Automated Detection of Tailing Impoundments in Multi-Sensor High-Resolution Satellite Images Through Advanced Deep Learning Architectures by Lin Qin, Wenyue Song

“…Accurate spatial mapping of Tailing Impoundments (TIs) is vital for environmental sustainability in mining ecosystems. While remote sensing enables large-scale monitoring, conventional methods relying on single-sensor data and traditional machine learning-based algorithm suffer from reduced accuracy in cluttered environments. …”
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Real-time motion detection using dynamic mode decomposition by Marco Mignacca, Simone Brugiapaglia, Jason J. Bramburger

“…Effectiveness is analyzed using receiver operating characteristic curves, while we use cross-validation to optimize the threshold parameter that identifies movement.…”
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Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage by Yongqiang Zhang, Haijie Pang, Jinlong Ma, Guilei Ma, Xiaoming Zhang, Menghua Man

“…On the MNIST dataset, the accuracy of the spiking neural network decreased by 3.91% at a sparsity of 30%, while the artificial neural network decreased by 10.13%. …”
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A cartographic generalization method for 3D visualization of trajectories in space–time cubes: case study of epidemic spread by Fei Yang, Jie Shen, Fengzhen Zhu, Junrui Zhang

“…The proposed method incorporates a 3D generalization algorithm that mitigates visual stickiness, while leveraging a 3D line field visualization technique to optimize opacity, thereby minimizing visual occlusion and spatial clutter. …”
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Hybrid precoding and power allocation for mmWave NOMA systems based on time delay line arrays by Gangcan SUN, Xinli WU, Wanming HAO, Zhengyu ZHU

“…Specifically,the Dinkelbach method is applied in the outer layer to transform the fractional structure of the objective function in EE optimization into a subtractive structure, and the non-convex objective function is transformed into a convex function by using mathematical tools in the inner layer, and then an iterative algorithm based on alternating optimization (AO) is proposed for power allocation, and finally the solution of the initial problem is obtained by circular iteration in both inner and outer layers. …”
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Shells and Spheres: An n-Dimensional Framework for Medial-Based Image Segmentation by Aaron Cois, John Galeotti, Robert Tamburo, Michael Sacks, George Stetten

“…For the automated 3D algorithm, the only manual interaction consists of tracing a single contour on a 2D slice to optimize parameters, and identifying an initial point within the target structure.…”
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Jumping knowledge graph attention network for resource allocation in wireless cellular system by Qiushi Sun, Zhou Fang, Yin Li, Ovanes Petrosian

“…The realization of these features hinges on the development of rational resource allocation strategies to optimize the utilization of radio resources. This study addresses the beamforming design problem for downlink transmission in multi-cell cellular networks, with a focus on maximizing user data rates while adhering to stringent power constraints. …”
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Enhancing Secure Energy Efficiency of SWIPT IoT Network Considering IRS and Artificial-Noise: A Deep Learning Approach by Kimchheang Chhea, Jung-Ryun Lee

“…Our goal is to maximize secure EE, where the secure EE is defined as the secrecy rate over the power consumption of the user. We aim to jointly optimize phase-shift of IRS, transmit power of jammer and user, to maximize the objective function while ensuring that the secrecy rate is greater than the predefined threshold while allowing the eavesdroppers to harvest energy using SWIPT. …”
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Deep Reinforcement Learning-Based Multi-Agent System with Advanced Actor–Critic Framework for Complex Environment by Zihao Cui, Kailian Deng, Hongtao Zhang, Zhongyi Zha, Sayed Jobaer

“…We introduce an advanced multi-agent deep reinforcement learning (DRL) framework, specifically a Multi-Agent Proximal Policy Optimization (MA-PPO), designed to optimize target acquisition while operating within defined ammunition and time constraints. …”
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Research on RF Intensity Temperature Sensing based on 1D-CNN by DING Meiqi, GUI Lin, WANG Ziyi, SHANG Disen, QIAN Min, LI Qiankun

“…【Results】The experimental results show that the RMSE of the prediction model based on 1D-CNN reaches the order of 10^-3, while the RMSE of the traditional algorithms is usually in the order of 10^-1. …”
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FedACT: An adaptive chained training approach for federated learning in computing power networks by Min Wei, Qianying Zhao, Bo Lei, Yizhuo Cai, Yushun Zhang, Xing Zhang, Wenbo Wang

“…Second, we propose a Genetic-Algorithm-based Sorting (GAS) method to optimize the order of clients participating in training. …”
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Introducing an oncoplastic approach for centrally located breast cancer patients by Mohammadreza Karoobi, Seyed Mostafa Meshkati Yazd, Fatemeh Aminolroaya, Hadiseh Mahram, Samineh Saghafinia, Stefano Pompei, Nahid Nafissi, Pantea Khalili

“…This study aims to present a comprehensive algorithm designed to optimize surgical planning and enhance aesthetic outcomes for patients undergoing surgery for central breast cancers. …”
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Conceptual Framework of Energy-and-Ecology of Indoor Plant Lighting by Sergei A. Rakut’ko

“…(Conclusions) For the first time, the author raises a question about the development of structural elements of the BAT formation algorithm in lighting horticulture in terms of energy-ecological indicators as an integrative optimality criterion of the system. …”
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Quantifying ruminal health: A statistical review and application of area and time under the curve in animal science by Luis O. Tedeschi

“…These insights allow researchers and practitioners to evaluate feeding strategies, diagnose metabolic disorders, and optimize animal management practices. AUC-based metrics, supported by the ATAUC algorithm, enable scalable and pragmatic solutions for real-time monitoring and decision-making. …”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…This effectively reduces the difficulty and cost of deployment on mobile terminals while significantly improving algorithm accuracy, meeting real-time requirements, and providing a more efficient and feasible technical solution for relevant applications. …”
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An Efficient and Cost-Effective Vehicle Detection and Tracking System for Collision Avoidance in Foggy Weather by Naeem Raza, Muhammad Asif Habib, H. M. Sajid Imran, Abdul Qayum, Sajida Perveen, Sohail Jabbar, Shahzad Sarwar, Mudassar Ahmad

“…The proposed ECE-VDT system encompasses an optimized SimYOLO-V5s algorithm and its five variants for vehicle detection, while the optimized deep-SORT algorithm is proposed for vehicle tracking. …”
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Computer Modelling «Smart Building» by O. Yu. Maryasin, A. S. Kolodkina, A. A. Ogarkov

“…The peculiarity of this model is the use of specialized management and control algorithms which allow providing coordinated interaction of subsystems and optimizing power consumption.…”
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Improving cancer detection through computer-aided diagnosis: A comprehensive analysis of nonlinear and texture features in breast thermograms. by Hamed Khodadadi, Shima Nazem

“…The effectiveness of the proposed approach is enhanced by integrating texture and complexity features. Besides, to optimize feature selection and reduce redundancy, a metaheuristic optimization technique called Non-Dominated Sorting Genetic Algorithm (NSGA III) is applied. …”
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UAV Small Target Detection Model Based on Dual Branches and Adaptive Feature Fusion by Guogang Wang, Mingxing Gao, Yunpeng Liu

“…The model first constructs a small target detection framework with dual branches to improve the detection accuracy while reducing the number of parameters. Secondly, the model introduces semantic and detail injection (SDI) in the neck network and embeds bidirectional adaptive feature fusion in the detection head to innovate and optimize the feature fusion mechanism, achieve the full interaction of deep and shallow information, enhance the feature representation of small targets, and overcome the problem of scale inconsistency. …”
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Cost-benefit analysis in demand response with penalty and grid management using blockchain by Manikandan Ramasamy, Thenmalar Kaliannan, Saravanakumar Ramasamy

“…Two distinct optimization methods such as the gray wolf optimization algorithm and particle swarm optimization are employed to solve the optimization model. …”
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