Systematic Approach for Malware Detection in IoT Devices: Enhancing Security and Performance by Vasudeva Pai, B. H. Karthik Pai, G. S. Sudhiksha, Vandya Kamath, K. Varsha, S. Manjunatha

“…Abstract The proliferation of Internet of Things (IoT) devices has introduced significant security challenges, particularly concerning the detection and mitigation of malware threats. This study presents a systematic approach to malware detection that aims to improve both the security and performance of IoT systems. …”
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Lightweight Multi-Task Learning Method for System Log Anomaly Detection by Tuan-Anh Pham, Jong-Hoon Lee

“…Log anomaly detection is a crucial task in monitoring IT systems along with metrics and traces. …”
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Pedestrian dynamics modeling and social force analysis based on object detection by Fangyan Yang, Rong Liu, Daoyu Zhu

“…IntroductionObject detection is a fundamental component of modern computational applications, playing a crucial role in pedestrian analysis, autonomous navigation, and crowd monitoring. …”
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Detection of single and dual pulmonary diseases using an optimized vision transformer by Almughamisi Naif, Abosamra Gibrael, Albar Adnan, Saleh Mostafa

“…Chest X-rays (CXRs) serve as a critical diagnostic tool for identifying lung diseases; however, many pulmonary conditions exhibit similar patterns on CXRs, making differentiation challenging even for experienced radiologists. …”
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Formulation of solution to prevent lysis time erythrocyte and detecting blood type by Ria Amelia, Elfira Maya Sari

“…The solution with the most extended stability was further tested for ABO blood grouping using the tube method to analyze agglutination patterns. Results: The test solution that can maintain erythrocytes for a long time is the citrate phosphate dextrose (CPD) solution. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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Detection of Abnormal Symptoms Using Acoustic-Spectrogram-Based Deep Learning by Seong-Yoon Kim, Hyun-Min Lee, Chae-Young Lim, Hyun-Woo Kim

“…These findings demonstrate the effectiveness of spectrogram-based deep learning models in identifying latent patterns within acoustic data and detecting abnormal symptoms. …”
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Detecting Black-Box Model Probing Attacks Through Probability Scores by Yongzhi Wang, Ahsan Habib, Likhitha Reddy Kesara, Brahmarshi Jasti, Renjie Hu, Tejasv Singh

“…Our research discovered that the sequences of top-2 probability scores generated by different model probing attacks form distinct patterns that can be detected through time-series classification methods, such as Transformer and Bidirectional Long Short-Term Memory (BiLSTM). …”
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Multimodal Deep Learning in Early Autism Detection—Recent Advances and Challenges by Sheril Sophia Dcouto, Jawahar Pradeepkandhasamy

“…Deep learning models, with their ability to analyze complex patterns and extract meaningful features from large datasets, offer great promise in addressing the challenge of early ASD detection. …”
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Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

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Heterogeneous Graph Neural Network Framework for Session-Based Cyberbullying Detection by Munkhbuyan Buyankhishig, Thanda Shwe, Israel Mendonca, Masayoshi Aritsugi

“…Consequently, critical patterns and insights within sessions may be overlooked. …”
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Optimized driver fatigue detection method using multimodal neural networks by Shengli Cao, Peihua Feng, Wei Kang, Zeyi Chen, Bo Wang

“…This dynamic interaction between features enhances the model’s ability to capture complex patterns associated with driver fatigue, leading to superior performance. …”
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Neuropathic Pain Detection: An EEG-Based Brain Functional Network Approach by Abdulyekeen T. Adebisi, Ho-Won Lee, Kalyana C. Veluvolu

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Personalizing Seizure Detection for Individual Patients by Optimal Selection of EEG Signals by Rosanna Ferrara, Martino Giaquinto, Gennaro Percannella, Leonardo Rundo, Alessia Saggese

“…These channels are automatically selected using a data-driven mechanism that identifies the most informative scalp regions based on each patient’s unique seizure patterns. The proposed approach ensures high reliability, even with small datasets, and improves interpretability for clinicians by overcoming the limitations of more complex methods. …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…This study aims to identify the best deep learning and machine learning models to identify the unethical behavior patterns of learners using distance education exam data of an educational institution. …”
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Botnet detection in internet of things using stacked ensemble learning model by Mudasir Ali, Muhammad Faheem Mushtaq, Urooj Akram, Daniel Gavilanes Aray, Manuel Masias Vergara, Hanen Karamti, Imran Ashraf

“…Despite existing approaches for cyber attack detection, botnets prove to be a particularly difficult problem that calls for more advanced detection methods. …”
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Electrothermal Modeling of Photovoltaic Modules for the Detection of Hot-Spots Caused by Soiling by Peter Winkel, Jakob Smretschnig, Stefan Wilbert, Marc Röger, Florian Sutter, Niklas Blum, José Antonio Carballo, Aránzazu Fernandez, Maria del Carmen Alonso-García, Jesus Polo, Robert Pitz-Paal

“…Furthermore, the model is capable of predicting which soiling pattern can cause critical hot-spots.…”
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First Detection of <i>Lactococcus petauri</i> in Domestic Dogs in Italy by Simona Sciuto, Giuseppe Esposito, Paolo Pastorino, Khalid Shahin, Katia Varello, Eliana Trabunella, Giulia Milanese, Sonia Scala, Marino Prearo, Pier Luigi Acutis, Angelo Salerno, Simona Zoppi, Silvia Colussi

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Atrial fibrillation detection via contactless radio monitoring and knowledge transfer by Yuqin Yuan, Jinbo Chen, Dongheng Zhang, Ruixu Geng, Hanqin Gong, Guixin Xu, Yu Pu, Zhi Lu, Yang Hu, Dong Zhang, Likun Ma, Qibin Sun, Yan Chen

“…Our approach analyzes the mechanical motion of the heart using radar sensing and leverages AI-powered knowledge transfer from established clinical ECG diagnostic practices to read AF-associated motion patterns precisely. Our system is evaluated on 6258 outpatient visitors, including 229 with AF, and achieves AF detection with a sensitivity of 0.844 (95% Confidence Interval (CI), 0.790-0.884) and a specificity of 0.995 (95% CI, 0.993-0.997), which is comparable to the performance of ECG-based methods. …”
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Explainable MRI-Based Ensemble Learnable Architecture for Alzheimer’s Disease Detection by Opeyemi Taiwo Adeniran, Blessing Ojeme, Temitope Ezekiel Ajibola, Ojonugwa Oluwafemi Ejiga Peter, Abiola Olayinka Ajala, Md Mahmudur Rahman, Fahmi Khalifa

“…For the present study, it is a major drawback to the deployment of deep learning methods mandated with detecting patterns and prognosticating Alzheimer’s disease. …”
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