AI-Driven Belt Failure Prediction and Prescriptive Maintenance with Motor Current Signature Analysis by João Paulo Costa, José Torres Farinha, Mateus Mendes, Jorge O. Estima

“…Through the integration of motor current signature analysis (MCSA) and machine learning algorithms, particularly long short-term memory (LSTM) networks, this study aims to predict and detect belt degradation in real time. …”
Get full text

Small Sample Fiber Full State Diagnosis Based on Fuzzy Clustering and Improved ResNet Network by Xiangqun Li, Jiawen Liang, Jinyu Zhu, Shengping Shi, Fangyu Ding, Jianpeng Sun, Bo Liu

“…The optical time domain reflectometer (OTDR) curve features of communication fibers exhibit subtle differences among their normal, subhealthy, and faulty operating states, making it challenging for existing machine learning-based fault diagnosis algorithms to extract these minute features. …”
Get full text

Cybersecurity and Major Cyber Threats of Smart Meters: A Systematic Mapping Review by Jones Márcio Nambundo, Otávio de Souza Martins Gomes, Adler Diniz de Souza, Raphael Carlos Santos Machado

“…These gaps include design requirements, software and firmware updates, physical security, the use of big data to detect vulnerabilities, user data privacy, and inconsistencies in machine learning algorithms. …”
Get full text

Special Issue on Contemporary Research Studies in Operations Research, Business Analytics, and Business Intelligence by Viswanath Kumar Ganesan, S. Vinodh, Malolan Sundararaman, M. Vimala Rani, M. Mathirajan

“…Through empirical and statistical analysis, this study identifies top-performing algorithms. A Hybrid Framework for Real-Time Data Drift and Anomaly Identification Using Hierarchical Temporal Memory and Statistical Tests: This paper introduces a hybrid framework combining Hierarchical Temporal Memory and Sequential Probability Ratio Test for real-time data drift detection and anomaly identification. …”
Get full text

AstroM3: A Self-supervised Multimodal Model for Astronomy by M. Rizhko, J. S. Bloom

“…While machine-learned models are now routinely employed to facilitate astronomical inquiry, model inputs tend to be limited to a primary data source (namely images or time series) and, in the more advanced approaches, some metadata. …”
Get full text

Sensing technology for greenhouse tomato production: A systematic review by Jingxin Yu, Jiang Liu, Congcong Sun, Jiaqi Wang, Jianchao Ci, Jing Jin, Ni Ren, Wengang Zheng, Xiaoming Wei

“…Key findings show that deep learning-based multimodal data fusion models significantly improve accuracy in disease detection, facilitating tomato growth monitoring. …”
Get full text

Analysis of Generalization Ability for Different AdaBoost Variants Based on Classification and Regression Trees by Shuqiong Wu, Hiroshi Nagahashi

“…As a machine learning method, AdaBoost is widely applied to data classification and object detection because of its robustness and efficiency. …”
Get full text

Enhanced path planning for robot navigation in Gaussian noise environments with YOLO v10 and depth deterministic strategies by Feng Xiao, Shiwei Chu, Xing Guo, Youhai Zhang, Rubing Huang

“…A reward function is designed to motivate the agent to learn. The weighted average method is used to fuse the visual information of YOLO v10 with LiDAR data. …”
Get full text

Local adaptation and validation of a transdiagnostic risk calculator for first episode psychosis using mental health patient records by Elizabeth Ford, James Stone, James Stone, James Stone, Dominic Oliver, Dominic Oliver, Dominic Oliver, Benjamin Fell, Gloria Roque, Sam Robertson, Paolo Fusar-Poli, Paolo Fusar-Poli, Paolo Fusar-Poli, Paolo Fusar-Poli, Kathryn Greenwood, Kathryn Greenwood

Get full text

A meta-review of remote sensing for rubber plantations by Zilong Yue, Chiwei Xiao

“…Additionally, deep learning improved classification accuracy by 15–20 %, especially in detecting young plantations under six years old. …”
Get full text

Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recog... by Andrea P Garzón-Partida, Kimberly Magaña-Plascencia, Diana Emilia Martínez-Fernández, Joaquín García-Estrada, Sonia Luquin, David Fernández-Quezada

“…Digital health technologies, including wearables and machine learning, show promise for diagnosis, monitoring, and intervention, from relapse prediction to early detection of comorbidities. …”
Get full text

The impact of artificial intelligence on medical diagnostics: A letter to the editor by Sahar Imtiaz, Sheikh Abdul Qadir Jillani

“…By leveraging machine learning algorithms, AI systems can process and analyze large volumes of medical data, including patient records, laboratory results, medical images, and genomic data. …”
Get full text

HOLESOM: Constraining the Properties of Slowly Accreting Massive Black Holes with Self-organizing Maps by Valentina La Torre, Fabio Pacucci

“…We present HOLESOM (HOLESOM is publicly available at: http://github.com/valentinalatorre/holesom ), a machine learning-powered tool based on the self-organizing maps (SOMs) algorithm, specifically designed to identify slowly accreting MBHs using sparse photometric data. …”
Get full text

Variational optimization for quantum problems using deep generative networks by Lingxia Zhang, Xiaodie Lin, Peidong Wang, Kaiyan Yang, Xiao Zeng, Zhaohui Wei, Zizhu Wang

“…Abstract Optimization drives advances in quantum science and machine learning, yet most generative models aim to mimic data rather than to discover optimal answers to challenging problems. …”
Get full text

Early diagnosis of lung cancer using a sensor gas analysis complex: case report by E. O. Rodionov, D. E. Kulbakin, D. V. Podolko, E. V. Obkhodskaya, A. V. Obkhodskiy, S. V. Miller, A. A. Mokh, V. I. Sachkov, A. S. Popov, V. I. Chernov

“…Conclusion. Machine learning algorithms are actively used to diagnose socially significant diseases. the platforms being developed based on arrays of chemical sensors with data analysis using a neural network are promising candidates for implementation in screening activities.…”
Get full text

Knowing Your Users by Heart: A Critical Examination of the Scientific Research on Emotions Conducted by Social Media Platforms by Camille Alloing, Elsa Fortant, Julien Pierre, Fabien Richert, Rémi Palisser

“…Finally, we examine the various methods employed to identify emotions, which primarily serve to feed these platforms’ machine learning algorithms with data labeled as emotional. …”
Get full text

Neuromorphic principles for machine olfaction by Nik Dennler, Aaron True, André van Schaik, Michael Schmuker

Get full text

Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches by Guohua Li, Qian Shi, Qibiao Wu, Xinbing Sui

“…Recent advances in artificial intelligence (AI) have further enhanced the field by improving target prediction and streamlining data analysis. AI-driven models, especially machine learning algorithms, have proven effective in processing complex proteomic data and predicting potential NP-protein interactions. …”
Get full text

Electronic Nose System Based on Metal Oxide Semiconductor Sensors for the Analysis of Volatile Organic Compounds in Exhaled Breath for the Discrimination of Liver Cirrhosis Patient... by Makhtar War, Benachir Bouchikhi, Omar Zaim, Naoual Lagdali, Fatima Zohra Ajana, Nezha El Bari

“…This study included 55 participants: 27 LC patients and 28 HCs. Sensor’s measurement data were analyzed using machine learning techniques, such as principal component analysis (PCA), discriminant function analysis (DFA), and support vector machines (SVMs) that were utilized to uncover meaningful patterns and facilitate accurate classification of sensor-derived information. …”
Get full text

End-to-end multiple object tracking in high-resolution optical sensors of drones with transformer models by Yubin Yuan, Yiquan Wu, Langyue Zhao, Yuqi Liu, Yaxuan Pang

“…Conventional approaches rely heavily on manual feature engineering and intricate algorithms, which can further limit efficiency. To overcome these limitations, we propose a novel Transformer-based end-to-end multi-object tracking framework. …”
Get full text