Hybrid E-Recommendation System for Multi-Shop Environment by Hawraz Abdalla Abubakr, Kamaran Faraj

“…The system uses techniques such as hybrid/blended methods using singular value decomposition and K-nearest neighbors for collaborative filtering (CF) to recommend shops and products based on customer ratings, alongside term frequency-inverse document frequency vectorization and cosine similarity for content-based filtering. …”
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Near-Instantaneously Adaptive Learning-Assisted and Compressed Sensing-Aided Joint Multi-Dimensional Index Modulation by Xinyu Feng, Mohammed El-Hajjar, Chao Xu, Lajos Hanzo

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TAE Predict: An Ensemble Methodology for Multivariate Time Series Forecasting of Climate Variables in the Context of Climate Change by Juan Frausto Solís, Erick Estrada-Patiño, Mirna Ponce Flores, Juan Paulo Sánchez-Hernández, Guadalupe Castilla-Valdez, Javier González-Barbosa

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Thermal Model of Heavy Truck Swapping Station Battery Considering V2G by Xialing PENG, Song HAN, Xunchuan LIU, Guogang HE

“…[Method] To solve the above problems, a coupled bidirectional charging machine's battery thermal-electric coupling model was established to investigate the thermal characteristics of the electric heavy-duty truck's power battery, and the COMSOL-SIMULINK was used for joint simulation. …”
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Artificial intelligence in acoustic ecology: Soundscape classification in the Cerrado by Bruno Daleffi da Silva, Linilson Rodrigues Padovese

“…Considering the importance of the Cerrado in biodiversity and hydrology, along with the challenges faced by the biome due to agricultural expansion, the study seeks more efficient and cost-effective methods for identifying its phytophysiognomies. Five statistical models were developed and evaluated, utilizing both traditional Machine Learning and Deep Learning, with Mel Frequency Cepstral Coefficients (MFCCs) and spectrogram images as input variables. …”
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An Overview of Inertia Emulation Strategies for DC Microgrids: Stability Analysis and AC Microgrid Analogies by Mahdis Haddadi, Saman A. Gorji, Samson S. Yu

“…Inertia is a critical factor in maintaining the frequency stability of power systems. However, the growing integration of power electronics-based renewable energy sources (RESs) has significantly reduced system inertia. …”
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Artificial Intelligence Empowering Dynamic Spectrum Access in Advanced Wireless Communications: A Comprehensive Overview by Abiodun Gbenga-Ilori, Agbotiname Lucky Imoize, Kinzah Noor, Paul Oluwadara Adebolu-Ololade

“…Additionally, the paper discusses the role of machine learning (ML) in predicting spectrum requirements, which is crucial for efficient frequency management in the fifth generation (5G) networks and beyond. …”
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Ensemble Learning Approaches for Multi-Class Intrusion Detection Systems for the Internet of Vehicles (IoV): A Comprehensive Survey by Manal Alharthi, Faiza Medjek, Djamel Djenouri

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Fault Diagnosis of Switching Power Supplies Using Dynamic Wavelet Packet Transform and Optimized SVM by Jie Xu, Jingjing Zhu, Zhifeng Wang

“…To improve the accuracy and reliability of fault diagnosis, this paper proposes an intelligent diagnosis method based on Dynamic Wavelet Packet Transform (DWPT) and Improved Artificial Bee Colony Optimized Support Vector Machine (APABC-SVM). …”
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Electroencephalography Signal Analysis: Classification Techniques and Applications by Iosif-Beniamin GOGA

“…Several signal acquisition and preprocessing techniques were investigated, including artifact removal, feature extraction methods, such as wavelet transforms and common spatial patterns, combined with classification approaches like support vector machines (SVM), and signal enhancement methods. …”
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An Adaptive SVD-Based Approach to Clutter Suppression for Slow-Moving Targets by Yuhao Hou, Baixiao Chen

“…To address this limitation, this paper proposes an adaptive singular value decomposition (A-SVD) method utilizing support vector machines (SVM). The proposed approach leverages the augmented implicitly restarted Lanczos bidiagonalization (AIRLB) algorithm to decompose echo matrices into different subspaces, which are then characterized in relation to Doppler frequency, energy, and correlation. …”
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Mitigating Cyber Risks in Smart Cyber-Physical Power Systems Through Deep Learning and Hybrid Security Models by M. A. S. P. Dayarathne, M. S. M. Jayathilaka, R. M. V. A. Bandara, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara

“…To address these risks, the research proposes a hybrid approach that integrates conventional cybersecurity strategies with machine learning (ML) approaches to improve cyber-attack detection. …”
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Тhe operability analysis of spindle-motor hybrid electromechanical systems by Катерина Олійник

“…Such systems are used in metalworking complexes, lathes, milling, drilling, grinding, multi-purpose and other machines. In modern designs of spindle units rolling bearings, hydrostatic, hydrodynamic, gas-static (aerostatic), gas-dynamic (aerodynamic), magnetic bearings and their combinations (hybrids) are used, for example, gas-magnetic (gas-static bearings with a magnetic suspension that allows to provide rotational frequencies) up to 10-20 thousand rpm, and in drilling and milling and grinding up to 100-200 thousand rpm and above. …”
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EEG based real time classification of consecutive two eye blinks for brain computer interface applications by Masud Rabbani, Nafi Us Sabbir Sabith, Anubhav Parida, Iysa Iqbal, Sayed Mashroor Mamun, Rumi Ahmed Khan, Farhad Ahmed, Sheikh Iqbal Ahamed

“…The data were preprocessed and analyzed using four feature extraction techniques: basic statistical, time-domain, amplitude-driven, and frequency-domain methods. The most significant features were selected to develop three machine learning models: XGBoost, support vector machine (SVM), and neural network (NN). …”
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Feature extraction and fault diagnosis of gearbox based on ICEEMDAN, MPE, RF and SVM by DING Xiaofeng, ZHANG Yuhua

“…To solve the challenges related to non-stationary vibration signals in gearboxes, i.e. difficult feature extraction, high redundancy of feature vectors and low fault identification rate, this paper proposed a method of feature extraction and fault diagnosis of gearboxes based on the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), multi-scale permutation entropy (MPE), random forest (RF) feature importance ranking and support vector machine (SVM). …”
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Controllable vibration of mobility links of production mechanism by Nikolay F. Karnaukhov, Maxim N. Filimonov, Roman S. Mironenko

“…Materials and Methods. To solve the research problems, the concept of bimodal AVI control that provides the formation of quasi-sinusoidal voltage for AM power supply in the “AVI - AM” system with the harmonic coefficients Ku < 8% and Ku > 8% is used. …”
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Optimization of the prognosis of postoperative complications in patients with breast cancer by L. A. Trusova

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Fractional-Order LC Three-Phase Inverter Using Fractional-Order Virtual Synchronous Generator Control and Adaptive Rotational Inertia Optimization by Junhua Xu, Chunwei Wang, Yue Lan, Bin Liu, Yingheng Li, Yongzeng Xie

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Fault Feature Extraction Based on Variational Modal Decomposition and Lifting Wavelet Transform: Application in Gear of Mine Scraper Conveyor Gearbox by Zhengxiong Lu, Linyue Li, Chuanwei Zhang, Shuanfeng Zhao, Lingxiao Gong

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Simulated Centrifugal Fan Blade Fault Diagnosis Based on Modulational Depthwise Convolution–One-Dimensional Convolution Neural Network (MDC-1DCNN) Model by Zhaohui Ren, Yulin Liu, Tianzhuang Yu, Shihua Zhou, Yongchao Zhang, Zeyu Jiang

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