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As a result, all submissions are subject to an article publication charge (APC) if accepted (unless a waiver is applied) and will be published in Discover Computing. Please see our FAQs journal update for more information on APCs, funding options, and waivers. Discover Computing is a fully open access, peer-reviewed journal that supports multidisciplinary research and policy developments across all fields relevant to computer science. The journal aims to be a resource for researchers, policy makers and the general public for recent advances in computer science, and its uses in research development and society. As a fully open access journal, we ensure that our research is highly discoverable and instantly available globally to everyone. The journal particularly welcomes work that aims to address the United Nations Sustainable Development Goals, especially, Industry, Innovation and Infrastructure. Topics Topics welcomed at Discover Computing include but are not limited to the following: Foundational computing theories: Algorithms, data structures, computational complexity Automata theory, graph theory, formal languages Turing machines, P vs NP problem, lambda calculus Modern computing architectures and systems: Quantum computing, distributed systems, parallel computing Microarchitecture, multicore processors, memory hierarchies Cloud computing, edge computing, serverless architectures Human-computer interaction: User experience (UX), user interface (UI), accessibility Cognitive ergonomics, adaptive systems, virtual reality User-centered design, haptic feedback, gesture recognition Artificial intelligence and machine learning: Neural networks, deep learning, reinforcement learning Natural language processing, computer vision, robotics Generative adversarial networks (GANs), transfer learning, explainable AI Cybersecurity and privacy: Cryptography, firewall, intrusion detection systems Digital forensics, malware analysis, blockchain security Data anonymization, end-to-end encryption, zero trust architectures Emergent technologies: Augmented reality (AR), virtual reality (VR), mixed reality (MR) Internet of Things (IoT), 5G, smart cities Drones, autonomous vehicles, wearable tech Societal impacts of computing: Digital ethics, algorithmic bias, technological unemployment Digital divide, accessibility, information equity Digital literacy, e-governance, surveillance capitalism Content types Discover Computing welcomes a variety of article types – please see our submission guidelines for details. The journal also publishes guest-edited Topical Collections of relevance to all aspects of computer science and its applications. For more information, please follow up with our journal publishing contact.</pre><div class="alert alert-warning"> Last updated by <a href="/researcher/1">Dou Sun</a> in 2024-07-20</div> </div> </div> <div class="portlet" id="yw2"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-list-alt"></i> Special Issues</div> </div> <div class="portlet-content"> <a name="4695"></a><pre>Special Issue on Edge-Computing AI for Medical Devices</br>Submission Date: 2025-03-28</br></br>Electronic medical devices can be implantables, wearables, and remote. These devices can collect varioius multimodal and multigrain bio-signals invasively or non-invasively. This large heterogeneous data from medical devices contains tremendous information that can be analyzed with artificial intelligence (AI). Many medical applications require edge-computing AI for real-time data processing, decision making, or feedback for unsupervised settings to seamlessly generate meaningful interpretations and actionable decisions with high degree of accuracy and reliability. Rapid progress in embedded technologies with high computing power and ubiquitous connectivity using Bluetooth, Wi-Fi, and 5G along with miniature, low-cost, flexible, and reliable sensors have paved the hardware revolution for these technologies. Advancements in edge-computing AI algorithms with machine learning (ML) and deep learning (DL) techniques with real-time interactive systems. The purpose of this collection is to address the on-going research activities in these fields with focus on edge-computing AI for a variety of applications including biomedical, assistive technologies, elderly monitoring, mobile-health, and smart-health. This Collection supports and amplifies research related to: SDG 3</pre><div class="alert alert-warning">Last updated by <a href="/researcher/1">Dou Sun</a> in 2024-07-20</div><a name="4693"></a><pre>Special Issue on AI in University Education: Transforming Learning, Teaching, and Curriculum Development</br>Submission Date: 2025-03-31</br></br>A topical collection on “AI in University Education: Transforming Learning, Teaching, and Curriculum Development” delves into how artificial intelligence is reshaping higher education, with a particular emphasis on teaching, learning, assessment and curriculum development. This collection explores AI-driven personalized learning platforms and adaptive educational systems, examining their impact on student outcomes. It highlights the development and evaluation of intelligent tutoring systems and virtual assistants that enhance student engagement and provide academic support. The focus on AI-driven curriculum development covers methods for using AI to design and optimize curricula, identifying knowledge gaps, aligning with industry needs, and ensuring relevance to job market trends. Additionally, automated assessment and feedback systems are analyzed for their potential to reduce grading workload while ensuring fairness and accuracy. The collection also discusses AI applications in administrative efficiency, predictive analytics for student retention, and streamlining processes. Ethical and privacy concerns are addressed, emphasizing data security and the balance between innovation and ethics. AI-enhanced research tools and platforms that facilitate collaboration and data management are showcased. The perspectives of students and faculty on AI integration, along with training and professional development for faculty on AI tools, are explored. Real-world case studies of successful AI integration in universities, comparative analyses of AI adoption across regions, and best practices offer practical insights. This topical collection aims to provide valuable guidance for educators, administrators, policymakers, and technology developers on leveraging AI to create dynamic, relevant, and effective educational programs while considering the broader impacts on higher education. Topics include but are not limited to: - Use of personalized learning environments in tertiary education - Adaptive educational tools/systems and their implementation in tertiary education - AI-driven personalized learning platforms and their impact on student outcomes - Intelligent tutoring systems and virtual assistants - Virtual assistants for student support - Enhancing student engagement and learning through conversational AI - Leveraging big data to personalize learning experiences, optimize curriculum development, and improve student outcomes - Methods for using AI to design and optimize curricula - Case studies of AI-assisted curriculum redesign in universities - Automated assessment and feedback systems - AI in automated grading and providing personalized feedback - Ensuring fairness and accuracy in AI-based assessment - Training and professional development for faculty on AI tools - Impact of AI on teaching and learning experience - Predictive analytics for student retention and success - Addressing ethical issues related to the use of AI in education - Ensuring data privacy and security in AI-driven educational tools - Balancing innovation with ethical considerations in AI deployment - Comparative analysis of AI adoption in higher education across different regions - Lessons learned and best practices from AI implementations in academia This Collection supports and amplifies research related to SDG 4 and SDG 11. Keywords: AI-driven education, personalized learning environments, intelligent tutoring systems, AI-enabled curriculum development, automated assessment</pre><div class="alert alert-warning">Last updated by <a href="/researcher/1">Dou Sun</a> in 2024-07-20</div><a name="4692"></a><pre>Special Issue on Advances in Large Language Models and Natural Language Processing</br>Submission Date: 2025-04-30</br></br>The advent of Large Language Models (LLMs) has revolutionized the field of Natural Language Processing (NLP), enabling unprecedented advancements in language understanding, generation, and interaction. This Topical Collection aims to gather pioneering research on the development and application of LLMs, focusing on their transformative impact across various domains such as education, healthcare, and finance. By addressing key challenges and opportunities, the collection seeks to foster a deeper understanding of LLM capabilities and limitations, promoting innovative methodologies and practical solutions. Specific areas of interest include, but are not limited to, LLM architectures, fine-tuning techniques, ethical considerations, real-world applications, and performance evaluation metrics. This collection will serve as a comprehensive resource for scholars, practitioners, and industry experts, driving forward the conversation on the future of NLP and AI. This Collection supports and amplifies research related to SDG 4, SDG 8, and SDG 9. Keywords: Large Language Models, Natural Language Processing, Computational Linguistics, Text Generation, NLP Techniques. </pre><div class="alert alert-warning">Last updated by <a href="/researcher/1">Dou Sun</a> in 2024-07-20</div></div> </div>  <div class="portlet" id="yw3"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-file"></i> Related Journals</div> </div> <div class="portlet-content"> <div class="hidden-phone"> <div id="yw4" class="grid-view"> <table class="table table-hover table-striped table-bordered table-condensed"> <thead> <tr> <th id="yw4_c0">CCF</th><th id="yw4_c1">Full Name</th><th id="yw4_c2">Impact Factor</th><th id="yw4_c3">Publisher</th><th id="yw4_c4">ISSN</th></tr> </thead> <tbody> <tr class="odd"> <td><span class="badge badge-warning">c</span></td><td><a href="/journal/695">IEEE Signal Processing Letters</a></td><td>3.200</td><td>IEEE</td><td>1070-9908</td></tr> <tr class="even"> <td><span class="badge 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table-striped table-bordered table-condensed"> <thead> <tr> <th id="yw8_c0">Short</th><th id="yw8_c1">Full Name</th><th id="yw8_c2">Submission</th><th id="yw8_c3">Conference</th></tr> </thead> <tbody> <tr class="odd"> <td>ECIR</td><td><a href="/conference/159">European Conference on Information Retrieval</a></td><td>2024-10-02</td><td>2025-04-06</td></tr> <tr class="even"> <td>SBMicro</td><td><a href="/conference/1710">Symposium on Microelectronics Technology and Devices</a></td><td>2015-03-30</td><td>2015-08-31</td></tr> <tr class="odd"> <td>ICNS</td><td><a href="/conference/709">International Conference on Networking and Services</a></td><td>2022-02-20</td><td>2022-05-22</td></tr> <tr class="even"> <td>IFIPTM</td><td><a href="/conference/375">IFIP WG 11.11 International Conference on Trust Management</a></td><td>2019-04-09</td><td>2019-07-17</td></tr> <tr class="odd"> <td>CCEM</td><td><a href="/conference/1781">IEEE International Conference on Cloud Computing in Emerging Markets</a></td><td>2021-07-24</td><td>2021-10-27</td></tr> <tr class="even"> <td>ICALP</td><td><a href="/conference/381">International Colloquium on Automata, Languages and Programming</a></td><td>2025-02-07</td><td>2025-07-08</td></tr> <tr class="odd"> <td>ROSENET</td><td><a href="/conference/3163">International Conference on Robotic Sensor Networks</a></td><td>2020-07-30</td><td>2020-11-21</td></tr> <tr class="even"> <td>SSP</td><td><a href="/conference/831">IEEE Statistical Signal Processing Workshop</a></td><td> </td><td>2012-08-05</td></tr> <tr class="odd"> <td>CSECS</td><td><a href="/conference/4610">International Conference on Software Engineering and Computer Science</a></td><td>2025-02-28</td><td>2025-03-21</td></tr> <tr class="even"> <td>BSB</td><td><a href="/conference/982">Brazilian Symposium on Bioinformatics</a></td><td>2013-06-11</td><td>2013-11-03</td></tr> </tbody> </table><div class="keys" style="display:none" title="/journal/114"><span>159</span><span>1710</span><span>709</span><span>375</span><span>1781</span><span>381</span><span>3163</span><span>831</span><span>4610</span><span>982</span></div> </div></div> </div> </div> <div class="portlet" id="yw9"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-eye-open"></i> Recommendation</div> </div> <div class="portlet-content"> <div align="center"> <script async src="//pagead2.googlesyndication.com/pagead/js/adsbygoogle.js"></script>  <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-6743617430731451" data-ad-slot="1870704128" data-ad-format="autorelaxed"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script> </div> </div> </div> </div> <div class="span2 hidden-phone"> <div class="sidebar-nav"> <ul id="yw10"> <li><a href="http://www.myhuiban.com/journal/track/id/114"><i class="icon icon-plus"></i>   Track It <span class="badge badge-warning pull-right">15</span></a></li> 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