Applications of Machine Learning in Food Safety and HACCP Monitoring of Animal-Source Foods by Panagiota-Kyriaki Revelou, Efstathia Tsakali, Anthimia Batrinou, Irini F. Strati

“…Integrating advanced computing techniques into food safety management has attracted significant attention recently. …”
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Ternary Toward Binary: Circuit-Level Implementation of Ternary Logic Using Depletion-Mode and Conventional MOSFETs by Hyundong Lee, Seonghoon Kim, Jongbeom Kim, Jaehoon Jeong, Jeonggyu Yang, Taigon Song

“…We also propose the first methodology to design a ternary cell layout in multi-height standard cell design. We propose an algorithm for the best ternary cell layout and a concept of integrated layout that reduces area when required cells are close to each other.…”
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Intelligent optimization of fracturing stage and cluster parameters for tight oil reservoir by Huiying Tang, Qi Ruan, Liehui Zhang, Dandan Hu, Jianhua Qin, Yulong Zhao, Yiping Ye

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Emerging Diagnostic Approaches for Musculoskeletal Disorders: Advances in Imaging, Biomarkers, and Clinical Assessment by Rahul Kumar, Kiran Marla, Kyle Sporn, Phani Paladugu, Akshay Khanna, Chirag Gowda, Alex Ngo, Ethan Waisberg, Ram Jagadeesan, Alireza Tavakkoli

“…Artificial intelligence and machine learning algorithms now automate image interpretation, predict clinical outcomes, and enhance clinical decision support, complementing conventional clinical evaluations. …”
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Intelligent Network-Level Energy Saving Strategy With STGNN-Driven Traffic Prediction and Path Optimization in Transport Networks and Field Trial by Xinyu Chen, Liuyan Han, Minxue Wang, Jiang Sun, Yong Gao, Xuegang Ou, Dechao Zhang, Han Li

“…The proposed approach integrates AI-driven traffic prediction with intelligent resource allocation, where the STGNN model captures complex spatiotemporal traffic patterns over joint port-tunnel traffic modeling across large-scale network elements, achieving prediction accuracy with a 19.44% improvement over traditional LSTM models. …”
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A robust approach to satellite image encryption using chaotic map and circulant matrices by Shamsa Kanwal, Saba Inam, Asghar Ali Shah, Halima Iqbal, Anas Bilal, Muhammad Usman Hashmi, Raheem Sarwar

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Leveraging Thermal Infrared Imaging for Pig Ear Detection Research: The TIRPigEar Dataset and Performances of Deep Learning Models by Weihong Ma, Xingmeng Wang, Simon X. Yang, Lepeng Song, Qifeng Li

“…Establishing the TIRPigEar dataset is highly significant, as it allows for a valuable resource for AI and precision livestock farming researchers to validate and improve their algorithms. …”
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Modify a dual ridge horn antenna for drone jamming applications by Alaa Hussein Hilal, Ahmed Hameed Reja, Mohammed J. Mohammed

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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

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Embedded Hardware-Efficient FPGA Architecture for SVM Learning and Inference by B. B. Shabarinath, Muralidhar Pullakandam

“…Edge computing allows to do AI processing on devices with limited resources, but the challenge remains high computational costs followed by the energy limitations of such devices making on-device machine learning inefficient, especially for Support Vector Machine (SVM) classifiers. …”
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Machine Learning-Augmented Triage for Sepsis: Real-Time ICU Mortality Prediction Using SHAP-Explained Meta-Ensemble Models by Hülya Yilmaz Başer, Turan Evran, Mehmet Akif Cifci

“…Our hybrid modeling approach integrates ensemble-based ML algorithms with deep learning architectures, optimized through the Red Piranha Optimization algorithm for feature selection and hyperparameter tuning. …”
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Hybrid intelligence framework for optimizing shear capacity of lightweight FRP-reinforced concrete beams by Iman Faridmehr, Moncef L. Nehdi, Mohammad Ali Sahraei, Kiyanets Aleksandr Valerievich, Chiara Bedon

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Air quality and dust level monitoring systems in hospitals using IoT by A. Parkavi, B. J. Sowmya, Sini Anna Alex, S. Supreeth, G. Shruthi, S. Rohith, Sudipta Chatterjee, K. Lingaraj

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Automatic Detect Incorrect Lifting Posture with the Pose Estimation Model by Gee-Sern Jison Hsu, Jie Syuan Wu, Yin-Kai Dean Huang, Chun-Chieh Chiu, Jiunn-Horng Kang

“…We used the OpenPose algorithm to detect and extract key body points to calculate relevant biomechanical features. …”
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Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data by Nicholas Fiorentini, Massimo Losa

“…The findings highlight the importance of integrating multi-source remote sensing data with advanced AI-based techniques to develop cost-effective, automated, and scalable solutions for road authorities. …”
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Ethics, Animal Welfare, and Artificial Intelligence in Livestock: A Bibliometric Review by Taize Calvacante Santana, Cristiane Guiselini, Héliton Pandorfi, Ricardo Brauer Vigoderis, José Antônio Delfino Barbosa Filho, Rodrigo Gabriel Ferreira Soares, Maria de Fátima Araújo, Nicoly Farias Gomes, Leandro Dias de Lima, Paulo César da Silva Santos

“…This study presents a bibliometric review aimed at mapping and analyzing the scientific literature related to the ethical implications of artificial intelligence (AI) in livestock farming, which is a rapidly emerging yet still underexplored field in international research. …”
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Segmentation of CAD models using hybrid representation by Claude Uwimana, Shengdi Zhou, Limei Yang, Zhuqing Li, Norbelt Mutagisha, Edouard Niyongabo, Bin Zhou

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Automated Lightweight Model for Asthma Detection Using Respiratory and Cough Sound Signals by Shuting Xu, Ravinesh C. Deo, Oliver Faust, Prabal D. Barua, Jeffrey Soar, Rajendra Acharya

“…<b>Methods:</b> To build an automated, lightweight model for asthma detection, tested separately with respiratory and cough sounds to assess their suitability for detecting asthma and COPD, the proposed AI models integrate the following ML algorithms: RF, SVM, DT, NN, and KNN, with an overall aim to demonstrate the efficacy of the proposed method for future clinical use. …”
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Advancements in deep learning for early diagnosis of Alzheimer’s disease using multimodal neuroimaging: challenges and future directions by Muhammad Liaquat Raza, Muhammad Liaquat Raza, Muhammad Liaquat Raza, Syed Tawassul Hassan, Subia Jamil, Noorulain Hyder, Kinza Batool, Sajidah Walji, Muhammad Khizar Abbas

“…Recent advancements in deep learning algorithms applied to multimodal brain imaging offer promising solutions for improving diagnostic accuracy and predicting disease progression.MethodThis narrative review synthesizes current literature on deep learning applications in Alzheimer’s disease diagnosis using multimodal neuroimaging. …”
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Comparison of clinical nasal endoscopy, optical biopsy, and artificial intelligence in early diagnosis and treatment planning in laryngeal cancer: a prospective observational study by Ruifang Hu, Xianping Liu, Yong Zhang, Clement Arthur, Dongguang Qin

“…The patients were assessed using one or more optical biopsy techniques (Narrow Band Imaging [NBI], SPIES, or ISCAN), depending on available equipment and whether the lesions were visible. AI algorithms were retrospectively applied to endoscopic images to categorize lesions as cancerous or non-cancerous depending on vascular, textural, and color characteristics. …”
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