Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…The second one is LSGO-Rever, where the boolean operators in the equation are reversed or exchanged and hence, no variables are lost. The three algorithms have been simulated with various datasets of knapsack and its variant problems and bin-packing problem for thorough testing on different problem types and scalability. …”
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Deep learning-based analysis of 12-lead electrocardiograms in school-age children: a proof of concept study by Shuhei Toba, Yoshihide Mitani, Yusuke Sugitani, Yusuke Sugitani, Hiroyuki Ohashi, Hirofumi Sawada, Mami Takeoka, Naoki Tsuboya, Kazunobu Ohya, Noriko Yodoya, Takato Yamasaki, Yuki Nakayama, Hisato Ito, Masahiro Hirayama, Motoshi Takao

“…The diagnostic performance of the model and a conventional algorithm (ECAPS12C, Nihon Kohden, Japan) for classifying abnormal electrocardiograms were evaluated using the cross-tabulation, McNemar's test, and decision curve analysis.ResultsWe included 1,842 ECGs performed in 1,062 patients in this study, and 310 electrocardiograms performed in 177 patients were included in the test group. …”
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Efficient Solar Cell Design through Grey Wolf Optimization: Multi-Layer Thickness Optimization for Enhanced Short-Circuit Current Density by Hamed Kargaran, Hassan Alipour, Maryam Amirhoseiny, Ghasem Alahyarizadeh

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Numerical Analysis of Digital Twin System Modeling Methods Aided by Graph-Theoretic Combinatorial Optimization by Sujing Zhou

“…Secondly, a scheduling technology framework for capacity simulation evaluation and optimization is established, and batching optimization, outsourcing decision, and rolling scheduling techniques are thus proposed to form a batching optimization algorithm based on priority rules, which realizes batching processing, outsourcing decision, and rolling scheduling of production orders to optimize equipment utilization and capacity. …”
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A Machine Learning Approach to Evaluate the Performance of Rural Bank by Jun Wei, Tao Ye, Zhe Zhang

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A Fast Approach for Reoptimization of Railway Train Platforming in Case of Train Delays by Yongxiang Zhang, Qingwei Zhong, Yong Yin, Xu Yan, Qiyuan Peng

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Network access and spectrum allocation in next-generation multi-heterogeneous networks by Xiaoqing Dong, Lianglun Cheng, Gengzhong Zheng, Tao Wang

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Optimizing the Joint Replenishment and Delivery Scheduling Problem under Fuzzy Environment Using Inverse Weight Fuzzy Nonlinear Programming Method by Yu-Rong Zeng, Lin Wang, Xian-Hao Xu, Qing-Liang Fu

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University proceedings. Volga region. Technical sciences by V.S. Knyazkov, A.I. Ivanov, K.S. Isupov, M.M. Butayev

Analyzing the efficacy of trimethylolpropane trioleate oil for predicting cutting power and surface roughness in high-speed drilling of Al-6061 through machine learning. by Pramod S Kathmore, Bhanudas D Bachchhav, Duran Kaya, Sachin Salunkhe, Lenka Cepova, Ondřej Mizera, Emad Abouel Nasr

“…The decision tree performed better than other models in accurately predicting power and surface roughness. …”
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Water quality assessment monitoring system using fuzzy logic and the internet of things by Hanif Fakhrurroja, Edi Triono Nuryatno, Aris Munandar, Muhammad Fahmi, Novan Agung Mahardiono

“…Our system serves as a decision support tool, enabling continuous assessment of water quality. …”
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Ensemble Learning-Based Alzheimer’s Disease Classification Using Electroencephalogram Signals and Clock Drawing Test Images by Young Jae Huh, Jun-ha Park, Young Jae Kim, Kwang Gi Kim

“…In this research, we demonstrate that three machine learning algorithms, trained on an ensemble of electroencephalogram (EEG) and clock drawing test (CDT) feature data for an AD classification task, show improved AD detection accuracy compared to when either the EEG or CDT dataset is used independently. …”
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Determination of disintegration time using formulation data for solid dosage oral formulations via advanced machine learning integrated optimizer models by Mohammed Ghazwani, Umme Hani

“…Utilizing a dataset of approximately 2,000 entries encompassing molecular properties, physical properties, excipient composition, and formulation characteristics, three ML models were evaluated: TabNet, Radial Basis Function Support Vector Regression (RBF-SVR), and Neural Oblivious Decision Ensembles (NODE). …”
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SOFTWARE OPTIMIZATION TECHNOLOGY OF AIRCRAFT COMPOSITION IN OPERATIONAL PLANNING IN THE AEROSPACE SEARCH AND RESCUE SYSTEM by A. V. Sobolev, V. A. Popov

“…The article provides an analysis of domestic developments in the field of information and technical support for search and rescue (SAR), an algorithm for decision-making based on factors influencing the choice of search and rescue forces and assets. …”
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Skincare Recommendation System Based on Facial Skin Type with Real-Time Weather Integration by Gabrielle Sheila Sylvagno, Theresia Herlina Rochadiani

“…The system consists of three main components: a ResNet50-based Skin Analyzer, a Weather Analyzer using the Decision Tree algorithm, and a Product Recommendation module. …”
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Hybrid modeling of adsorption process using mass transfer and machine learning techniques for concentration prediction by Jing Lv, Lei Wang

“…To improve model performance, hyperparameters were optimized using the bio-inspired Barnacles Mating Optimizer (BMO) algorithm. Model evaluation based on R2, root mean square error (RMSE), and mean absolute error (MAE) demonstrated that RBF-SVM outperformed the other models, achieving an R2 of 0.9537, RMSE of 3.5136, and MAE of 1.5326. …”
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A Novel Method for Diagnosing Heart Diseases Based on Internet of Things by Samir Paul

“…The architecture includes three phases: data collection from sensors, decision-making via the fuzzy logic controller on the Arduino platform, and real-time communication of results to medical teams. …”
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A Dynamic Framework for Community-Facility Siting with Inter-Community Competition by Sisi Zhu, Haoying Han, Anran Dai

“…This framework includes the BOMSDM itself, the data collection and processing method, and the constrained NSGA-II as the computational algorithm. Under this framework, the BOMSDM, along with three comparative frameworks derived from traditional models—including a random allocation non-incremental model, a random allocation incremental model, and an average allocation non-incremental model—was applied to a real-world scenario in Shaoxing. …”
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Sentiment Analysis on Google Reviews Using Naïve Bayes, K-Nearest Neighbors, and Logistic Regression to Improve Novotel Services by Yonathan Arya Dhamma, Simon Prananta Barus

“…This study aims to obtain sentiment analysis results from Novotel hotel Google reviews based on machine learning by comparing three algorithms, namely Naïve Bayes, K-Nearest Neighbors (KNN), and Logistic Regression. …”
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Machine learning-based analysis on pharmaceutical compounds interaction with polymer to estimate drug solubility in formulations by Ahmad J. Obaidullah, Wael A. Mahdi

“…The primary goal is to improve the accuracy of predictions by using ensemble learning techniques. Three base models were evaluated including: Decision Tree (DT), K-Nearest Neighbors (KNN), and Multilayer Perceptron (MLP), which are subsequently improved with the AdaBoost ensemble method. …”
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