Domain-Specific Modeling Language for Security Analysis of EV Charging Infrastructure by Anas Motii, Mahmoud El Hamlaoui, Robert Basmadjian

“…This interconnection raises concerns about security, privacy, and the expanding risk of cyber-attacks within the electric vehicle landscape. …”
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Beijing’s urbanization reflected in apartment layouts: a computer vision and isovist analysis (1970–2020) by Yanhua Yao, Ashutosh Kumar, Martina Mazzarello, Fábio Duarte, Lei Shao, Limin Song, Carlo Ratti

“…Our findings show a trend in the isovist intensity of living rooms, dining rooms, and kitchens, indicative of shifts toward privacy and mixed-use spaces, shaped by household occupancy patterns. …”
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HELA-CMM: capability maturity model for adoption of learning analytics in higher education by Diana Šimić, Nina Begičević Ređep, Sabina Rako, Nikola Kadoić, Wim Van Petegem, Bart Rienties, Nati Cabrera Lanzo, Michael Eichhorn, Lourdes Guàrdia, Sandra Kučina Softić, Alexander Tillmann

“…The proposed maturity model comprises 28 capabilities grouped into eight categories: (1) Teaching / Learning / Assessment, (2) Data Management and Analytics, (3) Ethics, Privacy, Legal Issues, (4) People Competences, (5) Management / Leadership, (6) Culture, (7) Infrastructure, and (8) Quality Assurance. …”
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A Deep Learning-Based Ensemble Framework for Robust Android Malware Detection by Sainag Nethala, Pronoy Chopra, Khaja Kamaluddin, Shahid Alam, Soltan Alharbi, Mohammad Alsaffar

“…The exponential growth of Android applications has resulted in a surge of malware threats, posing severe risks to user privacy and data security. To address these challenges, this study introduces a novel malware detection approach utilizing an ensemble of Convolutional Neural Networks (CNNs) for enhanced classification accuracy. …”
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Barriers and facilitators of the electronic medical record adoption among healthcare providers in Addis Ababa, Ethiopia by Tadesse Alemu Bekele, Lemma Derseh Gezie, Herman Willems, Jonathan Metzger, Biruhtesfa Abere, Blen Seyoum, Loko Abraham, Naod Wendrad, Selamawit Meressa, Bethel Desta, Tariku Nigatu Bogale

“…Methods A descriptive-phenomenological approach was used. Data were collected from one hospital and three health centers from 5–13 June, 2023, that implemented the EMR. …”
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Zero-Touch Network Security (ZTNS): A Network Intrusion Detection System Based on Deep Learning by Emad-Ul-Haq Qazi, Tanveer Zia, Muhammad Hamza Faheem, Khurram Shahzad, Muhammad Imran, Zeeshan Ahmed

“…The rapid evaluation of smart cities has revolutionized the research and development field to a very extensive level which presents challenges in handling massive amounts of data. However, the integration of IoT into various aspects of life has introduced various challenges related to the security and privacy of IoT systems. …”
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Large Language Model and Traditional Machine Learning Scoring of Evolutionary Explanations: Benefits and Drawbacks by Yunlong Pan, Ross H. Nehm

“…Few studies have compared Large Language Models (LLMs) to traditional Machine Learning (ML)-based automated scoring methods in terms of accuracy, ethics, and economics. Using a corpus of 1000 expert-scored and interview-validated scientific explanations derived from the ACORNS instrument, this study employed three LLMs and the ML-based scoring engine, EvoGrader. …”
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Detecting Learning Behavior in Programming Assignments by Analyzing Versioned Repositories by John Chen, Serena Lau, Juho Leinonen, Valerio Terragni, Nasser Giacaman

“…The Polivr ecosystem comprises three key modules: Polivr Anonymiser, which ensures data privacy by anonymising student identities; Polivr Core, which mines learning metrics from Git repositories; and Polivr Web Viewer, which transforms the raw metrics into insightful visualisations for educators. …”
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Quality of Breast Cancer Information on the Internet by African Organizations: An Appraisal by Cynthia Pomaa Akuoko

“…The identified websites were assessed using European Commission (EC) quality criteria for health-related websites, which comprises different assessment areas including, completeness, transparency and honesty, authority, privacy and data protection, updating of information, accountability, and accessibility. …”
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Contrastive Self-Supervised Learning for Sensor-Based Human Activity Recognition: A Review by Hui Chen, Charles Gouin-Vallerand, Kevin Bouchard, Sebastien Gaboury, Melanie Couture, Nathalie Bier, Sylvain Giroux

“…Next, we comprehensively review data augmentation methods for sensor data and commonly used benchmark datasets for activity recognition. …”
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Perspectives of stakeholders on enhancing access to self-injectable contraception in rural South Sudan by Grace W. Kimemia, Mamothena Carol Mothupi, Lual Agok Luka, Teresia Macharia, Sidonia Akon, Alom Atak Ayom, Lual James Baak, Amijong Deng, Kadra Noor, Taban John Mark, Naoko Kozuki

“…Abstract Background Although self-injectable subcutaneous depot medroxyprogesterone acetate (DMPA-SC) has demonstrated promise, there are significant barriers in promoting initiation and continued use in low-resource settings. This study sought to understand the perspectives of stakeholders on promotion of self-injectable contraception use in rural South Sudan. …”
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Multicountry research on comprehensive abortion policy implementation in Latin America: a mixed-methods study protocol by Guillermo Carroli, Antonella Lavelanet, Silvina Ramos, Mariana Romero, Rodolfo Gomez Ponce de Leon, Berenise Carroli, Celina Gialdini, Agustina Ramón Michel, Mercedes Vila Ortiz

“…Informed consent will be obtained from participants. Data will be treated with careful attention to protecting privacy and confidentiality. …”
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Application of Terminal Audio Mixing in Multi-Bandwidth End-to-End Encrypted Voice Conference by Chi-Hung Lien, Ya-Ching Tu, Sheng-Lian Liao, Juei-Chi Chu, Chia-Yu Hsieh, Jyun-Jia Jhang

“…It can be used in low-bandwidth scenarios such as satellite networks. …”
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Analyzing Visitor Behavior to Enhance Personalized Experiences in Smart Museums: A Systematic Literature Review by Rosen Ivanov, Victoria Velkova

“…Behavioral Analytics Platforms and Mobile/Wearable Devices are the most used technologies (42.4%) for delivering personalized content. …”
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Hybrid Convolutional Neural Network-Based Intrusion Detection System for Secure IoT Networks by Sami Qawasmeh, Ahmad Habboush, Bassam Elzaghmouri, Qasem Kharma, Da'ad Albalawneh

“…The training model defines the convolutional layer's structure, sliding window size, neuron connection weights, and outputs using the improved data. The training period is used for attack detection, and the weights are calculated from trained and real-time data. …”
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A qualitative study on the unmet sexual needs of older women by Farzaneh Saadatmand, Mitra Savabi-Esfahani, Zahra Heidari, Marjan Beigi

“…Data were analyzed using the Graneheim and Lundman approach. …”
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Federated learning based reference evapotranspiration estimation for distributed crop fields. by Muhammad Tausif, Muhammad Waseem Iqbal, Rab Nawaz Bashir, Bayan AlGhofaily, Alex Elyassih, Amjad Rehman Khan

“…The study intends to propose ETo estimation of multiple locations with distinct weather conditions using a federated learning approach. Traditional centralized approaches require aggregating all data in one place, which can be problematic due to privacy concerns and data transfer limitations. …”
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A STUDY OF PEOPLE’S PERCEPTION OF ARTIFICIAL INTELLIGENCE IN FINANCE AND SOCIETY by Dan MITRA, Ioana-Florina COITA

“…This paper investigates how people perceive artificial intelligence (AI), using both original survey data and insights from recent academic and policy literature. …”
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AI in humanitarian healthcare: a game changer for crisis response by Diala Haykal, Mohamad Goldust, Hugues Cartier, Patrick Treacy

“…Ethical concerns such as data privacy, bias, and access inequities remain critical to responsible deployment. …”
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Cooperative inference analysis based on DNN convolutional kernel partitioning by Jialin ZHI, Yinglei TENG, Xinyang ZHANG, Tao NIU, Mei SONG

“…With the popularity of intelligent chip in the application of edge terminal devices, a large number of AI applications will be deployed on the edge of networks closer to data sources in the future.The method based on DNN partition can realize deep learning model training and deployment on resource-constrained terminal devices, and solve the bottleneck problem of edge AI computing ability.Thekernel based partition method (KPM) was proposed as a new scheme on the basis of traditional workload based partition method (WPM).The quantitative analysis of inference performance was carried out from three aspects of computation FLOPS, memory consumption and communication cost respectively, and the qualitative analysis of the above two schemes was carried out from the perspective of flexibility, robustness and privacy of inference process.Finally, a software and hardware experimental platform was built, and AlexNet and VGG11 networks were implemented using PyTorch to further verify the performance advantages of the proposed scheme in terms of delay and energy consumption.It was concluded that, compared with the WPM scheme, the KPM scheme had better DNN reasoning acceleration effect in large-scale computing scenarios.And it has lower memory usage and energy consumption.…”
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