An Integrated Approach to the Determination of Wages of Bank Employees by Alexander S. Artamonov

“…The integrated approach that was used to calculate the wages of employees of the bank employees taking into account the proposed comparison algorithm with market data on wages submitted by the consulting companies, may potentially contribute to improving the competitiveness of HR-brand of the organization and optimize the size of the wage fund.…”
Get full text

Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

“…To reduce data complexity and improve model efficiency, the input by selecting specific frequency points based on SHAP values is further optimized. …”
Get full text

A Review of Embodied Grasping by Jianghao Sun, Pengjun Mao, Lingju Kong, Jun Wang

“…In reinforcement learning, the pre-trained model is used to obtain the optimal reward function, which improves the learning efficiency and ability of reinforcement learning; (3) embodied agent: The pre-trained model adopts hierarchical or holistic execution to achieve end-to-end robot control. …”
Get full text

An Analysis of the Design and Kinematic Characteristics of an Octopedic Land–Air Bionic Robot by Jianwei Zhao, Jiaping Gao, Mingsong Bao, Hao Zhai, Xu Pei, Zheng Jiang

Get full text

Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Through comprehensive evaluation using both synthetic and real-world traces from deep learning training workloads, our method demonstrates substantial improvements over state-of-the-art algorithms: achieving up to 45.1% reduction in average I/O latency, 32.5% improvement in throughput for critical applications, and 28.8% reduction in storage costs. …”
Get full text

Fault reconfiguration control strategy of islanded marine ranching power supply system based on deep reinforcement learning by Yichun Wang, Bo Zhang, Rongjie Wang, Jiang Desong, Yabo Cui, Zhouyang Sun, Hao Liu

“…To enhance convergence efficiency and generalization capability of the algorithm, noise networks are used to improve exploration ability of dueling DQN algorithm by implementing linear layers with learnable noise using an adaptive noise model. …”
Get full text

Path Planning and Motion Control of Robot Dog Through Rough Terrain Based on Vision Navigation by Tianxiang Chen, Yipeng Huangfu, Sutthiphong Srigrarom, Boo Cheong Khoo

“…A significant innovation is the customization of the EGO-Planner to optimize trajectory planning in dynamically changing terrains, coupled with the implementation of a multi-body dynamics model that significantly improves the robot’s stability and maneuverability across various surfaces. …”
Get full text

Digital Reconstruction Method for Low-Illumination Road Traffic Accident Scenes Using UAV and Auxiliary Equipment by Xinyi Zhang, Zhiwei Guan, Xiaofeng Liu, Zejiang Zhang

“…Subsequently, the collected point cloud data are processed with a multiscale voxel iteration method for down-sampling to determine optimal parameters. Then, the improved normal distributions transform (NDT) algorithm and different filtering algorithms are adopted to register the ground and air point clouds, and the optimal combination of algorithms is selected, thus, to reconstruct a high-precision 3D point cloud model of the accident scene. …”
Get full text

BIM and AI Integration for Dynamic Schedule Management: A Practical Framework and Case Study by Heap-Yih Chong, Xinyi Yang, Cheng Siew Goh, Yan Luo

“…This study addresses this challenge by proposing a dynamic optimization framework that integrates Building Information Modeling (BIM) and Artificial Intelligence (AI) to enhance schedule management. …”
Get full text

Leveraging LLMs for optimised feature selection and embedding in structured data: A case study on graduate employment classification by Radiah Haque, Hui-Ngo Goh, Choo-Yee Ting, Albert Quek, M.D. Rakibul Hasan

“…The primary objective is to determine whether converting structured data into text format improves model accuracy. The study involves several ML models including Artificial Neural Networks (ANN), CatBoost, and BERT classifier. …”
Get full text

Machine learning applications in placenta accreta spectrum disorders by Mahsa Danaei, Maryam Yeganegi, Sepideh Azizi, Fatemeh Jayervand, Seyedeh Elham Shams, Mohammad Hossein Sharifi, Reza Bahrami, Ali Masoudi, Amirhossein Shahbazi, Amirmasoud Shiri, Heewa Rashnavadi, Kazem Aghili, Hossein Neamatzadeh

“…Emphasizing the need for standardized methodologies to ensure consistent feature extraction and model performance, this review advocates for the integration of radiomics and ML into clinical workflows, aiming to improve patient outcomes and foster a multidisciplinary approach in high-risk pregnancies. …”
Get full text

CMDMamba: dual-layer Mamba architecture with dual convolutional feed-forward networks for efficient financial time series forecasting by Zhenkai Qin, Zhenkai Qin, Zhenkai Qin, Baozhong Wei, Baozhong Wei, Yujia Zhai, Ziqian Lin, Xiaochuan Yu, Xiaochuan Yu, Jingxuan Jiang

“…By doing so, it provides more accurate time series modeling, optimizes algorithmic trading strategies, and facilitates investment portfolio risk warnings.ResultsExperiments conducted on four real-world financial datasets demonstrate that CMDMamba achieves a 10.4% improvement in prediction accuracy for multivariate forecasting tasks compared to state-of-the-art models.DiscussionMoreover, CMDMamba excels in both predictive accuracy and computational efficiency, setting a new benchmark in the field of financial time series forecasting.…”
Get full text

A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

“…Hence, this study proposes a Metaheuristic-Hybrid Metaheuritstic eXplainable Artificial Intelligence (MHMXAI) driven Feature Selection (FS) approach and Deep Learning (DL) models for CKD stage prediction. MHMXAI approach selects the features with the highest scores from the Metaheuristic algorithm-Eagle Search Strategy, Hybrid Metaheuristic algorithm-Great Salmon Run-Thermal Exchange Optimization and eXplainable AI (XAI) tools like Local Interpretable Model-agnostic Explanations (LIME) and Shapley Additive exPlanations (SHAP) for their effectiveness. …”
Get full text

Domain Knowledge-Enhanced Process Mining for Anomaly Detection in Commercial Bank Business Processes by Yanying Li, Zaiwen Ni, Binqing Xiao

“…Additionally, we employed large language models (LLMs) for root cause analysis and process optimization recommendations. …”
Get full text

Application of machine learning for predicting the incubation period of water droplet erosion in metals by Khaled AlHammad, Mamoun Medraj, Moussa Tembely

“…Feature importance analysis through SHAP values revealed that impact velocity and surface hardness were the most influential factors affecting incubation period, providing valuable physical insights into the erosion mechanism. Hyperparameter optimization techniques showed minimal improvement in model performance, suggesting that the transformations effectively captured the underlying relationships in the data. …”
Get full text

Prediction of Diabetes in Middle-Aged Adults: A Machine Learning Approach by Gideon Addo, Bismark Amponsah Yeboah, Michael Obuobi, Raphael Doh-Nani, Seidu Mohammed, David Kojo Amakye

“…Chi-square tests assessed diabetes-symptom associations, and the Boruta algorithm examined feature influence. Seven ML classification models were evaluated for predictive accuracy. …”
Get full text

Comparative effect of traditional and collaborative watershed management approaches on flood components by Ali Nasiri Khiavi, Mehdi Vafakhah, Seyed Hamidreza Sadeghi, Changhyun Jun, Sayed M. Bateni

Get full text

Application of Energy Dispersive X-ray Fluorescence Spectroscopy in Analysis of Heavy Metals in Soil: A Review by Aosong JIANG, Longhua WU, Zhu LI

“…Therefore, the current mainstream focus is on combining the advantages of different algorithms for the preprocessing analysis of ED-XRF spectroscopy and the establishment of quantitative analysis models to improve the accuracy of ED-XRF detection. …”
Get full text

SLAM: Sales Lead AMplification Through GenAI and ML for e-Learning Platforms by Ganesan Ramachandran, Tanmay Narang, Vallidevi Krishnamurthy

“…This study investigates sales lead prediction utilizing machine learning techniques, with a particular focus on the ensemble method of stacking algorithms. The research objective is to improve the predictive accuracy of sales lead identification through the utilization of advanced machine learning methodologies. …”
Get full text

Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques by Stephanie Ness, Vishwanath Eswarakrishnan, Harish Sridharan, Varun Shinde, Naga Venkata Prasad Janapareddy, Vineet Dhanawat

“…By comparing different algorithms, this research contributes to advancing the application of machine learning in network security, offering guidance on model selection and optimization for improved detection of cyber threats.…”
Get full text