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the Way of machine learning Based Solicit for Detecting Deceit in Online Based Transaction System with Security

The Way of Machine Learning Based Solicit for Detecting Dece...

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Advance Computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Naila Iqbal Qureshi Alba Meça Management Department College of Business Administration Princess Noura Bint Abdul Rahman University Riyadh KSA Università degli Studi di Padova Epoka University

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

Detection of fraud still remains one of the most important challenges that continue to stir up research and following implementation of advanced technologies in the field of financial transactions, like machine learning. In this respect, the financial transaction fraud detection seeks to find and compare different approaches in machine learning and understand effectiveness, challenges, and potential directions of future development in a comprehensive way. the paper outlines in the beginning the significance of fraud detection in transactions of finance. It reflects on the general impacts of fraud such as the negative effects on individuals, businesses, and the economy at large due to fraudulent activities. Traditional methods to detect fraud are very valuable; however, they usually fall short against such schemes that are either sophisticated or keep evolving, for which even more sophisticated methods are required. However, with machine learning-based solutions in fraud detection, it is now offering some promise, as these solutions can leverage algorithms processing huge volumes of transactional data to pinpoint any pattern signaling probable fraudulent behavior. Supervised learning techniques, such as logistic regression, decision trees, and support vector machines, have gained great popularity in fraud detection.

关键词： Support vector machines Logistic regression machine learning algorithms Systematics Supervised learning machine learning Fraud

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Weighted Cross-Product Constraint Transformation to Optimize Spatial Structure of data 4

Weighted Cross-Product Constraint Transformation to Optimize...

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4th international conference on Artificial Intelligence and Big data, ICAIBD 2021

作者： Wang, Siqing Li, Deqi Zhang, Xin Zhang, Shutao School of Science China University of Geosciences Beijing China School of Statistics Beijing Normal University Beijing China

ISBN: (纸本)9780738131702

the research of data spatial structure optimization is significant in data mining. Many methods optimize the space based on a specific criterion, which in a certain extent destroys the original spatial distribution of data with uncertain optimization effects. Based on the heterogeneous distribution spatial structure of the data and the importance of the data attributes to distinguish categories, we proposed the weighted cross-product constraint transformation (WCCT) method to improve the accuracy of data analysis. this method retains the spatial distribution of the original data and maps the data to a limited high-dimensional space with constraints, which increases the proximity between the same data category and the discrimination between different data categories. Moreover, we established a statistical evaluation system of spatial structure to prove the effectiveness of this method in optimizing the spatial structure of data attributes. Experimental analysis on real data demonstrates that the proposed method obtains excellent classification performance with different machine learning classifiers. © 2021 IEEE.

关键词： data mining

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7th EAI international conference on e-learning, e-Education, and Online Training, eLEOT 2021

7th EAI International Conference on e-Learning, e-Education,...

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7th EAI international conference on e-learning, e-Education, and Online Training, eLEOT 2021

ISBN: (纸本)9783030843854

the proceedings contain 104 papers. the special focus in this conference is on e-learning, e-Education, and Online Training. the topics include: data mining Method of English Online learning Behavior Based on machine learning Technology;intelligent Recommendation Model of Distance Education Courses Based on Facial Expression recognition;online Teaching Method of Conductive Characteristics of Graphene Materials Based on Big data mining;distance Teaching Method of Accounting Informatization Course Based on Big data mining;University Ideological and Political Multimedia Network Teaching Based on MOOC;an Efficient Teaching Method for Physiological Basic Course of Online and Offline Integration;decision Support Model for Online Education of Logistics Management Major from the Perspective of "Credit Bank";comprehensive Control Method of Network Teaching data Scheduling Based on Fuzzy Mathematics;design of Personal learning Model recognition Model for Online Teaching of Ideological and Political theory Course;reform and Practice of Digital Teaching of Engineering Mechanics Course Under the Background of "Double High Program";Research on the Ideological and Political Teaching Mode of Dual System Curriculum in Colleges and Universities Based on MOOC;pattern recognition Method of Training Japanese Talents in Online Education;research on Hybrid learning Mode of Financial Management Course in Cloud Classroom Environment;research on pattern recognition Method of Online English Education Based on Feature Self learning;pattern recognition Method of English Distance Online Education Based on Big data Algorithm;big data Based Human Resources Professional Distance Training Platform;design of Personalized Employment Guidance System for College Students Based on Big data.

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mining Social Media for data-Driven Analysis of Educational data with machine learning

Mining Social Media for Data-Driven Analysis of Educational ...

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Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), international conference on

作者： Lany L. Maceda Jo-Ann M. Cordovilla John Ruel L. Locaba Arlene A. Satuito Mideth B. Abisado Computer Science and Information Technology Department Bicol University Legazpi City Philippines Physics Department Bicol University Legazpi City Philippines College of Computing and Information Technologies National University Manila Philippines

ISBN: (数字)9798350391183

ISBN: (纸本)9798350391190

the Philippine Republic Act 10931, otherwise known as the Universal Access to Quality Tertiary Education (UAQTE) Act aims to provide free higher education opportunities and subsidies to undergraduate students. Despite the recent increase in its national budget allocation, there remains uncertainty on its effectiveness in the perspective of its stakeholders. In this study, we performed topic modeling analysis using Latent Dirichlet Allocation on a corpus of 7,754 preprocessed texts sourced from Facebook and Twitter. Among the identified themes, Clientele Satisfaction stands out as the dominant topic, followed by Information and Inquiries, Social Media Presence, Gratitude and Appreciation, and Educational Opportunities. the emerging dominant topics per region conveyed expressions of gratitude and appreciation for the support provided by the program. However, based on the analysis, the policymakers and program implementers should consider improving the dissemination of information to their stakeholders. this study offers insights into public perceptions, emphasizing the programs' impacts and areas necessitating improvements.

关键词： Uncertainty Mechatronics Social networking (online) Education machine learning Market research Stakeholders Resource management data mining Sustainable development

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Sleep Behaviour and Online Engagement in learning Management System at Higher Education during COVID-19 Pandemic 7

Sleep Behaviour and Online Engagement in Learning Management...

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7th international conference on Software Engineering and Computer Systems and 4th international conference on Computational Science and Information Management, ICSECS-ICOCSIM 2021

作者： Abdullah, Aziman Faculty of Computing College of Computing and Applied Sciences Universiti Malaysia Pahang Pekan Malaysia

ISBN: (纸本)9781665414074

During COVID-19 pandemic, many higher education institutions have shifted their teaching and learning operation towards full online learning. As a result, using learning management system (LMS) become more intensive, crucial and compulsory. the issue is, there is lack of research to prove that online learning engagement may cause sleep disorder among student and instructor in higher education. therefore, this paper aim to investigate user engagement in LMS and it associate with the risk of sleep disorder. this study adopts educational data mining (EDM) to extract the data from Moodle LMS log to discover the potential insights with business intelligence software tools. the outlier's detection using box-plot visualization manage to determine the indicators of sleep disorder behavior pattern. the findings from this study show that there are some student and instructor that potential to have experience sleep disorder. this novel finding is critical for institution to respond by developing a policy and risk mitigation strategy associated with unhealthy sleep behavior in online learning engagement. © 2021 IEEE.

关键词： COVID-19

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Gaussian process multi-label classification based on multi-view similarity fusion 4

Gaussian process multi-label classification based on multi-v...

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4th international conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2022

作者： Xiang, Hui Gu, Shenming School of Information Engineering Zhejiang Ocean University Zhoushan316022 China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhejiang Ocean University Zhoushan316022 China

ISBN: (纸本)9781450398343

Multi-view multi-label learning serves as a vital framework for learning from objects with diverse representations and rich semantics. the Gaussian process (GP), as an efficient and flexible Bayesian nonparametric model, the GP has effectively solved various tasks in machine learning. However, the Gaussian process has rarely been directly applied to multi-view multi-label learning scenarios. therefore, in this paper, we propose a new multi-view multi-label learning method (mvml-DSimGP) based on the Gaussian pass latent variable model (GPLVM), which consists of similar non-parametric mapping function learning, rule constraint learning and label learning. Similarity nonparametric study mapping function for multiple-views data analysis, it studied the view within the similarity and latent mapping function between the parameters. On the basis of the similarity of nonparametric function learning, regular constraints are introduced, and put forward multi-label learning. Instances with similar label information are encouraged to have similar output representations in the embedded space, making it sufficient discernment in the embedded space. Numerous experiments on real-world datasets clearly show that mvml-DSimGP has good performance compared to other general multi-view multi-label learning methods. © 2022 ACM.

关键词： Semantics

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Research on Deep learning-based AI Information Extraction Methods of Substation Engineering Design 4

Research on Deep Learning-based AI Information Extraction Me...

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4th international conference on Energy, Electrical and Power Engineering, CEEPE 2021

作者： Chen, Ying Jiang, Wei Wang, Yali Hu, Junhui Guan, Lan Zhu, Zhanwei Power Grid Subsidiary Company Powerchina Sichuan Electric Power Engineering Co. LTD. Chengdu China State Grid Beijing Electric Power Company Construction Department Beijing China

ISBN: (纸本)9781665433631

Substation engineering construction has accumulated a large amount of documents and a wealth of explicit and implicit knowledge in the long-term work practice. Using artificial intelligence technology to extract knowledge from unstructured documents, drawings and photos into structured data, is a prerequisite for providing guidance for new engineering design. through the research on application of artificial intelligence in the design of substation engineering, two functions are realized in the structuring of data: 1) using deep learning-based image recognition technology (SSD_mobilenet), the elements intelligent identification and quantity statistic in engineering drawings is realized. It provides a possibility of automatic generation for the structuring of design data. 2) through computer vision and machine learning technology (CTPN and CRNN), an electrical information recognition system is established to errata automatically, which saves manpower and time and provides auxiliary functions for data collection operations of previous engineering projects. the implementation results verify the effectiveness of the deep learning methods using in substation engineering design. © 2021 IEEE.

关键词： Deep learning

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the Design of the Multimodal-Based Educational Support Platform for Music and Reading in Elementary Schools

The Design of the Multimodal-Based Educational Support Platf...

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Electronic Communications, Internet of things and Big data (ICEIB), international conference on

作者： Lin Mengzhe Hong Meiyu Liu Ye State Key Laboratory of Brain and Cognitive Sciences Institute of Psychology Chinese Academy of Sciences Beijing China Department of Psychology University of Chinese Academy of Sciences Beijing China Xiamen Huming Primary School Xiamen China

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

this study aimes to design a multimodal educational support platform for music and reading in elementary schools to improve the reading ability of students. Numerous studies have shown that there is strong correlation between musical ability and reading ability of children in elementary school. this study further explored this correlation, and designed a multimodal educational support platform based on this finding. the platform integrateed the two disciplines of music and reading, and combined multimodal elements such as visual, auditory, and emotion feedback. this study has created an innovative educational tool. the platform is aimed for providing a fun, interactive, and personalized learning experience to stimulate the pupils' learning interest and to develop their linguistic and musical abilities comprehensively.

关键词： Emotion recognition Visualization Correlation Education Music machine learning Solids

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the Role of Artificial Intelligence in Information Acquisition

The Role of Artificial Intelligence in Information Acquisiti...

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Advances in Computing, Communication Control and Networking (ICAC3N), international conference on

作者： J.N. Singh Saurabh Saxena Riyanshu Saini Manali Chauan Kavita Saini School of Computing Science and Engineering Galgotias University Greater Noida UP India

ISBN: (数字)9798350330861

ISBN: (纸本)9798350330878

Search engines use artificial intelligence to find potential leads. Early concepts in both fields are introduced in Bush and Turing’s publications, which are also utilized to define artificial intelligence and data mining in this article. the foundation for further exploration of intellectual notions of art and their application to information retrieval is a straightforward model of an information retrieval system. pattern recognition, representation, problem solving and planning, reasoning, and learning are among the concepts covered. this paper finishes by outlining future directions for artificial intelligence research in data mining systems.

关键词： Natural languages machine learning Organizations Writing Search engines Market research Knowledge management

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4th international conference on Optimization, learning Algorithms and Applications, OL2A 2024

4th International Conference on Optimization, Learning Algor...

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4th international conference on Optimization, learning Algorithms and Applications, OL2A 2024

ISBN: (纸本)9783031774256

the proceedings contain 41 papers. the special focus in this conference is on Optimization, learning Algorithms and Applications. the topics include: Facial Expression recognition in Virtual Reality Simulations;augmented Reality in Industrial Training: A Comparative Analysis of Teaching Methods;comparison Between Single and Multi-objective Clustering Algorithms: MathE Case Study;learning Algorithms for Breast Cancer Classification and Diagnosis;fuzzy c-Means as a Decision Support Tool for Liver Disease Diagnosis Based on data Analysis;optimization of machine learning Models Applied to Robot Localization in the RobotAtFactory 4.0 Competition;p-Fuzzy System Applied to Population Dynamics: A Case Study;enhancing K-Way Circuit Partitioning: A Deep Reinforcement learning Methodology;optimizing Olive Disease Classification through Hybrid machine learning and Deep learning Techniques;a Neural Network-Based Approach to Identifying Wrinkles and Recommending Cosmetic Products;colorectal Polyp Segmentation: Impact of Combining Different datasets on Deep learning Model Performance;A Comparative Analysis of MATLAB and Python Neural Networks for Diabetes Prediction;cochineal Colony Detection in Cactus Pear: A Deep learning Approach;enhancing Quadruped Robot Performance through Gait Optimization;assessment of Logistics Performance Indicators in Southern European Countries Optimizing the Decision Making;Predicting Retail Store Transaction patterns: A Comparison of ARIMA and machine learning Models;route Optimization for Urban Last-Mile Delivery: Truck vs. Drone Performance;speeding up Line Search for Composite Objective Function with a Linear Inside Part;the Infodemic Issue: Numerical Modelling;a Multi-objective Approach for Solving Distributed Job Shop Scheduling Problems.

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