Deep Neural Networks (DNNs) have been widely used in Natural Language Processing (NLP) applications. However, due to the lack of interpretability, recent studies have shown that the DNN-based models used in NLP are vu...
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The proceedings contain 126 papers. The special focus in this conference is on Machine Learning and Big dataanalytics for IoT Security and Privacy. The topics include: Development of Industrial Chain of Internet of T...
ISBN:
(纸本)9783030627454
The proceedings contain 126 papers. The special focus in this conference is on Machine Learning and Big dataanalytics for IoT Security and Privacy. The topics include: Development of Industrial Chain of Internet of Things Based on 5G Communication Technique;path Choice of smart City Construction from the Perspective of Economic Growth;computer Audit Quality Control in Big data Era;MOOC System in the Era of Big data Improves the Effectiveness of College Physical Education;Risks and Prevention in the Application of AI;improvement of Microblog Recommendation System Based on Interaction Strategies of Agricultural E-Commerce Enterprise;exploration and Construction of "One Ring, Three Deductions" Innovation and Entrepreneurship Talent Cultivation Model for Higher Vocational Art Design Major Based on Information Technology;research Progress of Neuroimaging Techniques in Organizational Behavior Under the Background of smart City;recommendation Strategies for smart Tourism Scenic Spots Based on smart City;control Strategy of Environmental Control System in Power Transmission;design and Implementation of Self-service Tourism Management Information System Based on B/S Architecture;MATLAB Software in the Numerical Calculation of Civil Engineering;Low Latency V2X Application of MEC Architecture in Traffic Safety;cloud computing Technology for the Network Resource Allocation on the Research of Application;talent Evaluation Model of College Students Based on Big data Technology;application of Cloud Class in Comprehensive English Teaching in the Context of Internet Plus;the Application of 3D Printing Technology in Sculpture;the Development Strategy of Current Medical Scientific Research Information;on the Development of the Industry Trend of "Ai+Education".
The intermingling of sports and modern technologies, including artificial intelligence (AI), machine learning (ML), and wearables, have transformed athletic performance, sports analytics, and event management. Thus, t...
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ISBN:
(数字)9798350367973
ISBN:
(纸本)9798350367980
The intermingling of sports and modern technologies, including artificial intelligence (AI), machine learning (ML), and wearables, have transformed athletic performance, sports analytics, and event management. Thus, the research aims to explore the influence of solutions on Olympic athlete performance and medal outcomes. On this occasion, advanced techniques like hypothesis testing and logistic regression methods will be applied accordingly to assess the influence of the various attributes of the athletes, such as their age in years, height in meters, and weight in kilograms. Gender and sport-specific differences will be analyzed using IBM SPSS tools. The study also aims to explore the importance of atmospheric conditions and organizational arrangements put across by the host city, providing a clear understanding of how external factors influence medal distribution. In this regard, real-time dataanalytics, wearable technologies, and augmented reality have also been explored to enhance training regimens and fan engagement. The findings have constructed AI, machine learning, sports analytics, and trends to aid coaches, teams, and athletes in making smart decisions toward enhancing competitiveness and gaining an edge.
The proceedings contain 126 papers. The special focus in this conference is on Machine Learning and Big dataanalytics for IoT Security and Privacy. The topics include: Development of Industrial Chain of Internet of T...
ISBN:
(纸本)9783030627423
The proceedings contain 126 papers. The special focus in this conference is on Machine Learning and Big dataanalytics for IoT Security and Privacy. The topics include: Development of Industrial Chain of Internet of Things Based on 5G Communication Technique;path Choice of smart City Construction from the Perspective of Economic Growth;computer Audit Quality Control in Big data Era;MOOC System in the Era of Big data Improves the Effectiveness of College Physical Education;Risks and Prevention in the Application of AI;improvement of Microblog Recommendation System Based on Interaction Strategies of Agricultural E-Commerce Enterprise;exploration and Construction of "One Ring, Three Deductions" Innovation and Entrepreneurship Talent Cultivation Model for Higher Vocational Art Design Major Based on Information Technology;research Progress of Neuroimaging Techniques in Organizational Behavior Under the Background of smart City;recommendation Strategies for smart Tourism Scenic Spots Based on smart City;control Strategy of Environmental Control System in Power Transmission;design and Implementation of Self-service Tourism Management Information System Based on B/S Architecture;MATLAB Software in the Numerical Calculation of Civil Engineering;Low Latency V2X Application of MEC Architecture in Traffic Safety;cloud computing Technology for the Network Resource Allocation on the Research of Application;talent Evaluation Model of College Students Based on Big data Technology;application of Cloud Class in Comprehensive English Teaching in the Context of Internet Plus;the Application of 3D Printing Technology in Sculpture;the Development Strategy of Current Medical Scientific Research Information;on the Development of the Industry Trend of "Ai+Education".
The amount of data produced by distributed devices, such as smart devices and the IoT, is increasing continuously. The cost of transmitting data and also distributed computing power raise interest in distributed data ...
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ISBN:
(纸本)9781665494021
The amount of data produced by distributed devices, such as smart devices and the IoT, is increasing continuously. The cost of transmitting data and also distributed computing power raise interest in distributed data mining (DDM). However, in a pure DDM scenario, data availability may not be enough to generate reliable models in a distributed environment. So, the ability to exchange data efficiently and effectively will become a crucial component of DDM. In this paper, we propose the concept of the Machine Learning data Market (MLDM), a framework for the exchange of data among autonomous agents. We consider a set of learning agents in a cooperative distributed ML, where agents negotiate data to improve the models they use locally. In the proposed data market, the system's predictive accuracy is investigated, as well as the economic value of data. The question addressed in this paper is: How data exchange among the agents will improve the accuracy of the learning model. Agent budget is defined as a limitation of negotiation. We defined a multi-agent system with negotiation and assessed it against the multi-agent system baseline and the single-agent system. The proposed framework is analyzed based on the different sizes of batch data collected over time to find out how this changes the effect of the negotiation on the accuracy of the model. The results indicate that even simple negotiation among agents increases their learning accuracy.
One in every four cancer cases in women is breast cancer, which is the most prevalent malignancy in this group globally. In 2020, breast cancer will account for one in every eight new instances of cancer, according to...
One in every four cancer cases in women is breast cancer, which is the most prevalent malignancy in this group globally. In 2020, breast cancer will account for one in every eight new instances of cancer, according to projections of 2.3 million new cases. Breast cancer identification, both early and accurate, is critical to improve patient outcomes and survival rates. Magnetic resonance imaging (MRI) has developed as a valuable method for diagnosing breast cancer. Deep learning algorithms, notably convolutional neural networks (CNNs), have demonstrated exceptional effectiveness in a variety of medical image processing applications, including breast cancer classification. The ResNet-50 architecture has received a lot of interest in this context because of its excellent performance in image recognition tasks. ResNet-50 is a deep residual network that introduces skip connections and residual learning to solve the difficulty of training very deep neural networks. A total number of 1480 cancer MRI samples are collected from the Kaggle database, having two classes, which include healthy and malignant scans. It is observed that our proposed model with the data pre-processing techniques has achieved a classification accuracy of 92.01%.
This paper designs an intelligent collaboration mechanism between the distributed edge data center and the core data center platform. The core data center is responsible for managing and monitoring the distributed dat...
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Sustainable home techniques and methods are becoming more popular as homeowners recognize the need to perform their part to slow global warming and save their energy bills. One effective solution for lowering househol...
Sustainable home techniques and methods are becoming more popular as homeowners recognize the need to perform their part to slow global warming and save their energy bills. One effective solution for lowering household energy use and carbon emissions is installing a solar water heating system. To increase the effectiveness, convenience, and sustainability of solar water heating systems, it investigates how to combine these technologies. It discusses the limitations of traditional solar water heating systems, such as their inefficiency, high maintenance costs, and complicated operation. The potential for sensors, dataanalytics, and remote control to improve energy gathering and distribution is explored in the Internet of Things (IoT)-enabled solar water heating systems. It also proceeds through how predictive maintenance algorithms might help extend the system's life and reduce repair bills. It provides a household installation to evaluate the economics and benefits of IoT-enabled solar water heating systems. Our research shows that energy efficiency has significantly increased, potentially saving up to 30% more money than traditional systems. IoT technology's real-time monitoring and management functions give households more agency over and understanding of energy use.
Digital twins are becoming more relevant for business and academic users due to advances in IoT, AI, and Big data. Due to global urbanization, pollution, public safety, traffic congestion, and other challenges have ar...
Digital twins are becoming more relevant for business and academic users due to advances in IoT, AI, and Big data. Due to global urbanization, pollution, public safety, traffic congestion, and other challenges have arisen. New technologies make cities smarter to keep up with growth. In the Internet of Things (IoT) age, many sensing devices acquire and/or produce a broad range of sensory data over long periods of time for a variety of businesses and applications. The use case determines the device’s data stream volume and speed. The efficacy of the analytics process used to analyze these streams of data to learn, predict, and act determines IoT’s worth as a business paradigm changer and quality-of-life technology. This study introduces Deep Learning (DL), a family of advanced machine learning techniques, to enhance IoT analytics and teaching. Introducing new results, challenges, and research opportunities. This study may assist academics and newbies comprehend how to use DL to smart cities. Analyzing and summarizing major IoT DL research initiatives. Check out smart IoT devices with DL embedded into their AI. Ultimately, the study will identify issues and suggest additional research. Each chapter concludes with experimental findings and the newest literature review.
In today's healthcare system, data overload presents challenges and opportunities. This effort uses Blockchain and Machine Learning to recommend new healthcare data management methods. Machine learning rapidly ext...
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ISBN:
(数字)9798331513023
ISBN:
(纸本)9798331513030
In today's healthcare system, data overload presents challenges and opportunities. This effort uses Blockchain and Machine Learning to recommend new healthcare data management methods. Machine learning rapidly extracts meaningful data from enormous datasets. Blockchain technology also employs consensus mechanisms to protect healthcare data, making data exchange more reliable. Blockchain, deep learning, and IoT improve healthcare. Technology's rapid expansion allows this integration to provide real-time monitoring, secure data management, and accurate disease prediction. IoT-connected medical devices record patient health data for early diagnosis and treatment. However, handling and preserving such large amounts of sensitive medical data remains a challenge. Blockchain technology secures, privates, and interoperates healthcare providers' data by offering a distributed, immutable, and tamper-proof ledger. Time-series health data is evaluated using recurrent neural networks (RNNs), notably LSTM networks, to improve predictive analytics. LSTM can detect long-term dependencies in sequential data, making it good at forecasting diabetic problems. Through these technologies, we can develop a trustworthy, effective, and smart healthcare environment that allows for earlier diagnosis, more targeted treatment regimens, and improved patient outcomes. This platform automates data processing and prediction, relieving clinicians of some of their workload while improving healthcare security and efficiency. These benefits won't guarantee widespread adoption unless computing costs, scalability, and integration with healthcare infrastructures are addressed. Future research should improve these technologies to make healthcare safer, easier, and patient-centered.
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