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检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

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Prevention of Misuse of Information Technology in the Health Industry 8

Prevention of Misuse of Information Technology in the Health...

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8th IEEE international conference on computing, Engineering and Design, ICCED 2022

作者： Ahmad, Hastanto Januar Mantoro, Teddy Yulivan, Ivan State Intelligence College Medical Intelligence Postgraduate Program Bogor Indonesia Sampoerna University and State Intelligence College Media-Tech Lab Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9781665453899

Technological advances in the field of digitalization and networks of information have made the world enter the industrial revolution 4.0 including in the health and medical sector. This revolution is marked by the easy exchange of information in a short amount of time without being limited by geographical constraints and the shift from paper-based documents to digital. The health sector has also begun to adopt the 4.0 revolution by making health services more accessible to the public such as online medical applications, the use of electronic medical records, and the use of big data to personalize medical therapy for sick people. Even though the use of this information technology has a lot of benefits, there is also potential to be misused such as the purchase of dangerous medicines and leakage of patient's medical data also inadequate support from telemedical services due to a lack of guidance for personnel which has the potential to harm both physically and materially. Indonesia currently does not have a defense mechanism and regulations to protect its citizen from the misuse of information technology in the health industry. Systematic efforts are needed so that the use of information technology can run properly and safely. There need to be some measures to prevent the unlawful use of health information technology such as strict regulation and monitoring, defense against cyber hacking and leakage, also adequate training for the operators of health services in using the technology © 2022 IEEE.

关键词： Medical applications

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A Solution of Stream computing Processing Real-time Service Based on flume 22

A Solution of Stream Computing Processing Real-time Service ...

引用

5th international conference on big data Technologies, ICBDT 2022

作者： Shao, Guiwei Wang, Lili Yang, Xiaowei Tu, Shengxia Liao, Denghong Liu, Songling School of Artificial Intelligence and Big Data Hefei University Hefei China An Hui Shujia Information Technologies Co. Ltd. Hefei China Huawei Technologies Co. Ltd. Shenzhen China

ISBN: (纸本)9781450396875

With the development of computer network, the demand of real-time data processing is growing rapidly, and various processing schemes are *** problem that the demand of various industries, enterprises and institutions for real-time data processing, and its current project development methods and supporting tools are not compatible is gradually highlighted. Therefore, through flume technology, with the use of Ali cloud products,this paper achieve a real-time business processing *** the direction of data stream - data source, data collection, cache queue, real-time processing calculation and data display four directions. © 2022 ACM.

关键词： Information services

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Research on big data Prediction Algorithm of Automobile Weatherability Based on Nested Network

Research on Big Data Prediction Algorithm of Automobile Weat...

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2021 international conference on Computer Graphics, Artificial intelligence, and data Processing, ICCAID 2021

作者： Zhang, Xiaodong Wang, Haixin Liu, Xiongjun Qi, Li Wang, Jun Li, Huai Chen, Xinxin Beijing Jinghang Research Institute of Computing and Communication China China National Electric Apparatus Research Institute Co. Ltd China

ISBN: (数字)9781510652170

ISBN: (纸本)9781510652163

In the field of passenger cars, the weather resistance of vehicles affects the appearance, interior decoration and user experience of vehicles. At present, many vehicles have undergone automobile weather resistance tests, and a large amount of data has been accumulated. How to use big data analysis algorithms to get the vehicle temperature value, so as to quickly predict the temperature value of auto parts based on atmospheric environmental data, so as to obtain the environmental equivalent damage stress. Major automobile manufacturers and automobile weather resistance test institutions urgently need to solve problems. This paper proposes a vehicle weather resistance temperature prediction algorithm based on deep learning. By constructing a nested network that integrates long and short-term deep learning networks and full feature extraction networks. Nested network realize the prediction of the temperature of the vehicle measurement point, and obtain the predicted value of the vehicle measurement point temperature. The deep learning pre-diction model improves the efficiency of vehicle weather resistance analysis, shortens the weather resistance test cycle, and brings benefits to automobile manufacturers. © 2022 SPIE.

关键词： Feature extraction

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Accuracy Indoor Localization Based on Fuzzy Transfer Learning Model 19

Accuracy Indoor Localization Based on Fuzzy Transfer Learnin...

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2022 IEEE SmartWorld, 19th IEEE international conference on Ubiquitous intelligence and computing, 2022 IEEE international conference on Autonomous and Trusted Vehicles conference, 22nd IEEE international conference on Scalable computing and Communications, 2022 IEEE international conference on Digital Twin, 8th IEEE international conference on Privacy computing and 2022 IEEE international conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Wu, Sheng Ji, Yanhui Zhu, Licai Zhao, Liang Yang, Hao Nanjing Tech University Yancheng Teachers University Nanjing China Shenyang Aerospace University Shenyang China Yancheng Teachers University Yancheng China University of Electronic Science and Technology of China Network and Data Security Key Laboratory of Sichuan Province Chengdu China

ISBN: (纸本)9798350346558

Location-based services greatly facilitate people's daily life, which puts forward higher requirements for the location calculation of target objects in different environments. Since the fingerprint positioning method does not require additional special equipment and easy to implement, it has become one of the most attractive solutions. In order to ensure the positioning accuracy, this method requires complete sampling of the fingerprints of the positioning area, so a lot of sampling costs are required. In particular, when sampling buildings with multiple floors, the labor and time of the entire sampling process will increase dramatically. At the same time, certain floors or rooms may not be allowed to open, so their fingerprints cannot be sampled. In fact, the floor structures of buildings are mostly similar or the same, such as office buildings, hotels. Therefore, this paper proposes a fuzzy transfer learning model and builds the corresponding prototype system FTLoc. On the premise of ensuring the positioning accuracy of different floors, the system greatly reduces the sampling cost of the entire building. First, for the complete fingerprint data (source domain) of a certain floor, we mine the fingerprint features fine-grained to generate a short-term feature set for each sampling point. Then, according to the sparsity and timing of short-term features, we design an optimized SELSTM, and obtain an effective localization model as the PreModel for transfer learning. Finally, fuzzy clustering is used to add category labels to the source domain data and target domain data, and input them into PreModel to realize the localization model transfer, so as to avoid their data distribution differences affecting the transfer effect as much as possible. FTLoc is fully validated in a multi-storey building. According to the experimental results, when using the first floor sampling data as the source domain, the errors of the FTLoc system on the adjacent floor (second floor) are

关键词： Floors

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An Improved Visual Recognition Model of Interference Noise Image 9

An Improved Visual Recognition Model of Interference Noise I...

引用

9th international conference on Dependable Systems and Their Applications, DSA 2022

作者： Hsu, Tse-Chuan Chu, William Cheng-Chung Chang, Dong-Meau Soochow University Dept. of Computer Science & Information Management Taipei Taiwan Tunghai University Dept. of Computer Science Taichung Taiwan School of Computer Science and Intelligence Education Lingnan Normal University Guangdong Zhanjiang China

ISBN: (数字)9781665488778

ISBN: (纸本)9781665488778

Edge computing can take advantage of the convenience of a relatively close test environment to quickly obtain on-site environmental data. Image data collection can be quickly acquired and can be repeatedly learned and analyzed in big data. In this study, establish an edge computing inspection mechanism, through structural similarity index measure (SSIM) image recognition, first compare the sampling target data to analyze whether it is the same as the previous sampling. Because of the difference in image value changes after flickering during the image sampling process, when the digital image comparison is completed, the image data are sampled and compared through the hierarchical distribution verification technology, and then analyzed. The image visual comparison model proposed in the research can improve the image comparison accuracy by 4%∼5% and optimize the calculation efficiency through experimental verification. © 2022 IEEE.

关键词： Image recognition

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Fbereum: A Novel Distributed Ledger Technology System 7th

Fbereum: A Novel Distributed Ledger Technology System

引用

7th international conference on Smart computing and Communication, SmartCom 2022

作者： Yu, Dylan Yang, Ethan Shen, Alissa Tamir, Dan Rishe, Naphtali Dulles High School Sugar LandTX United States Westwood High School AustinTX United States St. Stephen’s Episcopal School AustinTX United States Texas State University San MarcosTX United States Florida International University MiamiFL United States

ISBN: (纸本)9783031281235

Over the past several years, due to the progression toward data-driven scientific disciplines, the field of big data has gained significant importance. These developments pose certain challenges in the area of efficient, effective, and secure management and transmission of digital information. This paper presents and evaluates a novel Distributed Ledger Technology (DLT) system, Fibereum, in a variety of use-cases, including a DLT-based system for big data exchange, as well as the fungible and non-fungible exchange of artwork, goods, commodities, and digital currency. Fibereum’s innovations include the application of non-linear data structures and a new concept of Lazy Verification. We demonstrate the benefits of these novel features for DLT system applications’ cost performance and their added resilience towards cyber-attacks via the consideration of several use cases. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cybersecurity

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E-commerce big data Classification and Mining Algorithm Based on Artificial intelligence 11th

E-commerce Big Data Classification and Mining Algorithm Base...

引用

11th international conference on Frontier computing, FC 2021

作者： Chen, Hongfeng Jiangxi Vocational Technical College of Industry and Trade 699 Jiayan Road Jiangxi Nanchang city330038 China

ISBN: (纸本)9789811680519

Some languages have been applied to people’s daily life and learning, which has a profound impact on and learning, and also profound impact on the development of Chinese language and literature teaching. Therefore, on the basis of expounding the characteristics of network language, this paper analyzes from both negative and positive aspects, and makes a strategic analysis on how to better literature with the help of network language, so as to better promote education. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： big data

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Research on the big data collection mode of consumers for innovative products and brand value factors 5

Research on the big data collection mode of consumers for in...

引用

5th Artificial intelligence and Cloud computing conference, AICCC 2022

作者： Yu, Xiaohong Huang, Yu-Che Economic and Trade College Shandong Management University Jinan China Department of Industrial Design Chaoyang University of Technology Taichung Taiwan

ISBN: (纸本)9781450398749

The collection of machine learning and big data can help us understand consumers more clearly. However, in today's increasingly serious product homogeneity, consumers' perception of brands and product demands cannot be really clearly analyzed. Although the brand has become the basis for the image, popularity and reputation of the enterprise. However, it also reflects that the brand value will develop wrong products due to a temporary data misjudgment;therefore, building brand influence has become the goal of reducing the depth of the company's operations, and its evaluation results are expected to help the industry improve itself and provide the main reference for brand strategy. Through structural reconstruction and value chain inductive analysis, this research will provide the core value of products that should be paid attention to when designing and positioning products in the future and what should be paid attention to when collecting big data, and should be able to fully comply with the positioning strategy of the entire product brand, so as to avoid causing brand damage. value. and consumer perception. Through the construction of these data, market-related researchers can also focus on the balance and value chain between brand value and product positioning through this research, and provide reference and product development positioning for relevant education researchers or market data collectors. © 2022 ACM.

关键词： big data

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A Dynamic Spatial-Temporal Attention Ensemble Model for Traffic Flow Prediction 3

A Dynamic Spatial-Temporal Attention Ensemble Model for Traf...

引用

3rd international conference on Artificial intelligence and Electromechanical Automation, AIEA 2022

作者： Zhang, Jiakun Yang, Guoyan School of Data Science and Technology Heilongjiang University Harbin150080 China School of Information and Communication Engineering Guangzhou Maritime University Guangzhou510725 China

ISBN: (纸本)9781510657281

With the advent of the era of big data, a large number of sensors are scattered on traffic roads, generating traffic flow data, posing huge challenges to traffic flow prediction. Therefore, capturing the spatial features of traffic flow data is greatly significant to improve the accuracy of traffic flow predicted models. Analysis of spatial and temporal characteristics of traffic flow data, this paper proposes a Spatial-Temporal Attention (MA-STLGAT) model to predict the traffic speed in the traffic network. The Graph Attention Network (GAT) assigns different weights to neighbor nodes to capture the dynamic topology structure. Learning the temporal correlation of traffic flow data through Long Short-Term Memory network (LSTM), and Multi-Head Attention is introduced to learn the contribution of nodes, improve the convergence speed and save computing costs. The experimental results on real data set PeMSD7 show that the predict performance of MA-STLGAT is better than other baseline models. © 2022 SPIE.

关键词： Long short-term memory

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Distributed Air Traffic Management Strategy Based on 5G Edge computing 24

Distributed Air Traffic Management Strategy Based on 5G Edge...

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4th international conference on big data, Artificial intelligence and Risk Management, ICBAR 2024

作者： Cao, Lei Tang, Tao Qin, Chao Yang, Molinna Zhao, Min Wu, Qinggang The Second Research Institute of Civil Aviation Administration of China Sichuan Chengdu China Civil Unmanned Aircraft Traffic Management Key Laboratory of Sichuan Province Sichuan Chengdu China Guizhou Air Traffic Management Sub Bureau CAAC Guizhou Guiyang China Guangzhou Baiyun International Airport Co. Ltd. Guangdong Guangzhou China

ISBN: (纸本)9798400709753

This paper introduces a distributed air traffic management (ATM) strategy for unmanned aerial vehicles (UAVs), leveraging 5G edge computing. It proposes integrating various computing layers - terminal, edge, and cloud - to handle the complexities of UAV operations in low-altitude urban airspace. The strategy focuses on enhancing safety, efficiency, and real-time data processing capabilities in UAV air traffic management. By leveraging the advanced capabilities of 5G technology and edge computing, the strategy aims to address the challenges of managing high-density UAV traffic, ensuring seamless and safe UAV operations in increasingly crowded urban airspace. © 2024 Copyright held by the owner/author(s).

关键词： 5G Edge computing Distributed Air Traffic Management Real-Time data Processing Unmanned Aerial Vehicles (UAVs)

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