Deep joint learning diagnosis of Alzheimer’s disease based on multimodal feature fusion by Jingru Wang, Shipeng Wen, Wenjie Liu, Xianglian Meng, Zhuqing Jiao

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Key informants’ perspectives on simulation-based learning experiences: a qualitative study by Liz Kingston, Kathleen Markey, Owen Doody, Louise Murphy, Pauline Meskell, Therese Hennessy, Mairead Moloney

“…In this study, simulation-based learning experiences (SBLEs) were used to redress missed learning opportunities in real-life settings during restrictive conditions. …”
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Problem-based learning in radiology achieves similar results in classroom and metaverse settings by Teodoro Rudolphi-Solero, Fernando Bajos-Ariza, Rocío Lorenzo-Álvarez, Dolores Domínguez-Pinos, Miguel José Ruiz-Gómez, Francisco Sendra-Portero

“…This study compared a problem-based learning experience in radiology conducted face-to-face in real life (RL) and within the MV. …”
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Developing Quality Social Relationships: Technology-Based Learning Model to Enhance Social Skills in Boarding Schools by Fadhila Aisyah Nurunisa, Sadam Fajar Shodiq

“…The research results show a positive impact of technology-based learning on students' social abilities; many students are confident and shrewd even though technology continues to develop. …”
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Using concept maps to structure a small-scale literature review: an approach to research-based learning in pre-service teacher education by Victoria I. Marín

“…One popular (meta)methodology considered in educational research (and that is well suited to school research) is design-based research (DBR). Incorporating this approach into RBL as a method for developing teaching innovation in schools could be one way to include RBL in teacher education and place pre-service teachers in the position of teacher as researcher. …”
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Flip the Triangle: using quality improvement methods to embed a positive behaviour support approach on a medium secure forensic ward for men with intellectual disabilities by Amar Shah, Day Njovana, Charlotte Whittle, George Chingosho, Kate Parker, Manaal Jama, Sidrah Babar

“…This study aimed to promote positive culture change and embed the evidence-based practice of positive behaviour support by shifting focus and efforts from the use of physical and restrictive interventions to manage crises to intervening positively and proactively to prevent crises from occurring. …”
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Research progress in globular fruit picking recognition algorithm based on deep learning by LI Hui, ZHANG Jun, YU Shuochen, LI Zhixin

“…Automatic picking equipment combined with computer vision often uses object detection algorithms to identify objects, and object detection algorithms can be divided into both traditional algorithms and deep learning-based object detection algorithms. Traditional algorithms identify the position and bounding box of a specific object in an image or a video, usually by preprocessing the image (Scaling, grayscale or normalization), feature extraction (using traditional hand-designed features or automatic learning based on machine learning), classification or regression (confirming object class and location), and non-maximum suppression to further optimize and filter detected objects. …”
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FDIA Detection in Power Grid Based on Opposition-Based Whale Optimization Algorithm and Multi-layer Extreme Learning Machine by Lei XI, Yixiao WANG, Miao HE, Chen CHENG, Xilong TIAN

“…Therefore, this paper proposes a FDIA location detection method based on opposition-based learning whale optimization algorithm and multi-layer extreme learning machine (OWOA-ELMML). …”
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An Ensemble Learning-Based Predictive Parameterization Approach for Permanent Magnet Synchronous Machines by Sema Nur Ipek, Nur Bekiroglu, Murat Taskiran

“…Permanent Magnet Synchronous Machines (PMSMs) are extensively utilized for their ability to deliver accurate position control, and the equivalent circuit characteristics of these machines are essential in several applications, particularly in formulating the control strategy. …”
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Research on fusion model based on deep learning for text content security enhancement by Shaomin WANG, Zheng WANG, Hua REN

“…The rapid expansion of information content on the internet and the mobile internet has resulted in violations of laws and regulations and bad information,which affects the content security of the internet space.Traditional text content security recognition methods based on matching of sensitive words ignore context semantics,resulting in high false positive rate and low accuracy.Based on the analysis of traditional text content security recognition methods,a fusion recognition model using deep learning and a model fusion algorithm process were proposed.Text content security recognition system based on the fusion recognition model using deep learning and experimental verification was introducted deeply.Results show that the proposed model can effectively solve the problem of high false positive rate caused by the lack of semantic understanding of traditional recognition methods,and improve the accuracy of the bad information detection.…”
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Graph learning based suicidal ideation detection via tree-drawing test by Ye Liu, Jiashuo Zheng, Yang Zeng, Fang Luo, Xuetao Tian, Xuetao Tian

“…To evaluate this method, a real dataset of 806 students from primary and secondary school in Shaanxi Province, China, is collected, and some metrics including macro-F1, G-mean, and false positive rate are used.ResultsThe results demonstrate that the proposed method significantly outperforms traditional machine learning and convolution neural network approaches. …”
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Hybrid deep learning for IoT-based health monitoring with physiological event extraction by Sivanagaraju Vallabhuni, Kumar Debasis

“…Robust statistical methods based on M-estimator theory had been integrated for the treatment of outliers and missing data, which helped in reducing bias in estimation by 30% and increasing the False Positive Rate (FPR) by 12%. …”
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Deep learning-based diffusion MRI tractography: Integrating spatial and anatomical information by Yiqiong Yang, Yitian Yuan, Baoxing Ren, Ye Wu, Yanqiu Feng, Xinyuan Zhang

“…However, the accuracy of reconstructed tractograms has been a longstanding challenge. Recently, deep learning methods have been applied to improve tractograms for better white matter coverage, but often comes at the expense of generating excessive false-positive connections. …”
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Developing Adult Learners' Language Competence in Culture-Based Blended-Learning Course by Ineta Luka

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PRACTICAL TRAINING OF OFFICERS OF THE STATE FIRE SERVICE THROUGH GAME-BASED LEARNING by V. V. Bulgakov, A. A. Lazarev, E. P. Konovalenko, T. A. Mochalova

“…The research is based on the provisions of the associative-reflex theory, the theory of motivation development and the theory of contextual, modular, problem-based, reflexive and game-based learning.Results and scientific novelty. …”
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The Application of Machine Learning Algorithms for Text Mining based on Sentiment Analysis Approach by Reza Samizade, Elnaz Mahmoudi Saeid Abad

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Development of a diagnostic classification model for lateral cephalograms based on multitask learning by Qiao Chang, Shaofeng Wang, Fan Wang, Beiwen Gong, Yajie Wang, Feifei Zuo, Xianju Xie, Yuxing Bai

“…Abstract Objectives This study aimed to develop a cephalometric classification method based on multitask learning for eight diagnostic classifications. …”
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An optimized LSTM-based deep learning model for anomaly network intrusion detection by Nitu Dash, Sujata Chakravarty, Amiya Kumar Rath, Nimay Chandra Giri, Kareem M. AboRas, N. Gowtham

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A Multitask-Based Transfer Framework for Cooperative Multi-Agent Reinforcement Learning by Cheng Hu, Chenxu Wang, Weijun Luo, Chaowen Yang, Liuyu Xiang, Zhaofeng He

“…However, existing knowledge transfer-based methods only focus on strategies or agent-level knowledge in a single task, and the transfer of knowledge in such a specific task to new and different types of tasks is likely to fail. …”
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High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

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