Prototyping a graph-based approach for efficient vehicle tracking in a cluster controlled CCTV surveillance systems by Apurva NARAYAN, Charumathi PARIVALLAL, Olirva MAHESWARAN, Sarath CHANDRAN KALATHILPARAMBIL RAMACHANDRAN

“…The optical character recognition (OCR) enables a detailed number plate recognition, while the multimodal data fusion enhances the robustness of vehicle tracking in dynamic conditions. …”
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A reconstruction and recovery network-based channel estimation in high-speed railway wireless communications by Qingmiao Zhang, Yuhao Zhao, Hanzhi Dong, Junhui Zhao

“…Simulation results show that the accuracy of the channel estimation model surpasses that of the standard channel estimation method, while also exhibiting reduced algorithmic complexity.…”
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A Hybrid Evolutionary Fuzzy Ensemble Approach for Accurate Software Defect Prediction by Raghunath Dey, Jayashree Piri, Biswaranjan Acharya, Pragyan Paramita Das, Vassilis C. Gerogiannis, Andreas Kanavos

“…The results show that the proposed method improves classification performance by 1% to 13% while retaining only 33% to 57% of the original feature set, offering a reliable and interpretable solution for software defect prediction. …”
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Research on Spaceborne Neural Network Accelerator and Its Fault Tolerance Design by Yingzhao Shao, Junyi Wang, Xiaodong Han, Yunsong Li, Yaolin Li, Zhanpeng Tao

“…To meet the high-reliability requirements of real-time on-orbit tasks, this paper proposes a fault-tolerant reinforcement design method for spaceborne intelligent processing algorithms based on convolutional neural networks (CNNs). …”
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A Security-Awareness Virtual Machine Management Scheme Based on Chinese Wall Policy in Cloud Computing by Si Yu, Xiaolin Gui, Jiancai Lin, Feng Tian, Jianqiang Zhao, Min Dai

“…Third, the VMs placement and migration algorithms are designed to enforce VMs isolation between the conflict users. …”
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Video analysis reveals early signs of Bradykinesia in REM sleep behavior disorder and Parkinson’s disease by Diego L. Guarín, Gabriela Acevedo, Carolina Calonge, Joshua K. Wong, Nikolaus R. McFarland, Adolfo Ramirez-Zamora, David E. Vaillancourt

“…Movement amplitude, speed, and their decrements during the task were directly estimated from the videos using machine learning algorithms. Bradykinesia and hypokinesia were detectable in PD but not in iRBD, while decrement in movement amplitude and speed were observed in PD and iRBD. …”
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Artificial Intelligence in Gastroenterology: A Comprehensive Review by Raju Vaishya, Mahesh Kumar Goenka, Anupam Sibal, Sujoy Kar, Sangita Reddy

“…This review highlights AI's multifaceted benefits to Gastroenterology while noting limitations and future perspectives. …”
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Community Vitality in Dynamic Temporal Networks by Fu Cai, Li Min, Zou Deqing, Qu Shuyan, Han Lansheng, James J. Park

“…A number of community detection algorithms can obtain community structure on each time slice or each period of time but rarely present the evolution of community structure. …”
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The urban heat Island effect: A review on predictive approaches using artificial intelligence models by Ali Najah Ahmed, Nouar AlDahoul, Nurhanani A. Aziz, Y.F. Huang, Mohsen Sherif, Ahmed El-Shafie

“…While conventional ML algorithms remain widely used, DL and hybrid models have shown superior performance in predictive accuracy. …”
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3-Dimensional Spatial Analysis of Parking Lot Wall Scratch Using Mobile Point Cloud Data by Y. Li, C. Ye, Y. Zhang, Z. Kang

“…A novel approach integrating YOLOv10 object detection and PTv3 point cloud processing algorithms is developed to detect and localize scratches, while spatial analysis evaluates design factors affecting scratch distribution. …”
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Artificial intelligence and robotic surgery in clinical medicine: progress, challenges, and future directions by Salih Beyaz, Alaaddin Levent Özgözen, Necmettin Turgut, Hakkı Can Ölke

“…However, limitations such as algorithmic opacity, legal-ethical uncertainties, and fragmented digital infrastructures continue to hinder broader implementation. …”
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Students' performance prediction employing Decision Tree by Abtahi Ahmed, Farzana Akter Nipa, Wasi Uddin Bhuyian, Khaled Md Mushfique, Kamrul Islam Shahin, Huu-Hoa Nguyen, Dewan Md. Farid

“…Traditional machine learning algorithms perform quite well in general, with SVM giving a best accuracy of around 95% with academic data, while training and testing the model without academic data still gives a good performance of 93%. …”
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Multimodal Video Analysis for Crowd Anomaly Detection Using Open Access Tourism Cameras by Alejandro Dionis-Ros, Joan Vila-Francés, Rafael Magdalena-Benedito, Fernando Mateo, Antonio J. Serrano-López

“…Through pattern recognition algorithms and segmentation, informative measures of the number of people and image occupancy are extracted at regular intervals, which are then analyzed to obtain trends and anomalous behaviors. …”
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Advances in UAV Path Planning: A Comprehensive Review of Methods, Challenges, and Future Directions by Wenlong Meng, Xuegang Zhang, Lvzhuoyu Zhou, Hangyu Guo, Xin Hu

“…A fundamental aspect of UAV autonomy lies in route optimization, which determines efficient paths while considering factors like mission goals, safety, and power consumption. …”
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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The IAST employs a globally adaptive Gaussian window as its kernel function, which automatically adjusts window length and spectral resolution based on real-time frequency characteristics, thereby enhancing time–frequency localization accuracy while reducing algorithmic complexity. To optimize computational efficiency, window parameters are determined through an energy concentration maximization criterion, enabling rapid extraction of discriminative features from diverse PQ disturbances (e.g., voltage sags and transient interruptions). …”
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A Logarithmic Compression Method for Magnitude-Rich Data: The LPPIE Approach by Vasileios Alevizos, Zongliang Yue, Sabrina Edralin, Clark Xu, Nikitas Gerolimos, George A. Papakostas

“…This study introduces Logarithmic Positional Partition Interval Encoding (LPPIE), a novel lossless compression methodology employing iterative logarithmic transformations to drastically reduce data size. While conventional dictionary-based algorithms rely on repeated sequences, LPPIE translates numeric data sequences into highly compact logarithmic representations. …”
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Merging Multiple System Perspectives: The Key to Effective Inland Shipping Emission-Reduction Policy Design by Solange van der Werff, Fedor Baart, Mark van Koningsveld

“…Policymakers in the maritime sector face the challenge of designing and implementing decarbonization policies while maintaining safe navigation. Herein, the inland sector serves as a promising stepping stone due to the possibility of creating a dense energy supply infrastructure and shorter distances compared to marine shipping. …”
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Raw dataset of tensile tests in a 3D-printed nylon reinforced with oriented short carbon fibersMendeley Data by Ênio H. Pires, João V. Barreto Netto, Marcelo L. Ribeiro

“…Mechanical test data were collected using an Instron universal testing machine, while SEM images were captured to examine microstructural features and fracture surfaces, both before and after testing. …”
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Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling by Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Idrees Alsolbi

“…Simulation analysis demonstrates that the new method can decrease energy consumption and average delay much lower than Round-Robin and threshold-based algorithms. The feature of temperature adaptation within Boltzmann further guarantees the achievement of the optimal scheduling actions while ensuring flexibility in the case or altering load percentages. …”
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Innovative Driver Monitoring Systems and On-Board-Vehicle Devices in a Smart-Road Scenario Based on the Internet of Vehicle Paradigm: A Literature and Commercial Solutions Overview by Paolo Visconti, Giuseppe Rausa, Carolina Del-Valle-Soto, Ramiro Velázquez, Donato Cafagna, Roberto De Fazio

“…The paper describes vehicle condition monitoring architectures, including diagnostic solutions for identifying anomalies, malfunctions, and instability while driving on slippery or wet roads. It also covers systems for classifying driving style, as well as tire and emissions monitoring. …”
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