Analysis of The Use of Discussion And Question And Answer Methods As an Effort to Improve Student Physics Learning Outcomes by Delia Sapitri, Siti Indriyati

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A Review of Task Multi-criteria Prioritization Methods by PAN Zheping, ZOU Gui, ZHAO Jun, CHENG Weizheng

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The Method of Teaching Schoolchildren the Basics of Security on The Internet by M. V. Romanova, E. V. Chernova

“…The following methods were used in the work: analysis of pedagogical, psychological, scientific, technical and methodological literature on the research problem, systematization, generalization, experiment, questioning, testing, survey, diagnostic methods (methods of Internet addiction by S.Kulikov and Kimberly-Young in adapted by S. …”
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MODERN DIRECTION FOR IMPROVING THE QUALITY OF TRAINING STUDENTS OF DENTAL FACULTY by M.V. Storozheva, S.N. Grigorov, L.P. Rekova

Subjects: “…motivation, learning methods, educational situation.…”
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Visual Place Recognition Method Based on Attention Mechanism by DAI Tian-hong, YANG Xiao-yun, SONG Jie-qi

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Imbalanced data stream classification method with limited labels by LI Yanhong, LI Zhihua, ZHENG Jianxing, BAI Hexiang, GUO Xin

“…However, existing data stream classification methods based on extreme learning machine often struggle to simultaneously address common challenges in data stream, such as multi-class imbalance, concept drift, and the expensive labeling cost. …”
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An XNet-CNN Diabetic Retinal Image Classification Method by CHEN Yu, ZHOU Yujia, DING Hui

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Imbalanced data stream classification method with limited labels by LI Yanhong, LI Zhihua, ZHENG Jianxing, BAI Hexiang, GUO Xin

“…However, existing data stream classification methods based on extreme learning machine often struggle to simultaneously address common challenges in data stream, such as multi-class imbalance, concept drift, and the expensive labeling cost. …”
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Power Load Forecasting Method Based on MT-BSGP by LI Zhi-yong, SU Yin-sheng, LI Bin, LIU Chun-xiao, LI Bao, TAN Shou-biao

“…In order to better capture the relevance between different residential communities，a new multi-task learning ( MTL) method，namely low rank dirty model ( LＲDM) ，is proposed. …”
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Semi-supervised method for anomaly detection in HTTP traffic by Malki Ishara Wasundara, Junwei Zhou, Yanchao Yang, Dongdong Zhao, Jianwen Xiang

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Investigating the Effects of Spectroscopic Method in Estimating Soluble Solid Content Values and Firmness of Cherries from an Environmental Point of View: Prediction of Environmental Parameters with Machine Learning Method by Shirzad Naim, Shahgholi Gholamhossein, Ardabili Sina, Szymanek Mariusz

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Comparing between virtual reality based pre-clinical implantation training and traditional learning methods by Yangjie Li, Xu Chen, Yuan ding Huang, Qingqing He, Dize Li, Shanshan Hu, Peng Xu, Tao Chen, Xiongwen Ran

“…In this case, we anticipate the possible application of virtual reality (VR) technology to pre-clinical implantation training (PCIT) in order to improve the students’ learning efficiency and effectiveness. Methods The study divided 20 subjects into two groups on average—VR based PCIT (experimental group) and traditional PCIT (control group) with the completion of the background survey (BS) before PCITs, to guarantee no apparent backgroud variation including learning of oral implantology and VR technology, learning habits, interests and hobbies, etc. …”
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Evolving Machine Learning Methods for Density Estimation of Liquid Alkali Metals over the Wide Ranges by Tao Lin, Amir Seraj

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Computerized diagnosis of prostate cancer based on whole slide histology images and deep learning methods by V. A. Kovalev, D. M. Voynov, V. D. Malyshau, E. D. Lapo

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Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

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SYSTEM-ACTIVITY APPROACH TO FORMATION OF RESEARCH COMPETENCE OF FUTURE TRANSLATORS BY PROJECT-BASED LEARNING METHODS by Valeriia M. Vasyliuk

“…The article reveals the essence of the system-activity approach to the formation of research competence of future translators by means of project-based learning and identifies its features in the process of their professional training in higher education. …”
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Bridging readiness and reasoning: A mixed methods study on learning readiness and students’ argumentation in mathematics by Nur Fauziyah, Erfina Jamil, Fatimatul Khikmiyah, Sarwo Edy

“…This study aimed to investigate the relationship between learning readiness and students' argumentation patterns in mathematics learning, and to describe these patterns using Toulmin's argumentation model. …”
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A Review of Advanced Deep Learning Methods of Multi-Target Segmentation for Breast Cancer WSIs by Qiaoyi Xu, Afzan Adam, Azizi Abdullah, Nurkhairul Bariyah

“…Based on this analysis, this paper proposes six criteria to enhance the diagnostic performance of deep learning methods in multi-target segmentation for breast cancer digital pathology and to improve the clinical acceptability of deep learning methods.…”
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Deep learning-based multimodal trajectory prediction methods for autonomous driving: state of the art and perspectives by Jun HUANG, Yonglin TIAN, Xingyuan DAI, Xiao WANG, Zhixing PING

“…Although deep learning methods have achieved better results than traditional trajectory prediction algorithms, there are still problems such as information loss, interaction and uncertainty difficulties in modelling, and lack of interpretability of predictions when implementing multimodal high-precision prediction for autonomous vehicles in heterogeneous, highly dynamic and complex changing environments.The newly developed Transformer's long-range modelling capability and parallel computing ability make it a great success not only in the field of natural language processing, but also in solving the above problems when extended to the task of multimodal trajectory prediction for autonomous driving.Based on this, the aim of this paper is to provide a comprehensive summary and review of past deep neural network-based approaches, in particular the Transformer-based approach.The advantages of Transformer over traditional sequential network, graphical neural network and generative model were also analyzed and classified in relation to existing challenges, simultaneously.Transformer models can be better applied to multimodal trajectory prediction tasks, and that such models have better generalisation and interpretability.Finally, the future directions of multimodal trajectory prediction were presented.…”
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Teacher acceptability of physically active learning in UK secondary schools – a mixed methods study by Lara E. Hollander, Zoi Toumpakari, Lydia Emm-Collison

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