Clustering and Interpretability of Residential Electricity Demand Profiles by Sarra Kallel, Manar Amayri, Nizar Bouguila

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Features of Recruitment: Intelligent Text Analysis of Resume and Vacancies by Irina L. Sizova

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A Comparison of the Artificial Neural Network with Classical Methods in Corporate Credit Scoring by Şahap Kavcıoğlu

“…The subject of this research is to evaluate the performance of machine learning and logistic regression models on credit scoring by comparison. …”
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An Improved Strategy for Torque Ripple Reduction of Dual Three-Phase Brushless DC Motor Fed by Two Diode-Clamped, Three-Level Inverters Using Model Predictive Control by Zahra Emami, Abolfazl Halvaei Niasar

“…This paper proposes a new finite control set model predictive control (FCS-MPC) approach with reduction of computational for diode-clamped three-level (DC3L) inverter fed to dual three-phase BLDCM (DTP-BLDCM) by selecting optimal vectors to solve the above problems. …”
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Research on the Design of an On-Line Lubrication System for Wire Ropes by Fan Zhou, Yuemin Wang, Ruqing Gong

“…Kinematic modeling and grease consumption analysis guided greasing parameters optimization, validated through simulations and practical tests. …”
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Rolling window for detecting multiple Chan signatures to diagnose excessive water production by Ahmed MohamedSalih Musa Hamdoon, A. P. Mohammed Abdalla Ayoub Mohammed, A. P. Khaled Abdalla Elraies

“…Chan identified various distinct water problem patterns exhibited by wells during their production lifecycle based on slope features: Constant water-oil ratio (WOR), Normal Displacement, Coning, Channeling, depletion, and Multilayer Channeling. While machine learning models were developed to automate Chan plot interpretation and reduce human bias, they often failed to capture the evolution of water production over time, typically detecting only a single pattern or capturing patterns after it fully materialized, reducing the chance of early diagnosing. …”
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Assessment of the Applicability and Steps of Implementing the Six Sigma Method in the Quality Management System of Additive Manufacturing by Ivan S. Kushnir, Anna P. Adylina, Tatyana A. Levina

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Enhancing DeepLabv3+ Convolutional Neural Network Model for Precise Apple Orchard Identification Using GF-6 Remote Sensing Images and PIE-Engine Cloud Platform by Guining Gao, Zhihan Chen, Yicheng Wei, Xicun Zhu, Xinyang Yu

“…This study enhanced the DeepLabv3+ model to achieve superior performance in apple orchard identification by incorporating ResNet, optimizing the algorithm, and adjusting hyperparameter configuration using the PIE-Engine cloud platform. …”
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IoT-Edge Hybrid Architecture with Cross-Modal Transformer and Federated Manifold Learning for Safety-Critical Gesture Control in Adaptive Mobility Platforms by Xinmin Jin, Jian Teng, Jiaji Chen

“…This research presents an IoT-empowered adaptive mobility framework that integrates high-dimensional gesture recognition with edge-cloud orchestration for safety-critical human–machine interaction. The system architecture establishes a three-tier IoT network: a perception layer with 60 GHz FMCW radar and TOF infrared arrays (12-node mesh topology, 15 cm baseline spacing) for real-time motion tracking; an edge intelligence layer deploying a time-aware neural network via NVIDIA Jetson Nano to achieve up to 99.1% recognition accuracy with latency as low as 48 ms under optimal conditions (typical performance: 97.8% ± 1.4% accuracy, 68.7 ms ± 15.3 ms latency); and a federated cloud layer enabling distributed model synchronization across 32 edge nodes via LoRaWAN-optimized protocols (κ = 0.912 consensus). …”
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Predicting Suitable Spatial Distribution Areas for Urban Trees Under Climate Change Scenarios Using Species Distribution Models: A Case Study of <i>Michelia chapensis</i> by Chenbin Shen, Xi Chen, Chao Zhou, Lingzi Xu, Mingyi Qian, Hongbo Zhao, Kun Li

“…Therefore, our study aims to optimize traditional SDMs by integrating multiple machine learning algorithms and to propose a framework for identifying suitable distribution ranges of urban trees under climate change. …”
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Hybrid Deep Learning Approach for Accurate Detection and Multiclass Classification of Broken Conductor Faults in Power Distribution Systems by Firas Saadoon Mohammed Al-Jumaili, Mustafa Onat

“…Moreover, we use an appropriate DenseNet pre-trained model to extract features and estimate the topology state with reliable data representation. …”
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Transient overvoltage suppression measures for new energy high penetration system at the sending end under bipolar blocking fault by Xinyue LI, Chunya YIN, Lin LI, Sijue WANG, Ying CHEN

“…The simulation results show that the proposed reactive power optimization allocation scheme and machine-cutting scheme can reduce the transient overvoltage of the target node by 0.12 p.u., and the accuracy can reach 95.56%. …”
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Power capacity enhancement of hydropower plant through the penetration of solar and wind energy by Ahmad Shah Irshad, Ahmad Shah Amin, Amir Mohammad Ilham, M.H. Elkholy, Said Elias, Tomonobu Senjyu

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Unlocking the potential of sugarcane bagasse: a comprehensive analysis for advanced energy conversion by Nestor Proenza Pérez, Javier Alejandro Rodríguez Travieso, Elbis D´Espaux Shelton, Daniel Travieso Pedroso, Einara Blanco Machin, Celso Eduardo Tuna, José Luz Silveira

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Design Features of the Seeder for Direct Sowing of Grain Crops by M. A. Eruslanova, K. V. Nemtinov, K. A. Eruslanov, V. A. Nemtinov

“…The proposed design aims to reduce metal consumption; enhance manufacturability; and ensure optimal conditions for crop growth. (Materials and methods) The design of the electronic model (digital twin) of the seeder and its physical prototype were developed using system analysis methods; mathematical modeling; and experimental planning. …”
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Multi-Feature Fusion-Based Speech Disorder Classification Using MobileNetV3-EfficientNetB7, Linformer-Performer, and SHAP-Aware XGBoost by Abdul Rahaman Wahab Sait, Suresh Sankaranarayanan, P. Gouthaman

“…Direct voice classification lacks effective approaches to capture temporal dependencies. Machine learning (ML) models face challenges in extracting the complex temporal and spectral variations in speech signals. …”
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Real-time prediction of the rate of penetration via computational intelligence: a comparative study on complex lithology in Southwest Iran by Mohammad Najafi, Yousef Shiri

“…Sensitivity analysis was used to find the best machine learning (ML) structures. The ROP estimation on evaluation data from three unseen wells demonstrated superior performance of the hybrid model and ANN compared with the SVR, RF, and Physical Model. …”
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Self-DSNet: A Novel Self-ONNs Based Deep Learning Framework for Multimodal Driving Distraction Detection by Mamun Or Rashid, Md. Mosarrof Hossen, Mohammad Nashbat, Mazhar Hasan-Zia, Ali K. Ansaruddin Kunju, Amith Khandakar, Azad Ashraf, Molla Ehsanul Majid, Saad Bin Abul Kashem, Muhammad E. H. Chowdhury

“…Current strategies for distraction detection widely rely on machine learning models, but the non-linear relationships among various data modalities complicate the identification of optimal combinations. …”
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Landslide Hazard Warning in Guangdong-Hong Kong-Macao Greater Bay Area Based on Historical Ranking Rainfall Threshold by JIN Yi, YU Haixia

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Vehicle detection and recognition approach in smart surveillance system: A comparative analysis by Stephanie Ness

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