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Proposing a Blockchain-Based Open data Platform and Its Decentralized Oracle 11th

Proposing a Blockchain-Based Open Data Platform and Its Dece...

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11th international conference on intelligent Networking and Collaborative Systems (INCoS) / 22nd international conference on Network-Based Information Systems (NBiS)

作者： Fujihara, Akihiro Chiba Inst Technol 2-17-1 Tsudanuma Narashino Chiba 2750016 Japan

ISBN: (纸本)9783030290351;9783030290344

Bitcoin has been attracted attention to issue digital currency and also to manage transactions in a decentralized and trustless way without assuming any reliable third-party organization. To enhance the potential of Bitcoin, blockchain technologies have been studied to find more applications to smart contract, identification, and certificate which is valid even after the original issuer disappears. On the other hand, mobile crowdsensing is known as a method to collectively gather and share local data with the help of many and unspecified participants having their portable devices with sensors like smartphones to extract useful information from them. Expectation-Maximization (EM) algorithm is considered to estimate true information from task results from many independent workers and to evaluate workers' scores. By the combination of blockchain and mobile crowdsensing technologies, a open data platform to save true information into the blockchain and issue currency to workers based on their reliability scores. In this research, we explain how to create this open data platform to generate Big and Long-time Open data (BaLOD) to certify events that occurred in reality and everyone can validate the events.

关键词： Open data

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A User Specific APDS for smart City Applications

A User Specific APDS for Smart City Applications

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international conference on Research in intelligent and computing in Engineering, RICE 2020

作者： Sahoo, Goutam Kumar Pradhan, Prasanta Kumar Das, Santos Kumar Singh, Poonam Department of Electronics and Communication Engineering National Institute of Technology Rourkela RourkelaOdisha India Department of ECE J B Institute of Engineering and Technology Hyderabad India

ISBN: (纸本)9789811575266

Road accidents are the major risk factor in day-to-day life. The prevention and quick detection of an accident is the priority in saving the lives of human beings. Advances in technologies like the internet of things (IoT) make life better for everyone but adding technologies to control and manage traffic in a smarter way is a big challenge. Accident prevention and detection system (APDS) is developed to provide real time support to the people through IoT. The APDS aims to provide an early solution to day-to-day traffic incidents. The prevention of accidents is more important as vehicles are controlled by human beings. The parameters, like change in speed, human body part movements, overtaking, rule braking, etc., are responsible for the accident. It can be managed or controlled using some rule-based techniques. The abnormal behavior of each parameter can be identified by continuous monitoring, and reporting the same well in before may reduce the occurrence of an accident. Once an accident occurs, the detail information of accident data are shared with end-users with some proper authentication. The information sharing is established through machine-to-machine (M2M) communication. The end-users will get all the data regarding location, time of the accident, and many more details by accessing the web link through the internet. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Business english word frequency analysis method based on big data

Business english word frequency analysis method based on big...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Xing, Yichen Shandong Women’s University JinanShandong250000 China

ISBN: (纸本)9789811525674

With the rapid development of information, big data has increasingly become an important strategic resource and reliable action basis for various activities. At the same time, in the trend of economic globalization, the economic links between countries are increasingly close. As a global language, English is widely used in various business activities. In this case, business English is getting more and more attention. In business English for key word, this study search China hownet, ten thousand, d PuSanDa database, 1585 pieces of the sifting effective literature as the analysis sample, using statistical analysis software SATI3.2 literature citations information, social network analysis software Ucinet6.0 *** the Draw, using word frequency analysis and spectrum analysis method of combining the knowledge, comprehensive and integrated analysis of the business English category of highlight the word frequency and large data for subsequent business English research to provide the reference. The research results of this paper show that the research of big data is increasing, and the research content of business English is gaining increasing attention. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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Tiny Neural Networks for Environmental Predictions: an integrated approach with Miosix 6

Tiny Neural Networks for Environmental Predictions: an integ...

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6th IEEE international conference on smart computing (smartCOMP)

作者： Alongi, Francesco Ghielmetti, Nicolo Pau, Danilo Terraneo, Federico Fornaciari, William Politecn Milan DEIB Dipartimento Elettron Informaz & Bioingn Milan Italy STMicroelectronics Syst Res & Applicat Milan Italy

ISBN: (纸本)9781728169972

Collecting vast amount of data and performing complex calculations to feed modern Numerical Weather Prediction (NWP) algorithms require to centralize intelligence into some of the most powerful energy and resource hungry supercomputers in the world. This is due to the chaotic complex nature of the atmosphere which interpretation require virtually unlimited computing and storage resources. With Machine Learning (ML) techniques, a statistical approach can be designed in order to perform weather forecasting activity. Moreover, the recently growing interest in Edge computing Tiny intelligent architectures is proposing a shift towards the deployment of ML algorithms on Tiny Embedded Systems (ES). This paper describes how Deep but Tiny Neural Networks (DTNN) can be designed to be parsimonious and can be automatically converted into a STM32 microcontroller-optimized C-library through X-CUBE-AI toolchain;we propose the integration of the obtained library with Miosix, a Real Time Operating System (RTOS) tailored for resource constrained and tiny processors, which is an enabling factor for system scalability and multi tasking. With our experiments we demonstrate that it is possible to deploy a DTNN, with a FLASH and RAM occupation of 45,5 KByte and 480 Byte respectively, for atmospheric pressure forecasting in an affordable cost effective system. We deployed the system in a real context, obtaining the same prediction quality as the same DNN model deployed on the cloud but with the advantage of processing all the necessary data to perform the prediction close to environmental sensors, avoiding raw data traffic to the cloud.

关键词： Tiny Machine Learning Neural Networks Embedded Systems Real Time Operating Systems Edge computing

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Design of Primary System for 110kV smart Substation

Design of Primary System for 110kV Smart Substation

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2020 international conference on intelligent computing, Automation and Systems, ICICAS 2020

作者： Chang, Kuo-Chi Chen, Hongkai Chu, Kai-Chun Chang, Fu-Hsiang Wang, Hsiao-Chuan Hsu, Tsui-Lien Lin, Yuh-Chung Zhou, Yuwen Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China North Borneo University College Department of Business Administration Sabah Malaysia College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Fujian University of Technology Department of Business Management Fuzhou China Shih-Hsin University Department of Tourism Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan

ISBN: (纸本)9781728191461

Substation is the bridge between power plant and load, and it is the place where high-quality energy is transported. And China's power technology has been in the world's top level, because of the complex terrain in China, so the design of power station should consider the impact of terrain factors, economic factors, and future development factors and so on. Therefore, smart substation design is worthy of our research and innovation. Installation of lightning arrester can effectively reduce the threat of lightning. © 2020 IEEE.

关键词： Timing circuits

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Cloud computing Services Adoption by University Students: Pilot Study Results 4th

Cloud Computing Services Adoption by University Students: Pi...

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4th international conference of Reliable Information and Communication Technology (IRICT)

作者： Almazroi, Abdulwahab Ali Shen, Haifeng Mohammed, Fathey Al-Kumaim, Nabil Hasan Univ Jeddah Fac Comp & Informat Technol Khulais Saudi Arabia Australian Catholic Univ Fac Law & Business Brisbane Qld Australia Univ Utara Malaysia Sch Comp Bukit Kayu Hitam Malaysia Univ Teknikal Malaysia Fac Technol Management & Technopreneurship Melaka Malaysia

ISBN: (纸本)9783030335823;9783030335816

Cloud computing applications provide computing resources and services on demand via the Internet. Implementation and adoption of cloud services can lead to improved performance and reduced cost related to the computing services. In developing countries, more specific in the high education sector, cloud computing services adoption is low. This paper presents the pilot study which is conducted to validate the instrument developed for examining the factors affecting the adoption of cloud computing services by university students. A small sample of university students in Saudi Arabia was targeted to collect the data for validating the questionnaire which was developed by adapting TAM3 and related studies constructs' items. The results indicate that all the measures used in the questionnaire are reliable.

关键词： Cloud services University students Technology acceptance model Adoption

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Role and Challenges of Unstructured Big data in Healthcare 3rd

Role and Challenges of Unstructured Big Data in Healthcare

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international conference on data Management, analytics and Innovation (ICDMAI)

作者： Adnan, Kiran Akbar, Rehan Khor, Siak Wang Ali, Adnan Bin Amanat Univ Tunku Abdul Rahman Fac Informat & Commun Technol Kampar 31900 Malaysia

ISBN: (纸本)9789813299498;9789813299481

Unprecedented growth in the volume of unstructured healthcare data has immense potential in valuable insight extraction, improved healthcare services, quality patient care, and secure data management. However, technological advancements are required to achieve the potential benefits from unstructured data in healthcare according to the growth rate. The heterogeneity, diversity of sources, quality of data and various representations of unstructured data in healthcare increases the number of challenges as compared to structured data. This systematic review of the literature identifies the challenges and problems of data-driven healthcare due to the unstructured nature of data. The systematic review was carried out using five major scientific databases: ACM, Springer, ScienceDirect, PubMed, and IEEE Xplore. The inclusion of articles in review at the initial stage was based on English language and publication date from 2010 to 2018. A total of 103 articles were selected according to the inclusion criteria. Based on the review, various types of healthcare unstructured data have been discussed from different domains of healthcare. Also, potential challenges associated with unstructured big data have been identified in healthcare for future research directions in the technological advancement of healthcare services and quality patient care.

关键词： Unstructured data Healthcare Big data Systematic literature review Challenges of healthcare data

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A Blockchain and Defensive Deception Co-design for Webcam Spyware Detection 18

A Blockchain and Defensive Deception Co-design for Webcam Sp...

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18th IEEE international conference on Pervasive intelligent and computing (PICom)

作者： Badih, Haissam Alagrash, Yasamin Rrushi, Julian Oakland Univ Dept Comp Sci & Engn Rochester MI 48309 USA

ISBN: (纸本)9781728166094

Recently there have been rapid developments in the progression of advanced malware attacks, requiring the need for robust malware detection methods. We show that the integration of access control with defensive deception is more efficient than approaches from those categories of tools running alone, since malware operate under the heavy influence of deception mechanisms while trying to evade access control. We facilitate the identification of second-order webcam spyware through an approach that is larger than ever in terms of behavior. We propose to integrate defensive deception mechanisms in a series of interactions that lead to the use of a decoy I/O device and decoy server, in this case, a decoy smart contract and decoy key management server case study. Our approach combines blockchain concepts, such as smart contracts, with key management methods, to create confusion in malware's operations to benefit their detection.

关键词： Spyware decoy process co-design smart contract blockchain

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A Rigorous Analysis of Biomedical Edge computing: An Arrhythmia Classification Use-Case Leveraging Deep Learning

A Rigorous Analysis of Biomedical Edge Computing: An Arrhyth...

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IEEE international conference on Internet of Things and Intelligence System (IOTAIS)

作者： Sadman Sakib Mostafa M. Fouda Zubair Md Fadlullah Lakehead University Thunder Bay Ontario Canada Idaho State University Pocatello ID USA

ISBN: (数字)9781728194486

ISBN: (纸本)9781728194493

Biomedical Edge computing is an exciting area of interdisciplinary research involving the Internet of Medical Things (IoMT) sensors and devices with lightweight Artificial Intelligence (AI) logic. To address the rapidly growing need for smart and portable biomedical devices with localized decision-making capability, we present a proof-of-concept logic-in-sensor design with an arrhythmia analytics use-case. Existing signal processing techniques for arrhythmia analytics such as discrete wave transform (DWT) and non-linear delay differential equation (DDE) lead to high complexity and computational burden on biomedical edge devices due to expensive preprocessing steps. As a solution, we propose a deep learning-based lightweight arrhythmia classification method leveraging a customized one-dimensional (1-D) convolutional neural network (CNN). A rigorous analysis of the proposed method's performances and generalization potential are assessed using four publicly available datasets.

关键词： Decision making Electrocardiography Sensor systems Biosensors Artificial intelligence intelligent sensors Edge computing

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Half Hourly Electricity Load Forecasting Using Convolutional Neural Network 13th

Half Hourly Electricity Load Forecasting Using Convolutional...

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13th international conference on Innovative Mobile and Internet Services in Ubiquitous computing (IMIS)

作者： Khan, Abdul Basit Majeed Khan, Sajjad Aimal, Sayeda Khan, Muddassar Ruqia, Bibi Javaid, Nadeem Abasyn Univ Islamabad Islamabad 44000 Pakistan COMSATS Univ Islamabad Islamabad 44000 Pakistan Sardar Bhadur Khan Women Univ Quetta Quetta 87300 Pakistan

ISBN: (纸本)9783030222635;9783030222628

In this paper, enhanced Deep Learning (DL) method is implemented to resolve the accurate electricity load forecasting problem. Electricity load is a factor which plays major role in operations of smart Grid (SM). For solving this problem, we propose a model which is based on preprocessing, selection and classification of historical data. Features are selected by Combine Feature Selection (CFS) using Decision Tree (DT) and Mutual Information (MI) techniques, and then CFS Convolutional Neural Network (CFSCNN) is used for forecasting of load. Our proposed scheme is also compared with other benchmark schemes. Simulation results show better efficiency and accuracy of proposed model for half hourly electricity load forecasting for one day, one week and one month ahead for the data obtained from ISO NE-CA electricity market.

关键词： Deep learning Classification Mutual information smart grid Decision tree Convolutional neural network

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