Cost-Efficient Fall Risk Assessment With Attention Augmented Vision Machine Learning on Sit-to-Stand Test Videos by Chunhua Pan, Boting Qu, Rui Miao, Xin Wang

“…Median-average filtering is used to reduce noise caused by video shaking and pose estimation inaccuracies, while a new Dynamic Time Warping (DTW)-based matching algorithm is designed to handle interference from irrelevant individuals appearing in the video. …”
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Experimental and numerical investigation on thermal performance of enhanced geothermal system: A case study of Guanzhong basin by Guoyao Jin, Yuxiang Zhao, Ye Min, Xiao Zhang, Chao Jiang, Zijing Tan

“…A multi-objective genetic algorithm correlates operational variables with extraction efficiency, providing a quantitative framework for optimization. …”
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A Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions by Bing Yang, Kaiwei Wu, Zhe Guo, Yanbin Liang, Shijun Hao, Zhonghua Huang

“…To address these limitations while satisfying real-time processing requirements, this study proposes (1) a novel segmented low-order bistable stochastic resonance (SLOBSR) system based on piecewise polynomial potential functions and (2) a corresponding fixed-distance target detection algorithm incorporating signal pre-processing, particle swarm optimization (PSO)-based parameter optimization, and kurtosis threshold detection. …”
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Numerical Prediction of Solid Particle Erosion in Jet Pumps Based on a Calibrated Model by Xuanchen Wan, Mengxue Dong, Maosen Xu, Chuanhao Fan, Jiegang Mou, Shuai Han

“…The CFD-DEM method was used to simulate the solid–liquid two-phase flow in the jet pump, comparing six erosion models for predicting erosion rates. The Grey Wolf Optimization algorithm was applied to calibrate model coefficients. …”
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RL-Based Vibration-Aware Path Planning for Mobile Robots’ Health and Safety by Sathian Pookkuttath, Braulio Felix Gomez, Mohan Rajesh Elara

“…Hence, self-awareness and optimal path selection, avoiding such terrain anomalies, is essential. …”
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IMPROVEMENT OF PASSENGER SERVICE PROCESSES OF DEPARTING FLIGHT BASED ON PROJECT MANAGEMENT METHODS by S. A. Kropiventseva

“…In order to find the critical path of the network graph it is recommended to apply the Dijkstra algorithm. It allows us to identify all critical paths from the initial vertex to the final one if there are several. …”
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A review of state-of-the-art resolution improvement techniques in SPECT imaging by Zhibiao Cheng, Ping Chen, Jianhua Yan

“…It delves into advancements in detector design and modifications, projection sampling techniques, traditional reconstruction algorithm development and optimization, and the emerging role of deep learning. …”
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Improved deep learning model for accurate energy demand prediction and conservation in electric vehicles integrated with cognitive radio networks by V. Niranjani, Anandakumar Haldorai

“…To overcome this issue, this paper proposed a model of Empirical Mode Decomposition with CNN and optimized with Seagull Optimization Algorithm (EMD-CNN-SOA). …”
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HASSDE-NAS: Heuristic–Adaptive Spectral–Spatial Neural Architecture Search with Dynamic Cell Evolution for Hyperspectral Water Body Identification by Feng Chen, Baishun Su, Zongpu Jia

“…Additionally, a bidirectional fusion alignment cell jointly optimizes spectral and spatial dependencies. A heuristic cell search algorithm optimizes the network architecture through architecture stability, feature diversity, and gradient sensitivity analysis, which improves search efficiency and model robustness. …”
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Voltage Support Capacity Improvement for Wind Farms with Reactive Power Substitution Control by Yuegong Li, Guorong Zhu, Jianghua Lu, Hua Geng

“…Considering differences in terminal voltage characteristics and operating conditions, this RPS control method employs a particle swarm optimization (PSO) algorithm to ensure that wind turbines can provide their optimal reactive power support capacity. …”
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Exploring the Impact of Resource Management Strategies on Simulated Edge Cloud Performance: An Experimental Study by Nikolaos Kaftantzis, Dimitrios G. Kogias, Charalampos Z. Patrikakis

“…This allows us to determine the optimal algorithm for tasks that prioritize minimal resource use, low latency, or a combination of the two. …”
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A Beyond 5G OTFS Waveform Radio for Smart Hospital: PAPR Reduction in OTFS Using the Cuckoo Search–Based PTS Method by Arun Kumar, Aziz Nanthaamornphong

“…The results revealed that the proposed PTS + CS obtained significant PAPR and PSD performance while retaining the BER of the framework. The optimal PAPR, BER, PSD, and power-saving performance of the advanced radio enhance the quality of the B5G-based intelligent healthcare system.…”
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Robust Low-Overlap Point Cloud Registration via Displacement-Corrected Geometric Consistency for Enhanced 3D Sensing by Xin Wang, Qingguang Li

“…To address this challenge, this paper proposes a novel geometric consistency optimization and rectification deep learning network named GeoCORNet. …”
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Identification of Gene Modules Associated with Low Temperatures Response in Bambara Groundnut by Network-Based Analysis. by Venkata Suresh Bonthala, Katie Mayes, Joanna Moreton, Martin Blythe, Victoria Wright, Sean Tobias May, Festo Massawe, Sean Mayes, Jamie Twycross

“…The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. …”
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Coasting-cruising Combined Control Strategy Based on Train Energy-efficient Operation by GAO Hao, CHAI Juan, LING Xiaoque, XU Haigui

“…Multiple control stages are divided according to the line conditions, with maximum traction, coasting, cruising, and maximum braking as control inputs for each stage. The genetic algorithm is used to calculate respectively the train energy-efficient optimized operation curves under the coasting-cruising combined control strategy and the multiple coasting control strategy. …”
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Deep Reinforcement Learning for Dynamic Pricing and Ordering Policies in Perishable Inventory Management by Yusuke Nomura, Ziang Liu, Tatsushi Nishi

“…To tackle this challenge, we propose eliminating irrational actions in dynamic programming without sacrificing optimality. To solve this problem more efficiently, we also implement a deep reinforcement learning algorithm, proximal policy optimization, to solve this problem. …”
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Application of machine learning for predicting the incubation period of water droplet erosion in metals by Khaled AlHammad, Mamoun Medraj, Moussa Tembely

“…The performance of various ML algorithms is evaluated while investigating the effect of data transformation techniques on prediction accuracy. …”
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Modeling the Stability of the Housing and Construction Complex Based on Organizational and Economic Interaction of Entities by N. N. Shelomentseva, O. V. Grushina

“…A genetic algorithm in MATLAB was used for this purpose. Acceptable options for all participants were selected from a set of Pareto-optimal alternatives based on the preferences of the decision-maker. …”
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MAOOA‐Residual‐Attention‐BiConvLSTM: An Automated Deep Learning Framework for Global TEC Map Prediction by Haoran Wang, Haijun Liu, Jing Yuan, Huijun Le, Weifeng Shan, Liangchao Li

“…It also includes an optimization algorithm, MAOOA, for optimizing the hyper‐parameters of the model. …”
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Spatiotemporal pattern analysis of land use in Jiangsu Province based on long-term time series remote sensing images by Zhendong Ji, Lingzhi Yin, Jinhong Wang

“…Principal Component Analysis (PCA) was applied to reduce feature dimensionality, and the Random Forest classification algorithm was optimized with Bayesian Optimization and Tree-structured Parzen Estimators (TPE) for improved performance. …”
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