AI Roles in 4R Crop Pest Management—A Review by Hengyuan Yang, Yuexia Jin, Lili Jiang, Jia Lu, Guoqi Wen

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Rolling Bearing Fault Diagnosis Based on SCNN and Optimized HKELM by Yulin Wang, Xianjun Du

“…The issue of insufficient multi-scale feature extraction and difficulty in accurately classifying fault features in rolling bearing fault diagnosis is addressed by proposing a novel diagnostic method that integrates stochastic convolutional neural networks (SCNNs) and a hybrid kernel extreme learning machine (HKELM). First, the convolutional layers of the CNN were designed as multi-branch parallel layers to extract richer features. …”
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Pre-Routing Slack Prediction Based on Graph Attention Network by Jinke Li, Jiahui Hu, Yue Wu, Xiaoyan Yang

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Dual defense: Combining preemptive exclusion of members and knowledge distillation to mitigate membership inference attacks by Jun Niu, Peng Liu, Chunhui Huang, Yangming Zhang, Moxuan Zeng, Kuo Shen, Yangzhong Wang, Suyu An, Yulong Shen, Xiaohong Jiang, Jianfeng Ma, He Wang, Gaofei Wu, Anmin Fu, Chunjie Cao, Xiaoyan Zhu, Yuqing Zhang

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A Systematic Review on the Use of Big Data in Tourism by Jafar Ahangaran, Abbas Sadeghnia

“…Results By examining the results obtained from the research questions, it was found that, firstly, the use of big data analysis in scientific articles has grown significantly, and secondly, in most of the researches conducted around the topic of tourism using big data analysis, the most source of big data collection is the data produced. by users (UGC) with the approach of statistical analysis and then analysis by artificial intelligence and machine learning. This means that social networks, which are responsible for the dissemination of user-generated data, can play a more prominent role in scientific research, and the traditional method of collecting questionnaires will give way to examining the real opinions of users on social networks about a specific topic. …”
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CNC machining data repository: Geometry, NC code & high-frequency energy consumption data for aluminum and plastic machiningMendeley Data by Markus Brillinger, Muaaz Abdul Hadi, Stefan Trabesinger, Johannes Schmid, Florian Lackner

“…Potential use cases include optimizing machining parameters for energy reduction based on power consumption patterns, and enhancing digital twin models with real-world machining data. …”
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Improved Liquefaction Hazard Assessment via Deep Feature Extraction and Stacked Ensemble Learning on Microtremor Data by Oussama Arab, Soufiana Mekouar, Mohamed Mastere, Roberto Cabieces, David Rodríguez Collantes

“…The main novelty is the integration of machine learning, particularly stacked ensemble learning, for liquefaction potential classification from imbalanced seismic datasets. …”
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Flight-Safe Inference: SVD-Compressed LSTM Acceleration for Real-Time UAV Engine Monitoring Using Custom FPGA Hardware Architecture by Sreevalliputhuru Siri Priya, Penneru Shaswathi Sanjana, Rama Muni Reddy Yanamala, Rayappa David Amar Raj, Archana Pallakonda, Christian Napoli, Cristian Randieri

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Improved Deviation Sparse Fuzzy C-Means-2D Cumulative Sum Average Filter and Modified Sine Cosine Crow Search Algorithm-Wavelet Extreme Learning Machine for Brain Tumor Detection a... by Suvashisa Dash, Satyasis Mishra, Mohammed Siddique, Demissie J. Gelmecha, Ram Sewak Singh

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A Novel Transformer-Based Approach for Reliability Evaluation of Composite Systems With Renewables and Plug-in Hybrid Electric Vehicles by Chiranjeevi Yarramsetty, Tukaram Moger, Debashisha Jena, Veeranki Srinivasa Rao

“…This paper proposes a novel hybrid framework that integrates machine learning (ML) techniques with Sequential Monte Carlo Simulation (SMCS) to enhance the reliability assessment of modern power systems incorporating renewable energy resources (RER) and plug-in hybrid electric vehicle (PHEVs) integration. …”
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Enhancing power transformer health assessment through dimensional reduction and ensemble approaches in Dissolved Gas Analysis by Abdelmoumene Hechifa, Saurabh Dutta, Abdelaziz Lakehal, Hazlee Azil Illias, Arnaud Nanfak, Chouaib Labiod

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Loss reduction optimization strategies for medium and low-voltage distribution networks based on Intelligent optimization algorithms by Nian Liu, Yuehan Zhao

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Safe Switching Model-Free Value Iteration for General Nonlinear Systems by Timotei Lala

“…This subset of the state space is determined using single-class Support Vector Machine (SVM) classification. The method includes mechanisms for early instability detection and chattering reduction near switching surfaces. …”
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Understanding the environmental health implications of tourism on carbon emissions in China by Jinhua Shao, Sheng Fang, Meiling Zhao, Wanxin Qian, Cai Wang

“…In this study, we simulate the complex relationship between the tourism industry and carbon emissions in China using machine learning models. This study is the first to employ interpretable machine learning to analyze the impact of the tourism industry on carbon emissions in China. …”
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AI-driven hybrid rehabilitation: synergizing robotics and electrical stimulation for upper-limb recovery after stroke by Ismail Ben Abdallah, Ismail Ben Abdallah, Yassine Bouteraa, Yassine Bouteraa, Ahmed Alotaibi, Ahmed Alotaibi

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Softening of Vibrational Modes and Anharmonicity Induced Thermal Conductivity Reduction in a‐Si:H at High Temperatures by Zhuo Chen, Yuejin Yuan, Yanzhou Wang, Penghua Ying, Shouhang Li, Cheng Shao, Wenyang Ding, Gang Zhang, Meng An

“…In this study, we developed a neuroevolution machine learning potential based on first‐principles calculations of energy, forces, and virial, which enables accurate modeling of interatomic interaction in both a‐Si:H and a‐Si systems. …”
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Artificial intelligence in food system: Innovative approach to minimizing food spoilage and food waste by Helen Onyeaka, Adenike Akinsemolu, Taghi Miri, Nnabueze Darlington Nnaji, Keru Duan, Gu Pang, Phemelo Tamasiga, Samran Khalid, Zainab T. Al-Sharify, Chinenye Ugwa

“…This paper examines the deployment of AI technologies such as machine learning models, predictive analytics, and advanced algorithm in predicting food spoilage with high accuracy, thereby reducing food waste substantially. …”
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Prediction of Rice Chlorophyll Index (CHI) Using Nighttime Multi-Source Spectral Data by Cong Liu, Lin Wang, Xuetong Fu, Junzhe Zhang, Ran Wang, Xiaofeng Wang, Nan Chai, Longfeng Guan, Qingshan Chen, Zhongchen Zhang

“…This study aimed to explore the feasibility of predicting rice canopy CHI using nighttime multi-source spectral data combined with machine learning models. In this study, ground truth CHI values were obtained using a SPAD-502 chlorophyll meter. …”
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Data Compactness Versus Prediction Performance: Achieving Both by Pruning Redundant Samples With Dominant Patterns and Hamming Distance Based Sampling Scheme by Abdul Majeed, Seong Oun Hwang

“…Machine learning (ML) practitioners are always in pursuit of refined data to develop robust and generalizable ML models to solve real-world problems. …”
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Prediction of Imbalance Prices Through Gradient Boosting Algorithms: An Application to the Greek Balancing Market by Konstantinos Plakas, Nikos Andriopoulos, Dimitrios Papadaskalopoulos, Alexios Birbas, Efthymios Housos, Ioannis Moraitis

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