose a redundancy-aware Sem-nCG metric and demonstrate how the revised Sem-nCG metric can be used to evaluate model summaries against multiple references as well which was missing in previous research. Experimental results demonstrate that the revised Sem-nCG metric has a stronger correlation with human judgments compared to the previous Sem-nCG metric and traditional ROUGE and BERTScore metric for both single and multiple reference scenarios. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.02270v2-abstract-full').style.display = 'none'; document.getElementById('2308.02270v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 27 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 4 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Accepted to KNOVENS 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.09248">arXiv:2306.09248</a> <span> [<a href="https://arxiv.org/pdf/2306.09248">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> </div> </div> <p class="title is-5 mathjax"> Quantum Cryptography for Enhanced Network Security: A Comprehensive Survey of Research, Developments, and Future Directions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.09248v1-abstract-short" style="display: inline;"> With the ever-growing concern for internet security, the field of quantum cryptography emerges as a promising solution for enhancing the security of networking systems. In this paper, 20 notable papers from leading conferences and journals are reviewed and categorized based on their focus on various aspects of quantum cryptography, including key distribution, quantum bit commitment, post quantum c… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.09248v1-abstract-full').style.display = 'inline'; document.getElementById('2306.09248v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.09248v1-abstract-full" style="display: none;"> With the ever-growing concern for internet security, the field of quantum cryptography emerges as a promising solution for enhancing the security of networking systems. In this paper, 20 notable papers from leading conferences and journals are reviewed and categorized based on their focus on various aspects of quantum cryptography, including key distribution, quantum bit commitment, post quantum cryptography, and counterfactual quantum key distribution. The paper explores the motivations and challenges of employing quantum cryptography, addressing security and privacy concerns along with existing solutions. Secure key distribution, a critical component in ensuring the confidentiality and integrity of transmitted information over a network, is emphasized in the discussion. The survey examines the potential of quantum cryptography to enable secure key exchange between parties, even when faced with eavesdropping, and other applications of quantum cryptography. Additionally, the paper analyzes the methodologies, findings, and limitations of each reviewed study, pinpointing trends such as the increasing focus on practical implementation of quantum cryptography protocols and the growing interest in postquantum cryptography research. Furthermore, the survey identifies challenges and open research questions, including the need for more efficient quantum repeater networks, improved security proofs for continuous variable quantum key distribution, and the development of quantum resistant cryptographic algorithms. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.09248v1-abstract-full').style.display = 'none'; document.getElementById('2306.09248v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.08060">arXiv:2306.08060</a> <span> [<a href="https://arxiv.org/pdf/2306.08060">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/BigData55660.2022.10020813">10.1109/BigData55660.2022.10020813 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Software Supply Chain Vulnerabilities Detection in Source Code: Performance Comparison between Traditional and Quantum Machine Learning Algorithms </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Faruk%2C+M+J+H">Md Jobair Hossain Faruk</a>, <a href="/search/cs?searchtype=author&query=Anjum%2C+N">Nafisa Anjum</a>, <a href="/search/cs?searchtype=author&query=Masum%2C+M">Mohammad Masum</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Rahman%2C+A">Akond Rahman</a>, <a href="/search/cs?searchtype=author&query=Wu%2C+F">Fan Wu</a>, <a href="/search/cs?searchtype=author&query=Cuzzocrea%2C+A">Alfredo Cuzzocrea</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.08060v1-abstract-short" style="display: inline;"> The software supply chain (SSC) attack has become one of the crucial issues that are being increased rapidly with the advancement of the software development domain. In general, SSC attacks execute during the software development processes lead to vulnerabilities in software products targeting downstream customers and even involved stakeholders. Machine Learning approaches are proven in detecting… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.08060v1-abstract-full').style.display = 'inline'; document.getElementById('2306.08060v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.08060v1-abstract-full" style="display: none;"> The software supply chain (SSC) attack has become one of the crucial issues that are being increased rapidly with the advancement of the software development domain. In general, SSC attacks execute during the software development processes lead to vulnerabilities in software products targeting downstream customers and even involved stakeholders. Machine Learning approaches are proven in detecting and preventing software security vulnerabilities. Besides, emerging quantum machine learning can be promising in addressing SSC attacks. Considering the distinction between traditional and quantum machine learning, performance could be varies based on the proportions of the experimenting dataset. In this paper, we conduct a comparative analysis between quantum neural networks (QNN) and conventional neural networks (NN) with a software supply chain attack dataset known as ClaMP. Our goal is to distinguish the performance between QNN and NN and to conduct the experiment, we develop two different models for QNN and NN by utilizing Pennylane for quantum and TensorFlow and Keras for traditional respectively. We evaluated the performance of both models with different proportions of the ClaMP dataset to identify the f1 score, recall, precision, and accuracy. We also measure the execution time to check the efficiency of both models. The demonstration result indicates that execution time for QNN is slower than NN with a higher percentage of datasets. Due to recent advancements in QNN, a large level of experiments shall be carried out to understand both models accurately in our future research. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.08060v1-abstract-full').style.display = 'none'; document.getElementById('2306.08060v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 31 May, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.07981">arXiv:2306.07981</a> <span> [<a href="https://arxiv.org/pdf/2306.07981">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> </div> </div> <p class="title is-5 mathjax"> Feature Engineering-Based Detection of Buffer Overflow Vulnerability in Source Code Using Neural Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Cardenas%2C+J+R">Juan Rodriguez Cardenas</a>, <a href="/search/cs?searchtype=author&query=Ahamed%2C+S+I">Sheikh Iqbal Ahamed</a>, <a href="/search/cs?searchtype=author&query=Cuzzocrea%2C+A">Alfredo Cuzzocrea</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.07981v1-abstract-short" style="display: inline;"> One of the most significant challenges in the field of software code auditing is the presence of vulnerabilities in software source code. Every year, more and more software flaws are discovered, either internally in proprietary code or publicly disclosed. These flaws are highly likely to be exploited and can lead to system compromise, data leakage, or denial of service. To create a large-scale mac… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.07981v1-abstract-full').style.display = 'inline'; document.getElementById('2306.07981v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.07981v1-abstract-full" style="display: none;"> One of the most significant challenges in the field of software code auditing is the presence of vulnerabilities in software source code. Every year, more and more software flaws are discovered, either internally in proprietary code or publicly disclosed. These flaws are highly likely to be exploited and can lead to system compromise, data leakage, or denial of service. To create a large-scale machine learning system for function level vulnerability identification, we utilized a sizable dataset of C and C++ open-source code containing millions of functions with potential buffer overflow exploits. We have developed an efficient and scalable vulnerability detection method based on neural network models that learn features extracted from the source codes. The source code is first converted into an intermediate representation to remove unnecessary components and shorten dependencies. We maintain the semantic and syntactic information using state of the art word embedding algorithms such as GloVe and fastText. The embedded vectors are subsequently fed into neural networks such as LSTM, BiLSTM, LSTM Autoencoder, word2vec, BERT, and GPT2 to classify the possible vulnerabilities. We maintain the semantic and syntactic information using state of the art word embedding algorithms such as GloVe and fastText. The embedded vectors are subsequently fed into neural networks such as LSTM, BiLSTM, LSTM Autoencoder, word2vec, BERT, and GPT2 to classify the possible vulnerabilities. Furthermore, we have proposed a neural network model that can overcome issues associated with traditional neural networks. We have used evaluation metrics such as F1 score, precision, recall, accuracy, and total execution time to measure the performance. We have conducted a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.07981v1-abstract-full').style.display = 'none'; document.getElementById('2306.07981v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 31 May, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.02289">arXiv:2306.02289</a> <span> [<a href="https://arxiv.org/pdf/2306.02289">pdf</a>, <a href="https://arxiv.org/format/2306.02289">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> Evaluating the Impact of Community Oversight for Managing Mobile Privacy and Security </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Tabassum%2C+M">Madiha Tabassum</a>, <a href="/search/cs?searchtype=author&query=Miazi%2C+N+S">Nazmus Sakib Miazi</a>, <a href="/search/cs?searchtype=author&query=Alghamdi%2C+L">Leena Alghamdi</a>, <a href="/search/cs?searchtype=author&query=Kropczynski%2C+J">Jess Kropczynski</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a>, <a href="/search/cs?searchtype=author&query=Lipford%2C+H">Heather Lipford</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.02289v3-abstract-short" style="display: inline;"> Mobile privacy and security can be a collaborative process where individuals seek advice and help from their trusted communities. To support such collective privacy and security management, we developed a mobile app for Community Oversight of Privacy and Security ("CO-oPS") that allows community members to review one another's apps installed and permissions granted to provide feedback. We conducte… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.02289v3-abstract-full').style.display = 'inline'; document.getElementById('2306.02289v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.02289v3-abstract-full" style="display: none;"> Mobile privacy and security can be a collaborative process where individuals seek advice and help from their trusted communities. To support such collective privacy and security management, we developed a mobile app for Community Oversight of Privacy and Security ("CO-oPS") that allows community members to review one another's apps installed and permissions granted to provide feedback. We conducted a four-week-long field study with 22 communities (101 participants) of friends, families, or co-workers who installed the CO-oPS app on their phones. Measures of transparency, trust, and awareness of one another's mobile privacy and security behaviors, along with individual and community participation in mobile privacy and security co-management, increased from pre- to post-study. Interview findings confirmed that the app features supported collective considerations of apps and permissions. However, participants expressed a range of concerns regarding having community members with different levels of technical expertise and knowledge regarding mobile privacy and security that can impact motivation to participate and perform oversight. Our study demonstrates the potential and challenges of community oversight mechanisms to support communities to co-manage mobile privacy and security. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.02289v3-abstract-full').style.display = 'none'; document.getElementById('2306.02289v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 4 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">20 pages; The Nineteenth Symposium on Usable Privacy and Security (SOUPS 2023)</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.02287">arXiv:2306.02287</a> <span> [<a href="https://arxiv.org/pdf/2306.02287">pdf</a>, <a href="https://arxiv.org/format/2306.02287">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1145/3544549.3585904">10.1145/3544549.3585904 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> It Takes a Village: A Case for Including Extended Family Members in the Joint Oversight of Family-based Privacy and Security for Mobile Smartphones </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Alghamdi%2C+L">Leena Alghamdi</a>, <a href="/search/cs?searchtype=author&query=Kropczynski%2C+J">Jess Kropczynski</a>, <a href="/search/cs?searchtype=author&query=Lipford%2C+H">Heather Lipford</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.02287v2-abstract-short" style="display: inline;"> We conducted a user study with 19 parent-teen dyads to understand the perceived benefits and drawbacks of using a mobile app that allows them to co-manage mobile privacy, safety, and security within their families. While the primary goal of the study was to understand the use case as it pertained to parents and teens, an emerging finding from our study was that participants found value in extendin… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.02287v2-abstract-full').style.display = 'inline'; document.getElementById('2306.02287v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.02287v2-abstract-full" style="display: none;"> We conducted a user study with 19 parent-teen dyads to understand the perceived benefits and drawbacks of using a mobile app that allows them to co-manage mobile privacy, safety, and security within their families. While the primary goal of the study was to understand the use case as it pertained to parents and teens, an emerging finding from our study was that participants found value in extending app use to other family members (siblings, cousins, and grandparents). Participants felt that it would help bring the necessary expertise into their immediate family network and help protect the older adults and children of the family from privacy and security risks. However, participants expressed that co-monitoring by extended family members might cause tensions in their families, creating interpersonal conflicts. To alleviate these concerns, participants suggested more control over the privacy features to facilitate sharing their installed apps with only trusted family members. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.02287v2-abstract-full').style.display = 'none'; document.getElementById('2306.02287v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 4 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.00284">arXiv:2306.00284</a> <span> [<a href="https://arxiv.org/pdf/2306.00284">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> </div> </div> <p class="title is-5 mathjax"> Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Ahamed%2C+S+I">Sheikh Iqbal Ahamed</a>, <a href="/search/cs?searchtype=author&query=Gupta%2C+K+D">Kishor Datta Gupta</a>, <a href="/search/cs?searchtype=author&query=Rahman%2C+M">Muhammad Rahman</a>, <a href="/search/cs?searchtype=author&query=Mohamed%2C+A">Atef Mohamed</a>, <a href="/search/cs?searchtype=author&query=Rahman%2C+M">Mohammad Rahman</a>, <a href="/search/cs?searchtype=author&query=Rahman%2C+A">Akond Rahman</a>, <a href="/search/cs?searchtype=author&query=Wu%2C+F">Fan Wu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.00284v1-abstract-short" style="display: inline;"> Quantum machine learning (QML) is an emerging field of research that leverages quantum computing to improve the classical machine learning approach to solve complex real world problems. QML has the potential to address cybersecurity related challenges. Considering the novelty and complex architecture of QML, resources are not yet explicitly available that can pave cybersecurity learners to instill… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.00284v1-abstract-full').style.display = 'inline'; document.getElementById('2306.00284v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.00284v1-abstract-full" style="display: none;"> Quantum machine learning (QML) is an emerging field of research that leverages quantum computing to improve the classical machine learning approach to solve complex real world problems. QML has the potential to address cybersecurity related challenges. Considering the novelty and complex architecture of QML, resources are not yet explicitly available that can pave cybersecurity learners to instill efficient knowledge of this emerging technology. In this research, we design and develop QML-based ten learning modules covering various cybersecurity topics by adopting student centering case-study based learning approach. We apply one subtopic of QML on a cybersecurity topic comprised of pre-lab, lab, and post-lab activities towards providing learners with hands-on QML experiences in solving real-world security problems. In order to engage and motivate students in a learning environment that encourages all students to learn, pre-lab offers a brief introduction to both the QML subtopic and cybersecurity problem. In this paper, we utilize quantum support vector machine (QSVM) for malware classification and protection where we use open source Pennylane QML framework on the drebin215 dataset. We demonstrate our QSVM model and achieve an accuracy of 95% in malware classification and protection. We will develop all the modules and introduce them to the cybersecurity community in the coming days. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.00284v1-abstract-full').style.display = 'none'; document.getElementById('2306.00284v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 31 May, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.00283">arXiv:2306.00283</a> <span> [<a href="https://arxiv.org/pdf/2306.00283">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Autism Disease Detection Using Transfer Learning Techniques: Performance Comparison Between Central Processing Unit vs Graphics Processing Unit Functions for Neural Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Cuzzocrea%2C+A">Alfredo Cuzzocrea</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.00283v1-abstract-short" style="display: inline;"> Neural network approaches are machine learning methods that are widely used in various domains, such as healthcare and cybersecurity. Neural networks are especially renowned for their ability to deal with image datasets. During the training process with images, various fundamental mathematical operations are performed in the neural network. These operations include several algebraic and mathematic… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.00283v1-abstract-full').style.display = 'inline'; document.getElementById('2306.00283v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.00283v1-abstract-full" style="display: none;"> Neural network approaches are machine learning methods that are widely used in various domains, such as healthcare and cybersecurity. Neural networks are especially renowned for their ability to deal with image datasets. During the training process with images, various fundamental mathematical operations are performed in the neural network. These operations include several algebraic and mathematical functions, such as derivatives, convolutions, and matrix inversions and transpositions. Such operations demand higher processing power than what is typically required for regular computer usage. Since CPUs are built with serial processing, they are not appropriate for handling large image datasets. On the other hand, GPUs have parallel processing capabilities and can provide higher speed. This paper utilizes advanced neural network techniques, such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST VGG16, and our proposed models, to compare CPU and GPU resources. We implemented a system for classifying Autism disease using face images of autistic and non-autistic children to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It was observed that GPU outperformed CPU in all tests conducted. Moreover, the performance of the neural network models in terms of accuracy increased on GPU compared to CPU. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.00283v1-abstract-full').style.display = 'none'; document.getElementById('2306.00283v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 31 May, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2305.19593">arXiv:2305.19593</a> <span> [<a href="https://arxiv.org/pdf/2305.19593">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> </div> </div> <p class="title is-5 mathjax"> Exploring the Vulnerabilities of Machine Learning and Quantum Machine Learning to Adversarial Attacks using a Malware Dataset: A Comparative Analysis </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Iqbal%2C+I">Iysa Iqbal</a>, <a href="/search/cs?searchtype=author&query=Hossain%2C+M">MD Hossain</a>, <a href="/search/cs?searchtype=author&query=Karim%2C+M+A">M. A. Karim</a>, <a href="/search/cs?searchtype=author&query=Clincy%2C+V">Victor Clincy</a>, <a href="/search/cs?searchtype=author&query=Voicu%2C+R">Razvan Voicu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2305.19593v1-abstract-short" style="display: inline;"> The burgeoning fields of machine learning (ML) and quantum machine learning (QML) have shown remarkable potential in tackling complex problems across various domains. However, their susceptibility to adversarial attacks raises concerns when deploying these systems in security sensitive applications. In this study, we present a comparative analysis of the vulnerability of ML and QML models, specifi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2305.19593v1-abstract-full').style.display = 'inline'; document.getElementById('2305.19593v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2305.19593v1-abstract-full" style="display: none;"> The burgeoning fields of machine learning (ML) and quantum machine learning (QML) have shown remarkable potential in tackling complex problems across various domains. However, their susceptibility to adversarial attacks raises concerns when deploying these systems in security sensitive applications. In this study, we present a comparative analysis of the vulnerability of ML and QML models, specifically conventional neural networks (NN) and quantum neural networks (QNN), to adversarial attacks using a malware dataset. We utilize a software supply chain attack dataset known as ClaMP and develop two distinct models for QNN and NN, employing Pennylane for quantum implementations and TensorFlow and Keras for traditional implementations. Our methodology involves crafting adversarial samples by introducing random noise to a small portion of the dataset and evaluating the impact on the models performance using accuracy, precision, recall, and F1 score metrics. Based on our observations, both ML and QML models exhibit vulnerability to adversarial attacks. While the QNNs accuracy decreases more significantly compared to the NN after the attack, it demonstrates better performance in terms of precision and recall, indicating higher resilience in detecting true positives under adversarial conditions. We also find that adversarial samples crafted for one model type can impair the performance of the other, highlighting the need for robust defense mechanisms. Our study serves as a foundation for future research focused on enhancing the security and resilience of ML and QML models, particularly QNN, given its recent advancements. A more extensive range of experiments will be conducted to better understand the performance and robustness of both models in the face of adversarial attacks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2305.19593v1-abstract-full').style.display = 'none'; document.getElementById('2305.19593v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 31 May, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2304.04613">arXiv:2304.04613</a> <span> [<a href="https://arxiv.org/pdf/2304.04613">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> On Evaluation of Bangla Word Analogies </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mousumi Akter</a>, <a href="/search/cs?searchtype=author&query=Sarkar%2C+S">Souvika Sarkar</a>, <a href="/search/cs?searchtype=author&query=Santu%2C+S+K+K">Shubhra Kanti Karmaker Santu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2304.04613v1-abstract-short" style="display: inline;"> This paper presents a high-quality dataset for evaluating the quality of Bangla word embeddings, which is a fundamental task in the field of Natural Language Processing (NLP). Despite being the 7th most-spoken language in the world, Bangla is a low-resource language and popular NLP models fail to perform well. Developing a reliable evaluation test set for Bangla word embeddings are crucial for ben… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.04613v1-abstract-full').style.display = 'inline'; document.getElementById('2304.04613v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2304.04613v1-abstract-full" style="display: none;"> This paper presents a high-quality dataset for evaluating the quality of Bangla word embeddings, which is a fundamental task in the field of Natural Language Processing (NLP). Despite being the 7th most-spoken language in the world, Bangla is a low-resource language and popular NLP models fail to perform well. Developing a reliable evaluation test set for Bangla word embeddings are crucial for benchmarking and guiding future research. We provide a Mikolov-style word analogy evaluation set specifically for Bangla, with a sample size of 16678, as well as a translated and curated version of the Mikolov dataset, which contains 10594 samples for cross-lingual research. Our experiments with different state-of-the-art embedding models reveal that Bangla has its own unique characteristics, and current embeddings for Bangla still struggle to achieve high accuracy on both datasets. We suggest that future research should focus on training models with larger datasets and considering the unique morphological characteristics of Bangla. This study represents the first step towards building a reliable NLP system for the Bangla language1. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.04613v1-abstract-full').style.display = 'none'; document.getElementById('2304.04613v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 April, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2303.07530">arXiv:2303.07530</a> <span> [<a href="https://arxiv.org/pdf/2303.07530">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/CNS56114.2022.10044378">10.1109/CNS56114.2022.10044378 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Towards Unsupervised Learning based Denoising of Cyber Physical System Data to Mitigate Security Concerns </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2303.07530v1-abstract-short" style="display: inline;"> A dataset, collected under an industrial setting, often contains a significant portion of noises. In many cases, using trivial filters is not enough to retrieve useful information i.e., accurate value without the noise. One such data is time-series sensor readings collected from moving vehicles containing fuel information. Due to the noisy dynamics and mobile environment, the sensor readings can b… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07530v1-abstract-full').style.display = 'inline'; document.getElementById('2303.07530v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2303.07530v1-abstract-full" style="display: none;"> A dataset, collected under an industrial setting, often contains a significant portion of noises. In many cases, using trivial filters is not enough to retrieve useful information i.e., accurate value without the noise. One such data is time-series sensor readings collected from moving vehicles containing fuel information. Due to the noisy dynamics and mobile environment, the sensor readings can be very noisy. Denoising such a dataset is a prerequisite for any useful application and security issues. Security is a primitive concern in present vehicular schemes. The server side for retrieving the fuel information can be easily hacked. Providing the accurate and noise free fuel information via vehicular networks become crutial. Therefore, it has led us to develop a system that can remove noise and keep the original value. The system is also helpful for vehicle industry, fuel station, and power-plant station that require fuel. In this work, we have only considered the value of fuel level, and we have come up with a unique solution to filter out the noise of high magnitudes using several algorithms such as interpolation, extrapolation, spectral clustering, agglomerative clustering, wavelet analysis, and median filtering. We have also employed peak detection and peak validation algorithms to detect fuel refill and consumption in charge-discharge cycles. We have used the R-squared metric to evaluate our model, and it is 98 percent In most cases, the difference between detected value and real value remains within the range of 1L. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07530v1-abstract-full').style.display = 'none'; document.getElementById('2303.07530v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2303.07525">arXiv:2303.07525</a> <span> [<a href="https://arxiv.org/pdf/2303.07525">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Automated Vulnerability Detection in Source Code Using Quantum Natural Language Processing </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Bhuiya%2C+Z+A">Zakirul Alam Bhuiya</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2303.07525v1-abstract-short" style="display: inline;"> One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. These flaws are highly likely ex-ploited and lead to system compromise, data leakage, or denial of ser-vice. C and C++ open source code are now available in order to create a large-scale, classical machine-learning and quantum machine-learning system for function-lev… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07525v1-abstract-full').style.display = 'inline'; document.getElementById('2303.07525v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2303.07525v1-abstract-full" style="display: none;"> One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. These flaws are highly likely ex-ploited and lead to system compromise, data leakage, or denial of ser-vice. C and C++ open source code are now available in order to create a large-scale, classical machine-learning and quantum machine-learning system for function-level vulnerability identification. We assembled a siz-able dataset of millions of open-source functions that point to poten-tial exploits. We created an efficient and scalable vulnerability detection method based on a deep neural network model Long Short Term Memory (LSTM), and quantum machine learning model Long Short Term Memory (QLSTM), that can learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the de-pendency. Therefore, We keep the semantic and syntactic information using state of the art word embedding algorithms such as Glove and fastText. The embedded vectors are subsequently fed into the classical and quantum convolutional neural networks to classify the possible vulnerabilities. To measure the performance, we used evaluation metrics such as F1 score, precision, re-call, accuracy, and total execution time. We made a comparison between the results derived from the classical LSTM and quantum LSTM using basic feature representation as well as semantic and syntactic represen-tation. We found that the QLSTM with semantic and syntactic features detects significantly accurate vulnerability and runs faster than its classical counterpart. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07525v1-abstract-full').style.display = 'none'; document.getElementById('2303.07525v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2303.07520">arXiv:2303.07520</a> <span> [<a href="https://arxiv.org/pdf/2303.07520">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/BigData55660.2022.10020302">10.1109/BigData55660.2022.10020302 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Multi-class Skin Cancer Classification Architecture Based on Deep Convolutional Neural Network </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Sneha%2C+S">Sweta Sneha</a>, <a href="/search/cs?searchtype=author&query=Cuzzocrea%2C+A">Alfredo Cuzzocrea</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2303.07520v1-abstract-short" style="display: inline;"> Skin cancer detection is challenging since different types of skin lesions share high similarities. This paper proposes a computer-based deep learning approach that will accurately identify different kinds of skin lesions. Deep learning approaches can detect skin cancer very accurately since the models learn each pixel of an image. Sometimes humans can get confused by the similarities of the skin… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07520v1-abstract-full').style.display = 'inline'; document.getElementById('2303.07520v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2303.07520v1-abstract-full" style="display: none;"> Skin cancer detection is challenging since different types of skin lesions share high similarities. This paper proposes a computer-based deep learning approach that will accurately identify different kinds of skin lesions. Deep learning approaches can detect skin cancer very accurately since the models learn each pixel of an image. Sometimes humans can get confused by the similarities of the skin lesions, which we can minimize by involving the machine. However, not all deep learning approaches can give better predictions. Some deep learning models have limitations, leading the model to a false-positive result. We have introduced several deep learning models to classify skin lesions to distinguish skin cancer from different types of skin lesions. Before classifying the skin lesions, data preprocessing and data augmentation methods are used. Finally, a Convolutional Neural Network (CNN) model and six transfer learning models such as Resnet-50, VGG-16, Densenet, Mobilenet, Inceptionv3, and Xception are applied to the publically available benchmark HAM10000 dataset to classify seven classes of skin lesions and to conduct a comparative analysis. The models will detect skin cancer by differentiating the cancerous cell from the non-cancerous ones. The models performance is measured using performance metrics such as precision, recall, f1 score, and accuracy. We receive accuracy of 90, 88, 88, 87, 82, and 77 percent for inceptionv3, Xception, Densenet, Mobilenet, Resnet, CNN, and VGG16, respectively. Furthermore, we develop five different stacking models such as inceptionv3-inceptionv3, Densenet-mobilenet, inceptionv3-Xception, Resnet50-Vgg16, and stack-six for classifying the skin lesions and found that the stacking models perform poorly. We achieve the highest accuracy of 78 percent among all the stacking models. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07520v1-abstract-full').style.display = 'none'; document.getElementById('2303.07520v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2303.07514">arXiv:2303.07514</a> <span> [<a href="https://arxiv.org/pdf/2303.07514">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/BigData55660.2022.10021025">10.1109/BigData55660.2022.10021025 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Handwritten Word Recognition using Deep Learning Approach: A Novel Way of Generating Handwritten Words </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Cuzzocrea%2C+A">Alfredo Cuzzocrea</a>, <a href="/search/cs?searchtype=author&query=Ahmed%2C+N">Nova Ahmed</a>, <a href="/search/cs?searchtype=author&query=Leung%2C+C">Carson Leung</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2303.07514v1-abstract-short" style="display: inline;"> A handwritten word recognition system comes with issues such as lack of large and diverse datasets. It is necessary to resolve such issues since millions of official documents can be digitized by training deep learning models using a large and diverse dataset. Due to the lack of data availability, the trained model does not give the expected result. Thus, it has a high chance of showing poor resul… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07514v1-abstract-full').style.display = 'inline'; document.getElementById('2303.07514v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2303.07514v1-abstract-full" style="display: none;"> A handwritten word recognition system comes with issues such as lack of large and diverse datasets. It is necessary to resolve such issues since millions of official documents can be digitized by training deep learning models using a large and diverse dataset. Due to the lack of data availability, the trained model does not give the expected result. Thus, it has a high chance of showing poor results. This paper proposes a novel way of generating diverse handwritten word images using handwritten characters. The idea of our project is to train the BiLSTM-CTC architecture with generated synthetic handwritten words. The whole approach shows the process of generating two types of large and diverse handwritten word datasets: overlapped and non-overlapped. Since handwritten words also have issues like overlapping between two characters, we have tried to put it into our experimental part. We have also demonstrated the process of recognizing handwritten documents using the deep learning model. For the experiments, we have targeted the Bangla language, which lacks the handwritten word dataset, and can be followed for any language. Our approach is less complex and less costly than traditional GAN models. Finally, we have evaluated our model using Word Error Rate (WER), accuracy, f1-score, precision, and recall metrics. The model gives 39% WER score, 92% percent accuracy, and 92% percent f1 scores using non-overlapped data and 63% percent WER score, 83% percent accuracy, and 85% percent f1 scores using overlapped data. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07514v1-abstract-full').style.display = 'none'; document.getElementById('2303.07514v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2303.07484">arXiv:2303.07484</a> <span> [<a href="https://arxiv.org/pdf/2303.07484">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/BigData55660.2022.10020249">10.1109/BigData55660.2022.10020249 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Deep Learning Approach for Classifying the Aggressive Comments on Social Media: Machine Translated Data Vs Real Life Data </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M+S">Mst Shapna Akter</a>, <a href="/search/cs?searchtype=author&query=Shahriar%2C+H">Hossain Shahriar</a>, <a href="/search/cs?searchtype=author&query=Ahmed%2C+N">Nova Ahmed</a>, <a href="/search/cs?searchtype=author&query=Cuzzocrea%2C+A">Alfredo Cuzzocrea</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2303.07484v1-abstract-short" style="display: inline;"> Aggressive comments on social media negatively impact human life. Such offensive contents are responsible for depression and suicidal-related activities. Since online social networking is increasing day by day, the hate content is also increasing. Several investigations have been done on the domain of cyberbullying, cyberaggression, hate speech, etc. The majority of the inquiry has been done in th… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07484v1-abstract-full').style.display = 'inline'; document.getElementById('2303.07484v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2303.07484v1-abstract-full" style="display: none;"> Aggressive comments on social media negatively impact human life. Such offensive contents are responsible for depression and suicidal-related activities. Since online social networking is increasing day by day, the hate content is also increasing. Several investigations have been done on the domain of cyberbullying, cyberaggression, hate speech, etc. The majority of the inquiry has been done in the English language. Some languages (Hindi and Bangla) still lack proper investigations due to the lack of a dataset. This paper particularly worked on the Hindi, Bangla, and English datasets to detect aggressive comments and have shown a novel way of generating machine-translated data to resolve data unavailability issues. A fully machine-translated English dataset has been analyzed with the models such as the Long Short term memory model (LSTM), Bidirectional Long-short term memory model (BiLSTM), LSTM-Autoencoder, word2vec, Bidirectional Encoder Representations from Transformers (BERT), and generative pre-trained transformer (GPT-2) to make an observation on how the models perform on a machine-translated noisy dataset. We have compared the performance of using the noisy data with two more datasets such as raw data, which does not contain any noises, and semi-noisy data, which contains a certain amount of noisy data. We have classified both the raw and semi-noisy data using the aforementioned models. To evaluate the performance of the models, we have used evaluation metrics such as F1-score,accuracy, precision, and recall. We have achieved the highest accuracy on raw data using the gpt2 model, semi-noisy data using the BERT model, and fully machine-translated data using the BERT model. Since many languages do not have proper data availability, our approach will help researchers create machine-translated datasets for several analysis purposes. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.07484v1-abstract-full').style.display = 'none'; document.getElementById('2303.07484v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2301.06652">arXiv:2301.06652</a> <span> [<a href="https://arxiv.org/pdf/2301.06652">pdf</a>, <a href="https://arxiv.org/format/2301.06652">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> Co-designing Community-based Sharing of Smarthome Devices for the Purpose of Co-monitoring In-home Emergencies </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Alghamdi%2C+L">Leena Alghamdi</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Kropczynski%2C+J">Jess Kropczynski</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a>, <a href="/search/cs?searchtype=author&query=Lipford%2C+H">Heather Lipford</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2301.06652v2-abstract-short" style="display: inline;"> We conducted 26 co-design interviews with 50 smarthome device owners to understand the perceived benefits, drawbacks, and design considerations for developing a smarthome system that facilitates co-monitoring with emergency contacts who live outside of one's home. Participants felt that such a system would help ensure their personal safety, safeguard from material loss, and give them peace of mind… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2301.06652v2-abstract-full').style.display = 'inline'; document.getElementById('2301.06652v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2301.06652v2-abstract-full" style="display: none;"> We conducted 26 co-design interviews with 50 smarthome device owners to understand the perceived benefits, drawbacks, and design considerations for developing a smarthome system that facilitates co-monitoring with emergency contacts who live outside of one's home. Participants felt that such a system would help ensure their personal safety, safeguard from material loss, and give them peace of mind by ensuring quick response and verifying potential threats. However, they also expressed concerns regarding privacy, overburdening others, and other potential threats, such as unauthorized access and security breaches. To alleviate these concerns, participants designed for flexible and granular access control and fail-safe back-up features. Our study reveals why peer-based co-monitoring of smarthomes for emergencies may be beneficial but also difficult to implement. Based on the insights gained from our study, we provide recommendations for designing technologies that facilitate such co-monitoring while mitigating its risks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2301.06652v2-abstract-full').style.display = 'none'; document.getElementById('2301.06652v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 16 January, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">21 pages</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2212.05932">arXiv:2212.05932</a> <span> [<a href="https://arxiv.org/pdf/2212.05932">pdf</a>, <a href="https://arxiv.org/format/2212.05932">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> </div> </div> <p class="title is-5 mathjax"> Automated Level Crossing System: A Computer Vision Based Approach with Raspberry Pi Microcontroller </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Murshed%2C+R+U">Rafid Umayer Murshed</a>, <a href="/search/cs?searchtype=author&query=Dhruba%2C+S+K">Sandip Kollol Dhruba</a>, <a href="/search/cs?searchtype=author&query=Bhuian%2C+M+T+I">Md. Tawheedul Islam Bhuian</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M+R">Mst. Rumi Akter</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2212.05932v1-abstract-short" style="display: inline;"> In a rapidly flourishing country like Bangladesh, accidents in unmanned level crossings are increasing daily. This study presents a deep learning-based approach for automating level crossing junctions, ensuring maximum safety. Here, we develop a fully automated technique using computer vision on a microcontroller that will reduce and eliminate level-crossing deaths and accidents. A Raspberry Pi mi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2212.05932v1-abstract-full').style.display = 'inline'; document.getElementById('2212.05932v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2212.05932v1-abstract-full" style="display: none;"> In a rapidly flourishing country like Bangladesh, accidents in unmanned level crossings are increasing daily. This study presents a deep learning-based approach for automating level crossing junctions, ensuring maximum safety. Here, we develop a fully automated technique using computer vision on a microcontroller that will reduce and eliminate level-crossing deaths and accidents. A Raspberry Pi microcontroller detects impending trains using computer vision on live video, and the intersection is closed until the incoming train passes unimpeded. Live video activity recognition and object detection algorithms scan the junction 24/7. Self-regulating microcontrollers control the entire process. When persistent unauthorized activity is identified, authorities, such as police and fire brigade, are notified via automated messages and notifications. The microcontroller evaluates live rail-track data, and arrival and departure times to anticipate ETAs, train position, velocity, and track problems to avoid head-on collisions. This proposed scheme reduces level crossing accidents and fatalities at a lower cost than current market solutions. Index Terms: Deep Learning, Microcontroller, Object Detection, Railway Crossing, Raspberry Pi <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2212.05932v1-abstract-full').style.display = 'none'; document.getElementById('2212.05932v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 December, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">4 pages, 7 figures, accepted at the 12th International Conference on Electrical and Computer Engineering (ICECE 2022) to be held on 21-23rd December in Dhaka, Bangladesh</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2208.02743">arXiv:2208.02743</a> <span> [<a href="https://arxiv.org/pdf/2208.02743">pdf</a>, <a href="https://arxiv.org/format/2208.02743">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Integrating Knowledge Graph embedding and pretrained Language Models in Hypercomplex Spaces </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Nayyeri%2C+M">Mojtaba Nayyeri</a>, <a href="/search/cs?searchtype=author&query=Wang%2C+Z">Zihao Wang</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M+M">Mst. Mahfuja Akter</a>, <a href="/search/cs?searchtype=author&query=Alam%2C+M+M">Mirza Mohtashim Alam</a>, <a href="/search/cs?searchtype=author&query=Rony%2C+M+R+A+H">Md Rashad Al Hasan Rony</a>, <a href="/search/cs?searchtype=author&query=Lehmann%2C+J">Jens Lehmann</a>, <a href="/search/cs?searchtype=author&query=Staab%2C+S">Steffen Staab</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2208.02743v3-abstract-short" style="display: inline;"> Knowledge Graphs, such as Wikidata, comprise structural and textual knowledge in order to represent knowledge. For each of the two modalities dedicated approaches for graph embedding and language models learn patterns that allow for predicting novel structural knowledge. Few approaches have integrated learning and inference with both modalities and these existing ones could only partially exploit… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.02743v3-abstract-full').style.display = 'inline'; document.getElementById('2208.02743v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2208.02743v3-abstract-full" style="display: none;"> Knowledge Graphs, such as Wikidata, comprise structural and textual knowledge in order to represent knowledge. For each of the two modalities dedicated approaches for graph embedding and language models learn patterns that allow for predicting novel structural knowledge. Few approaches have integrated learning and inference with both modalities and these existing ones could only partially exploit the interaction of structural and textual knowledge. In our approach, we build on existing strong representations of single modalities and we use hypercomplex algebra to represent both, (i), single-modality embedding as well as, (ii), the interaction between different modalities and their complementary means of knowledge representation. More specifically, we suggest Dihedron and Quaternion representations of 4D hypercomplex numbers to integrate four modalities namely structural knowledge graph embedding, word-level representations (e.g.\ Word2vec, Fasttext), sentence-level representations (Sentence transformer), and document-level representations (sentence transformer, Doc2vec). Our unified vector representation scores the plausibility of labelled edges via Hamilton and Dihedron products, thus modeling pairwise interactions between different modalities. Extensive experimental evaluation on standard benchmark datasets shows the superiority of our two new models using abundant textual information besides sparse structural knowledge to enhance performance in link prediction tasks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.02743v3-abstract-full').style.display = 'none'; document.getElementById('2208.02743v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 4 August, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">ISWC2023 version</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2208.02226">arXiv:2208.02226</a> <span> [<a href="https://arxiv.org/pdf/2208.02226">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.14569/IJACSA.2021.0120653">10.14569/IJACSA.2021.0120653 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Internet of Things (IoT) based ECG System for Rural Health Care </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Rahman%2C+M+O">Md. Obaidur Rahman</a>, <a href="/search/cs?searchtype=author&query=Kashem%2C+M+A">Mohammod Abul Kashem</a>, <a href="/search/cs?searchtype=author&query=Nayan%2C+A">Al-Akhir Nayan</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M+F">Most. Fahmida Akter</a>, <a href="/search/cs?searchtype=author&query=Rabbi%2C+F">Fazly Rabbi</a>, <a href="/search/cs?searchtype=author&query=Ahmed%2C+M">Marzia Ahmed</a>, <a href="/search/cs?searchtype=author&query=Asaduzzaman%2C+M">Mohammad Asaduzzaman</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2208.02226v1-abstract-short" style="display: inline;"> Nearly 30% of the people in the rural areas of Bangladesh are below the poverty level. Moreover, due to the unavailability of modernized healthcare-related technology, nursing and diagnosis facilities are limited for rural people. Therefore, rural people are deprived of proper healthcare. In this perspective, modern technology can be facilitated to mitigate their health problems. ECG sensing tools… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.02226v1-abstract-full').style.display = 'inline'; document.getElementById('2208.02226v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2208.02226v1-abstract-full" style="display: none;"> Nearly 30% of the people in the rural areas of Bangladesh are below the poverty level. Moreover, due to the unavailability of modernized healthcare-related technology, nursing and diagnosis facilities are limited for rural people. Therefore, rural people are deprived of proper healthcare. In this perspective, modern technology can be facilitated to mitigate their health problems. ECG sensing tools are interfaced with the human chest, and requisite cardiovascular data is collected through an IoT device. These data are stored in the cloud incorporates with the MQTT and HTTP servers. An innovative IoT-based method for ECG monitoring systems on cardiovascular or heart patients has been suggested in this study. The ECG signal parameters P, Q, R, S, T are collected, pre-processed, and predicted to monitor the cardiovascular conditions for further health management. The machine learning algorithm is used to determine the significance of ECG signal parameters and error rate. The logistic regression model fitted the better agreements between the train and test data. The prediction has been performed to determine the variation of PQRST quality and its suitability in the ECG Monitoring System. Considering the values of quality parameters, satisfactory results are obtained. The proposed IoT-based ECG system reduces the health care cost and complexity of cardiovascular diseases in the future. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.02226v1-abstract-full').style.display = 'none'; document.getElementById('2208.02226v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 July, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> International Journal of Advanced Computer Science and Applications, vol. 12, no. 6, pp. 470-477, 2021 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2204.07751">arXiv:2204.07751</a> <span> [<a href="https://arxiv.org/pdf/2204.07751">pdf</a>, <a href="https://arxiv.org/format/2204.07751">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> A User Study to Evaluate a Web-based Prototype for Smart Home Internet of Things Device Management </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Alghamdi%2C+L">Leena Alghamdi</a>, <a href="/search/cs?searchtype=author&query=Alsoubai%2C+A">Ashwaq Alsoubai</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Alghamdi%2C+F">Faisal Alghamdi</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2204.07751v1-abstract-short" style="display: inline;"> With the growing advances in the Internet of Things (IoT) technology, IoT device management platforms are becoming increasingly important. We conducted a web-based survey and usability study with 43 participants who use IoT devices frequently to: 1) examine their smart home IoT usage patterns and privacy preferences, and 2) evaluate a web-based prototype for smart home IoT device management. We fo… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2204.07751v1-abstract-full').style.display = 'inline'; document.getElementById('2204.07751v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2204.07751v1-abstract-full" style="display: none;"> With the growing advances in the Internet of Things (IoT) technology, IoT device management platforms are becoming increasingly important. We conducted a web-based survey and usability study with 43 participants who use IoT devices frequently to: 1) examine their smart home IoT usage patterns and privacy preferences, and 2) evaluate a web-based prototype for smart home IoT device management. We found that participants perceived privacy as more important than the convenience afforded by the IoT devices. Based on their average scores of privacy vs. convenience importance, participants with low privacy and low convenience significantly reported less privacy control and convenience preferences than participants with high privacy and high convenience. Overall, all participants were satisfied with the proposed website prototype and their actual usability evaluation demonstrated a good understanding of the website features. This paper provides an empirical examination of the privacy versus convenience trade-offs smart home users make when managing their IoT devices. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2204.07751v1-abstract-full').style.display = 'none'; document.getElementById('2204.07751v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 April, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2204.07749">arXiv:2204.07749</a> <span> [<a href="https://arxiv.org/pdf/2204.07749">pdf</a>, <a href="https://arxiv.org/format/2204.07749">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1145/3512904">10.1145/3512904 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> From Parental Control to Joint Family Oversight: Can Parents and Teens Manage Mobile Online Safety and Privacy as Equals? </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mamtaj Akter</a>, <a href="/search/cs?searchtype=author&query=Godfrey%2C+A">Amy Godfrey</a>, <a href="/search/cs?searchtype=author&query=Kropczynski%2C+J">Jess Kropczynski</a>, <a href="/search/cs?searchtype=author&query=Lipford%2C+H">Heather Lipford</a>, <a href="/search/cs?searchtype=author&query=Wisniewski%2C+P">Pamela Wisniewski</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2204.07749v2-abstract-short" style="display: inline;"> Our research aims to highlight and alleviate the complex tensions around online safety, privacy, and smartphone usage in families so that parents and teens can work together to better manage mobile privacy and security-related risks. We developed a mobile application ("app") for Community Oversight of Privacy and Security ("CO-oPS") and had parents and teens assess whether it would be applicable f… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2204.07749v2-abstract-full').style.display = 'inline'; document.getElementById('2204.07749v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2204.07749v2-abstract-full" style="display: none;"> Our research aims to highlight and alleviate the complex tensions around online safety, privacy, and smartphone usage in families so that parents and teens can work together to better manage mobile privacy and security-related risks. We developed a mobile application ("app") for Community Oversight of Privacy and Security ("CO-oPS") and had parents and teens assess whether it would be applicable for use with their families. CO-oPS is an Android app that allows a group of users to co-monitor the apps installed on one another's devices and the privacy permissions granted to those apps. We conducted a study with 19 parent-teen (ages 13-17) pairs to understand how they currently managed mobile safety and app privacy within their family and then had them install, use, and evaluate the CO-oPS app. We found that both parents and teens gave little consideration to online safety and privacy before installing new apps or granting privacy permissions. When using CO-oPS, participants liked how the app increased transparency into one another's devices in a way that facilitated communication, but were less inclined to use features for in-app messaging or to hide apps from one another. Key themes related to power imbalances between parents and teens surfaced that made co-management challenging. Parents were more open to collaborative oversight than teens, who felt that it was not their place to monitor their parents, even though both often believed parents lacked the technological expertise to monitor themselves. Our study sheds light on why collaborative practices for managing online safety and privacy within families may be beneficial but also quite difficult to implement in practice. We provide recommendations for overcoming these challenges based on the insights gained from our study. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2204.07749v2-abstract-full').style.display = 'none'; document.getElementById('2204.07749v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 16 April, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.05303">arXiv:2203.05303</a> <span> [<a href="https://arxiv.org/pdf/2203.05303">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.5121/hiij.2022.11101">10.5121/hiij.2022.11101 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Use of Digital Technologies in Public Health Responses to Tackle Covid-19: the Bangladesh Perspective </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Dey%2C+S+K">Samrat Kumar Dey</a>, <a href="/search/cs?searchtype=author&query=Mehrin%2C+K">Khaleda Mehrin</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+L">Lubana Akter</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mshura Akter</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.05303v1-abstract-short" style="display: inline;"> This paper aims to study the fight against COVID-19 in Bangladesh and digital intervention initiatives. To achieve the purpose of our research, we conducted a methodical review of online content. We have reviewed the first digital intervention that COVID-19 has been used to fight against worldwide. Then we reviewed the initiatives that have been taken in Bangladesh. Our paper has shown that while… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.05303v1-abstract-full').style.display = 'inline'; document.getElementById('2203.05303v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.05303v1-abstract-full" style="display: none;"> This paper aims to study the fight against COVID-19 in Bangladesh and digital intervention initiatives. To achieve the purpose of our research, we conducted a methodical review of online content. We have reviewed the first digital intervention that COVID-19 has been used to fight against worldwide. Then we reviewed the initiatives that have been taken in Bangladesh. Our paper has shown that while Bangladesh can take advantage of the digital intervention approach, it will require rigorous collaboration between government organizations and universities to get the most out of it. Public health can become increasingly digital in the future, and we are reviewing international alignment requirements. This exploration also focused on the strategies for controlling, evaluating, and using digital technology to strengthen epidemic management and future preparations for COVID-19. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.05303v1-abstract-full').style.display = 'none'; document.getElementById('2203.05303v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">13 pages, 11 figures, 1 table</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Health Informatics: An International Journal 11 (1), 1-13, 2022 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2201.05294">arXiv:2201.05294</a> <span> [<a href="https://arxiv.org/pdf/2201.05294">pdf</a>, <a href="https://arxiv.org/format/2201.05294">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Multi-Narrative Semantic Overlap Task: Evaluation and Benchmark </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Bansal%2C+N">Naman Bansal</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+M">Mousumi Akter</a>, <a href="/search/cs?searchtype=author&query=Santu%2C+S+K+K">Shubhra Kanti Karmaker Santu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2201.05294v1-abstract-short" style="display: inline;"> In this paper, we introduce an important yet relatively unexplored NLP task called Multi-Narrative Semantic Overlap (MNSO), which entails generating a Semantic Overlap of multiple alternate narratives. As no benchmark dataset is readily available for this task, we created one by crawling 2,925 narrative pairs from the web and then, went through the tedious process of manually creating 411 differen… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2201.05294v1-abstract-full').style.display = 'inline'; document.getElementById('2201.05294v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2201.05294v1-abstract-full" style="display: none;"> In this paper, we introduce an important yet relatively unexplored NLP task called Multi-Narrative Semantic Overlap (MNSO), which entails generating a Semantic Overlap of multiple alternate narratives. As no benchmark dataset is readily available for this task, we created one by crawling 2,925 narrative pairs from the web and then, went through the tedious process of manually creating 411 different ground-truth semantic overlaps by engaging human annotators. As a way to evaluate this novel task, we first conducted a systematic study by borrowing the popular ROUGE metric from text-summarization literature and discovered that ROUGE is not suitable for our task. Subsequently, we conducted further human annotations/validations to create 200 document-level and 1,518 sentence-level ground-truth labels which helped us formulate a new precision-recall style evaluation metric, called SEM-F1 (semantic F1). Experimental results show that the proposed SEM-F1 metric yields higher correlation with human judgement as well as higher inter-rater-agreement compared to ROUGE metric. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2201.05294v1-abstract-full').style.display = 'none'; document.getElementById('2201.05294v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 January, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1204.6364">arXiv:1204.6364</a> <span> [<a href="https://arxiv.org/pdf/1204.6364">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> A Corpus-based Evaluation of a Domain-specific Text to Knowledge Mapping Prototype </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Shams%2C+R">Rushdi Shams</a>, <a href="/search/cs?searchtype=author&query=Elsayed%2C+A">Adel Elsayed</a>, <a href="/search/cs?searchtype=author&query=Akter%2C+Q+M">Quazi Mah-Zereen Akter</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1204.6364v1-abstract-short" style="display: inline;"> The aim of this paper is to evaluate a Text to Knowledge Mapping (TKM) Prototype. The prototype is domain-specific, the purpose of which is to map instructional text onto a knowledge domain. The context of the knowledge domain is DC electrical circuit. During development, the prototype has been tested with a limited data set from the domain. The prototype reached a stage where it needs to be evalu… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1204.6364v1-abstract-full').style.display = 'inline'; document.getElementById('1204.6364v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1204.6364v1-abstract-full" style="display: none;"> The aim of this paper is to evaluate a Text to Knowledge Mapping (TKM) Prototype. The prototype is domain-specific, the purpose of which is to map instructional text onto a knowledge domain. The context of the knowledge domain is DC electrical circuit. During development, the prototype has been tested with a limited data set from the domain. The prototype reached a stage where it needs to be evaluated with a representative linguistic data set called corpus. A corpus is a collection of text drawn from typical sources which can be used as a test data set to evaluate NLP systems. As there is no available corpus for the domain, we developed and annotated a representative corpus. The evaluation of the prototype considers two of its major components- lexical components and knowledge model. Evaluation on lexical components enriches the lexical resources of the prototype like vocabulary and grammar structures. This leads the prototype to parse a reasonable amount of sentences in the corpus. While dealing with the lexicon was straight forward, the identification and extraction of appropriate semantic relations was much more involved. It was necessary, therefore, to manually develop a conceptual structure for the domain to formulate a domain-specific framework of semantic relations. The framework of semantic relationsthat has resulted from this study consisted of 55 relations, out of which 42 have inverse relations. We also conducted rhetorical analysis on the corpus to prove its representativeness in conveying semantic. Finally, we conducted a topical and discourse analysis on the corpus to analyze the coverage of discourse by the prototype. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1204.6364v1-abstract-full').style.display = 'none'; document.getElementById('1204.6364v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 27 April, 2012; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2012. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Journal of Computers, Academy Publishers 2010</span> </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> 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