Elevator Control Simulation Using Fuzzy Logic Management by Mehr Ali Qasimi, Asmatullah Nashir

“…Within a set of fuzzy rules, three important linguistic variables are added to improve the performance of the elevator group. …”
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Can digital transformation improve the transparency and accountability of Indonesian public governance? by M. Irwan Tahir, Ani Martini, Anak Agung Ngurah Gunawan, Yogi Makbul, Nirma Yossa, Wisber Wiryanto, Moch Fahrudin, Rahmat Ilya

“…The research uses quantitative methods to test the relationship between variables. The respondents of this research were 478 government public service office employees who were determined using a simple random sampling method. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…This study investigates an advanced diagnostic strategy to assess particulate filter health based on resistive soot sensors and available engine variables. The sensor data are projected to generate a 2D signature that reflects the changes in filtration efficiency. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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Reference Intervals for Echocardiography Parameters of Children Living in the Arkhangelsk Region and a Digital Application for Their Assessment by Aleksey A Karyakin, Igor’ S. Chub, Ol’ga E. Karyakina, Andrey M. Grjibovski, Aleksey V. Artemov, Ul’yana R. Zakharchenko

“…Reference intervals of echocardiography parameters were determined using body surface area as the dependent variable. The values were automatically calculated in our digital application that allows one to increase the accuracy and efficiency of interpretation of cardiac ultrasound parameters. …”
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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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Approximate analytical solution of a class of highly nonlinear time–fractional-order partial differential equations by Richard Olu Awonusika

“…The method assumes a fractional power series in the time variable whose expansion coefficients are functions of the space variable. …”
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Expanding a Health Technology Solution to Address Therapist Challenges in Implementing Homework With Adult Clients: Mixed Methods Study by Brian E Bunnell, Kaitlyn R Schuler, Julia Ivanova, Lea Flynn, Janelle F Barrera, Jasmine Niazi, Dylan Turner, Brandon M Welch

“… BackgroundHomework is implemented with variable effectiveness in real-world therapy settings, indicating a need for innovative solutions to homework challenges. …”
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Impact of IgG subclass on monoclonal antibody developability by Paul Cain, Lihua Huang, Yu Tang, Victor Anguiano, Yiqing Feng

“…We thus conducted a systematic study of 12 mAbs derived from three sets of unrelated variable regions, each cloned into IgG1, an IgG1 variant with diminished effector functions, IgG2, and a stabilized IgG4 variant with further reduced FcγR interaction, to evaluate the impact of IgG subclass on manufacturability and high concentration stability in a common formulation buffer matrix. …”
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Multi-Scale Multi-Domain Hybrid Finite Element Modeling of Light Propagation by Jingwei Wang, Zhanwen Wang, Lida Liu, Yuntian Chen

“…We revisit finite element method of modeling multi-scale photonic/electromagnetic devices via the proposed beam basis function, in combination with domain decompositions. …”
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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 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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Bayesian inference for peak feature extraction and prediction of material property in X-ray diffraction data by Ryo Murakami, Taisuke T. Sasaki, Hideki Yoshikawa, Yoshitaka Matsushita, Keitaro Sodeyama, Tadakatsu Ohkubo, Hiroshi Shinotsuka, Kenji Nagata

“…We then applied Bayesian linear regression to the maximum energy product [Formula: see text], using the extracted peak features as the explanatory variable. The outcomes yielded reasonable and robust regression results. …”
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Modelación de la Solubilidad de Panela Granulada y Otros Edulcorantes en Agua by Nelly Lara, Alejandra Clavijo, Verónica Barrera

“…Se evaluó el efecto de las variables independientes (genotipo  de caña panelera, temperatura de la fuente de calentamiento y la condición higiénica  de la caña) sobre las constantes de solubilidad de las muestras experimentales de panela granulada. …”
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Modelación de la Solubilidad de Panela Granulada y Otros Edulcorantes en Agua by Nelly Lara, Alejandra Clavijo, Verónica Barrera

“…Se evaluó el efecto de las variables independientes (genotipo  de caña panelera, temperatura de la fuente de calentamiento y la condición higiénica  de la caña) sobre las constantes de solubilidad de las muestras experimentales de panela granulada. …”
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Modelación de la Solubilidad de Panela Granulada y Otros Edulcorantes en Agua by Nelly Lara, Alejandra Clavijo, Verónica Barrera

“…Se evaluó el efecto de las variables independientes (genotipo  de caña panelera, temperatura de la fuente de calentamiento y la condición higiénica  de la caña) sobre las constantes de solubilidad de las muestras experimentales de panela granulada. …”
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