AI-driven diagnosis and health management of autonomous electric vehicle powertrains: An empirical data-driven approach by Hicham El hadraoui, Adila El maghraoui, Oussama Laayati, Erroumayssae Sabani, Mourad Zegrari, Ahmed Chebak

“…Among the models, the optimized neural network combined with CA-selected features achieved the most consistent diagnostic performance, supported by low root mean square error and balanced evaluation metrics. …”
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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

“…Using the IoT23 dataset, which contains a wide range of network traffic patterns from various IoT devices and malware families, the research explores and evaluates multiple machine learning techniques. …”
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A Novel Lightweight Framework for Non-Contact Broiler Face Identification in Intensive Farming by Bin Gao, Yongmin Guo, Pengshen Zheng, Kaisi Yang, Changxi Chen

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LEO mega-constellation network:networking technologies and state of the art by Quan CHEN, Lei YANG, Jianming GUO, Xingchen LI, Yong ZHAO, Xiaoqian CHEN

“…The emerging low earth orbit (LEO) mega-constellation network (MCN) represented by Starlink and OneWeb were studied.The system architecture and basic working modes were introduced, and the main features of the emerging broadband MCN were summarized.Based on the system architecture of MCN, the methodology and research progress of five key technologies were investigated and summarized, including network topology dynamics management, space-ground handover scheme, high-efficiency routing algorithm design, gateway placement design, network simulation and performance evaluation.The focus was on recent mega-constellation-related studies.The challenges caused by the large scale and complexity of MCN and the applicability of existing techniques and solutions in MCN were analyzed.…”
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Decom-UNet3+: A Retinal Vessel Segmentation Method Optimized With Decomposed Convolutions by Qun Li, Juntao Zhang, Licheng Hua, Songyin Fu, Chenjie Gu

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YOLO-LSD: A Lightweight Object Detection Model for Small Targets at Long Distances to Secure Pedestrian Safety by Ming-An Chung, Sung-Yun Chai, Ming-Chun Hsieh, Chia-Wei Lin, Kai-Xiang Chen, Shang-Jui Huang, Jun-Hao Zhang

“…The proposed model integrates the C3C2 and the new Efficient Layer Aggregation Network - Convolutional Block Attention Module(ELAN-CBAM) modules to improve the efficiency of feature extraction while reducing computational overhead. …”
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I2DNet - Design and real-time evaluation of an appearance-based gaze estimation system by L R D Murthy, Siddhi Brahmbhatt, Somnath Arjun, Pradipta Biswas

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Evaluation of Post Hoc Uncertainty Quantification Approaches for Flood Detection From SAR Imagery by Jakob Ludwig, Ronny Hansch

“…In particular when these predictions are used by human decision makers in high stake scenarios, e.g., during detection and monitoring of natural disasters, trustworthiness is a necessary feature. In the context of flood detection from SAR imagery, this work evaluates a variety of uncertainty quantification methods that are applicable to already trained models (i.e., post hoc approaches) and provides detailed experiments evaluating the quantification quality of the different methods. …”
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Comparison and Analysis of Network Construction Methods for Seismicity Based on Complex Networks by Xuan He, Syed Bilal Hussain Shah, Bo Wei, Zheng Liu

“…By using the same dataset from the Southern California Seismic Network, three networks are constructed. They all present the scale-free, small-world properties, a strength-degree correlation, and an assortative mixing feature. …”
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Scene Semantic Recognition Based on Modified Fuzzy C-Mean and Maximum Entropy Using Object-to-Object Relations by Ahmad Jalal, Abrar Ahmed, Adnan Ahmed Rafique, Kibum Kim

“…An Artificial Neural Network recognizes the multiple objects using the different patterns of objects. …”
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Deep Learning-Based Semantic Segmentation for Objective Colonoscopy Quality Assessment by Radu Alexandru Vulpoi, Adrian Ciobanu, Vasile Liviu Drug, Catalina Mihai, Oana Bogdana Barboi, Diana Elena Floria, Alexandru Ionut Coseru, Andrei Olteanu, Vadim Rosca, Mihaela Luca

“…<b>Background:</b> This study aims to objectively evaluate the overall quality of colonoscopies using a specially trained deep learning-based semantic segmentation neural network. …”
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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…From the results measured by evaluation metrics, the proposed model ANN with the combination of parameter tuning, feature selection algorithm, SMOTE-ENN, and optimal hyper-parameters demonstrates superior performance compared to traditional methods, achieving an F1 Score of 98.5% and an accuracy of 98.6%. …”
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Evaluating the impact of hyperparameters on the performance of 1D CNN model for nutritional profiling of underutilized crops using NIRS data by Simardeep Kaur, Naseeb Singh, Amit Kumar, Philanim W S, Veerendra Kumar Verma, Amit Kumar Patil, Rakesh Bhardwaj, Amritbir Riar

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EVALUATION OF OPERATIONAL RELIABILITY AND EFFICIENCY OF PRIMARY DESIGNS OF PULSE SUPERCHARGERS USING HYDRAULIC SHOCK ENERGY by A. N. Makeev

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Quantum neural network-based approach for optimizing road network selection by Haohua Zheng, Heying Li, Jianchen Zhang, Guangxia Wang, Jianzhong Guo, Jiayao Wang

“…Our study delves into the impact of feature encoding methods and circuit structures on the performance of quantum neural networks in road selection. …”
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LANet for medical image segmentation by Di Zhao, Yi Tang, D. Y. Pertsau, A. B. Gourinovitch, D. V. Kupryianava

“…The paper presents an original LANet model for improving medical image segmentation results based on MobileViT neural network. The developed and integrated Efficient Fusion Attention and Adaptive Feature Fusion blocks improve the quality of feature extraction and reduce data redundancy. …”
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A recurrent multimodal sparse transformer framework for gastrointestinal disease classification by V. Sharmila, S. Geetha

“…The approach integrates clinical text and WCE images using a robust multi-modal fusion strategy that incorporates Bio-RoBERTa for textual feature extraction, a graph vision spatial channel attention transformer network for image feature learning, and cross-attention mechanisms for modality alignment. …”
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HD-6mAPred: a hybrid deep learning approach for accurate prediction of N6-methyladenine sites in plant species by Huimin Li, Wei Gao, Yi Tang, Xiaotian Guo

“…Secondly, a hold-out search strategy was employed to identify the optimal features or feature combinations for both BiGRU and CNN. …”
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Morphology and dynamics of sporadic E layers observed by amateur radio by WenYu Hao, Tao Yu, Yang-Yi Sun, Jin Wang, LiHui Qiu

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DDoS classification of network traffic in software defined networking SDN using a hybrid convolutional and gated recurrent neural network by Ahmed M. Elshewey, Safia Abbas, Ahmed M. Osman, Eman Abdullah Aldakheel, Yasser Fouad

“…This paper presents a comprehensive evaluation of six deep learning models (Multilayer Perceptron (MLP), one-dimensional Convolutional Neural Network (1D-CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), and a proposed hybrid CNN-GRU model) for binary classification of network traffic into benign or attack classes. …”
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