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class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 8</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Racha Khairallah</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8</span> Knowledge Spillovers from Patent Citations: Evidence from Swiss Manufacturing Industry</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Racha%20Khairallah">Racha Khairallah</a>, <a href="https://publications.waset.org/abstracts/search?q=Lamia%20Ben%20Hamida"> Lamia Ben Hamida</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Our paper attempts to examine how Swiss manufacturing firms manage to learn from patent citations to improve their innovation performance. We argue that the assessment of these effects needs a detailed analysis of spillovers according to the source of knowledge with respect to formal and informal patent citations made in European and internal search, the horizontal and vertical mechanisms by which knowledge spillovers take place, and the technological characteristics of innovative firms that able them to absorb external knowledge and integrate it in their existing innovation process. We use OECD data and find evidence that knowledge spillovers occur only from horizontal and backward linkages. The importance of these effects depends on the type of citation, in which the references to non-patent literature (informal citations made in European and international searches) have a greater impact. In addition, only firms with high technological capacities benefit from knowledge spillovers from formal and informal citations. Low-technology firms fail to catch up and efficiently learn external knowledge from patent citations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=innovation%20performance" title="innovation performance">innovation performance</a>, <a href="https://publications.waset.org/abstracts/search?q=patent%20citation" title=" patent citation"> patent citation</a>, <a href="https://publications.waset.org/abstracts/search?q=absorptive%20capacity" title=" absorptive capacity"> absorptive capacity</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20spillover%20mechanisms" title=" knowledge spillover mechanisms"> knowledge spillover mechanisms</a> </p> <a href="https://publications.waset.org/abstracts/162143/knowledge-spillovers-from-patent-citations-evidence-from-swiss-manufacturing-industry" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162143.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">129</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7</span> The Chromatic Identity of the Ancestral Architecture of the Ksour of Bechar, Algeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Racha%20Ghariri">Racha Ghariri</a>, <a href="https://publications.waset.org/abstracts/search?q=Khaldia%20Belkheir"> Khaldia Belkheir</a>, <a href="https://publications.waset.org/abstracts/search?q=Assil%20Ghariri"> Assil Ghariri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the researchers present a part of their research on the colors of the city of Bechar (Algeria). It is about a chromatic study of the ancient architecture of the Ksour. Being a subject of intervention, regarding their degradable state, the Ksour are the case of their study, especially that the subject of color does not occupy, virtually, the involved on these heritage sites. This research aims to put the basics for methods which allow to know what to preserve as a color and how to do so, especially during a restoration, and to understand the evolution of the chromatic state of the city. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=architecture%2Fcolours" title="architecture/colours">architecture/colours</a>, <a href="https://publications.waset.org/abstracts/search?q=chromatic%20identity" title=" chromatic identity"> chromatic identity</a>, <a href="https://publications.waset.org/abstracts/search?q=geography%20of%20colour" title=" geography of colour"> geography of colour</a>, <a href="https://publications.waset.org/abstracts/search?q=regional%20palette" title=" regional palette"> regional palette</a>, <a href="https://publications.waset.org/abstracts/search?q=chromatic%20architectural%20analysis" title=" chromatic architectural analysis"> chromatic architectural analysis</a> </p> <a href="https://publications.waset.org/abstracts/68009/the-chromatic-identity-of-the-ancestral-architecture-of-the-ksour-of-bechar-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68009.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">314</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6</span> Packet Analysis in Network Forensics: Insights, Tools, and Case Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dalal%20Nasser%20Fathi">Dalal Nasser Fathi</a>, <a href="https://publications.waset.org/abstracts/search?q=Amal%20Saud%20Al-Mutairi"> Amal Saud Al-Mutairi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mada%20Hamed%20Al-Towairqi"> Mada Hamed Al-Towairqi</a>, <a href="https://publications.waset.org/abstracts/search?q=Enas%20Fawzi%20Khairallah"> Enas Fawzi Khairallah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Network forensics is essential for investigating cyber incidents and detecting malicious activities by analyzing network traffic, with a focus on packet and protocol data. This process involves capturing, filtering, and examining network data to identify patterns and signs of attacks. Packet analysis, a core technique in this field, provides insights into the origins of data, the protocols used, and any suspicious payloads, which aids in detecting malicious activity. This paper explores network forensics, providing guidance for the analyst on what to look for and identifying attack sites guided by the seven layers of the OSI model. Additionally, it explains the most commonly used tools in network forensics and demonstrates a practical example using Wireshark. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=network%20forensic" title="network forensic">network forensic</a>, <a href="https://publications.waset.org/abstracts/search?q=packet%20analysis" title=" packet analysis"> packet analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=Wireshark%20tools" title=" Wireshark tools"> Wireshark tools</a>, <a href="https://publications.waset.org/abstracts/search?q=forensic%20investigation" title=" forensic investigation"> forensic investigation</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20evidence" title=" digital evidence"> digital evidence</a> </p> <a href="https://publications.waset.org/abstracts/196200/packet-analysis-in-network-forensics-insights-tools-and-case-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/196200.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">25</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5</span> Automatic Classification of the Stand-to-Sit Phase in the TUG Test Using Machine Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yasmine%20Abu%20Adla">Yasmine Abu Adla</a>, <a href="https://publications.waset.org/abstracts/search?q=Racha%20Soubra"> Racha Soubra</a>, <a href="https://publications.waset.org/abstracts/search?q=Milana%20Kasab"> Milana Kasab</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamad%20O.%20Diab"> Mohamad O. Diab</a>, <a href="https://publications.waset.org/abstracts/search?q=Aly%20Chkeir"> Aly Chkeir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals, out of which 11 were chosen based on their intraclass correlation coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, 5 features were introduced to the linear discriminant analysis classifier, and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90%, respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Doppler%20radar%20system" title="Doppler radar system">Doppler radar system</a>, <a href="https://publications.waset.org/abstracts/search?q=stand-to-sit%20phase" title=" stand-to-sit phase"> stand-to-sit phase</a>, <a href="https://publications.waset.org/abstracts/search?q=TUG%20test" title=" TUG test"> TUG test</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a> </p> <a href="https://publications.waset.org/abstracts/141688/automatic-classification-of-the-stand-to-sit-phase-in-the-tug-test-using-machine-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141688.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">166</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Nurses' Knowledge and Attitudes toward the Use of Physical Restraints</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatema%20Salman">Fatema Salman</a>, <a href="https://publications.waset.org/abstracts/search?q=Ridha%20Hammam"> Ridha Hammam</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatima%20Khairallah"> Fatima Khairallah</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatima%20Aradi"> Fatima Aradi</a>, <a href="https://publications.waset.org/abstracts/search?q=Nafeesa%20Abdulla"> Nafeesa Abdulla</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Alsafar"> Mohammed Alsafar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose: This study aims at measuring the extent of nurses’ knowledge and attitudes toward the use of physical restraints in different hospital wards at Salmaniya Medical Complex (SMC). Background: The habitual use of physical restraint is a widespread practice among nurses working in the clinical settings. Restraints inflict many deleterious consequences on patients physically and psychologically which in turn increases their morbidity and mortality risk and jeopardizes care quality. Nurses’ knowledge and attitudes toward physical restraints are crucial determinants of the persistence of this practice. Literature review: the evidence of lack of knowledge among nurses regarding the use of physical restraints is overwhelming in various clinical settings, especially in two main areas which are the negative consequences and the available alternatives to physical restraints. Studies explored nurses’ attitudes toward physical restraints yielded inconsistent findings. Equally comparable, some studies found that nurses hold positive attitudes toward the use of physical restraints while some others reported just the opposite. Methods: Self-administered knowledge and attitudes scales to 106 nurses working in the SMC. Findings: nurses hold the moderate level of knowledge about restraints (M=58%) with weak negative attitudes (M = -20%) toward using it. Significant moderately-strong negative correlation (r= -0.57, r2= 0.32, p= 0.000) was uncovered between nurses knowledge and their attitudes which provided an empirical explanation of this phenomenon (use of physical restraints). Recommendations: Induction of awareness program that especially focuses on the negative consequences and encourages the use of alternatives is an evident need. This effort necessarily should be adjoined with policy and procedure adjustments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=attitudes" title="attitudes">attitudes</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge" title=" knowledge"> knowledge</a>, <a href="https://publications.waset.org/abstracts/search?q=nurses" title=" nurses"> nurses</a>, <a href="https://publications.waset.org/abstracts/search?q=restraints" title=" restraints"> restraints</a> </p> <a href="https://publications.waset.org/abstracts/57820/nurses-knowledge-and-attitudes-toward-the-use-of-physical-restraints" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57820.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">325</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Effect of Sowing Dates on Growth, Agronomic Traits and Yield of Tossa Jute (Corchorus olitorius L.)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amira%20Racha%20Ben%20Yakoub">Amira Racha Ben Yakoub</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20Ferchichi"> Ali Ferchichi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to investigate the impact of sowing time on growth parameters, the length of the development cycle and yield of tossa jute (Corchorus olitorius L.), a field experiment was conducted from March to May 2011 at the Laboratoire d’Aridoculture et Cultures Oasiennes, ‘Institut des Régions Arides de Médénine’, Tunisia. Results of the experiment revealed that the early sowing (the middle of March, the beginning of April) induced a cycle of more than 100 days to reach the stage maturity and generates a marked drop in production. This period of plantation affects plant development and leads to a sharp drop in performance marked primarily by a reduction in growth, number and size of leaves, number of flowers and pods and weight of different parts of plant. Sowing from the end of April seems appropriate for shortening the development cycle and better profitability than the first two dates. Seeding of C. olitorius during May enhance the development of plants more dense, which explains the superiority of production marked by the increase of seed yield and leaf fresh and dry weight of this leafy vegetables. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=tossa%20jute%20%28Corchorus%20olitorius%20L%29" title="tossa jute (Corchorus olitorius L)">tossa jute (Corchorus olitorius L)</a>, <a href="https://publications.waset.org/abstracts/search?q=sowing%20date" title=" sowing date"> sowing date</a>, <a href="https://publications.waset.org/abstracts/search?q=growth" title=" growth"> growth</a>, <a href="https://publications.waset.org/abstracts/search?q=yield" title=" yield"> yield</a> </p> <a href="https://publications.waset.org/abstracts/14532/effect-of-sowing-dates-on-growth-agronomic-traits-and-yield-of-tossa-jute-corchorus-olitorius-l" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14532.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">355</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Neural Networks Based Prediction of Long Term Rainfall: Nine Pilot Study Zones over the Mediterranean Basin</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Racha%20El%20Kadiri">Racha El Kadiri</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Sultan"> Mohamed Sultan</a>, <a href="https://publications.waset.org/abstracts/search?q=Henrique%20Momm"> Henrique Momm</a>, <a href="https://publications.waset.org/abstracts/search?q=Zachary%20Blair"> Zachary Blair</a>, <a href="https://publications.waset.org/abstracts/search?q=Rachel%20Schultz"> Rachel Schultz</a>, <a href="https://publications.waset.org/abstracts/search?q=Tamer%20Al-Bayoumi"> Tamer Al-Bayoumi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Mediterranean Basin is a very diverse region of nationalities and climate zones, with a strong dependence on agricultural activities. Predicting long term (with a lead of 1 to 12 months) rainfall, and future droughts could contribute in a sustainable management of water resources and economical activities. In this study, an integrated approach was adopted to construct predictive tools with lead times of 0 to 12 months to forecast rainfall amounts over nine subzones of the Mediterranean Basin region. The following steps were conducted: (1) acquire, assess and intercorrelate temporal remote sensing-based rainfall products (e.g. The CPC Merged Analysis of Precipitation [CMAP]) throughout the investigation period (1979 to 2016), (2) acquire and assess monthly values for all of the climatic indices influencing the regional and global climatic patterns (e.g., Northern Atlantic Oscillation [NOI], Southern Oscillation Index [SOI], and Tropical North Atlantic Index [TNA]); (3) delineate homogenous climatic regions and select nine pilot study zones, (4) apply data mining methods (e.g. neural networks, principal component analyses) to extract relationships between the observed rainfall and the controlling factors (i.e. climatic indices with multiple lead-time periods) and (5) use the constructed predictive tools to forecast monthly rainfall and dry and wet periods. Preliminary results indicate that rainfall and dry/wet periods were successfully predicted with lead zones of 0 to 12 months using the adopted methodology, and that the approach is more accurately applicable in the southern Mediterranean region. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rainfall" title="rainfall">rainfall</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=climatic%20indices" title=" climatic indices"> climatic indices</a>, <a href="https://publications.waset.org/abstracts/search?q=Mediterranean" title=" Mediterranean"> Mediterranean</a> </p> <a href="https://publications.waset.org/abstracts/70457/neural-networks-based-prediction-of-long-term-rainfall-nine-pilot-study-zones-over-the-mediterranean-basin" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70457.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">318</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Machine Learning Approach for Automating Electronic Component Error Classification and Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monica%20Racha">Monica Racha</a>, <a href="https://publications.waset.org/abstracts/search?q=Siva%20Chandrasekaran"> Siva Chandrasekaran</a>, <a href="https://publications.waset.org/abstracts/search?q=Alex%20Stojcevski"> Alex Stojcevski</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=augmented%20reality" title="augmented reality">augmented reality</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=object%20recognition" title=" object recognition"> object recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=virtual%20laboratories" title=" virtual laboratories"> virtual laboratories</a> </p> <a href="https://publications.waset.org/abstracts/145582/machine-learning-approach-for-automating-electronic-component-error-classification-and-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145582.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">144</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2025 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); 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