HOW IS ARTIFICIAL INTELLIGENCE CHANGING HR? ADAPTIVE MANAGEMENT FOR THE NEW ENVIRONMENT by Dmytro Antoniuk, Bjoern Sven Ivens, Olexandr Kolyada

“…Special attention is paid to ethical issues such as algorithmic bias and transparency, as well as organisational barriers that may prevent the implementation of AI. …”
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Refining Software Clustering: The Impact of Code Co-Changes on Architectural Reconstruction by Adelina Diana Stana, Ioana Sora

“…We conduct experiments on four open-source Java projects using three clustering algorithms (Louvain, Leiden, and DBSCAN) and two evaluation metrics (Modularization Quality and MoJoFM). …”
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MASTERING THE TOOLS OF CITATION DATABASES IN HIGHER MEDICAL EDUCATION by H. Morokhovets, Yu. Lysanets, L. Ostrovska, T. Purdenko

“…The h-indices are calculated in terms of publications in these bases, and serve as qualitative indicators for scientific activity evaluation. Scopus and Web of Science, in addition to their own built-in tools for searching, visualizing, analyzing and tracking data, integrated with the registers of scientists, bibliographic managers, plugins that allow to automate the processes of citation, lists of literature, preparation of publications according to the requirements of a specific edition, work with full-text versions of articles in different formats.…”
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Utilization of Deep Learning YOLO V9 for Identification and Classification of Toraja Buffalo Breeds by Abdul Rachman Manga', Herawati Herawati, Purnawansyah Purnawansyah

“…This study aims to develop and evaluate a buffalo breed detection system that supports the cultural practices of the Toraja community, particularly in the context of the Rambu Solo’ ceremony. …”
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Efficient IDS for IoT Networks Using Host-Based Data Aggregation and Multi-Entropy Analysis by Yusei Katsura, Arata Endo, Ismail Arai, Kazutoshi Fujikawa

“…This enables the reduction of computational resources during detection processing while maintaining detection accuracy, even when using fewer features and lightweight machine learning algorithms. The evaluation results demonstrate that the proposed method achieves a maximum reduction of 99.7% (2916 milliseconds) in processing time and 86.4% (633 MiB) in memory usage while maintaining an intrusion detection accuracy of 99.97%, proving its feasibility in constrained environments comparable to IoT gateways.…”
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Predicting temporomandibular disorders in adults using interpretable machine learning methods: a model development and validation study by Yuchen Cui, Fujia Kang, Xinpeng Li, Xinning Shi, Han Zhang, Xianchun Zhu

“…The purpose of this study was to apply a machine learning (ML) approach to identify risk factors for the occurrence of TMD in adults and to develop and validate an interpretable predictive model for the risk of TMD in adults.MethodsA total of 949 adults who underwent oral examinations were enrolled in our study. 5 different ML algorithms were used for model development and comparison, and feature selection was performed by feature importance ranking and feature decreasing methods. …”
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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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Assessing the spatial relationship between mandibular third molars and the inferior alveolar canal using a deep learning-based approach: a proof-of-concept study by Wenjie Lyu, Shang Lou, Jieying Huang, Zelun Huang, Haoran Zheng, Huangan Liao, Yu Qiao, Kexiong OuYang

“…Statistical analysis was performed using one-way ANOVA with Tukey HSD post-hoc tests (p < 0.05), employing multiple error metrics for comprehensive evaluation. Results One-way ANOVA revealed significant differences among measurement methods. …”
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Identification of Disulfidptosis-Related Genes and Molecular Subgroups in Rheumatoid Arthritis for Diagnostic Model and Patient Stratification by Liu X, Wang S, Du X, Wang Y, Mo L, Li H, Qu Z, Wang X, Sun J, Li Y, Wang J

“…The machine learning algorithms were used to identify the hub genes. Second, a diagnostic model was constructed for RA based on the hub genes. …”
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Prediction on rock strength by mineral composition from machine learning of ECS logs by Dongwen Li, Xinlong Li, Li Liu, Wenhao He, Yongxin Li, Shuowen Li, Huaizhong Shi, Gaojian Fan

“…Although the Transformer model was less computationally efficient, it exhibited strengths in predicting subsurface strength parameters, particularly in capturing spatial variations and forecasting these parameters across different spatial locations. This study introduces a novel AI-driven approach to rock strength evaluation, bridging the gap between mineral composition and mechanical properties, with significant implications for resource extraction and reservoir management.…”
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A method based on clustering fast search for bearing performance degradation assessment by ShengWen Zhou, Li Zhang, Xiaoming Yang, Fan Xu, BaiGang Du, RuiPing Luo, Wenhui Zeng

“…Abstract To address the problem of relying on manual experience to determine the number of cluster centers, this paper introduces an approach for evaluating the performance degradation of rolling bearings using the clustering by fast search (CFS) algorithm. …”
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High-Accuracy Intermittent Strabismus Screening via Wearable Eye-Tracking and AI-Enhanced Ocular Feature Analysis by Zihe Zhao, Hongbei Meng, Shangru Li, Shengbo Wang, Jiaqi Wang, Shuo Gao

“…These features can be normalized, and reflect individual differences. After these features are processed by the random forest (RF) algorithm, this method experimentally yields 97.1% accuracy in strabismus detection in 70 people under diverse indoor testing conditions, validating the high accuracy and robustness of the method, and implying that the method has strong potential to support widespread and highly accurate strabismus screening.…”
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Mapping Landslide Sensitivity Based on Machine Learning: A Case Study in Ankang City, Shaanxi Province, China by Baoxin Zhao, Jingzhong Zhu, Youbiao Hu, Qimeng Liu, Yu Liu

“…The main purpose of this research is to apply the logistic regression (LR) model, the support vector machine (SVM) model based on radial basis function, the random forest (RF) model, and the coupled model of the whale optimization algorithm (WOA) and genetic algorithm (GA) with RF, to make landslide susceptibility mapping for the Ankang City of Shaanxi Province, China. …”
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Deep Learning-Based Cloud Detection for Optical Remote Sensing Images: A Survey by Zhengxin Wang, Longlong Zhao, Jintao Meng, Yu Han, Xiaoli Li, Ruixia Jiang, Jinsong Chen, Hongzhong Li

“…This review provides a comprehensive overview of cloud detection algorithms based on deep learning from the perspective of semantic segmentation, and elaborates on the research progress, advantages, and limitations of different categories in this field. …”
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Adaptation of the competence approach to the methodology of training it specialists in the field of programming by E. V. Savina, K. Ya. Radjabov, T. I. Isabekova

“…The research methods include: analysis of evaluation materials; methods based on algorithms for decomposing the program code proposed for solving the problem; methods for analyzing data from open sources, methods for analyzing algorithms and data structures. …”
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PRCFX-DT: a new graph-based approach for feature selection and classification of genomic sequences by Amin Khodaei, Sania Eskandari, Hadi Sharifi, Behzad Mozaffari-Tazehkand

“…The analysis of viral genomic sequences can be efficacious in evaluating the present and potentially forthcoming condition of viruses. …”
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A new iterative multi-step method for solving nonlinear equation by Muhammad Usman, Javed Iqbal, Alamgir Khan, Ikram Ullah, Hasib Khan, Jehad Alzabut, Hisham Mohammad Alkhawar

“…The findings reveal that the proposed technique surpasses several renowned iterative methods in both accuracy and computational efficiency. • High-order convergence: The method demonstrates a sixteenth-order convergence rate, requiring just five function evaluations per iteration, which enhances computational efficiency. • Derivative-free approach: The algorithm employs finite difference approximations, eliminating the need for second derivative calculations and increasing its applicability to complex problems. • Numerical validation: Comprehensive numerical tests and comparative studies validate the exceptional accuracy and efficiency of the proposed iterative approach.…”
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Advanced quantification pipeline reveals new spatial and temporal tumor characteristics in preclinical multiple myeloma by Zhixin Sun, Jacqueline M. Godbe, Alexander Zheleznyak, Brad Manion, Junhao Hu, Julie L. Prior, Kathleen Duncan, Ulugbek S. Kamilov, Monica Shokeen

“…Conclusions This pipeline enables reproducible, anatomically precise quantification of region-specific trends in MM progression, including joint-specific lesion tropism and sex-based differences, from longitudinal PET/CT scans. By mitigating common challenges such as excretion artifacts and inconsistent mouse positioning, our approach overcomes limitations of manual analysis and enhances evaluation of tumor biology and treatment response in preclinical models of bone-involved cancers. …”
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A Cone-Beam Computed Tomography-Based Assessment of Safe Zones for Orthodontic Mini-Implant Placement in the Lateral Maxilla: A Retrospective Morphometric Study by Iva Jakovljevic, Pavle Milanovic, Milica Vasiljevic, Jovana Milanovic, Momir Z. Stevanovic, Nemanja Jovicic, Milos Stepovic, Vladimir Ristic, Dragica Selakovic, Gvozden Rosic, Aleksandra Arnaut

“…CBCT scans (sagittal and axial cross-sections) were used to evaluate interdental bone characteristics in different regions. …”
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Factors influencing the response to periodontal therapy in patients with diabetes: post hoc analysis of a randomized clinical trial using machine learning by Nidia CASTRO DOS SANTOS, Arthur MANGUSSI, Tiago RIBEIRO, Rafael Nascimento de Brito SILVA, Mauro Pedrine SANTAMARIA, Magda FERES, Thomas VAN DYKE, Ana Carolina LORENA

“…A leave-one-out cross-validation strategy was used for model training and evaluation. We tested seven different algorithms: K-Nearest Neighbors, Decision Tree, Support Vector Machine, Random Forest, Extreme Gradient Boosting, and Logistic Regression. …”
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