Building Equi-Width Histograms on Homomorphically Encrypted Data by Dragoș Lazea, Anca Hangan, Tudor Cioara

“…To overcome the challenges posed by homomorphic encryption, we redesign the traditional histogram construction algorithm, optimizing it for secure computation by addressing constraints related to nested loops and conditional statements. …”
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Design and Simulation of a Four-Legged Mobile Robot for Autonomous Navigation on a Spacecraft Hull by Motaz Hassan, Kayla Dremann, Ashton Orosa, Emily Metzger, Nathan Doty, Julia Patek, Siamak Farhad, Ajay Mahajan

“…The robot demonstrated the ability to follow the computed optimal path with a positional deviation of less than 0.5% by the third trial. …”
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YOLO-MES: An Effective Lightweight Underwater Garbage Detection Scheme for Marine Ecosystems by Chengxu Huang, Wenyuan Zhang, Beitian Zheng, Jiahao Li, Bochen Xie, Ruisi Nan, Zongming Tan, Baohua Tan, Neal N. Xiong

“…To address this issue, this paper introduces YOLO-MES, an innovative underwater debris detection algorithm that integrates a lightweight design and a feature enhancement mechanism to enable efficient model deployment while preserving high accuracy. …”
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Semantic Segmentation-Driven Knowledge Distillation-Based Infrared Visible Image Fusion Framework by Xingshuo Wang

“…However, many existing fusion algorithms overly emphasize visual quality and traditional statistical evaluation metrics while neglecting the requirements of real-world applications, especially in high-level vision tasks. …”
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Applications, Challenges, and Future Perspectives of Artificial Intelligence in Psychopharmacology, Psychological Disorders and Physiological Psychology: A Comprehensive Review by Mohammad Hossein Salemi, Elham Foroozandeh, Molouk Khademi Ashkzari

“…However, challenges persist, including data privacy, algorithmic bias, ethical dilemmas, and regulatory hurdles, emphasizing the need for robust governance. …”
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Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy by Tobias Schraut, Anne Schützenberger, Tomás Arias-Vergara, Melda Kunduk, Matthias Echternach, Stephan Dürr, Julia Werz, Michael Döllinger

“…A videoendoscopic model was developed by selecting a suitable classification algorithm and a minimal-optimal subset of glottal parameters. …”
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Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

“…The integration of these advanced algorithms accurately identified defects and categorized them, thus optimizing manufacturing processes. …”
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Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

“…Ten machine learning (ML) algorithms were applied to construct multi-task prediction models. …”
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Increasing load factor in logistics and evaluating shipment performance with machine learning methods: A case from the automotive industry by Raziye Kılıç Sarıgül, Burak Erkayman, Bilal Usanmaz

“…To solve this problem, both supervised and unsupervised learning algorithms were applied. First, unsupervised clustering algorithms were used to group the shipment performance based on similarities. …”
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An edge awareness-enhanced visual SLAM method for underground coal mines by Qi MU, Xin LIANG, Yuanjie GUO, Yuhao WANG, Zhanli LI

“…Specifically, line features were extracted using the EDLines algorithm, while point features were extracted using the Oriented FAST and Rotated BRIEF (ORB) algorithms. …”
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MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network by Yi Zhang, Wei Song, Mingyue Shao, Xiangchun Liu

“…Lower-resolution features are more sensitive to larger objects closer to the camera, while higher-resolution features are more efficient for smaller objects further away. …”
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The role of precision tool positioning in enhancing machining accuracy by Tuyboyov Oybek, Baydullayev Azamat, Jeltuxin Andrey, Muxiddinov Zayniddin

“…Furthermore, the application of Setup-Maps (S-Maps) and Tolerance-Maps (T-Maps) optimized fixture design, reducing setup time by 25% and improving machining precision by 30%. …”
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Hybrid feedback control of PMSG-based WECS with multilevel flying-capacitor inverter enhanced by fractional order extremum seeking by Younes El Khlif, Abdelmounime El Magri, Rachid Lajouad, Omar Bouattane

“…The use of fractional-order calculus leads to improved convergence and more seamless performance while preserving the robust characteristics of the system. …”
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YED-Net: Yoga Exercise Dynamics Monitoring with YOLOv11-ECA-Enhanced Detection and DeepSORT Tracking by Youyu Zhou, Shu Dong, Hao Sheng, Wei Ke

“…A dynamic adaptive anchor mechanism and an Efficient Channel Attention (ECA) module are introduced, while the depthwise separable convolution in the C3k2 module is optimized with a kernel size of 2. …”
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AI and Machine Learning in V2G technology: A review of bi-directional converters, charging systems, and control strategies for smart grid integration by Nagarajan Munusamy, Indragandhi Vairavasundaram

“…We explore the potential of Artificial Intelligence (AI) and Machine Learning (ML) algorithms to optimize V2 G performance. By leveraging AI and ML, we can improve the efficiency, reliability, and scalability of V2 G systems. …”
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Relay-Assisted Wireless Sensor Networks Using KNN-DBSCAN Static Clustering by Thierry Taning Longla, Tansal Gucluoglu, Tamer Dag

“…To address this challenge, we propose KDL, a novel hybrid clustering algorithm that combines K-Nearest Neighbor (KNN) and Density-Based Spatial Clustering (DBSCAN) to optimize energy efficiency in WSNs. …”
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Blockchain based solid waste classification with AI powered tracking and IoT integration by Aliaa M. Alabdali

“…IoT-connected bins transmit data to a central server, which uses blockchain to ensure secure, transparent data storage. AI algorithms, including machine learning (ML) and deep learning (DL), classify waste in real-time, optimizing waste collection and recycling. …”
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Implementation of XGBoost Models for Predicting CO₂ Emission and Specific Tractor Fuel Consumption by Nebojša Balać, Zoran Mileusnić, Aleksandra Dragičević, Mihailo Milanović, Andrija Rajković, Rajko Miodragović, Olivera Ećim-Đurić

“…Although not optimized for high precision, these models offer a valuable basis for preliminary assessments and highlight the potential of data-driven approaches for improving energy efficiency and environmental sustainability in agricultural mechanization.…”
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The role of nanomedicine and artificial intelligence in cancer health care: individual applications and emerging integrations—a narrative review by Prasanthi Samathoti, Rajasekhar Komarla Kumarachari, Sarad Pawar Naik Bukke, Eashwar Sai Komarla Rajasekhar, Ashish Ashokkumar Jaiswal, Zohre Eftekhari

“…Nanomedicine leverages nanoparticles for targeted drug delivery, enhancing therapeutic efficacy while minimizing adverse effects. Concurrently, AI algorithms facilitate early cancer detection, personalized treatment planning, and predictive analytics, thereby optimizing clinical outcomes. …”
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Benefits and Challenges of AI-Based Digital Twin Integration in the Saudi Arabian Construction Industry: A Correspondence Analysis (CA) Approach by Aljawharah A. Alnaser, Haytham Elmousalami

“…However, several challenges hinder the realization of these benefits, including a lack of standardization of integrated DT and AI in construction projects, a lack of understanding of AI’s capabilities, a lack of logistics and the limited availability of IT infrastructure, and the complexity of AI algorithms. These findings underscore the transformative potential of integrating AI-driven DTs to optimize construction performance, improve decision-making, and address real-world complexities. …”
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