THE PROPOSAL MODEL OF RATIONAL WORKFORCE ASSIGNMENT IN DOKUZ EYLUL UNIVERSITY BY ANALYTIC HIERARCHY PROCESS BASED 0-1 INTEGER PROGRAMMING by Yılmaz GÖKŞEN, Hakan AŞAN, Onur DOĞAN, Mustafa ÜNLÜ, Osman PALA

“…The Assignment model of the type of linear programming models is a mathematical method used to match the right person for the right job. The coefficients of the variables in the objective function of the assignment model constitute potential contributions of employees. …”
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Data Mining of 24-Hour Cumulative Precipitation Data in Iran Using Machine Learning: Multilayer Perceptron Neural Network and Decision Tree by mozaffar faraji, Majid Rezaii Banafsheh Daragh, Behroz sarisarraf, Ali Mohammad Khorshid Dust

“…Two machine learning models including MLP with activation function σ and decision tree with entropy criterion were implemented. …”
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Optimal Operation of CCHP Smart Distribution Grid with Integration of Renewable Energy by Ghassan A. Bilal, Mohammed K. Al-Saadi, Ghaidaa A. Al-Sultany, Wisam Abed Kattea Al-Maliki

“…Recently, electric distribution grids supply not only electric loads but also heating and cooling loads simultaneously to increase the efficiency of the system and reduce the emission of greenhouse gases. …”
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Optimal Capacity Configuration of Residential Solar-Hydrogen Coupling Energy System with Hydrogen Vehicle Load by Zhenlan DOU, Chunyan ZHANG, Huirong ZHAO, Yuqi YAO, Daogang PENG

“…Secondly, by setting the capacity of the equipment in the system as the optimization variable, and the minimization of annual investment cost of the system as the objective function, the reliability of energy supply and other factors as the constraints, the system optimal capacity configuration model is established. …”
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Convolutional neural networks for accurate estimation of canopy cover by F. Puig, R. Gonzalez Perea, A. Daccache, M.A. Soriano, J.A. Rodríguez Díaz

“…Canopy Cover (CC) is a key variable in agriculture, providing critical information on crop growth and health. …”
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A Multi-Objective PSO-GWO Approach for Smart Grid Reconfiguration with Renewable Energy and Electric Vehicles by Tung Linh Nguyen, Quynh Anh Nguyen

“…Notably, the approach achieves substantial reductions in power losses during peak demand periods with distributed generation incorporation while maintaining voltage profiles within the stringent operational bounds of 0.94 to 1.0 per unit, thus ensuring stability amidst variable load conditions. Comparative analyses further demonstrate that the hybrid method surpasses conventional optimization techniques, as evidenced by enhanced convergence rates and superior objective function outcomes. …”
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Food Supply Chain: A Framework for the Governance of Digital Traceability by Maria Bonaria Lai, Daniele Vergamini, Gianluca Brunori

“…Under the context of increasing demand for transparency, efficiency, and trust in food systems, digital traceability is emerging as a key strategy for improving value creation across agri-food supply chains. …”
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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

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Sensitivity analysis of melting heat transfer in Williamson fluid by Aliya Batool, Zakir Hussain, Dilawar Hussain

“…The model is simplified to ordinary differential equations by introducing similarity variables and tackled by bvp4c Matlab function. The significant variables on flow model are identified by Response Surface Method (RSM). …”
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Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…The TD3 algorithm approximates the value function and policy by harnessing deep neural networks, equipping it to tackle complex and nonlinear sea condition challenges. …”
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Generalized Type-2 Fuzzy Approach for Parameter Adaptation in the Whale Optimization Algorithm by Leticia Amador-Angulo, Oscar Castillo, Patricia Melin, Zong Woo Geem

“…The efficiency of a fuzzy WOA with a GT2FLS (FWOA-GT2FLS) is highlighted by presenting the excellent results of the case study of the benchmark function optimization. …”
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Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor by Santiago Rómoli, Mario Serrano, Francisco Rossomando, Jorge Vega, Oscar Ortiz, Gustavo Scaglia

“…The lack of online information on some bioprocess variables and the presence of model and parametric uncertainties pose significant challenges to the design of efficient closed-loop control strategies. …”
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Evaluating the Potential Use of Wearable Fitness Devices as a Measure of Outcomes in Orthopaedics by Jordan Henderson BS, Santiago Logan-Baca BS, Sara Kisiel BS, Fadi Muheidat PhD, David Jaffe MD

“…Surveys utilized were the Foot and Ankle Ability Measure Computerized Adaptive Testing (FAAM CAT), PROMIS physical function, mobility and pain interference scores, and Visual Analog Scale (VAS). …”
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Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. …”
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The Relationship between Optimism and Mindfulness with Cognitive Performance in Older Adults by Sanaz Ghannadi, Morteza Tarkhan

“…Furthermore, 34% of the variance in cognitive function was explained by optimism and mindfulness.Conclusion: Therefore, based on the findings of the present study, it can be concluded that optimism and mindfulness are important variables in predicting cognitive function (p < 0.05).…”
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Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

“…The developed DL model integrates convolutional neural network (CNN) layers to capture spatial features and long short-term memory (LSTM) layers to extract temporal patterns from demographic and activity-related variables. These features are combined through a fusion layer, and a customized loss function is employed to accurately predict fitness scores.ResultsExtensive experimental evaluation demonstrates that the proposed model consistently outperforms competitive baseline models. …”
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Optimizing the Production of LNG and NGL from Arab Crudes and Wet Gases by Adel M. Hemeida, Mohammed S. Al-Blehed, Saad El-Din Desouky

“…The developed model should be utilized as a useful tool to help the design of an efficient processing of natural gases. A great deal of the unlimited what if questions can be answered using this model. …”
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Flow-based cytometric analysis of cell cycle via simulated cell populations. by M Rowan Brown, Huw D Summers, Paul Rees, Paul J Smith, Sally C Chappell, Rachel J Errington

“…We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. …”
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A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…Around the core of the system, a nonlinear constrained optimization model is established, which uses adjustments to newly retained gilts as decision variables and minimizes supply-demand squared errors as its objective function, incorporating multi-dimensional factors such as pig growth dynamics, epidemic impacts, consumption trends, and international trade into its analytical framework. …”
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A LINEAR SIMULATION MODEL FOR OPTIMIZING CROP STRUCTURE IN ORDER TO MAXIMIZE INCOME IN A VEGETAL AGRICULTURAL FARM by Sorin IONITESCU

“…The model included: the 8 unknown variables for the cultivated area with 8 crops: wheat, rye, barley, peas, rape, soybean, maize and sunflower, 14 restrictions regarding Diesel fuel, fertilizers, herbicides, total surface, expenditures, income, and area per each crop, and objective - function f(Max) Income. …”
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