Optimal Configuration of Virtual Links for Avionics Network Systems by Dongha An, Kyong Hoon Kim, Ki-Il Kim

“…Thus, in this paper, we present two configuration approaches to set MTU and BAG values on virtual links efficiently while meeting the requirement of AFDX. The first is to search available feasible configuration (MTU, BAG) pairs to satisfy application requirements as well as AFDX switch constraints, and the second is to get an optimal pair to minimize required bandwidth through well-known branch-and-bound algorithm. …”
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Social Media Users' Expression, Formation Mechanism, and Coping Strategies for Algorithm Aversion by Yan MOU

“…These insights are invaluable for improving and optimizing algorithms to ensure that they not only meet user expectations, but also enhance their overall experience and satisfaction. …”
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Bilevel Optimization for ISAC Systems with Proactive Eavesdropping Capabilities by Tingyue Xue, Wenhao Lu, Mianyi Zhang, Yinghui He, Yunlong Cai, Guanding Yu

“…With the help of the proposed algorithm, we obtain the optimal solution of the analog transmit beamforming matrix and the digital beamforming vector. …”
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Signal Timing Optimization Model for Intersections in Traffic Incidents by Jiawen Wang, Jiayu Hang, Xizhao Zhou

“…To satisfy the conditions for efficiently identifying feasible solutions in a short time, a heuristic algorithm (simulated annealing algorithm) is employed to solve the model. …”
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Optimal Poisson Cognitive System with Markov Learning Model by A. A. Solodov

“…Thus, the following assumptions are accepted in the work, apparently corresponding to the behavior of the system assuming human reactions, i.e. the cognitive system.The images analyzed by the system arise at random moments of time, while the duration of time between neighboring appearances of images is distributed exponentially.The system analyzes the resulting images and makes a decision about the presence or absence of an image at its input in accordance with the optimal Neуman-Pearson algorithm that maximizes the probability of correct identification of the image with a fixed probability of false identification.The system is trainable in the sense that decisions about the presence or absence of an image are made sequentially on a set of identical situations, and the probability of making a decision depends on the previous decision of the system.The new results of the study are analytical expressions for the probabilities of the system staying in each of the possible states, depending on the number of steps of the learning process and the intensities of useful and interfering stimuli at the input of the system. …”
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An Incentive Dynamic Programming Method for the Optimization of Scholarship Assignment by Di Huang, Yu Gu, Hans Wang, Zhiyuan Liu, Jun Chen

“…The objective is to find the optimal scholarship assignment scheme with the highest equity while accounting for both the practical constraints and the equity requirement. …”
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Optimizing Medical IoT Disaster Management with Data Compression by Nunudzai Mrewa, Athirah Mohd Ramly, Angela Amphawan, Tse Kian Neo

“…To tackle this issue, we introduce "Beyond Orion," a novel lossless compression method designed to optimize data compression in IoT systems. The algorithm employs advanced techniques such as Lempel Ziv-Welch and Huffman encoding, while also integrating strategies like pipelining, parallelism, and serialization for greater efficiency and lower resource usage. …”
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Optimizing the Finishing Treatment of Potato Harvester Transmission Shafts by A. V. Nemenko, M. M. Nikitin

“…This function is designed to maximize potato yield while monitoring concentrated defects. (Materials and methods) The implementation of the method requires equipment capable of being controlled through a technical vision channel. …”
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Layout Optimization of Campus Bike-Sharing Parking Spots by Tangyi Guo, Jie Yang, Liu He, Kun Tang

“…Thus, alternative parking spots are proposed based on the layout principle of parking spots for bicycles. An optimization model of the layout of campus bike-sharing parking spots with travel time and construction cost as the optimization goal is established, and the branch and bound algorithm is used to solve the model. …”
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Superposition Methods for Topology Optimization for Non-Concurrent Loads by Daniel Miler, Matija Hoić

“…Problems with non-concurrent loads with variable load directions are often encountered in engineering. While dynamic topology optimization more realistically solves such problems, it is also much more computationally expensive and requires complex mathematical formulations and solvers. …”
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Optimization of surgical treatment of abdominal hernias in patients with obesity by V. I. Belokonev, V. P. Zakharov, D. B. Grachev, S. Y. Pushkin, Z. V. Kovaleva, D. S. Pushkina

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Optimization of PID Controllers Using Groupers and Moray Eels Optimization with Dual-Stream Multi-Dependency Graph Neural Networks for Enhanced Dynamic Performance by Vaishali H. Kamble, Manisha Dale, R. B. Dhumale, Aziz Nanthaamornphong

“…This study presents a novel control strategy that integrates the Groupers and Moray Eels Optimization (GMEO) algorithm with a Dual-Stream Multi-Dependency Graph Neural Network (DMGNN) to optimize PID controller parameters. …”
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METHOD OF QUALIFICATION ESTIMATION AND OPTIMIZATION OF PROFESSIONAL TEAMS OF PROGRAMMERS by A. A. Prihozhy, A. M. Zhdanouski

“…The problem of building and optimizing the teams of programmers taking into account the qualification and the level of skills in programming technologies and tools is considered. …”
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Control Optimization of Steam Boilers via Reinforcement Learning by Emmanuel Okafor, Maad Alowaifeer

“…Extensive experimental validation confirms the superiority of hybrid controllers, achieving significantly faster settling times, peak overshoot reductions to <inline-formula> <tex-math notation="LaTeX">$(\leq 2\%)$ </tex-math></inline-formula>, and lower error metrics than MRAC alone. While optimized PID serves as a baseline, hybrid controllers consistently achieve faster settling times and improved robustness under most nonlinear operating conditions. …”
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Precision irrigation with AI-driven optimization of plant electrophysiology by Yiting Chen, Devon Scott, Hieu Trung Tran, Yan Sum Shirley Yip, Soomin Shin, Woo Soo Kim

“…By optimizing water consumption using the AI algorithm, our approach can achieve at least a 10 % reduction in water use while maintaining optimal water conditions for crops. …”
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A New Approach to Circulatory System-Based Optimization for the Shape and Sizing Design of Truss Structures by Ibrahim Behram Ugur, Sadik Ozgur Degertekin

“…This paper presents a new approach to the circulatory system-based optimization algorithm called NCSBO. The proposed method incorporates an adaptive parameter-tuning strategy and a refined mutation approach to improve the performance of optimizing the shape and size of truss structures. …”
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Engine Optimization Model for Accurate Prediction of Friction Model in Marine Dual-Fuel Engine by Mina Tadros

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Machine Learning for Decision Support and Automation in Games: A Study on Vehicle Optimal Path by Gonçalo Penelas, Luís Barbosa, Arsénio Reis, João Barroso, Tiago Pinto

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An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings by Chris Pliakos, Giorgos Efrem, Dimitrios Terzis, Pericles Panagiotou

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Optimization of non-smooth functions via differentiable surrogates. by Shikun Chen, Zebin Huang, Wenlong Zheng

“…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …”
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