Data mining methods application in reflexive adaptation realization in e-learning systems by A. S. Bozhday, Y. I. Evseeva, A. A. Gudkov

“…In recent years, e-learning technologies are rapidly gaining momentum in their evolution. In this regard, issues related to improving the quality of software for virtual educational systems are becoming topical: increasing the period of exploitation of programs, increasing their reliability and flexibility. …”
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Prediction of adverse drug reactions based on pharmacogenomics combination features: a preliminary study by Mingxiu He, Mingxiu He, Yiyang Shi, Fangfang Han, Fangfang Han, Fangfang Han, Yongming Cai, Yongming Cai, Yongming Cai

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A Novel Smart Molecular Fuzzy Decision Support System for Solid-State Battery Investments in Grid-Level Renewable Energy Storage by Gang Kou, Hasan Dincer, Serhat Yuksel, Edanur Ergun, Serkan Eti

“…For this purpose, a new decision-making model is developed that includes expert weighting with the entropy game, evaluation balancing with the Q-learning algorithm, calculation of criterion weights with the least squares optimization (LSO) and alternative ranking with the molecular ranking (MORAN) method. …”
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Fire Hawk Optimizer Adjusted Tri-Stage (1+PI)-PI-TID Cascade Controller for Automatic Generation Control of PSI by Moses Awal, Michael Robson Atim, Jimmy Nabende Wanzala, Johnes Obungoloch, Mohamed Barakat

“…This study aims to enhance the performance of automatic generation control (AGC) in power systems interconnection (PSI) by employing the fire hawk optimizer (FHO), a green algorithm, to optimize a novel tri-stage cascade controllers (CCs) configuration: (1+PI)-PI-PID and (1+PI)-PI-TID CCs. …”
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A spatio-temporal fusion-based approach for multi-dimensional classification of Parkinson’s disease progression using multi-modal dataset by Vinay Kukreja, Vandana Ahuja, Modafar Ati, Hariharan Shanmugasundaram, Murugaperumal Krishnamoorthy, Rishabh Sharma, Abhishek Bhattacherjee

“…Context: The progressive neurodegenerative disorder Parkinson’s disease (PD) features diverse symptom presentation that progresses at different speeds and demands effective disease classification with precise patient management. …”
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Load-dependent vehicle routing problem with route time constraint: a heuristic approach by Nguyen Thuy Trang, Parthana Parthanadee, Jirachai Buddhakulsomsiri, Pham Duc Tai

“…The performance of the proposed mathematical model and the heuristic algorithm is evaluated by using adapted problem instances, where different combinations of capacity, route time limitations, and base loads are included. …”
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FedPark: A Federated Learning Crowdsensing Solution for On-Street Parking Availability by Afraa Attiah, Shatha Alahmadi, Abeer Hakeem, Linda Mohaisen, Abeer Almakky, Reemah M. Alhebshi

“…Instead of transmitting raw data, only model updates are shared, reducing communication overhead and security risks. FedPark is evaluated under different urban conditions such as different numbers of drivers and destinations. …”
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Machine learning for Internet of Things (IoT) device identification: a comparative study by Hamid Tahaei, Anqi Liu, Hamid Forooghikian, Mehdi Gheisari, Faiz Zaki, Nor Badrul Anuar, Zhaoxi Fang, Longjun Huang

“…Numerous studies have proposed various solutions that incorporate ML and feature selection (FS) algorithms with different degrees of accuracy. Yet, the domain needs a comparative analysis of the accuracy of different classifiers and FS algorithms to comprehend their true capabilities in various datasets. …”
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Automated quantification of T1 and T2 relaxation times in liver mpMRI using deep learning: a sequence-adaptive approach by Lukas Zbinden, Samuel Erb, Damiano Catucci, Lars Doorenbos, Leona Hulbert, Annalisa Berzigotti, Michael Brönimann, Lukas Ebner, Andreas Christe, Verena Carola Obmann, Raphael Sznitman, Adrian Thomas Huber

“…Abstract Objectives To evaluate a deep learning sequence-adaptive liver multiparametric MRI (mpMRI) assessment with validation in different populations using total and segmental T1 and T2 relaxation time maps. …”
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External phantom-based validation of a deep-learning network trained for upscaling of digital low count PET data by Anja Braune, René Hosch, David Kersting, Juliane Müller, Frank Hofheinz, Ken Herrmann, Felix Nensa, Jörg Kotzerke, Robert Seifert

“…The performance of this algorithm has so far only been clinically evaluated on patient data featuring limited scan statistics and unknown actual activity concentration. …”
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An Improved Artificial Neural Network Model for Effective Diabetes Prediction by Muhammad Mazhar Bukhari, Bader Fahad Alkhamees, Saddam Hussain, Abdu Gumaei, Adel Assiri, Syed Sajid Ullah

“…This paper develops an improved ANN model trained using an artificial backpropagation scaled conjugate gradient neural network (ABP-SCGNN) algorithm to predict diabetes effectively. For validating the performance of the proposed model, we conduct a large set of experiments on a Pima Indian Diabetes (PID) dataset using accuracy and mean squared error (MSE) as evaluation metrics. …”
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Classification of Continuous Sky Brightness Data Using Random Forest by Rhorom Priyatikanto, Lidia Mayangsari, Rudi A. Prihandoko, Agustinus G. Admiranto

“…This study aims to develop a classification model based on Random Forest algorithm and to evaluate its performance. Using sky brightness data from 1250 nights with minute temporal resolution acquired at eight different stations in Indonesia, datasets consisting of 15 features were created to train and test the model. …”
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Optimization configuration method of integrated energy system for reliability improvement of distribution network by SHI Mingming, MIAO Huiyu, GUO Jiahao, JIANG Yunlong, XIAO Xiaolong

“…Then, based on the NSGA-Ⅱ (non-dominated sorting genetic agorithm Ⅱ) multi-objective optimization algorithm, the equipment capacity and access point location of IES are optimized with the objective of the economy and reliability of IES and distribution network respectively, and the optimal scheme under different planning scenarios is selected in Pareto solution set by utility function. …”
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Robust Optical and SAR Image Registration Using Weighted Feature Fusion by Ao Luo, Anxi Yu, Yongsheng Zhang, Wenhao Tong, Huatao Yu

“…To verify the effectiveness of the method, different optical and SAR datasets are used to compare it with the currently advanced algorithms MOGF, CFOG, and FED-HOPC. …”
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Phenotypic heterogeneity and diagnostic features of transthyretin amyloidosis with polyneuropathy by S. S. Nikitin, S. N. Bardakov, N. A. Suponeva, I. V. Zhirov, T. A. Adyan, D. A. Grishina, R. V. Deev

“…Molecular genetic testing should be considered early in the evaluation of a patient with unexplained peripheral neuropathy and cardiomyopathy. …”
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Pattern recognition method for the identification of Daiqu large yellow croaker based on computer vision by YU Xinjie, WU Xiongfei, SHEN Weiliang

“…Then principal component analysis (PCA) and successive projections algorithm (SPA) were respectively applied to extract and select the measured morphological parameters, and then obtained three groups of different characteristic variable sets, which were PCA transformed feature, PCA selected feature, SPA selected feature, respectively. …”
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Automatic detection of pupil reactions in cataract surgery videos. by Natalia Sokolova, Klaus Schoeffmann, Mario Taschwer, Stephanie Sarny, Doris Putzgruber-Adamitsch, Yosuf El-Shabrawi

“…We further investigate the generalization ability of this method on a slightly different dataset without retraining the model. In this evaluation, we achieve the H value of 49.3% with the PL of 18.15 seconds.…”
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Comprehensive Review of Robotics Operating System-Based Reinforcement Learning in Robotics by Mohammed Aljamal, Sarosh Patel, Ausif Mahmood

“…This work focuses on investigating ROS-based RL applications across various domains, aiming to enhance understanding through comprehensive discussion, analysis, and summarization. We base our evaluation on the application area, type of RL algorithm used, and degree of ROS–RL integration. …”
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Remote sensing image Super-resolution reconstruction by fusing multi-scale receptive fields and hybrid transformer by Denghui Liu, Lin Zhong, Haiyang Wu, Songyang Li, Yida Li

“…Abstract To enhance high-frequency perceptual information and texture details in remote sensing images and address the challenges of super-resolution reconstruction algorithms during training, particularly the issue of missing details, this paper proposes an improved remote sensing image super-resolution reconstruction model. …”
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Optimized Modeling Strategies for the Parametrization of a Two-Parameter Friction Model Through Inverse Modeling of Conical Tube-Upsetting Tests by Michel Henze, Lena Koch, David Bailly, Marco Teller, Gerhard Hirt

“…It is based on a comparison of the specimen’s outer contour for several points in time throughout the forming process according to the finite element model of the test. An optimization algorithm minimizes the deviation between the experimental and the simulated contour by adapting the friction model parameters. …”
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