PRODUCTION AND INCOME ANALYSIS OF DRIED FISH BUSINESS IN BENGKULU CITY by Bambang Sumantri, Irnad, Winta Septria, Melly Suryanti, Widya Kartika Laksmawati

“…R/C Ratio analysis obtained efficiency values of 2.13 and 1.91 respectively so the business is carried out proved to be efficient. …”
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Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

“…Industrial energy systems are increasingly required to reduce operating costs and CO₂ emissions while integrating variable renewable energy sources. Managing these objectives under uncertainty requires advanced optimization strategies capable of delivering reliable and real-time decisions. …”
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Notice of Violation of IEEE Publication Principles: VVC/H.266 Intra Mode QTMT Based CU Partition Using CNN by Sameena Javaid, Safdar Rizvi, Muhammad Talha Ubaid, Abdullah Tariq

“…Finally, a variable threshold decision system is established to achieve the targeted low complexity and RD performance. …”
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Impact of municipal wastewater use on urban and peri‑urban agricultural productivity: the endogenous treatment-effects approach by Mohammed Abdulai, Mohammed Tanko, Alhassan Andani

“…Using survey data from 416 vegetable farmers, we employed a semi-log production function augmented with an endogenous binary-treatment effect equation to estimate the drivers and impact of MWW use on value of vegetable output, accounting for selection bias and omitted variable problem. …”
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Machine learning with hyperparameter optimization applied in facies-supported permeability modeling in carbonate oil reservoirs by Watheq J. Al-Mudhafar, Alqassim A. Hasan, Mohammed A. Abbas, David A. Wood

“…On the other hand, highly permeable fractures function as the main flow conduits within such reservoirs. …”
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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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Modal Analysis of QP and LP Solution in Steady-state Optimization Layer of Two-layer Structure MPC by WANG Hongrui, ZHANG Xin, LIU Bowen, LIN Na, ZOU Tao

“…Simulation results prove that QP had better continuity than LP when the weight coefficient of decision variables are changed, and the weight coefficient of QP can more accurately adjust the bias of decision variables. …”
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Socio‑Economic Determinants of Construction Sector Development by Florian Gerth, Martin O’Brien, Karol S. Sikora

“…The empirical analysis applied uses data from the Statistical Yearbook of Cambodia (2021) to analyze the statistical relationship between socioeconomic , economic, demographic variables and construction. To do this, the study conducts a combination of regression analyses, Ordinary Least Squares in conjunction with Methods-of-Moments, while applying rigor to guarantee compliance with the CLR function assumptions. …”
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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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Research on Robust Adaptive Model Predictive Control Based on Vehicle State Uncertainty by Yinping Li, Li Liu

“…To overcome these limitations, three key innovations are introduced: a three-degree-of-freedom vehicle dynamic model integrated with recursive least squares-based online estimation of tire slip stiffness for real-time lateral force compensation; an adaptive weight adjustment mechanism that dynamically balances control energy consumption and tracking accuracy by tuning cost function weights based on real-time state errors; and a dynamic constraint relaxation strategy using slack variables with variable penalty terms to resolve infeasibility while suppressing excessive constraint violations. …”
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Analyzing Worn-Out Texture Regeneration from Urban Branding Perspective Using Structural Equation Modeling (SEM) (Case Study: Worn-Out Texture of Shahr-e-Kord) by Dvood Mahdavi, Ali Mohammadi Gojani, Waliullah Nazari

“…Furthermore, the findings demonstrated a strong, positive, and significant influence of the branding variable on the regeneration of the worn-out urban fabric with an impact coefficient of 0.833. …”
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Explaining the COVID19 mortality growth rate: an empirical analysis of Israeli cities by Yuval Arbel, Yifat Arbel, Amichai Kerner, Miryam Kerner, Miryam Kerner

“…These include population size, median age, a socio-economic ranking at a city level, a date variable and a dummy variable that equals 1 for post-vaccination and 0 for pre-vaccination era.MethodRegression analysis, where each variable is converted to the standard normal distribution function. …”
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Development of a Plant-Based Beverage with Tarwi (<i>Lupinus mutabilis</i>) Milk, Polysaccharides from Cushuro (<i>Nostoc sphaericum</i>), and Blueberry Extract by Santos Calderón, Renzo Bañón

“…The response variables were protein (%) content and viscosity coefficient (mPa·s). …”
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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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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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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 explanatory variables of the model are LNG and NGL volumes and prices, oil volume and prices, the initial costs of separators, chillers, demethanizer, compressor, partial condenser and boiler, the running cost which includes cost of refrigerants, cost of steam and other continuous operating and transportion cost. …”
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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 theory and data-driven method for rapid bottom hole pressure calculation in UGS by Yang Li, Haiwei Guo, Xianfeng Gong, Naixin Lu, Kairui Zhang

“…Subsequently, it delves into the characteristic variables closely related to bottom hole pressure and constructs a neural network model on this basis. …”
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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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