Bulk Low-Inertia Power Systems Adaptive Fault Type Classification Method Based on Machine Learning and Phasor Measurement Units Data by Mihail Senyuk, Svetlana Beryozkina, Inga Zicmane, Murodbek Safaraliev, Viktor Klassen, Firuz Kamalov

“…This research focuses on developing and testing a method for classifying disturbances in power systems using machine learning algorithms and phasor measurement unit (PMU) data. To enhance the speed and accuracy of disturbance classification, we employ a range of ensemble machine learning techniques, including Random forest, AdaBoost, Extreme gradient boosting (XGBoost), and LightGBM. …”
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Application of deconvolutional networks for feature interpretability in epilepsy detection by Sihao Shao, Yu Zhou, Ruiheng Wu, Aiping Yang, Qiang Li

“…Even automated detection algorithms are already available to assist clinicians in reviewing EEG data, many algorithms used for seizure detection in epilepsy fail to account for the contributions of different channels. …”
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HisCoM-mimi: software for hierarchical structural component analysis for miRNA-mRNA integration model for binary phenotypes by Yongkang Kim, Taesung Park

“…Another improvement of the new HisCoM-mimi approach is the inclusion of updated algorithms to provide the lasso and elastic-net penalties for users who want to fit a model with a smaller number of selected miRNAs and mRNAs. …”
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Multitask Convolutional Neural Network for Rolling Element Bearing Fault Identification by Mingxing Jia, Yuemei Xu, Maoyi Hong, Xiyu Hu

“…The traditional signal processing-based rolling bearing fault diagnosis algorithms rely on artificial feature extraction and expert knowledge. …”
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Noncontact Multiperson Respiratory Detection Method Based on Blind Source Separation by Xuan YANG, Ziying WANG, Li ZHANG, Heng ZHAO, Hong HONG

“…In recent years, there has been an increasing interest in respiratory monitoring in multiperson environments and simultaneous monitoring of the health status of multiple people. Among the algorithms developed for multiperson respiratory detection, blind source separation algorithms have attracted the attention of researchers because they do not require prior information and are less dependent on hardware performance. …”
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FPGA Implementation of Real-Time Compressive Sensing with Partial Fourier Dictionary by Yinghui Quan, Yachao Li, Xiaoxiao Gao, Mengdao Xing

“…However, reconstruction algorithms are computing demanding and software implementation of these algorithms is extremely slow and power consuming. …”
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Design and optimization of distributed energy management system based on edge computing and machine learning by Nan Feng, Conglin Ran

“…Future research can further explore how to integrate multiple machine learning algorithms to optimize energy scheduling strategies and improve the system’s adaptability in complex environments.…”
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Optimization of Vehicle Paths considering Carbon Emissions in a Time-Varying Road Network by Chong Ye, Fang Liu, YuKun Ou, Zeyu Xu

“…The experimental results show that compared with the two classical algorithms, the simulated annealing-genetic hybrid algorithm (GA-SA) has better solution performance, inherits the robustness and potential parallelism of the genetic algorithm, and has a higher practical value. …”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…The study highlights the potential of ML algorithms in early diabetes detection, enabling timely intervention and personalized management strategies. …”
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A Review of Numerical Techniques for Frictional Contact Analysis by Govind Vashishtha, Sumika Chauhan, Riya Singh, Manpreet Singh, Ghanshyam G. Tejani

“…This review paper delves into the future research that prioritizes developing computationally efficient algorithms and parallel computing strategies. Advancements in constitutive modelling are vital for improved accuracy, along with enhanced contact detection algorithms for complex geometries and large deformations. …”
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Influence of the distortion type on the image quality assessment when reducing its sizes by D. G. Asatryan, M. E. Harutyunyan, Y. I. Golub, V. V. Starovoitov

“…The well-known TID2013 image database was used as the material, which includes 3000 images distorted by 24 types of distorting algorithms with five levels. Each image of the base was reduced by 2, 4 and 8 times by the two most common methods and compared with the original image-original. …”
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Detection of COVID-19 Using Protein Sequence Data via Machine Learning Classification Approach by Siti Aminah, Gianinna Ardaneswari, Mufarrido Husnah, Ghani Deori, Handi Bagus Prasetyo

“…To optimize performance, we employed machine learning classification algorithms such as K-nearest neighbor (KNN), XGBoost, and Naïve Bayes, along with feature selection techniques like genetic algorithm (GA), LASSO, and support vector machine recursive feature elimination (SVM-RFE). …”
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Object Detection Post Processing Accelerator Based on Co-Design of Hardware and Software by Dengtian Yang, Lan Chen, Xiaoran Hao, Yiheng Zhang

“…Given the similarities between the training and inference post processes, we unify four typical post processing algorithms and design a hardware accelerator based on this framework. …”
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Nonintrusive Load Disaggregation Based on Attention Neural Networks by Shunfu Lin, Jiayu Yang, Yi Li, Yunwei Shen, Fangxing Li, Xiaoyan Bian, Dongdong Li

“…The proposed model achieves lower errors for all appliances compared to other algorithms. Specifically, the proposed model shows a 13.85% improvement in mean absolute error (MAE), a 21.27% improvement in signal aggregate error (SAE), and a 26.15% improvement in F1 score over existing algorithms. …”
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Matching Subsequence Music Retrieval in a Software Integration Environment by Zhencong Li, Qin Yao, Wanzhi Ma

“…This paper firstly introduces the basic knowledge of music, proposes the detailed design of a music retrieval system based on the knowledge of music, and analyzes the feature extraction algorithm and matching algorithm by using the features of music. …”
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Grid-Connected Solar PV System with Maximum Power Point Tracking and Battery Energy Storage Integrated with Sophisticated Three-Level NPC Inverter by D. Ravi Kishore, T. Vijay Muni, B. Srinivas Raja, Mukesh Pushkarna, B. Srikanth Goud, Kareem M. AboRas, Sadam Alphonse

“…The use of sufficiently sophisticated algorithms makes this a reality. Using simulation with MATLAB/Simulink, we were able to examine an NPC inverter’s performance in several setups. …”
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Optimization Approach for Yard Crane Scheduling Problem with Uncertain Parameters in Container Terminals by Wenqian Liu, Xiaoning Zhu, Li Wang, Baicheng Yan, Xuewei Zhang

“…The scheme does not require rescheduling when facing different situations. Subsequently, two algorithms based on certain rules are proposed to obtain the yard crane operation scheme in the deterministic environment, which are taken as the basic solution in the uncertain conditions, and then a tailored genetic algorithm is adopted to find the optimal solution with good adaptability to the uncertain scenarios. …”
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Determination of the effect of GA3 applications on plant development, nutrient content change and analysis of root architectural features using ML artificial neural network modelli... by Sari Ömer

“…Performance percentages of ML algorithms were listed as LR > MCC > MLP > J48 > PART > Baggin.…”
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Ferrography Wear Particles Image Recognition Based on Extreme Learning Machine by Qiong Li, Tingting Zhao, Lingchao Zhang, Wenhui Sun, Xi Zhao

“…With the rapid development of computer image processing technology, neural network based on traditional gradient training algorithm can be used to recognize them. However, the feedforward neural network based on traditional gradient training algorithms for image segmentation creates many issues, such as needing multiple iterations to converge and easy fall into local minimum, which restrict its development heavily. …”
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Prediction of case types from non-searchable pdf documents in arabic: Comparison of machine learning and deep learning with image processing by El Arrasse Mouad, Khourdifi Youness, Mounir Soufyane, El Alami Alae

“…To achieve this, we utilized image processing, text cleaning techniques, and machine learning algorithms.We carried out a comparative study using both machine learning and deep learning techniques. …”
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