Predicting Employee Turnover Using Machine Learning Techniques by Adil Benabou, Fatima Touhami, My Abdelouahed Sabri

“…Background: Employee turnover is a persistent issue in human resource management, leading to significant costs for organizations. This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to anticipate turnover and implement proactive retention strategies.Objective: This study aims to address the challenge of employee attrition by applying machine learning techniques to provide predictive insights that can improve retention strategies.Methods: Nine machine learning algorithms are applied to a dataset of 1,470 employee records. …”
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PERSONALIZED APPROACH TO THYROTOXICOSIS TREATMENT: THE HISTORY OF DOSIMETRIC CONCEPTS DEVELOPMENT by P. O. Rumyantsev, A. A. Trukhin, M. V. Degtyarev

“…Historically there were developed several methods for calculating effective therapeutic activity: prescription of standard activities (fixed activities) and personalized assessment of effective activity based on evaluation of individual radiobiokinetics, followed by the mathematical modeling. Accumulated variety of approaches to dosimetric planning of radionuclide therapy demonstrates that an optimal algorithm for calculation has not been developed so far. …”
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Increment of Academic Performance Prediction of At-Risk Student by Dealing With Data Imbalance Problem by Nguyen Giap Cu, Thi Lich Nghiem, Thi Hoai Ngo, Manh Tuong Lam Nguyen, Hong Quan Phung

“…Studies on automatically predicting student learning outcomes often focus on developing and optimizing machine learning algorithms that fit the data captured from different education systems. …”
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Estimation of mangrove heights and aboveground biomass using UAV-LiDAR, Sentinel-1 and ZY-3 stereo images by Bolin Fu, Yingying Wei, Linhang Jiang, Hang Yao, Xiaomin Li, Yanli Yang, Mingming Jia, Weiwei Sun

“…The ZY-3 stereo images based on MDN obtained the optimal inversion results (R2 = 0.719), with an improvement ranging from 0.143 to 0.198 when compared to the PLSR and RF algorithms. (3) Avicennia marina was associated with the highest estimation accuracy (R2 = 0.897) compared to the other dominant mangrove species. …”
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Research on the quantification and automatic classification method of Chinese cabbage plant type based on point cloud data and PointNet++ by Chongchong Yang, Chongchong Yang, Lei Sun, Lei Sun, Jun Zhang, Jun Zhang, Xiaofei Fan, Xiaofei Fan, Dongfang Zhang, Dongfang Zhang, Tianyi Ren, Tianyi Ren, Minggeng Liu, Minggeng Liu, Zhiming Zhang, Zhiming Zhang, Wei Ma, Wei Ma

“…Finally, we combined 1024 feature vectors with 10 custom dimensionless features and used the optimized PointNet++ model for supervised learning to achieve the automatic classification of Chinese cabbage plant types. …”
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THE PROBATION OFFICER AS AN AUTHORITY OF CRIMINAL ENFORCEMENT LAW. DEVELOPMENT PROSPECTS IN THE LIGHT OF MODERN TECHNOLOGIES by Tomasz Kalisz

“…Among the advantages are cost efficiency, increased work effectiveness, better prediction of recidivism risk, optimized resource use, individualized approach, and easier communication and collaboration. …”
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An SVDD-based post-processing approach for vibration risk assessment of the hydro-turbine-generator in a large hydropower station by Jinliang Zhang, Fengwei Yang, Chao Liang, Yuansheng Zhang, Yongchang Li

“…Then, the boundary extension operation with detailed theoretical deduction is performed and the extended boundary is further optimized inspired by path planning problem. The advantage of proposed approach is that it can improve the data fitting performance for single dimension (i.e. vibration amplitude) without leading to complex boundary which cannot be used for vibration risk assessment. …”
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Intelligent collaborative management and control platform for continuous mining equipment in open-pit mines by Zhiyong LEI, Xiaolong MA, Shujun ZHAO, Shiming ZHANG, Bin YAN

“…The platform integrates advanced technologies, including dual-ring network transmission, network security protocols, multi-machine cooperative control, digital twin modeling, and big data analytics, facilitating effective coordination among coal miners, transfer machines, unloaders, and conveyors for seamless continuous mining operations.Three critical technical challenges are addressed: ① The implementation of dual-ring network transmission technology reduces data transmission latency and enhances network stability. ② A secure network transmission framework has been developed to safeguard data confidentiality and integrity. ③ The multi-machine cooperative control system incorporates data acquisition, process control, and 3D visualization modules, employing real-time monitoring and optimized control algorithms to boost mining and transportation efficiency while ensuring the continuity of multi-machine operations. …”
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Using machine vision to determine the rotational forces of electric motors by O.O. Shelukha, K.V. Molchanova, I.H. Babichev

“…The system has a user interface and allows visualizing the received data. To improve the dynamic characteristics of the system, it is proposed to optimize image processing algorithms, use more powerful computing resources, implement hardware acceleration, and optimize the transmission of the video stream.…”
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Research on image generation technology based on deep learning by Li Jinchen

“…Based on the above problems, this paper analyzes the methods of improving and optimizing the mainstream image generation algorithm from the perspectives of improving and optimizing the loss function, improving the space modeling, revising the structure of both the generator and discriminator, while speeding up the training process. …”
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A New Support Vector Machine Based on Convolution Product by Wei-Chang Yeh, Yunzhi Jiang, Shi-Yi Tan, Chih-Yen Yeh

“…., convolutional neural networks (CNNs)) are the two most famous algorithms in small and big data, respectively. Nonetheless, smaller datasets may be very important, costly, and not easy to obtain in a short time. …”
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Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

“…Key advantages of AI integration in endoscopy include improved sensitivity, minimized detection errors, and the potential to optimize clinical workflow efficiency. …”
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Application of artificial intelligence in electrochemical diagnostics for human health by Koushlesh Ranjan, Basanti Barar, Minakshi Prasad, Gaya Prasad

“…AI also assists in optimizing sensor design, manages large datasets, and improves the performance and reliability of electrochemical diagnostics (ED) devices. …”
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A Comprehensive Review of the Diagnostics for Pediatric Tuberculosis Based on Assay Time, Ease of Operation, and Performance by Soumya Basu, Subhra Chakraborty

“…Gaps in the existing diagnostic methods, algorithms, and operational costs were also reviewed. …”
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Predicting Subcontractor Performance Using Web-Based Evolutionary Fuzzy Neural Networks by Chien-Ho Ko

“…The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. …”
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Evaluation of Liver Fibrosis through Noninvasive Tests in Steatotic Liver Disease by Yuri Cho

“…Further research is needed to refine these diagnostic tools and improve accessibility.…”
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AI-Driven Robotics: Innovations in Design, Perception, and Decision-Making by Lei Li, Li Li, Mantian Li, Ke Liang

“…Artificial intelligence (AI), driven by large datasets and advanced algorithms, plays a pivotal role in addressing these challenges and advancing robotics. …”
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From Culture-Negative to DNA-Positive: The Molecular Revolution in Infective Endocarditis Diagnosis by Myeongji Kim, Madiha Fida, Omar M. Abu Saleh, Nischal Ranganath

“…A multimodal approach integrating molecular diagnostics with conventional methods is essential to optimize patient management. Further research is needed to refine diagnostic algorithms and improve cost-effectiveness in clinical practice.…”
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Recent Advances in Multi-Agent Reinforcement Learning for Intelligent Automation and Control of Water Environment Systems by Lei Jia, Yan Pei

“…Multi-agent reinforcement learning (MARL) has demonstrated significant application potential in addressing cooperative control, policy optimization, and task allocation problems in complex systems. …”
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The Alliance of BIM and Artificial Intelligence: Challenges for a Reinvented Future – The State of the Art by Ellyssa Abdelmoula, Meriem Zammel, Najla Allani

“…A literature review was conducted to examine research published on the integration of BIM and AI, identifying key challenges, gaps and proposed solutions to improve interoperability, data security and workflow optimization. …”
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