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4th Annual international conference on Data Science, machine learning and Blockchain Technology, AICDMB 2023

4th Annual International Conference on Data Science, Machine...

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4th Annual international conference on Data Science, machine learning and Blockchain Technology, AICDMB 2023

ISBN: (纸本)9781032426853

the proceedings contain 50 papers. the special focus in this conference is on Data Science, machine learning and Blockchain Technology. the topics include: An unsupervised approach to creating a restaurant recommendation system;Classification of alzheimer’s disease using D-DEMNET framework;comparison of machine learning and deep learning methods for detection of liver abnormality;soil micronutrient detection using machine learning;a review of tracking concept drift detection in machine learning;wearable electrogastrogram perspective for healthcare applications;computer vision based home automation;Early autism detection using ML on behavioural pattern;implementation of application prototypes for human-to-computer interactions;recommendation system for anime using machine learning algorithms;predicting bitcoin price fluctuation by Twitter sentiment analysis;microarchitecture design and verification of co-processor for floating point operation;blockchain based higher education ecosystem;document verification using blockchain;blockchain-based traceability system for readymade food products;a cloud based interactive framework for emergency medical data sharing;the analysis and interpretation of higher education teachers based on student and teachers feedback;Implementing AI on microcontrollers in fog and edge architectures;abnormality detection in chest radiograph using deep learning models;a comprehensive review on hate speech recognition utilizing natural language processing and machine learning;prevalence of migraine among collegiate students in greater Noida;Indoor navigation using BLE beacons;strategic health planner and exercise suggester;perspective of deep learning strategies for analysis of 1D biomedical signals;revolution in agriculture sector using blockchain technology;customer churn prediction using ensemble learning with neural networks;Securing crime case summary and E-FIR using blockchain concept.

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applications of machine learning in Cryptography: A Survey 19

Applications of Machine Learning in Cryptography: A Survey

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3rd international conference on Cryptography, Security and Privacy (ICCSP) / 4th international conference on Multimedia and Image Processing (ICMIP)

作者： Alani, Mohammed M. Khawarizmi Int Coll Abu Dhabi U Arab Emirates

ISBN: (纸本)9781450366182

machine learning techniques have had a long list of applications in recent years. However, the use of machine learning in information and network security is not new. machine learning and cryptography have many things in common. the most apparent is the processing of large amounts of data and large search spaces. In its varying techniques, machine learning has been an interesting field of study with massive potential for application. In the past three decades, machine learning techniques, whether supervised or unsupervised, have been applied in cryptographic algorithms, cryptanalysis, steganography, among other data-security-related applications. this paper presents an updated survey of applications of machine learning techniques in cryptography and cryptanalysis. the paper summarizes the research done in these areas and provides suggestions for future directions in research.

关键词： cryptography cryptanalysis machine learning

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Design and application of Structure Mechanics CAI Courseware

Design and Application of Structure Mechanics CAI Courseware

引用

4th international conference on computer Science and Education

作者： Cheng, Tao Yan, Keqin Huangshi Inst Technol Sch Civil Engn Huangshi 435003 Hubei Peoples R China

ISBN: (纸本)9781424435197

the course of structure mechanics' design and execution is introduced in the article. And the particularity of professional course multimedia courseware is also expatiated. then, the importance of multimedia teaching applied to professional courses in colleges is explained by a "3-step" teaching example. It is shown that the CAI courseware is applicable to bring up the active learning custom and innovation consciousness of applied talents in civil engineering.

关键词： structure mechanics CAI Multimedia remote instruction

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application of Deep learning Neural Networks in Sports Shoe Brand Classification Task 4

Application of Deep Learning Neural Networks in Sports Shoe ...

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4th international conference on computer, Big Data and Artificial Intelligence, ICCBD+AI 2023

作者： Li, Biao Sun, Guang Sheng, Haoyu Liu, Junjun Hunan University of Finance and Economics School of Information Technology and Management Changsha China Central South University School of Computer Science and Engineering Changsha410083 China

ISBN: (纸本)9798350373233

In recent years, deep learning has gained widespread attention and importance due to its outstanding performance in image feature learning. the rapid development of machine learning and deep learning has provided a powerful tool for handling complex classification problems and has achieved significant results. the development of neural network algorithms has also benefited from the progress in deep learning research. Deep learning is a machine learning method based on multi-layer neural network structures, which improves the modeling capability for complex data and tasks by increasing the depth and complexity of the network. For the task of classifying shoe brands, deep learning can help neural network models better understand features such as appearance, texture, and brand logos of shoes, as well as identify other everyday items to assist in their classification. After identifying the items, using different optimizers can improve the accuracy of classification, enabling more effective classification decisions. © 2023 IEEE.

关键词： Image recognition

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Research on Distributed machine learning Methods in Databases 4

Research on Distributed Machine Learning Methods in Database...

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4th IEEE international conference on Advanced Information and Communication Technologies, AICT 2021

作者： Klymash, Mykhailo Kyryk, Marian Demydov, Ivan Hordiichuk-Bublivska, Olena Kopets, Halyna Pleskanka, Nazar Lviv Polytechnic National University Department of Telecommunications Lviv Ukraine Lviv Polytechnic National University Department of Management of Organizations Lviv Ukraine Lviv Polytechnic National University Department of Computer Aided Systems Lviv Ukraine

ISBN: (纸本)9781665406185

this article discusses the problems of processing large amounts of information in databases to more efficiently execute user queries. the methods of distributed machine learning were described in this research, which allow a faster analysis of large data. A modification of the distributed database system architecture was proposed, which ensures the effective application of machine learning methods. Software modeling of data arrays processing using distributed machine learning has been carried out. the obtained results indicate an increase in the efficiency of processing large amounts of information in databases using distributed machine learning methods. © 2021 IEEE.

关键词： Big data

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Comparative Analysis of machine learning Models in computer Network Intrusion Detection 4

Comparative Analysis of Machine Learning Models in Computer ...

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4th IEEE-Nigeria-Section international conference on Disruptive Technologies for Sustainable Development (IEEE NIGERCON)

作者： Osa, Edosa Oghenevbaire, Ogodo Efevberha Univ Benin Dept Elect & Elect Engn Fac Engn Benin Nigeria Western Delta Univ Coll Nat & Appl Sci Dept Math & Comp Sci Oghara Nigeria

ISBN: (纸本)9781665479783

Network security is a major concern of the modern era. With the rapid development and massive usage of computer networks over the past decade, the vulnerabilities of network systems continue to be of significant concern. Intrusion detection systems are used to monitor networks and identify unauthorized access or malicious traffic over secured networks. the application of machine learning algorithms to the intrusion detection domain could enhance such systems. this paper presents a comparative analysis of selected machine learning algorithms for network intrusion detection. the CICIDS 2017 dataset provided the necessary dataset for training the models. Results show that of all six considered, Decision Tree classifier was the overall best.

关键词： machine learning intrusion accuracy traffic algorithm

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application of machine learning in bipolar disorder 4

Application of machine learning in bipolar disorder

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4th international Symposium on Artificial Intelligence for Medicine Science (ISAIMS)

作者： Hong, Xin Hu, Maorong Jiangxi Univ Tradit Chinese Med Nanchang Peoples R China

ISBN: (纸本)9798400708138

Purpose of review: machine learning, a hot area of research today, has been attempted to be applied in various fields of clinical medicine. this paper reviews the current status of research on machine learning in the filed of bipolar disorder, including applications in the diagnosis, identification and the accurate treatment of bipolar disorder, and the prediction of suicidal behaviors in bipolar disorder. It also discusses the advantages and shortcomings and prospects of the applications of machine learning in bipolar disorder, in order to provide references for related researches and clinical treatment. Research methods: the literature on the application of machine learning in the field of bipolar disorder in recent years was searched through literature navigation. the aspects of prevention, diagnosis and treatment interventions in bipolar disorder were analyzed. Research conclusion: In recent years, researches on the clinical diagnosis and treatment of bipolar disorder by machine learning have been increasing. However, there are still some limitations and it still needs to be cautious in clinical application. As mental health practitioners, we should actively adapt to and promote the further development of machine learning in the field of bipolar disorder.

关键词： machine learning Artificial Intelligence Bipolar disorder Mental health

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A machine learning approach to improve congestion control over wireless computer networks

A machine learning approach to improve congestion control ov...

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4th IEEE international conference on Data Mining

作者： Geurts, P El Khayat, L Leduc, G Univ Liege B-4000 Liege Belgium

ISBN: (纸本)0769521428

In this paper we present the application of machine learning techniques to the improvement of the congestion control of TCP in wired/wireless networks. TCP is suboptimal in hybrid wired/wireless networks because it reacts in the same way to losses due to congestion and losses due to link errors. We thus propose to use machine learning techniques to build automatically a loss classifier from a database obtained by simulations of random network topologies. Several machine learning algorithms are compared for this task and the best method for this application turns out to be decision tree boosting. It outperforms ad hoc classifiers proposed in the networking literature.

关键词： learning systems

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application of machine learning methods to control the process of defectoscopy of railway tracks 4

Application of machine learning methods to control the proce...

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4th international conference on Control in Technical Systems, CTS 2021

作者： Subbotin, Alexey N. Zhdanov, Vladimir S. Saint Petersburg Electrotechnical University "LETI" St. Petersburg Russia Emperor Alexander I St. Petersburg State Transport University St. Petersburg Russia

ISBN: (纸本)9781665424547

this article describes the application of machine learning methods to control the process of railway flaw detection. It is told about the new capabilities of computer technology, which make it possible to clarify the damage for the lineman. A new way of interaction of a specialist with diagnostic information using the Internet of things is proposed. the description of architecture is given according to three standards at the design stage. An application for a smartphone has been developed. the effectiveness of using foggy computing environments and cloud technologies for recognizing damage to railway tracks using machine learning has been proven. Specific examples are given. © 2021 IEEE.

关键词： Internet of things

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application of extended isolation forest in avionics equipment fault diagnosis 4

Application of extended isolation forest in avionics equipme...

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4th international conference on machine learning and computer application, ICMLCA 2023

作者： Wu, Ziyu Niu, Wei Zhao, Yangyang Fan, Hong Xi’an Aeronautics Computing Technique Research Institute Xi’an China

ISBN: (数字)9781510680265

ISBN: (纸本)9781510680258

Avionics equipment is composed of multiple layers and complex structure, so it is difficult to research progress based on fault mechanism, and the amount of effective fault data of the model is insufficient, and it is difficult for the general fault diagnosis algorithm to train fault data. In order to realize the fault diagnosis of avionics equipment, machine learning is applied to the fault diagnosis of avionics equipment. Research samples are selected from ground operation simulation data, and an algorithm based on the combination of feature selection and extended isolation forest is proposed to detect and categorize typical faults of electronic modules. It can be well applied to the actual fault detection of avionics equipment . It can meet the requirements of lightweight applications and has practical engineering value. © 2024 SPIE.

关键词： Fault detection

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