Wood Panel Defect Detection Based on Improved YOLOv8n by Rui Li, Shilu Zhong, Xuemei Yang

“…Traditional detection methods are time-consuming and subjective, and they can lead to economic waste, while deep learning image recognition techniques offer a new approach. …”
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Thermal-aware resource allocation in earliest deadline first using fluid scheduling by Muhammad Naeem Shehzad, Qaisar Bashir, Ghufran Ahmad, Adeel Anjum, Muhammad Naeem Awais, Umar Manzoor, Zeeshan Azmat Shaikh, Muhammad A Balubaid, Tanzila Saba

“…This article proposes an improvement in earliest deadline first, a uni-processor scheduling algorithm, without compromising its optimality in order to reduce the thermal peaks and variations. …”
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Research on Lightweighting Methods for 3D Building Models Based on Semantic Constraints by J. Wu, T. Shen, L. Huo

“…In the transition from LOD2 to LOD1, a concave-convex face movement and merging algorithm is utilized to reduce redundant data while maintaining geometric similarity and optimizing the model's topological structure, ultimately producing a lightweight LOD1 model. …”
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Time series segmentation for recognition of epileptiform patterns recorded via microelectrode arrays in vitro. by Gabriel Galeote-Checa, Gabriella Panuccio, Angel Canal-Alonso, Bernabe Linares-Barranco, Teresa Serrano-Gotarredona

“…While initially trained specifically for detecting ictal activity, these algorithms can be fine-tuned for improved interictal detection, aiming at seizure prediction. …”
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Hybrid multi-objective node deployment for energy-coverage problem in mobile underwater wireless sensor networks by Salmah Fattah, Ismail Ahmedy, Mohd Yamani Idna Idris, Abdullah Gani

“…This study evaluated the solution to substantiate its efficacy, particularly regarding the nodes’ coverage rate, energy consumption and the system’s Pareto optimal metrics and execution time. The results and comparative analysis indicate that the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy) is a better solution to the multi-objective sensor node deployment problem, outperforming the non-dominated sorting genetic algorithm II, SPEA2 and MOEA/D algorithms. …”
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Biosynthesis, applications, and mathematical modeling dynamics of lactic acid bacteria exopolysaccharides: A review by Ankit Barot, Kalyan Das, Yogesh Patel, et al.

“…These models improve the economic viability of LAB-EPS production by optimizing output and reducing substrate use. White-box models, utilize comprehensive system knowledge, forecast performance, and optimize processes such as EPS biosynthesis while employing algorithms like fuzzy patterns, rule-based systems, and decision trees to increase productivity and identify bottlenecks. …”
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Bayesian adaptation in Poisson cognitive systems by Aleksander A. Solodov

“…In particular, to describe the stochastic properties of cognitive systems and the possibility of creating an optimal algorithm, the Bayesian approach recognized in a number of philosophical works is applied.The optimal estimate by the criterion of the minimum standard error is, as is known, a posteriori mathematical expectation of a random estimated value, which is applied in this work. …”
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Energy Efficiency Maximization through Cooperative Transmit and Receive Antenna Selection for Multicell MU-MIMO System by Yanjie Dong, Yinghai Zhang, Weidong Wang, Gaofeng Cui, Yang Yu

“…With this function, we can transform the whole system optimization problem to a sectional optimization problem and obtain a suboptimal antenna set using a heuristic algorithm. …”
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Automatic Segmentation of Plants and Weeds in Wide-Band Multispectral Imaging (WMI) by Sovi Guillaume Sodjinou, Amadou Tidjani Sanda Mahama, Pierre Gouton

“…Our investigation focuses specifically on scenes from the CAVIAR dataset of multispectral images. The proposed algorithm has enabled us to effectively capture complex details while regulating the learning process, achieving an impressive overall accuracy of 98.2%. …”
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Configuring adaptive PID-controllers of the automatic speed control system of the GTE by K. E. Chertilin, V. D. Ivchenko

“…This is conditioned by two factors: the complexity of solving the problem as a whole and the presence of a large number of technically diverse situations that need to be adapted and optimized. …”
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A LIFE EVALUATION METHED FOR FRONT AXLE BASED ON FRONT AXLE DYNAMICS MODEL by FENG Jinzhi, SANG Wuzhuang, ZHANG Dongdong, LI Liangliang, LIU Xinrong, ZHAO Lihui

“…Then, with the goal of minimizing the difference between the damage/life of the front axle and the reference value under each working condition, the adjustment coefficient of the amplitude of the three-way forces at the wheel center was optimized by combining the response surface method and genetic algorithm. …”
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Distributed Transmission Probability Control in Fading Channel with State Information by S. Xie, K.S. Low, E. Gunawan

“…Two simple yet effective guidelines on selecting among these CSI-related methods are formulated for systems with different SNRs and capture ratios. A distributed algorithm is proposed to find the optimal transmission probability. …”
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Pickup and delivery planning for the crowdsourced freight delivery routing problem. by Jingxian Zhang

“…The objective is to minimize total service costs, including fixed vehicle costs, transportation costs, and penalty costs for delays, while planning routes that cover all orders. To solve this combinatorial optimization problem, we propose an improved partheno genetic algorithm (IPGA) and a simulated annealing algorithm (SA). …”
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Microservice selection approach for mobile users in edge computing environment by ZHAO Shuxu, JIANG Kaijun, WANG Xiaolong

“…Then, a microservice deployment algorithm based on EGI was designed to achieve low-latency and high-hit-rate deployment. …”
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Automatic collaborative water surface coverage and cleaning strategy of UAV and USVs by Tianping Deng, Xiaohui Xu, Zeyan Ding, Xiao Xiao, Ming Zhu, Kai Peng

“…Second, we design a task scheduling and assignment algorithm for USVs to balance the garbage loads based on the particle swarm optimization algorithm. …”
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Identification of green leafhoppers (cicadellidae) in vineyards through an automatic image acquisition system from yellow sticky traps associated with deep-learning by Proença Maria da Conceição, Rebelo Maria Teresa, Valent Riccardo, Mateus Rebeca, Gaspar Pedro Diniz, Lopes Carlos Manuel, Franco José Carlos

“…The results demonstrated the algorithm’s capability to accurately identify green leafhopper species, improving the speed of identification compared to conventional methods while maintaining a high level of precision (80%), and a harmonic mean of the precision and recall (F1) of 0.85. …”
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Digital-twin driven alignment control method for marine shafting with air spring vibration isolation system by Song Liu, Liang Shi, Wei Xu, ZeChao Hu

“…To obtain the optimal air spring pressures, the genetic algorithm is introduced to solve the optimization problem, fully exploiting its global search capacity. …”
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Energy-Efficient Scheduling for Resilient Container-Supply Hybrid Flow Shops Under Transportation Constraints and Stochastic Arrivals by Huaixia Shi, Huaqiang Si, Jiyun Qin

“…To address the TDEHFSP model, the study proposes a Q-learning-based multi-swarm collaborative optimization algorithm (Q-MGCOA). The algorithm integrates a time gap left-shift scheduling strategy with a machine on–off control mechanism to construct an energy-saving optimization framework. …”
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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…Impermeable boundary conditions are imposed on these initial free-surface nodes, while other boundaries are assigned conditions according to the physical model. …”
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Eecs-fl: energy-efficient client selection for federated learning in AIoT by Yiyang Zhang, Yiming Luo, Tao Yang, Xiaofeng Wu, Bo Hu

“…We formulate the client selection problem as a multi-dimensional knapsack problem (MKP) and solve it using dynamic programming to maximize energy efficiency while maintaining fast convergence. Experimental results show that incorporating WPT leads to a reduction in unit energy consumption by over 24.54%; while, the proposed algorithm achieves a reduction of over 15.31% compared to random selection. …”
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