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An ann-based approach to identify smart appliances for ambient assisted living (aal) in the smart space 2nd

An ann-based approach to identify smart appliances for ambie...

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2nd international conference on Trends in Computational and Cognitive Engineering, TCCE 2020

作者： Uddin, Mohammad Helal Hossain, Mohammad Nahid Yang, S.-H. Department of Electronic Engineering Kwangwoon University Seoul139701 Korea Republic of

ISBN: (纸本)9789813346727

This research discusses about a way to identify appliances in the smart space using artificial neural network (ANN). smart appliances identification technique can solve a few specific problems for AAL like reducing the implementation complexity in the application level, finding the anomaly in the early stages. We have proposed an ANN-based approach to identify the appliances using smart space data. The smart appliances identification process is initiated by collecting data related to power consumption of smart appliances which are used for AAL services. An individual template along ANN-based approach is proposed to improve the accuracy. Through the interaction of the template, the proposed system has the ability to improve its identification by labeling the unlabeled input data. An ANN-based feedforward algorithm multilayer perceptron (MLP) is used for identifying the appliances. The output from MLP is observed whether the data pattern is a new class or not. The template provides the possible solution based on features and data. The proposed model has achieved identification performance with an average of 93% accuracy. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Neural networks

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An Edge computing Paradigm for Time-Sensitive Applications

An Edge Computing Paradigm for Time-Sensitive Applications

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4th World conference on smart Trends in Systems, Security and Sustainability (WorldS4)

作者： Jain, Arpit Jat, Dharm Singh Namibia Univ Sci & Technol Comp Sci Windhoek Namibia

ISBN: (纸本)9781728168234

Edge computing (EC) is a new developing computing technology where data are collected, and analysed nearer to the edge or sources of the data. Cloud to the edge, intelligent applications and analytics are part of the loT applications and technology. Edge computing technology aims to bring cloud computing features near to edge devices. For time-sensitive applications in cloud computing, architecture massive volume of data is generated at the edge and stored and analysed in the cloud. Cloud infrastructure is a composition of data centres and large-scale networks, which provides reliable services to users. Traditional cloud computing is inefficient due to delay in response, network delay and congestion as simultaneous transactions to the cloud, which is a centralised system. This paper presents a literature review on cloud-based edge computing technologies for delay-sensitive applications and suggests a conceptual model of edge computing architecture. Further, the paper also presents the implementation of QoS support edge computing paradigm in Python for further research to improve the latency and throughput for time-sensitive applications.

关键词： Cloud computing Fog computing Edge computing IOT QoS

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Social E-Commerce and Marketing Strategy Based on data Analysis

Social E-Commerce and Marketing Strategy Based on Data Analy...

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Tang, Qian Li, Zhen Beijing Institute of Technology Zhuhai Campus ZhuhaiGuangdong519088 China

ISBN: (纸本)9783030627423

As a derivative and transformation of traditional e-commerce, social e-commerce mine business information and user relationships through the networks, establish some models to provide personalized e-commerce services for consumers, which has become an important development direction. This paper summarizes the definition of social e-commerce through reference review, and compares the characteristics of social and traditional e-commerce, and deepens the understanding of social e-commerce business mode. Based on the analysis of the data of the article pushed by Jingdong WeChat public account, mining the marketing strategy of social e-commerce, which has certain significance for the actual social e-commerce operation. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： data mining

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Deep Neural Architecture for Face mask Detection on Simulated Masked Face dataset against Covid-19 Pandemic

Deep Neural Architecture for Face mask Detection on Simulate...

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international conference on computing, Communication, and intelligent Systems (ICCCIS)

作者： Negi, Alok Kumar, Krishan Chauhan, Prachi Rajput, R. S. Natl Inst Technol Uttarakhand Dept Comp Sci & Engn Srinagar 246174 Garhwal India GB Pant Univ Agr & Technol Coll Technol Pantnagar 263153 Uttar Pradesh India GB Pant Univ Agr & Technol Dept OfMath Stat & Comp Sci Pantnagar 263153 Uttar Pradesh India

ISBN: (纸本)9781728185293

The dangerous COVID-19 (SARS-CoV-2) is rising steadily and globally, with more than 72,851,747 confirmed cases observed to WHO including 1,643,339 deaths till 17 December 2020. The country's economy is now almost fully halted, people are stuck up and investment becomes deteriorating. So, this is turning to worry of the government for a development and health. Health organizations are often desperate for evolving decision-making innovations to overcome this viral virus and encourage people to receive rapid and effective responses in real-time. Thus, it is important to create auto-mechanisms as a preventive shield to ensure healthy humanity against SARS-CoV-2. Advanced analytics methods and other strategies could also empower researchers, learners and the pharmaceutical industry to acknowledge the hazardous COVID-19 and speed it up care procedures by efficiently testing vast volumes of research data. The prevention method consequence is being used to effectively manage, calculate, forecast and monitor current infected people and future potential cases. Therefore, we proposed CNN and VGG16 based deep learning models to incorporate and enforce AI-based precautionary measures to detect the face mask on Simulated Masked Face dataset (SMFD). This technique is capable of recognizing masked and unmasked faces to help monitor safety breaches, facilitate the use of face masks, and maintain a secure working atmosphere.

关键词： CNN Deep Learning data Augmentation Face Mask Detection Simulated Masked Face dataset (SMFD) VGG 16 WHO

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Communication Response of Internet Rumor Audiences Based on Big data Analysis

Communication Response of Internet Rumor Audiences Based on ...

引用

international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Liu, Sitong Guilin University of Aerospace Technology Guilin China

ISBN: (纸本)9783030627423

In the era of big data, the importance of data analysis has been put on the agenda, and at the same time, the authenticity of massive information has become a challenge. In the face of the fact that the number of Internet users in China has exceeded 850 million yuan and the trend of obvious growth, the research on the propagation response rule of the network rumor audiences in the era of big data is urgent. Based on the background of the era of big data, this paper USES the classic wt-sir rumor propagation model to simulate the rumor propagation mechanism in the Internet environment, and finds that the rumor propagation scale and propagation speed are significantly positively correlated with the importance and credibility of the rumor. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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IoTeST: IoT-Enabled smart Tourism—Shaping the Future of Tourism 1st

IoTeST: IoT-Enabled Smart Tourism—Shaping the Future of Tou...

引用

1st FICR international conference on Rising Threats in Expert Applications and Solutions, FICR-TEAS 2020

作者： Sharma, Shivani Rishi, O.P. Sharma, Anukrati University of Kota Kota Rajasthan India

ISBN: (纸本)9789811560132

There is increasing evidence of a technological shift in the sector of travel and tourism that has been coined as "IoT-enabled smart tourism" (IoTeST). IoT, i.e., Internet of Things continues to be in its pre-stage and is supposed to transform the Travel and Tourism Industry. It reforms the end processes of the accommodation, airlines, and alternative travel firms by linking smart devices, methods, and course of actions. By taking advantage of the IoT technology, travel business will realize better functioning competence and a lot of custom-made visitor experience. In the present time, IoT becomes the heart of smart tourism technology but ubiquitous Wi-Fi, Near-Field Communication (NFC), smart phones/mobile connectivity, Radio-Frequency Identification (RFID), and sophisticated data warehouses and data mining algorithms are also considered vital in creating a smart tourism technology infrastructure. As tourists started to explore the destinations and its attractions, IoT technology can make more efficient the entire tourism process. Sensors in IoT technology are there to assist the tourists to find and realize data concerning to their trip with the help of smart gazettes, smart phone, cameras, and sensors. These sensors collect information concerning tourist services and habits and reaction to completely diverse attractions so as to see patterns and optimize the experience. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Big data

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Computer Software Technology Under the Background of Big data Development

Computer Software Technology Under the Background of Big Dat...

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Ying, Lv Zhifeng, Zhang Laiwu Vocational and Technical College No.1 Shanghai Street Laiwu JinanShandong271100 China

ISBN: (纸本)9783030627454

With the continuous development of science and technology in our country, big data technology is becoming more and more mature. In recent years, the application of computer software in our country is more and more extensive. As an important part of social production, it is of great significance to strengthen the research of computer software technology. Computer technology, as one of the landmark technologies in the 21st century, has a direct relationship with social production and people’s quality of life. Therefore, this paper focuses on the application of computer software technology in the era of big data, to improve the data processing capacity and strengthen the economic benefits of social production. Therefore, it is of great significance to strengthen the application of computer software technology in the era of big data. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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The Positive Effect of Attention Module in Few-Shot Learning for Plant Disease Recognition 5

The Positive Effect of Attention Module in Few-Shot Learning...

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5th international conference on Pattern Recognition and Artificial Intelligence, PRAI 2022

作者： Lin, Hong Tse, Rita Tang, Su-Kit Qiang, Zhen-Ping Pau, Giovanni Macao Polytechnic University Faculty of Applied Sciences China Macao Polytechnic University Eng. Res. Ctr. of Appl. Technol. on Mach. Transl. and Artif. Intelligence of Ministry of Education China Southwest Forestry University College of Big Data and Intelligent Engineering KunMing China University of Bologna Department of Computer Science and Engineering-DISI Bologna Italy University of California Samueli Computer Science Department Los Angeles United States

ISBN: (数字)9781665499163

ISBN: (纸本)9781665499163

Few-shot learning is good solution for plant disease recognition which can generalize to new categories by using few samples. However, the features extracted from few shots are limited. Attention is a technique for focusing on the significant features which can help to obtain better feature representation. In this work, we use a naive metric-based few-shot learning network as the baseline method, exploit the effect of different kinds of attention module: channel attention, spatial attention and hybrid attention. In experiments, we choose the representative modules of each attention category to show their effects in few-shot learning paradigm: SE, ASPP, CBAM and Triplet Attention. We conduct experiments with two data settings of PlantVillage, and illustrate the usage these attention modules in Residual Networks. The results indicate that the different attention modules can improve recognition accuracy to varying degrees. Attention can be used as effective improvement of feature representation under few-shot condition. © 2022 IEEE.

关键词： Learning systems

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Application of Big data Technology in National Emergency Management System

Application of Big Data Technology in National Emergency Man...

引用

international conference on Application of intelligent Systems in Multi-modal Information analytics, MMIA 2020

作者： Tao, Yongmei Changchun Institute of Technology ChangchunJilin130021 China

ISBN: (纸本)9783030514303

China’s emergency management system has been established for a short period of time, and its development is relatively slow. There are many problems, such as lack of information sharing mechanism, large deviation of emergency response and poor decision-making quality In China’s emergency management system. In the era of big data, how to use big data technology to integrate multiple resources to establish an emergency big data sharing platform is an important problem faced by emergency management. Through literature review and field research, this study summarizes the urgent problems in China’s current emergency management development, and puts forward the implementation path of applying big data technology to China’s emergency management system. Such as to set up the big data thinking, as early as possible for the relevant practitioners to carry out systematic big data knowledge training;realize the organic integration of big data technology and emergency management system. In addition, computer network security technology should be further improved, and firewall technology should be used to effectively strengthen the control of user information in network access. © 2021, Springer Nature Switzerland AG.

关键词： Big data

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Feature Analysis of Chinese Drama Based on Big data Analysis

Feature Analysis of Chinese Drama Based on Big Data Analysis

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international conference on Application of intelligent Systems in Multi-modal Information analytics, MMIA 2020

作者： Liu, Chunhua Henan Vocational College of Science and Technology Henan China

ISBN: (纸本)9783030514303

"Big data" has become a well-deserved focus in the industry in the past year. Especially with the development of new SNS network, the surge of video traffic and the emergence of photo sharing needs, big data grows more rapidly in the fertile soil. The era of big data has come, we can use big data for all aspects of analysis, so as to provide us with more abundant information resources. This paper takes Chinese drama as the research object and analyzes the characteristics of Chinese drama with big data analysis method, so as to summarize the characteristics of Chinese drama and contribute to the development of Chinese drama. The big data analysis method adopted in this paper is to use crawler software and SPSS Modeler to conduct data mining and modeling and obtain the corresponding feature word cloud. The research of this paper shows that the unique performance style and expression technique of Chinese drama make the characteristics of drama obvious and have the characteristics of generality, freehand brushwork and theatricality. According to these characteristics, relevant laws and regulations can be issued at the national or government level to promote the development of Chinese drama and enable the broad masses of people to have a deeper understanding of Chinese drama. © 2021, Springer Nature Switzerland AG.

关键词： data mining

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