Physics-Informed Neural Networks for Enhanced State Estimation in Unbalanced Distribution Power Systems by Petros Iliadis, Stefanos Petridis, Angelos Skembris, Dimitrios Rakopoulos, Elias Kosmatopoulos

“…This paper introduces a PINN-based framework for state estimation in unbalanced distribution systems, leveraging available data and embedded physical knowledge to improve accuracy, computational efficiency, and robustness across diverse operating scenarios. …”
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EMS3D-KITTI: Synthetic 3D dataset in KITTI format with a fair distribution of Emergency Medical Services vehicles for autodrive AI model trainingZenodo by Chandra Jaiswal, Sally Acquaah, Christopher Nenebi, Issa AlHmoud, AKM Kamrul Islam, Balakrishna Gokaraju

“…To address this, we leveraged the Car Learning to Act (CARLA) simulator to generate and fairly distribute rare EMS vehicles, automatically labelling these objects in 3D point cloud data. …”
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Convolutional neural networks for specific and merged data sets of optical array probe images: compatibility of retrieved morphology-dependent size distributions by L. Jaffeux, J. Breiner, P. Coutris, A. Schwarzenböck

“…In addition, three new models are introduced in this study: one for the Cloud Imaging Probe (CIP), one for the High Volume Particle Spectrometer (HVPS), and a global model trained on a data set that merges all available data from the above four instruments. …”
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KL-FedDis: A federated learning approach with distribution information sharing using Kullback-Leibler divergence for non-IID data by Md. Rahad, Ruhan Shabab, Mohd. Sultan Ahammad, Md. Mahfuz Reza, Amit Karmaker, Md. Abir Hossain

“…Data Heterogeneity or Non-IID (non-independent and identically distributed) data identification is one of the prominent challenges in Federated Learning (FL). …”
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A Distributed Machine Learning-Based Scheme for Real-Time Highway Traffic Flow Prediction in Internet of Vehicles by Hani Alnami, Imad Mahgoub, Hamzah Al-Najada, Easa Alalwany

“…Centralized machine learning methods face a number of challenges due to the sheer volume of traffic data that needs to be processed in real-time. Thus, it is not scalable and lacks fault tolerance and data privacy. …”
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EMUs Electrical Connector Life Prediction Based on Accelerated Degradation Data by Jie MA, Lide WANG, Chuan YUE, Ping SHEN, Ji QIU

“…Using physical model of life prediction and data processing algorithm and accelerated degradation data modeling process based on degradation distribution, the reliability and life evaluation of EMUs electrical connectors were realized. …”
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Advanced air quality prediction using multimodal data and dynamic modeling techniques by Umesh Kumar Lilhore, Sarita Simaiya, Rajesh Kumar Singh, Abdullah M. Baqasah, Roobaea Alroobaea, Majed Alsafyani, Afnan Alhazmi, M. D. Monish Khan

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Short‐term load forecasting facilitated by edge data centres: A coordinated edge‐cloud approach by Junlong Li, Lurui Fang, Xiangyu Wei, Mengqiu Fang, Yue Xiang, Peipei You, Chao Zhang, Chenghong Gu

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Low-Scalability Distributed Systems for Artificial Intelligence: A Comparative Study of Distributed Deep Learning Frameworks for Image Classification by Manuel Rivera-Escobedo, Manuel de Jesús López-Martínez, Luis Octavio Solis-Sánchez, Héctor Alonso Guerrero-Osuna, Sodel Vázquez-Reyes, Daniel Acosta-Escareño, Carlos A. Olvera-Olvera

“…Currently, cloud services offer products for running distributed data training, such as NVIDIA Deep Learning Solutions, Amazon SageMaker, Microsoft Azure, and Google Cloud AI Platform. …”
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Shearography-Based Near-Surface Defect Detection in Composite Materials: A Spatiotemporal Object Detection Neural Network Trained Only with Simulated Data by Guanlin Li, Yao Hu, Hao Wang, Qun Hao, Yu Zhang

“…The experimental results show that, with only 4000 frames of simulated data for training, our network achieved a detection accuracy of 96.99% on experimental phase maps, which is considerably higher than the 65.37% accuracy achieved by training the YOLOv4 network with the same simulated data. …”
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Trends and distribution of malaria among children under five in Tamale Metropolis in Ghana, amidst interventions: Analysis of surveillance and program data, 2017 -2021 by Shahadu Shembla Sayibu, Basil Benduri Kaburi, Dora Dadzie, Delia Bandoh, Isaac Baffoe-Nyarko, Charles Lwanga Noora, Abdul Gafaru Mohammed, Francis Genye Salifu, Peter Apetorgbor, Paul Hilarius Asiwome Kosi Abiwu, Ernest Kenu

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The Effects of Questioning Skills Training on Question Forming Levels of Turkish Secondary School Students by Selim Bülbül, Serdar Derman

“…During the research process, the experimental group received 16 hours of training on question-asking skills. The collected data were analyzed using content analysis. …”
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Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient Operation by WANG Qingyuan, WEI Mi, HU Yunqing, WANG Jianhua, JIANG Fan, ZHANG Zhengfang, WANG Kaiyun

“…Drawing from multi-vehicle cooperative control techniques for high-speed trains, research into the distributed cooperative control of heavy-haul trains with multiple locomotives is of great significance, due to its active suppression of longitudinal impulses. …”
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On-line strength assessment of distribution systems with distributed energy resources by Jifeng Liang, Shiyang Rong, Tengkai Yu, Tiecheng Li, Hanzhang Qu, Ye Cao

“…An adaptive sampling strategy is employed to generate synthetic data for real-time assessment. To predict the strength of distribution systems under various conditions, a rectified linear unit (ReLU) neural network is trained and further reformulated as a mixed-integer linear programming (MILP) problem to verify its robustness and input stability. …”
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Oversampling and undersampling for intrusion detection system in the supervisory control and data acquisition IEC 60870‐5‐104 by M. Agus Syamsul Arifin, Deris Stiawan, Bhakti Yudho Suprapto, Susanto Susanto, Tasmi Salim, Mohd Yazid Idris, Rahmat Budiarto

“…Abstract Supervisory control and data acquisition systems are critical in Industry 4.0 for controlling and monitoring industrial processes. …”
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Fed-Hetero: A Self-Evaluating Federated Learning Framework for Data Heterogeneity by Aiswariya Milan Kummaya, Amudha Joseph, Kumar Rajamani, George Ghinea

“…Federated learning (FL) enables deep learning models to be trained locally on devices without the need for data sharing, ensuring data privacy. …”
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POISSON REGRESSION MODELLING OF AUTOMOBILE INSURANCE USING R by Sandy Vantika, Mokhammad Ridwan Yudhanegara, Karunia Eka Lestari

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Improving Balanced Accuracy for Minority Plant Species under Data Imbalance by Ruben Gonzalez-Villanueva, Jose Carranza-Rojas

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Sports data analysis of track and field athletes based on IID-OPK and NonIID-OPK algorithms by Xiaofeng Chen

“…The traditional K-means clustering algorithm randomly selects clustering center points, which can easily lead to unstable clustering results and be affected by outliers, making it unable to handle complex sports data of track and field athletes. Therefore, the research introduces the Independent and Identically Distributed (IID) and Non-Independent and Identically Distributed (NonIID) ideas based on the K-means algorithm to optimize the data analysis process. …”
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A traction load modeling method of metro trains based on the regenerative braking energy effective utilization and its application by SHI Dan, GAO Dongsheng, YANG Rui

“…This method first established the power probability distribution model of a single train under different working conditions, and then used Poisson distribution to model the number of trains in the power supply section, and then obtained the traction load model considering the time sequence of train. …”
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