Towards precision in IoT-based healthcare systems: a hybrid optimized framework for big data classification by Satheeshkumar Palanisamy, Vigneshwaran Thangaraju, Jeevitha Kandasamy, Ayodeji Olalekan Salau

“…However, traditional machine learning models often struggle with issues such as data imbalance, redundant features, and noise, limiting their reliability in clinical diagnostics. …”
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Development of an analog topology for a multi-layer neuronal network by Luã da Porciuncula Estrela, Marlon Soares Sigales, Elmer A. Gamboa Peñaloza, Marcelo Lemos Rossi, Mateus Beck Fonseca

“…This paper presents a novel approach to implementing artificial neural networks (ANNs) using analog circuits with counter circuits for storing and updating the weights and biases. …”
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The Role of Digital Twin in 6G-Based URLLCs: Current Contributions, Research Challenges, and Next Directions by Antonino Masaracchia, Dang van Huynh, Trung Q. Duong, Octavia A. Dobre, Arumugam Nallanathan, Berk Canberk

“…However, the integration of these technologies presents new optimization challenges, particularly for ensuring network reliability and maintaining stringent latency requirements. …”
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Automatic Extraction of Water Body from SAR Images Considering Enhanced Feature Fusion and Noise Suppression by Meijun Gao, Wenjie Dong, Lifu Chen, Zhongwu Wu

“…In the middle-level feature fusion stage, the Attention Feature Fusion module (AFFM) is presented for multi-scale feature learning to improve the performance of fine water segmentation. …”
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Leveraging Neural Trojan Side-Channels for Output Exfiltration by Vincent Meyers, Michael Hefenbrock, Dennis Gnad, Mehdi Tahoori

“…To achieve low latency and high efficiency, field-programmable gate arrays (FPGAs) are increasingly being employed as accelerators for neural network inference in cloud and edge devices. However, the rising costs and complexity of neural network training have led to the widespread use of outsourcing of training, pre-trained models, and machine learning services, raising significant concerns about security and trust. …”
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An Optimised CNN Hardware Accelerator Applicable to IoT End Nodes for Disruptive Healthcare by Arfan Ghani, Akinyemi Aina, Chan Hwang See

“…In the evolving landscape of computer vision, the integration of machine learning algorithms with cutting-edge hardware platforms is increasingly pivotal, especially in the context of disruptive healthcare systems. …”
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An Efficient Parallelization of Microscopic Traffic Simulation by Benyamin Heidary, Joerg Schweizer, Ngoc An Nguyen, Federico Rupi, Cristian Poliziani

“…The average speeds and waiting times are similar to the results from an established microsimulator (SUMO), but the execution time is up to 5000 times faster with respect to SUMO; the 28 million trips of the 24 h San Francisco Bay Area scenario was completed in 26 min. With cutting-edge GPUs, the simulation speed can possibly be further reduced by a factor of seven; (4) Conclusions: The parallelized simulator presented in this paper can perform large-scale microsimulations in a reasonable time on readily available and inexpensive computer hardware. …”
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Neural Network Optimization of Mechanical Properties of ABS-like Photopolymer Utilizing Stereolithography (SLA) 3D Printing by Abdulkader Ali Abdulkader Kadauw

“…The optimization of mechanical properties in acrylonitrile butadiene styrene-like (ABS-like) photopolymer utilizing neural network techniques presents a promising methodology for enhancing the performance and strength of components fabricated through stereolithography (SLA) 3D printing. …”
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Innovative Sentiment Analysis and Prediction of Stock Price Using FinBERT, GPT-4 and Logistic Regression: A Data-Driven Approach by Olamilekan Shobayo, Sidikat Adeyemi-Longe, Olusogo Popoola, Bayode Ogunleye

“…This study explores the comparative performance of cutting-edge AI models, i.e., Finaance Bidirectional Encoder representations from Transsformers (FinBERT), Generatice Pre-trained Transformer GPT-4, and Logistic Regression, for sentiment analysis and stock index prediction using financial news and the NGX All-Share Index data label. …”
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Enhancing Underwater Video from Consecutive Frames While Preserving Temporal Consistency by Kai Hu, Yuancheng Meng, Zichen Liao, Lei Tang, Xiaoling Ye

“…To address these issues, this paper presents a dual-branch underwater video enhancement network. …”
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Analog Computing for Nonlinear Shock Tube PDE Models: Test and Measurement of CMOS Chip by Hasantha Malavipathirana, Soumyajit Mandal, Nilan Udayanga, Yingying Wang, S. I. Hariharan, Arjuna Madanayake

“…Analog CMOS has power efficiency advantages over digital CMOS for low-precision applications in edge computing, scientific computing, and artificial intelligence/machine learning (AI/ML) verticals. …”
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Synthesis and evaluation of seamless, large-scale, multispectral satellite images using Generative Adversarial Networks on land use and land cover and Sentinel-2 data by Torben Dedring, Andreas Rienow

“…Artificial intelligence (AI) began to make its way into geoinformation science several decades ago and since then has constantly brought forth new cutting-edge approaches for diverse geographic use cases. …”
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Revolutionizing climbing perch disease management: AI-Driven solutions for sustainable aquaculture by Kosit Sriputhorn, Rapeepan Pitakaso, Surasak Matitopanum, Peerawat Luesak, Surajet Khonjun, Rungwasun Kraiklang, Chakat Chueadee, Sarayut Gonwirat

“…We present the Climbing Perch Disease Detection and Classification System (CPDDCS), employing cutting-edge imaging and deep learning technologies to automate disease detection. …”
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Surface distributions and vertical profiles of trace gases (CO, O₃, NO, NO₂) in the Arctic wintertime boundary layer using low-cost sensors during ALPACA-2022 by B. Barret, P. Medina, N. Brett, R. Pohorsky, K. S. Law, S. Bekki, G. J. Fochesatto, J. Schmale, S. R. Arnold, A. Baccarini, M. Busetto, M. Cesler-Maloney, B. D'Anna, S. Decesari, J. Mao, G. Pappaccogli, J. Savarino, F. Scoto, W. R. Simpson

“…The MICRO sensors for MEasurements of GASes (MICROMEGAS) instrument set up with CO, NO, NO<span class="inline-formula">₂</span>, and O<span class="inline-formula">₃</span> EGSs was operated on the ground at an outdoor reference site in downtown Fairbanks for calibration, while on board a vehicle moving through the city and its surroundings and on board a tethered balloon, the helikite, at a site at the edge of the city. To calibrate the measurements, a set of machine learning (ML) calibration methods were tested. …”
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A novel approach for detecting malicious hosts based on RE-GCN in intranet by Haochen Xu, Xiaoyu Geng, Junrong Liu, Zhigang Lu, Bo Jiang, Yuling Liu

“…Lastly, the traditional graph neural network model has limitations in processing edge information and is unable to directly learn the information in netflow. …”
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Modeling seismic hazard and landslide occurrence probabilities in northwestern Yunnan, China: exploring complex fault systems with multi-segment rupturing in a block rotational tec... by J. Cheng, C. Xu, X. Xu, S. Zhang, P. Zhu

“…This presents significant seismic hazards, particularly due to the potential for multi-segment ruptures and resulting landslides. …”
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Tree species classification using intensity patterns from individual tree point clouds by Andreas Tockner, Ralf Kraßnitzer, Christoph Gollob, Sarah Witzmann, Tim Ritter, Arne Nothdurft

“…Personal laser scanning has evolved into a cutting-edge technology for obtaining fast and accurate biometric measurements of individual trees in a forest. …”
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Artificial intelligence enabled smart design and manufacturing of advanced materials: The endless Frontier in AI+ era by William Yi Wang, Suyang Zhang, Gaonan Li, Jiaqi Lu, Yong Ren, Xinchao Wang, Xingyu Gao, Yanjing Su, Haifeng Song, Jinshan Li

“…A case study of AI agent assistant welding is presented, which is consisted of the large language model, auto‐coding via AI agent, image processing, image mosaic, and machine learning for welding defect detection. …”
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Lung Segmentation with Lightweight Convolutional Attention Residual U-Net by Meftahul Jannat, Shaikh Afnan Birahim, Mohammad Asif Hasan, Tonmoy Roy, Lubna Sultana, Hasan Sarker, Samia Fairuz, Hanaa A. Abdallah

“…This article presents a DL-based approach to accurately identify the lung mask region in CXR images to assist radiologists in recognizing early signs of high-risk lung diseases. …”
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Power transmission system’s fault location, detection, and classification: Pay close attention to transmission nodes by Chiagoziem C. Ukwuoma, Dongsheng Cai, Olusola Bamisile, Ejiyi J. Chukwuebuka, Ekong Favour, Gyarteng S.A. Emmanuel, Acen Caroline, Sabirin F. Abdi

“…This study, therefore, presents a fault localization, detection, and classification model for transmission systems that concentrate on the key distribution nodes. …”
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