HiViT-IDS: An Efficient Network Intrusion Detection Method Based on Vision Transformer by Hai Zhou, Haojie Zou, Wei Li, Di Li, Yinchun Kuang

“…As Internet of Things (IoT) technology sees extensive adoption in smart agriculture, smart healthcare, and smart cities, emerging systems are increasingly confronted with complex and dynamic security threats. Intrusion Detection Systems (IDS), a key technology in network security, effectively enhance IoT system safety by detecting and monitoring anomalous activities. …”
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SMART: Semantic, Multi-Objective, and Reinforcement-Based Adversarial Training for Email Spam Detection by Kamal Taha

“…SMART integrates several advanced techniques, including text cleaning and tokenization, word embeddings, K-means clustering for semantic enhancement, multiobjective adversarial training, and reinforcement learning for dynamic spam detection. By leveraging these components, SMART enhances the accuracy and efficiency of detecting and classifying spam emails, even in the face of evolving adversarial tactics. …”
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Spatial Dynamics and Ecological Risk Assessment of Microplastics in Littoral Sediments of the Sea of Marmara, Türkiye by Esra Billur Balcıoğlu İlhan

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A Special Points and Neural Network-Based Dynamic Multi-Objective Optimization Algorithm by Sanyi Li, Wenjie Hou, Peng Liu, Weichao Yue, Qian Wang

“…The FNN is trained with historical special points (knee point, boundary point, center point), and the current special points are generated by the FNN when an environmental change is detected. Then the decision variables are classified into convergence variables and diversity variables. …”
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The impact of MITF expression on tumor-infiltrating lymphocytes in melanoma: Insights into immune microenvironment dynamics by Damir Vučinić, Matea Lekić, Gordana Žauhar, Gordana Zamolo

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Efficient Deep Learning-Based Cyber-Attack Detection for Internet of Medical Things Devices by Abigail Judith, G. Jaspher W. Kathrine, Salaja Silas, Andrew J

“…Machine learning, particularly in cyber-attack detection systems, is crucial for identifying and classifying such attacks. …”
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Early Prediction Detection of Retail and Corporate Credit Risks Using Machine Learning Algorithms by Mohamed A. Hamada, Karim Farag, Adejor E. Abiche

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Anomaly detection using machine learning and adopted digital twin concepts in radio environments by Mohamed Hussien Moharam, Omar Hany, Ahmed Hany, Amenah Mahmoud, Mariam Mohamed, Sohila Saeed

“…This work presents an anomaly detection framework using Digital Twin (DT) technology to simulate and monitor dynamic radio environments. …”
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Detection of Sleep Posture via Humidity Fluctuation Analysis in a Sensor-Embedded Pillow by Won-Ho Jun, Youn-Sik Hong

“…Furthermore, the PELT algorithm was utilized for precise change-point detection. To classify sleep posture, we converted the humidity time series into images and implemented a transfer learning model using a Vision Transformer, achieving a classification accuracy of approximately 96%. …”
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Ransomware detection and family classification using fine-tuned BERT and RoBERTa models by Amjad Hussain, Ayesha Saadia, Faeiz M. Alserhani

“…This research explores these challenges and proposes a novel approach using hyperparameter-optimized transfer learning-based models, Bidirectional Encoder Representations from Transformers (BERT), and a Robustly Optimized BERT Approach (RoBERTa), to not only detect but also classify ransomware targeting IoT devices by analyzing dynamically executed API call sequences in a sandbox environment. …”
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Transformer-Based Deep Learning for Mesoscale Eddy Detection in Sea Surface Temperature Maps by Chen Ji, Wenyang Xu, Xiangtian Zheng, Yasmeen Ahmed, Saad Ahmed Jamal, Fakhar Imam, Mohammed Saleh Ali Muthanna, Maha Ibrahim, Sajid Ullah, Dmitry E. Kucher

“…Mesoscale eddies are dynamic oceanic phenomena significantly influencing marine ecosystems’ energy transfer, nutrients, and biogeochemical cycles. …”
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A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM by Guoli Song, Zheng Huang, Yiwen Zhao, Xingang Zhao, Yunhui Liu, Min Bao, Jianda Han, Peng Li

“…First, image standardization, including size normalization and background removal, is applied to produce standard images; then, the modified dynamic histogram equalization is implemented to enhance the low-contrast standard brain images, and skull removal based on outlier detection is presented. …”
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Hierarchical Deep Learning for Comprehensive Epileptic Seizure Analysis: From Detection to Fine-Grained Classification by Peter Akor, Godwin Enemali, Usman Muhammad, Rajiv Ranjan Singh, Hadi Larijani

“…Epileptic seizure detection and classification from EEG recordings faces significant challenges due to extreme class imbalance. …”
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Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…The present study contributes to this field by enhancing the frequency and accuracy of wildfire detection through advanced techniques for detecting, classifying, and segmenting wildfires using satellite imagery. …”
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SmartRipen: LSTM-GRU feature selection& XGBoost-CNN for fruit ripeness detection by Archana Ganesh Said, Bharti Joshi

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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…The multimodal approach enhances model accuracy, potentially supporting early disease detection and intervention in home settings.…”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…YOLOv11 provides high precision and quick vehicle detection and Deep SORT allows reliable tracking without losing track of individual cars. …”
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Evaluating Large Language Models for Optimized Intent Translation and Contradiction Detection Using KNN in IBN by Muhammad Asif, Talha Ahmed Khan, Wang-Cheol Song

“…Moreover, many methods lack robust validation mechanisms, reducing their reliability in dynamic environments. This research addresses these gaps by evaluating advanced Large Language Models (LLMs) such as BERT-base uncased (BERT-bu), GPT2, LLaMA3, Claude2 and small deep learning model BiLSTM with attention for translating intents and detecting contradictions. …”
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Securing IoT Communications via Anomaly Traffic Detection: Synergy of Genetic Algorithm and Ensemble Method by Behnam Seyedi, Octavian Postolache

“…In the final phase, an ensemble classifier combines the strengths of the Decision Tree, Random Forest, and XGBoost algorithms to achieve the accurate and robust detection of anomalous behaviors. …”
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Analytical assessment of metagenomic workflows for pathogen detection with NIST RM 8376 and two sample matrices by Jason G. Kralj, Stephanie L. Servetas, Samuel P. Forry, Monique E. Hunter, Jennifer N. Dootz, Scott A. Jackson

“…Sequencing and taxonomic classification were used to generate signals for each sample and taxa of interest and to estimate the limit of detection (LOD), the linearity of response, and linear dynamic range. …”
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