SECURE VERTEX-EDGE DOMINATION IN HYPERCUBE AND GRID GRAPHS: APPLICATIONS OF CYBERSECURITY IN BANKING FOR SECURE TRANSACTIONS by C. Ruby Sharmila, S. Meenakshi

“…Moreover, develop a Hidden Markov Model (HMM) framework to enhance the detection of anomalous activities within these graph structures. This algorithm efficiently computes the minimum number of security agents required to monitor transaction flows, thus reducing vulnerabilities. …”
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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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Active Magnetic Bearing Rotor Model Updating Using Resonance and MAC Error by Yuanping Xu, Jin Zhou, Long Di, Chen Zhao, Qintao Guo

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Stability and Complexity of a Novel Three-Dimensional Environmental Quality Dynamic Evolution System by LiuWei Zhao, Charles Oduro Acheampong Otoo

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A parameter centric service discovery framework for social digital twins in smart City by Farhan Amin, Salabat Khan, Gyu Sang Choi, Muhammad Ali Abid, Isabel de la Torre, Elisabeth Caro Montero, Irene Delgado Noya

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GeneSetCluster 2.0: a comprehensive toolset for summarizing and integrating gene-sets analysis by Asier Ortega-Legarreta, Alberto Maillo, Daniel Mouzo, Ana Rosa López-Pérez, Lara Kular, Majid Pahlevan Kakhki, Maja Jagodic, Jesper Tegner, Vincenzo Lagani, Ewoud Ewing, David Gomez-Cabrero

“…Computationally, the package is optimized for parallel processing, significantly reducing execution time. …”
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Performance evaluation of enhanced deep learning classifiers for person identification and gender classification by Vasu Krishna Suravarapu, Hemprasad Yashwant Patil

“…Further, an adaptive coati optimization algorithm is used to adjust the hyperparameters of the classification models. …”
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Modern approaches to diagnosis and surgical treatment of patients with acute obstructive intestinal obstruction by V. A. Samartsev, B. S. Pushkarev, V. A. Gavrilov, A. A. Parshakov, M. P. Kuznetsova, A. A. Domrachev

“…Based on the conducted studies, an algorithm for perioperative diagnosis and treatment of complications was proposed.CONCLUSION. …”
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A Multi-Scale Airspace Sectorization Framework Based on QTM and HDQN by Qingping Liu, Xuesheng Zhao, Xinglong Wang, Mengmeng Qin, Wenbin Sun

“…Experimental results demonstrate that the proposed framework outperforms traditional models in both computational efficiency and workload balancing performance.…”
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Remaining Useful Life Prediction Method for Bearings Based on Pruned Exact Linear Time State Segmentation and Time–Frequency Diagram by Xu Wei, Jingjing Fan, Huahua Wang, Lulu Cai

“…First, the PELT (Pruned Exact Linear Time) algorithm is used to segment the vibration signals over the full life cycle of the bearing, accurately identifying critical degradation states and optimizing the stage division of the degradation process. …”
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A Colored Traveling Salesman Problem with Varying City Colors by Xianghu Meng, Jun Li, MengChu Zhou

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GNSS-RTK-Based Navigation with Real-Time Obstacle Avoidance for Low-Speed Micro Electric Vehicles by Nuksit Noomwongs, Kanin Kiataramgul, Sunhapos Chantranuwathana, Gridsada Phanomchoeng

“…The system employs a scored predicted trajectory algorithm that simultaneously optimizes path-following accuracy and obstacle evasion. …”
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Personalized prediction of psoriasis relapse post-biologic discontinuation: a machine learning-driven population cohort study by Shan Huang, Yanping Bai, Ruozhou Qi, Hongda Yu, Xingwu Duan

“…Relapse predictors were identified using the Boruta algorithm combined with multivariate Cox regression. …”
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Numerical analysis of geometrical configuration effects on near-field shockwave propagation in CL-20 based underwater explosives by Ji-ping Chen, Jun Wang, Xian-pi Zhang, Yan-jie Zhao, Xing-xing Wu, Fang-zhou Zhu, Jun Yu

“…The numerical methodology employs an advanced compressible multiphase flow simulation framework incorporating high-order weighted essentially non-oscillatory schemes, complemented by rigorous validation procedures involving comparative analyses against benchmark experimental data and analytical predictions from gas dynamics theory. The computational framework implements algorithmic initiation modeling for detonation processes, coupled with a front-tracking methodology employing the modified ghost fluid method to resolve discontinuities at immiscible phase boundaries. …”
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Advancing Agricultural Machinery Maintenance: Deep Learning-Enabled Motor Fault Diagnosis by Xusong Bai, Qian Chen, Xiangjin Song, Weihang Hong

“…However, challenges remain in implementing these systems, including data acquisition limitations, computational resource requirements, and algorithm adaptability to diverse operational conditions. …”
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AILDP: a research on ship number recognition technology for complex scenarios by Tianjiao Wei, Zhuhua Hu, Yaochi Zhao, Xiyu Fan

“…Firstly, in the detection phase, for the problem of varying size and position in the ship number recognition task, the detection effect is optimized by a module (AIFI_LPE) that combines feature interaction and learned position encoding. …”
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Dataset exploring the atomic scale structure and ionic dynamics of polyanion sodium cathode materials by Martin Hoffmann Petersen, Jin Hyun Chang, Arghya Bhowmik, Juan Maria García Lastra

“…This dataset includes optimizations of structures, ab initio molecular dynamics simulation trajectories sampled at 1000 K, and structures generated from ML-driven molecular dynamics simulation at 1000 K using an active learning algorithm. …”
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A Quantitative Evaluation of UAV Flight Parameters for SfM-Based 3D Reconstruction of Buildings by Inho Jo, Yunku Lee, Namhyuk Ham, Juhyung Kim, Jae-Jun Kim

“…Under controlled environmental conditions on representative building structures, key variables were manipulated, and all collected data were processed through a consistent SfM pipeline based on the SIFT algorithm. Quantitative evaluation results using various analytical methodologies (multiple regression analysis, Kruskal–Wallis test, random forest feature importance, principal component analysis including K-means clustering, response surface methodology (RSM), preference ranking technique based on similarity to the ideal solution (TOPSIS), and Pareto optimization) revealed that the basic shooting pattern ‘type’ has a significant and statistically significant influence on all major SfM performance metrics (reprojection error, final point count, computation time, reconstruction completeness; Kruskal–Wallis <i>p</i> < 0.001). …”
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Lightweight deep neural network for contour detection and extraction of wheat spikes in complex field environments by Xin Xu, Haiyang Zhang, Jiangchuan Lu, Ziyi Guo, Juanjuan Zhang, Jibo Yue, Hongbo Qiao, Xinming Ma

“…Method Building on two-year multi-angle wheat spike imagery, we propose an enhanced YOLOv9-LDS multi-scale object detection framework. The algorithm innovatively constructs a lightweight depthwise separable network (LDSNet) as backbone, balancing computational efficiency and accuracy through channel re-parameterization strategy; incorporates an Efficient Local Attention (ELA) module to build feature enhancement networks, and employs dual-path feature fusion mechanisms to strengthen edge texture responses, significantly improving discrimination of overlapping spikes and complex backgrounds. …”
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Multi-exit Kolmogorov–Arnold networks: enhancing accuracy and parsimony by James Bagrow, Josh Bongard

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