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检索条件"任意字段=4th International Multi-Conference on Computing in the Global Information Technology"

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Towards Reliable Medical Transactions for Blockchain based Healthcare Systems using Hybrid Consensus Method 22

Towards Reliable Medical Transactions for Blockchain based H...

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Proceedings of the 4th international conference on information Management & Machine Intelligence

作者： Arun Prasath Selvaraj Suresh Annamalai Department of Networking and Communications School of Computing SRM Institute of Science & Technology India Department of Networking and Communications SRM Institute of Science and Technology India

ISBN: (纸本)9781450399937

Blockchain technology opens the door to securing and protecting massive amounts of IoT data storage, improving decentralized storage applications, getting rid of centralized trust servers, and facilitating data accountability and traceability. A hybrid blockchain can be used to build a network where sensors communicate with a device that performs smart contracts and records all events on the blockchain. Actual clinical observation and treatment choices would be provided by alerting patients and medical professionals and keeping a safe history of who started these acts. the proposed work aggrandize blockchain consensus algorithm that combines the benefits of the PoW and PoA algorithms. these PoW-PoA hybrid consensus methods are simulated with Merkle tree creation focusing conditional contrast large item set tree. the PoW mining mechanism is effectively utilized in proposed system to control the block creation time. With PoA consensus technique, the user generates the real blocks. the validating nodes, which are arbitrary chosen as reliable entities, protect PoA blockchain. the Proof of Authority concept is a highly scalable system since it only requires a small number of block validators. Participants who have been pre-approved serve as the system's moderators and confirm blocks and transactions. According to results, the proposed method performs better than conventional consensus algorithm in terms of scalability, network throughput, and the quantity of blocks generated.

关键词： Consensus Algorithm IoT Smart contract Blockchain Healthcare Applications Hybrid Method

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WHY ARE PEOPLE STILL NOT WALKING? thE NEED FOR A MICRO-SCALED multi-CRITERIA SPATIO-TEMPORAL DESIGN APPROACH TO IMPROVE WALK-QUALITY 7

WHY ARE PEOPLE STILL NOT WALKING? THE NEED FOR A MICRO-SCALE...

引用

7th international conference on Smart Data and Smart Cities, SDSC 2022

作者： White, M. Huang, X. Langenheim, N. Yang, T. Schofield, R. Young, M. Livesley, S.J. Seneviratne, S. Stevenson, M. Centre for Design Innovation Swinburne University of Technology Australia School of Architecture and Art North China University of Technology Beijing China Melbourne School of Design University of Melbourne Australia School of Geography Earth and Atmospheric Sciences University of Melbourne Australia Ecosystem and Forest Sciences Faculty of Science University of Melbourne Australia Melbourne Schools of Design| Engineering| Population and Global Health University of Melbourne Australia

Walking is essential for the health and well-being of communities as well as meeting environmental challenges of the 21st Century. there have been significant research contributions in recent decades to understanding factors that can influence the likelihood of citizens choosing active travel modes, with great advances in understanding the built environment, particularly macro-scaled urban factors such as land-use mix, population density, and street patterns. So why are people still not walking? And is there anything we can do to try to change this? To answer these questions, this paper explores walking environment assessment approaches using a trans-disciplinary narrative approach, touching on multiple critical disciplinary knowledge areas. We find that while much of the research into the built environment's influence on walking has made positive contributions in helping identify areas of cities that discourage active travel, the capacity to improve these areas has been limited. While macro-scaled factors commonly considered in 'walkability' analysis are highly influential to mode choice, unless working on green-field development, these factors may require re-zoning private land, substantial demolition and renewal, and may be financially or politically infeasible and thus extremely difficult to change. there is a need to augment macro-scaled analysis with micro-scaled tools, and to establish multi-criterion spatio-temporal design decision support approaches drawing from emerging technologies to make informed, integrated and effective urban design changes. these methods applied at precinct and streetscape levels have the potential to make feasible improvements to the 'walk-quality' of the built environment and contribute to facilitating active travel. © Author(s) 2022.

关键词： Computer vision

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Research on UAV Detection of threat Target around oil Pipeline Based on Deep Learning 2021

Research on UAV Detection of Threat Target around oil Pipeli...

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7th international conference on computing and Artificial Intelligence, ICCAI 2021

作者： Wu, Qiang Wu, Xuegang Zheng, Xin Yue, Bin Beijing University of Technology Information Department Beijing China Beijing Aeronautical Technology Research Cente China

ISBN: (纸本)9781450389501

With the development of UAV, UAV has been applied to various projects with its advantages of low construction cost, low safety risk coefficient and convenient *** terms of UAV platform, currently composite wing and multi-rotor UAV are typically adopted, which can realize basic flight route. In terms of image detection, neural network is mainly used to classify and recognize the target in the image. In this paper, the YOLOV4 algorithm is improved to make it more suitable for UAV detection of ground *** the ground detection of UAV, most of them are small targets, so clustering method is used to redesign anchor for small targets. Because the features of small targets have more details in the shallow feature layer, the shallow feature is superimposed into the feature extraction layer, and the shallow feature and the deep feature are *** the data processing, data enhancement, color dithering, flipping, cutting of the data set for expansion. through the test of the modified network, the following results are obtained: the overall mAP is improved by 9.3%, the detection mAP for small targets such as people is improved by 23.75%, and the detection mAP for working vehicles is improved by 15.4%. the detection efficiency of small targets is improved, and the speed can meet the real-time requirements, and it can be deployed in the UAV for UAV detection. © 2021 ACM.

关键词： Unmanned aerial vehicles (UAV)

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Optimal Operation of Reservoir Power Generation Based on Improved Grey Wolf Algorithm 6th

Optimal Operation of Reservoir Power Generation Based on Imp...

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6th international conference on Advanced Machine Learning Technologies and Applications, AMLTA 2021

作者： Chen, Ran-Fan Chang, Kuo-Chi Chu, Kai-Chun Chang, Fu-Hsiang Wang, Hsiao-Chuan Hsu, Tsui-Lien Liu, Jia-jing Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China School of Management Fujian University of Technology Fuzhou China Department of Tourism Shih-Hsin University Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9783030697167

the operation efficiency of the power station mainly depends on power generation. therefore, under the constraints of water level, water amount, and output of hydropower station, generation flow in each period can be reasonably controlled according to the initial operating conditions of reservoir and inflow runoff, maximize the power generation of cascade power station within the operation cycle. Grey wolf algorithm (GWO) is easy to implement, simple in structure, requires few parameters to be changed, and has a simple operating principle. the gray wolf algorithm’s solution process simulated wolves’ hunting behavior, and the prey was regarded as the optimal global solution. All the candidate solutions were regarded as a gray wolf population. As shown from the above results, the GWOs algorithm has a more vital exploration ability and development ability to optimize single-peak and multi-peak functions better than the other two algorithms. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Reservoirs (water)

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Cooperative Optimization Strategy between Active Distribution Network and Integrated Energy System Based on Autonomous State Space

Cooperative Optimization Strategy between Active Distributio...

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Smart Power & Internet Energy Systems (SPIES), international conference on

作者： Zihao Zhao Shaoxuan Zhang Jing Zhang Weichen Wang Chunguang He Shuqiang Yang Planning Research Center State Grid Hebei Economic Research Institute Shijiazhuang China School of Electronic and Information Engineering Hebei University of Technology Tianjin China Human Resource Department State Grid Hebei Economic Research Institute Shijiazhuang China

Aiming at the problem that the global optimization results of distribution network can not satisfy the needs of multiple parties, a cooperative development strategy of active distribution network and integrated energy system which based on autonomous state space is proposed. Firstly, the satisfactory solution group of the optimal operation of the distribution network is calculated, and, the interaction power between the distribution network and the integrated energy system is taken as the base point of the autonomous state space, and the shortest radius of the transient security region under the base point range is calculated, thereby determining the autonomous state space of the interaction between the integrated energy system and the active distribution network. Secondly, optimize the integrated energy system in the autonomous state space to determine the output and cost of dispatching equipment in the integrated energy system. the calculation example shows that the collaborative optimization strategy proposed in this paper can give consideration to the interests of active distribution network safety optimization operation and integrated energy system operator cost optimization at the stage of power market reform not yet fully mature.

关键词： Renewable energy sources Costs Systems operation Collaboration Distribution networks Safety Active distribution networks

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IoT Service-Based Crowdsourcing Ecosystem in Smart Cities 4th

IoT Service-Based Crowdsourcing Ecosystem in Smart Cities

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4th international conference on Smart computing and Informatics, SCI 2020

作者： Dutta, Arijit Roy, Ruben Misra, Chinmaya Singh, Kamakhya School of Computer Engineering KIIT Deemed to be University Bhubaneswar India Department of IT Government College of Engineering and Leather Technology Kolkata India School of Computer Application KIIT Deemed To Be University Bhubaneswar India

ISBN: (纸本)9789811615016

In this information era, online access gives netizens the opportunity to post or interact with each other. Online crowdsourcing is also known as citizen science. the rapid increase of service and demand for IoT devices drive the attention towards crowdsourcing, and the most eye-seeking part is that it involves the participation of the individual. It also can be stated as receiving services, ideas, or solutions to problems by getting connected to large groups of people via the Internet. Obviously, having a huge, well-disciplined network would be of prime importance in this case. Millions of devices are connected which may congest the network due to heavy traffic. To deal with the situation, researchers are explored different aspects to handle the situations. So, in this paper, we propose a reliable fog-based spatial-temporal crowdsourcing. Here, we try to tinker the data processing that takes place between fog nodes and cloud. We use the batch processing method for saving energy. However, how to allocate the tasks to proper fog nodes and eventually improve communication efficiency are critical. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fog computing

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Novel Image Compression and Deblocking Approach Using BPN and Deep Neural Network Architecture 4th

Novel Image Compression and Deblocking Approach Using BPN an...

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4th IFIP TC 12 international conference on Intelligence Science, ICIS 2020

作者： Manyam, Rajsekhar Reddy Sivagami, R. Krishankumar, R. Sangeetha, V. Ravichandran, K.S. Kar, Samarjit School of Computing SASTRA University ThanjavurTN613401 India Department of Mathematics NIT Durgapur Durgapur West Bengal India

ISBN: (纸本)9783030748258

Medical imaging is an important source of digital information to diagnose the illness of a patient. the digital information generated consists of different modalities that occupy more disk space, and the distribution of the data occupies more bandwidth. A digital image compression technique that can reduce an image's size without losing much of its important information is challenging. In this paper, a novel image compression technique based on BPN and Arithmetic coders is proposed. the high non-linearity and unpredictiveness of the interrelationship between the pixels present in the image to be compressed is handled by BPN. An efficient coding technique called Arithmetic coding is used to produce an image with a better compression ratio and lower redundancy. A deep CNN based image deblocker is used as a post-processing step to remove the artefacts present in the reconstructed image to improve the quality of the reconstructed image. the effectiveness of the proposed methodology is validated in terms of PSNR. the proposed method is able to achieve about a 3% improvement in PSNR compared with the existing methods. © 2021, IFIP international Federation for information Processing.

关键词： Magnetic resonance imaging

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SAR-Based Wind Resource Assessment near the Coast of Fujian 4

SAR-Based Wind Resource Assessment near the Coast of Fujian

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4th international conference on computing and Big Data, ICCBD 2021

作者： Li, Dongkun Yu, Peng Yang, Wenjin He, Yuanrong School of Environmental Science and Engineering Xiamen University of Technology Xiamen361024 China College of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China

ISBN: (纸本)9781450387194

Satellite remote sensing data is an important resource in the big data era. this study aims to investigate offshore wind resource near the coast of Fujian using high-resolution remote sensing data. Among all kinds of remote sensing sensors, the synthetic aperture radar (SAR) is a quite unique instrument that can monitor the earth's surface with very high spatial resolution under all-time and all-weather conditions. Totally over 2,340,000 data points from 102 Sentinel-1 SAR scenes are used to estimate the mean wind speed and direction. Wind power density at different heights of 10 m, 25 m, 50 m, and 90 m are then calculated to assess the offshore wind resource in the study area. the high wind speed and high energy density results show that the offshore wind resource is relatively stable and sufficient along the Fujian coast. the results found in this research from remote sensing data will help for evaluating of offshore wind energy resource and determining of potential locations of wind farms for China. © 2021 ACM.

关键词： Remote sensing

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Novel Approach for Resolution Enhancement of Satellite Images Using Wavelet Techniques 4th

Novel Approach for Resolution Enhancement of Satellite Image...

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4th international conference on Advanced computing and Intelligent Engineering, ICACIE 2019

作者： Rathod, Mansing Khanapuri, Jayashree Hiran, Dilendra Information Technology Department K.J.S.I.E/IT Mumbai400022 India Pacific University Udaipur313003 India Electronics and Telecommunication Department K.J.S.I.E/IT Mumbai400022 India

ISBN: (纸本)9789811565830

Today, many researchers are working on satellite images, to solve resolution problems. Some of the techniques are used to enhance the resolutions that are Stationary Wavelet (SWT), Discrete Wavelet (DWT) and Integer Wavelet Transforms (IWT). these wavelet transforms are considered for improving the quality in terms of resolution enhancement. Low resolution (LR) image is used for processing and decomposed by mentioned transforms. Interpolation techniques are applied to manipulate the output of transform images. Some estimated images determined through the interpolation factor 2 to make equal sizes of images. All the images are integrated with inverse wavelet transform to generate high resolution (HR). In this work, we have compared wavelet transform. LANDSAT5 satellite images are considered for verification of implemented techniques. In this paper, three types of results are presented that are enhanced the image with size 128 × 128 to 512 × 512, 256 × 256 to 512 × 512 and iterative resolution. Some of the quality parameters are applied, i.e. PSNR, RMSE, MAE and MSE for verification for the performance of implemented techniques. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Interpolation

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A DDoS Attack Detection Method Based on LSTM Neural Network in the Internet of Vehicles 2021

A DDoS Attack Detection Method Based on LSTM Neural Network ...

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the 4th international conference on information Technologies and Electrical Engineering

作者： Yuexin Zhang Yiyang LIU Yiying Zhang Longzhe Han Jia Zhao Yannian Wu School of Artificial Intelligence Tianjin University of Science and Technology China School of Information Engineering Nanchang Institute of Technology China CHINA GRIDCOM CO. LTD. China

ISBN: (纸本)9781450386494

With the continuous development and application of 5G wireless communication technology and smart car technology, the Internet of Vehicles has attracted more and more attention. Due to the application requirements of high bandwidth and low latency in the Internet of Vehicles, Mobile Edge computing (MEC) is introduced into the in-vehicle network. However, when mobile edge computing nodes are deployed near the edge of the Internet of Vehicles to bring users a good experience, more and more attacks on the Internet of Vehicles will follow. Distributed denial of service attacks are violent and direct, but they cause huge damage to the car networking system. Aiming at the problem that the existing DDoS attack detection methods are not suitable for the Internet of Vehicles environment and have hysteresis problems. this paper proposes a detection method based on LSTM neural network in the mobile edge computing environment of the Internet of Vehicles. this method can detect the current network traffic according to the LSTM prediction model, compare the current data with the prediction data of the LSTM detection model, and judge whether the car networking system is under DDOS attack according to the threshold value; in addition, the method can also continuously learn historical information and build local knowledge the database is continuously detected according to the attack signature database of the knowledge base.

关键词： LSTM mobile edge computing attack signature database DDoS Internet of Vehicles

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