Credit card fraud detection through machine learning algorithm by Agyan Panda, Bharath Yadlapalli, Zhi Zhou

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Translation Invariance-Based Deep Learning for Rotating Machinery Diagnosis by Wenliao Du, Shuangyuan Wang, Xiaoyun Gong, Hongchao Wang, Xingyan Yao, Michael Pecht

“…Discriminative feature extraction is a challenge for data-driven fault diagnosis. Although deep learning algorithms can automatically learn a good set of features without manual intervention, the lack of domain knowledge greatly limits the performance improvement, especially for nonstationary and nonlinear signals. …”
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THE ACCEPTANCE OF AN EDUCATIONAL INTEGRATED DEVELOPMENT ENVIRONMENT TO LEARN PROGRAMMING FUNDAMENTALS by Nor Farahwahida Mohd Noor, Aslina Saad, Abu Bakar Ibrahim, Norashady Mohd Noor

“…However, previous research shows that students face difficulties in learning programming due to its abstract concepts. …”
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Drone Landing and Reinforcement Learning: State-of-Art, Challenges and Opportunities by Jose Amendola, Linga Reddy Cenkeramaddi, Ajit Jha

Subjects: “…Deep reinforcement learning…”
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Machine Learning Methods for Forecasting Intermittent Tin Ore Production by Nabila Dhia Alifa Rahmah, Budhi Handoko, Anindya Apriliyanti Pravitasari

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Harnessing ICT for English Language Learning in Indonesia: Challenges and Opportunities by Aditya P. Nugraha, Fajar Duriat, Rusdayanti Rusdayanti

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THE IMPORTANCE OF USING DICTIONARY iN LANGUAGE LEARNING AND TEACHING by Ece SARIGÜL

“…<p>THE IMPORTANCE OF USING DICTIONARY iN LANGUAGE<br />LEARNING AND TEACHING</p>…”
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A Machine Learning Approach to Predict Air Quality in California by Mauro Castelli, Fabiana Martins Clemente, Aleš Popovič, Sara Silva, Leonardo Vanneschi

“…In this paper, we employ a popular machine learning method, support vector regression (SVR), to forecast pollutant and particulate levels and to predict the air quality index (AQI). …”
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Robust ensemble of handcrafted and learned approaches for DNA-binding proteins by Loris Nanni, Sheryl Brahnam

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Byzantine-robust federated learning over Non-IID data by Xindi MA, Qinghua LI, Qi JIANG, Zhuo MA, Sheng GAO, Youliang TIAN, Jianfeng MA

Subjects: “…federated learning…”
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Student Engagement Dataset (SED): An Online Learning Activity Dataset by M. S. S. Kassim, Z. H. Azizul, A. A. H. Ahmad Fuaad

Subjects: “…Learning analytics…”
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Application of Reinforcement Learning in Cognitive Radio Networks: Models and Algorithms by Kok-Lim Alvin Yau, Geong-Sen Poh, Su Fong Chien, Hasan A. A. Al-Rawi

“…Examples of the enhancements on RL, which do not appear in the traditional RL approach, are rules and cooperative learning. This paper also reviews performance enhancements brought about by the RL algorithms and open issues. …”
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USE OF LEARNING MANAGEMENT SYSTEMS IN HIGHER EDUCATION: PROGRESS AND POTENTIAL by S. V. BOGOLEPOVA, N. V. MALKOVA

Subjects: “…learning management system (lms)…”
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Hypergraph User Embeddings and Session Contrastive Learning for POI Recommendation by Yan Zhang, Bin Wang, Qian Zhang, Sulei Zhu, Yan Ma

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Retracted: Analyzing the Performance of Machine Learning Techniques in Disease Prediction by Journal of Food Quality

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Understanding why teachers entrust technology in innovating the learning outcomes by Sahlan Tampubolon, Lela Susanty, Khasanah Khasanah, Wisman Wisman, Agus Riyanto

“…This study aims to analyze why elementary school and college educators trust technology to achieve teaching and learning outcomes. To discuss in order to answer the problem comprehensively and with high validity, we have collected data with the help of technology in a database of academic works such as journals, books, proceedings, magazines, and digital era educational technology websites. …”
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An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning by S. M. Taslim Uddin Raju, Amlan Sarker, Apurba Das, Md. Milon Islam, Mabrook S. Al-Rakhami, Atif M. Al-Amri, Tasniah Mohiuddin, Fahad R. Albogamy

“…Bagging (random forest regression (RFR)), boosting (gradient boosting regression (GBR) and extreme gradient boosting regression (XGBR)), and stacking (STACK) are employed as ensemble models. Different machine learning (ML) approaches, including support vector regression (SVR), extreme learning machine (ELM), and multilayer perceptron neural network (MLP), are adopted as reference models. …”
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Exploring advanced machine learning techniques in oral cancer diagnosis by Bharath Kumar Jayam, Aravind Kumar Subramanian

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Intelligent cloud guidance technology based on natural language learning by Renjie TANG, Tao JIANG, Qiaojie YANG

“…The main problems existing in the current guidance system were analyzed.According to the intelligent guidance system researched in the current academic circles,a self-learning system for the disease which based on a large number of patient condition descriptions using a variety of machine learning algorithms was creatively proposed.The platform used Web crawler technology to obtain setting of the international and domestic medical institution departments and a large number of patient descriptions,which form a pathological knowledge base and a disease self-reported knowledge base.At the same time,the algorithm was innovatively constructed to combine the attention model with TextCNN to improve the accuracy of the consultation.…”
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A Vortex Identification Method Based on Extreme Learning Machine by Jun Wang, Lei Guo, Yueqing Wang, Liang Deng, Fang Wang, Tong Li

“…Recently, proposed deep learning methods have long network training time and high computational complexity. …”
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