Feather teaching and training based on Kinect sensor and gesture recognition technology by Luoluo Zhang, Pin Zhong

“…The auxiliary training system scientifically and standardly completes action training from three parts: badminton learning, action collection, and action evaluation. …”
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The implementation of the situational control concept of information security in automated training systems by A. M. Chernih, S. V. Fedoseev

“…Developed method of situational control of information security in automated learning systems, involves the participation of the operator in the development and decision-making (dialogue procedures statement of objectives situational control, the formation of the base of alternative sets of control actions, etc.).Another important feature of this technique is the necessity of using previously developed models (models of decision-making situation, a model of coordination and planning of operation of a subsystem of the control and protection of information, models of information processing about the status of the subsystem analysis models and evaluation of results) and the database obtained on the basis of operating experience of information protection systems in the automated learning systems.The implementation of the concept of situational control of information security ensures the timely adaptation of the algorithms and parameters of the information security system to changes in the external environment and the nature of tasks within the education systems and on this basis allows to improve the characteristics of the information protection system in the automated learning systems.…”
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Machine learning algorithm for the rapid and accurate detection of Plasmodium falciparum by Mr Andrew Hill

“…Consensus between 8 independent models suggests at least 150 training cells (more than 50% of all “confident but wrong” cells) are mislabelled, and training without these cells improves model convergence and reliability. …”
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A Genome Scaffold Algorithm for Extending Repetitive and Nonrepetitive Contigs by Shuaibin Lian, Gang Zheng, Ke Gong, Xiaoli Zhang, Jiantao Guo

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Spatiotemporal data modeling and prediction algorithms in intelligent management systems by Xin Cao, Chunxiao Mei, Zhiyong Song, Hao Li, Jingtao Chang, Zhihao Feng

“…In order to solve the problem of difficulty in learning semantic pattern representations between user dynamic interest sequences using path based and knowledge graph based entity embedding methods, the author proposes research on spatiotemporal data modeling and prediction algorithms in intelligent management systems. The author first makes a preliminary analysis of the wireless network data (mainly the data of cellular mobile networks) obtained by Internet service providers, reveals that the data of adjacent base stations have temporal and spatial correlations, then establishes a hybrid deep learning model for spatio-temporal prediction, and proposes a new spatial model training algorithm. …”
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Deep learning algorithms for detecting fractured instruments in root canals by Ekin Deniz Çatmabacak, İrem Çetinkaya

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Overhaul Scheduling Approach for Metro Vehicles Based on Genetic Algorithms by WANG Bingjing, LI Bingxin

“…In this scheduling approach, an evaluation function is applied to transform the train overhaul scheduling into the tasks to optimize the resource allocation for the overhaul process, and the resource allocation to the overhaul process is optimized leveraging the inherent parallelism and global optimization ability of the genetic algorithm, and the optimal chromosome is deemed as the final result of the overhaul scheduling. …”
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Évaluation comparative des algorithmes d'apprentissage automatique pour la classification des types de sols à partir de caractéristiques physico-chimiques : application de Random F... by Mamadou Ndiaye, René Boissy, Mbagnick Faye, N’kpomé Styvince Romaric Kouao

“…Using physico-chemical characteristics such as texture (percentages of sand, silt, and clay), pH, organic matter, cation exchange capacity (CEC), bulk density, and water retention, this study evaluates the performance of four algorithms: Random Forest, XGBoost, SVM, and KNN. …”
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Optimization of Intelligent English Pronunciation Training System Based on Android Platform by Qianyu Cao, Hanmei Hao

“…In the feedback mechanism of intelligent speech training, a double benchmark scoring mechanism is introduced to comprehensively evaluate the speech of the speech trainer and correct the speaker’s speech in time. …”
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Stop Plan of Express and Local Train for Regional Rail Transit Line by Qin Luo, Yufei Hou, Wei Li, Xiongfei Zhang

“…Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. …”
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Forensic Genetics: A Machine Learning Algorithm for Mutation Modelling by Sofia Antão Sousa, Leonor Gusmão, Marisa Faustino, António Amorim, Nádia Pinto

“…These results support that machine learning algorithms may be used to improve mutation modelling, statistical significance depending on the available data to be used as training and test sets. …”
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TDQE：a quality evaluation method for text data in deep learning by LUO Chunxu, XIONG Haixu, YE Yazhen, DING Yan, ZONG Shize, XIONG Yun, ZHU Yangyong

“…Text data quality is an important factor affecting the performance of language models. and its evaluation methodology is considered decisive for model training effectiveness. …”
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Training Large Models on Heterogeneous and Geo-Distributed Resource with Constricted Networks by Zan Zong, Minkun Guo, Mingshu Zhai, Yinan Tang, Jianjiang Li, Jidong Zhai

“…As the computational demands driven by large model technologies continue to grow rapidly, leveraging GPU hardware to expedite parallel training processes has emerged as a commonly-used strategy. …”
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Digital Staining Algorithm for Multi-Domain Transformation of Unstained Images by Dong-Bum Kim, Jong-Ha Lee

“…The proposed model was trained by incorporating a mask and latent loss within the framework of the StarGAN algorithm. …”
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A Partition-Based Hybrid Algorithm for Effective Imbalanced Classification by Kittipong Theephoowiang, Anantaporn Hanskunatai

“…To further evaluate its performance, the study compares the proposed algorithm with previous methods using G-Mean. …”
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Examining the Efficiency of Learning-Based Algorithms in the Process of Declaring Customs by Mustafa Günerkan, Ender Şahinaslan, Önder Şahınaslan

“…This study evaluates the efficiency performances of learning-based algorithms regarding the customs declaration process over 4,005,343 pieces of declaration data. …”
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Prediction of mung bean production using machine learning algorithms by Azanu Mirolgn Mequanenit, Aleka Melese Ayalew, Ayodeji Olalekan Salau, Eyerusalem Alebachew Nibret, Million Meshesha

“…Experimental result shows that the Xgboosting classifiers algorithm achieves the best performance with 98.65 % test accuracy and 99.8 % train accuracy. …”
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Optimized Detection Algorithm for Vertical Irregularities in Vertical Curve Segments by Rong Xie, Chunjun Chen

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Robust UAV Target Tracking Algorithm Based on Saliency Detection by Hanqing Wu, Weihua Wang, Gao Chen, Xin Li

“…Firstly, this article analyzes the features from both spatial and temporal dimensions, evaluates the representational and discriminative abilities of different features, and achieves adaptive feature fusion. …”
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Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms by Milad Mohebbi, Behnam Sobhani

“…These algorithms were evaluated for their effectiveness in adapting to seasonal variations in electricity consumption data. …”
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