Evaluation and optimization of adaptive cruise control in autonomous vehicles using the car learning to act simulator: A performance evaluation under various weather conditions by Roza Al-Hindawi, Taqwa Alhadidi

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THE USE OF PROJECT TECHNOLOGIES IN THE CONTEXT OF TRAINING FUTURE EDUCATORS FOR PROFESSIONAL ACTIVITY IN THE CONTEXT OF INCLUSIVE EDUCATION IN PRESCHOOL EDUCATION INSTITUTIONS by Л. Шевченко, М. Сорочан

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Sensitivity Analysis for Dynamic Parameters of High–Speed Train Based on Multimodal–Optimization Improved Kriging Model and Distance Correlation by Jie JIANG, Xufeng YANG, Guofu DING

“…There are many parameters that affect the dynamic performance of high-speed trains, and there are many evaluation indexes that can be used to assess this performance. …”
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A new format of bachelors’ final state certification in the field of training «Library-information activity»: a development technology by G. M. Bragina, A. Sh. Merkulova

“…The 3rd generation Federal Educational Standard requirements necessitate innovations in organizing and carrying out bachelors’ SFC, in particular, evaluation of their training quality based on a competence approach. …”
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Predicting Ocean Current Temperature Off the East Coast of America with XGBoost and Random Forest Algorithms Using Rstudio by Lulut Alfaris, Anas Noor Firdaus, Ukta Indra Nyuswantoro, Ruben Cornelius Siagian, Aldi Cahya Muhammad, Rohana Hassan, Rodulfo T. Aunzo, Jr., Reza Ariefka

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Fault analysis on deep groove ball bearing using ResNet50 and AlexNet50 algorithms by Vedant Jaiswal, Narendiranath Babu T, Pandiyan Murugan, Rama Prabha D

“…Automatic fault classification has been done by Artificial Neural Networks (ANN). Training on various algorithms is performed, noting and storing the probability of correct prediction for comparison. …”
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An enhanced time efficient technique for image watermarking using ant colony optimization and light gradient boosting algorithm by Vipul Sharma, Roohie Naaz Mir

“…When compared with the existing optimization methods, it has been found that the proposed method consumes very less time for the evaluation of optimum solutions. From the results, it has been identified that the proposed algorithm satisfies the image watermarking with the improvement in time enhancement. …”
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A hybrid machine learning model with self-improved optimization algorithm for trust and privacy preservation in cloud environment by Himani Saini, Gopal Singh, Sandeep Dalal, Iyyappan Moorthi, Sultan Mesfer Aldossary, Nasratullah Nuristani, Arshad Hashmi

“…Key contributions include a comprehensive methodology that encompasses dataset selection, preprocessing, model training, and evaluation across multiple datasets, including healthcare, financial, and pandemic-related data. …”
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Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…The optimized parameters were subsequently implemented in the RF classifier training. The composite algorithm reduced feature redundancy by approximately 30% while ensuring the effective retention of critical diagnostic indicators. …”
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FDRL: a data-driven algorithm for forecasting subsidence velocities in Himalayas using conventional and traditional soil features by Sahil Sankhyan, Ajoy Kumar, Praveen Kumar, Aaditya Sharma, K. V. Uday, Varun Dutt

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Hybrid quantum neural networks show strongly reduced need for free parameters in entity matching by Lukas Bischof, Stefan Teodoropol, Rudolf M. Füchslin, Kurt Stockinger

“…In this paper, we evaluate quantum machine learning algorithms for entity matching on a hand-crafted data set and compare them to similar classical algorithms. …”
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Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI by Sihwan Kim, Changmin Park, Gwanghyeon Jeon, Seohee Kim, Jong Hyo Kim

“…Two publicly available datasets were used in developing the ASHSC algorithm: 280 CT scans from the TotalSegmentator dataset for training and 274 CT scans from the Cancer Imaging Archive (TCIA) dataset for performance evaluation. …”
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BSDR: A Data-Efficient Deep Learning-Based Hyperspectral Band Selection Algorithm Using Discrete Relaxation by Mohammad Rahman, Shyh Wei Teng, Manzur Murshed, Manoranjan Paul, David Brennan

“…However, they require a large number of model parameters, which increases the need for extensive training data. To address this challenge, we propose Band Selection through Discrete Relaxation (BSDR), a novel deep learning-based algorithm. …”
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Deep learning-based recognition model of football player’s technical action behavior using PCA–LBP algorithm by Hongtao Chen, Zhengbai Lin, Quan Xu

“…It must consider the distinctions between individuals and then provide targeted training. Football players can perform better on the field with targeted scientific training, but scientific training is based on identifying football players’ technical actions and behaviors. …”
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Speed and efficiency analysis of artificial intelligence recognition system of glomerular pathology based on Faster R-CNN algorithm by YANG Hui, ZHANG Xing-na, JIANG Qiu-zhu, YUAN Cheng-ying, QU Chong-xiao, LIU Yun-xiao, WANG Chen, LI Ming, LI Rong-shan, ZHOU Xiao-shuang

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Multiagent Energy Management System Design Using Reinforcement Learning: The New Energy Lab Training Set Case Study by Parisa Mohammadi, Razieh Darshi, Hamidreza Gohari Darabkhani, Saeed Shamaghdari

“…We introduce a model-free Q-learning (QL) algorithm for managing energy in the NEL. Agents explore the environment, evaluate state-action pairs, and operate in a decentralized manner during training and implementation. …”
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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

“…Methods A previously trained pix2pixHD Generative Adversarial Network was evaluated. …”
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Development and validation of a deep reinforcement learning algorithm for auto-delineation of organs at risk in cervical cancer radiotherapy by Li Yucheng, Qiu Lingyun, Shao Kainan, Jia Yongshi, Zhan Wenming, Ding Jieni, Chen Weijun

“…Among these images, 122 CT images were used as a training set for the algorithm training of the DRL model based on the SAM model, and 28 CT images were used for the test set. …”
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SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…Next, the network intrusion detection process is modeled as a Markov decision process and integrated with the Soft Actor-Critic (SAC) reinforcement learning algorithm, with a view to constructing agents; In the context of adversarial training, two agents, designated as the attacker and the defender, are defined to perform asynchronous adversarial training. …”
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PaleAle 6.0: Prediction of Protein Relative Solvent Accessibility by Leveraging Pre-Trained Language Models (PLMs) by Wafa Alanazi, Di Meng, Gianluca Pollastri

“…Inspired by the remarkable success of NLP techniques, this study leverages pre-trained language models (PLMs) to enhance RSA prediction. …”
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