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检索条件"任意字段=5th IEEE International Conference on Big Data Analytics, ICBDA 2020"

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2020 5th ieee international conference on big data analytics, icbda 2020

2020 5th IEEE International Conference on Big Data Analytics...

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5th ieee international conference on big data analytics, icbda 2020

ISBN: (纸本)9781728141114

the proceedings contain 69 papers. the topics discussed include: deep reinforcement learning approach for autonomous agents in consumercentric electricity market;visual analysis of Chinese education big data research in recent five years;rankings correlation study-brand search volume vs. brand sales volume;the online attention of class 5A scenic spots in Jiangsu Province, China: a big data analysis of based on Baidu index;design method of front-end componentized architecture for big data visualization large-screen;data factory: an efficient data analysis solution in the era of big data;and security analysis of power system user behavior in big data based on comparative of neural network methods.

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2020 ieee 5th international conference on Cloud Computing and big data analytics, ICCCBDA 2020

2020 IEEE 5th International Conference on Cloud Computing an...

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5th ieee international conference on Cloud Computing and big data analytics, ICCCBDA 2020

ISBN: (纸本)9781728160245

the proceedings contain 103 papers. the topics discussed include: online purchase behavior prediction and analysis using ensemble learning;research on deep learning based code generation from natural language description;power consumption forecast of energy-intensive enterprises based on power marketing business data;a fast and accurate face alignment method based on deep learning on mobile device;time series segmentation of flood flow based on bi-LG-LSTM neural network;analysis of vessel anomalous behavior based on Bayesian recurrent neural network;operation framework of the command information system based on big data analysis;and a cooperative vehicles selection method based on privacy-preserving driving routes comparison for urban scenarios.

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Proceedings - ieee 18th international conference on Dependable, Autonomic and Secure Computing, ieee 18th international conference on Pervasive Intelligence and Computing, ieee 6th international conference on Cloud and big data Computing and ieee 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020

Proceedings - IEEE 18th International Conference on Dependab...

引用

18th ieee international conference on Dependable, Autonomic and Secure Computing, 18th ieee international conference on Pervasive Intelligence and Computing, 6th ieee international conference on Cloud and big data Computing and 5th ieee Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020

ISBN: (纸本)9781728166094

the proceedings contain 103 papers. the topics discussed include: artificial intelligence cyber security strategy;legal regulation of cyberbullying — from a Chinese perspective;cyber-based intelligent route planning with multi-constraints;a neural embedding for source code: security analysis and CWE lists;feature extraction approach to unearth domain generating algorithms (DGAs);a survey of key issues in UAV data collection in the Internet of things;a new dynamic conditional proxy broadcast re-encryption scheme for cloud storage and sharing;efficiency optimization in supply chain using RFID technology;and executing complex calculations in the cloud to enable real-time data processing.

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Distributed or Centralized: An Experimental Study on Spatial database Systems for Processing big Trajectory data 8

Distributed or Centralized: An Experimental Study on Spatial...

引用

ieee 8th international conference on big data analytics (icbda)

作者： Xiong, Shuyi Ouyang, Xue Xiong, Wei NUDT Coll Elect Sci Changsha Hunan Peoples R China Natl Univ Def Technol NUDT Coll Elect Sci Changsha Hunan Peoples R China

ISBN: (纸本)9798350310764

the continuous development of GPS-enabled equipments and location-based services has brought new challenges to the storage and management of trajectory big data. Traditional database system such as PostgreSQL/PostGIS to cope with this demand. Meanwhile, distributed trajectory management systems based on NoSQL have attracted increasing attention from both industry and acdemia. However, to the best of our knowledge, there are not many reseach discussing the comparision of these systems. this paper aiming at filling this gap by comparing the performance of the representitive relational database component PostGIS and the distributed NoSQL data management system GeoMesa in various range query and multi concurrent access scenarios through experimental analysis. the experimental results show that GeoMesa outperforms the relational spatial database component PostGIS in the large number of access results and multi-user access scenarios.

关键词： trajectory data management spatial NoSQL spatial database

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big data analytics Survey: Environment, Technologies, and Use Cases 5

Big Data Analytics Survey: Environment, Technologies, and Us...

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5th international conference on Smart Electronics and Communication, ICOSEC 2024

作者： Ramesh Babu, E. Kumar, M. Sunil Jawaharlal Nehru Technological University Dept. of Cse Ananthapuramu AP Anantapur India Dept. of Cse AP Tirupati India

ISBN: (纸本)9798331504403

In these days, massive amounts of data are generated by the latest technologies, sophisticated computing systems, and social media. these massive terabytes of data, whose is storage capacity is beyond the traditional databases and data processing applications is defined as big data. So, here for the problem of storing, processing & analyzing such a voluminous data requires latest technologies. Efficient technologies can utilize the data to look into the insights of data for decision making. the fundamental goal of the work is to examine the elements of big data, issues, different applications areas, and latest analytical tools. © 2024 ieee.

关键词： data analytics

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Risk Prediction in Financial Transactions Using IoT big data analytics 5

Risk Prediction in Financial Transactions Using IoT Big Data...

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5th international conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Chidambaranathan, P. Muthupriya, V. B.S. Abdur Rahman Crescent Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350379945

the Internet of things is a network of appliances and other items that can communicate and distribute data;as a result, Internet of things are equipped with actuators, sensors, microelectronics, software, and connections. IoT devices, to put simply, share data over wired or wireless networks. Inventions of IoT have endless possibilities that can make a huge difference in the world. IoT is having the most effect on business since has altered not just how various corporate processes are conducted, but also how the economy is managed. big data and IoT help optimize operations, reducing costs, enhancing productivity and improving lives. Globally, financial institutions and banks are coming up with fresh, creative approaches to quickly assimilate big data analytics for every step of the process in with the intention of maximizing efficiency. Numerous previous studies mostly concentrate on risk assessment along with big data analytics together in the banking industry;nevertheless, might not particularly address the difficulties posed by cross-border transactions. the purpose of the proposed study is to close this gap by focusing on the particulars and bringing up the approach of big data analytics for risk assessment in cross-border transactions. © 2024 ieee.

关键词： Microelectronics

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Proceedings - 2020 ieee 14th international conference on big data Science and Engineering, bigdataSE 2020

Proceedings - 2020 IEEE 14th International Conference on Big...

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14th ieee international conference on big data Science and Engineering, bigdataSE 2020

ISBN: (纸本)9781665403962

the proceedings contain 21 papers. the topics discussed include: policy enforcement for secure and trustworthy data sharing in multi-domain infrastructures;DP-AP: differential privacy-preserving affinity propagation clustering;side channel leakage alignment based on longest common subsequence;reputation-based trust: a robust mechanism for dynamic adaptive streaming over named data networking;web service composition sequence learning based on neural language networks;an improved RFID-based authentication protocol for rail transit;IoTDefender: a federated transfer learning intrusion detection framework for 5G IoT;real-time social media analytics with deep transformer language models: a big data approach;and a threat modelling approach to analyze and mitigate botnet attacks in smart home use case.

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Utilizing big data analytics for Social Media Insights 5

Utilizing Big Data Analytics for Social Media Insights

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5th international conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Vedhika Srinidhi, V.S. Sanjana, S. Rozario, Neo Joseph Dewan, Sia Gouthaman, P. School of Computing College of Engineering & Technology SRM Institute of Science and Technology Department of Networking and Communications Kattankulathur603203 India School of Computing Faculty of Engineering & Technology SRM Institute of Science and Technology Department of Networking and Communications Kattankulathur603203 India

ISBN: (纸本)9798331518097

big data analytics is a rapidly evolving field that offers profound insights into various sectors by enabling the analysis of massive and diverse datasets. this research paper focuses on the application of big data techniques to social media and airline networks, leveraging tools such as sentiment analysis, clustering, and data visualization to extract actionable information. the study analyses Twitter data to uncover public sentiment trends and classifies topics using advanced machine learning techniques. Furthermore, the research explores the use of clustering algorithms within the Hadoop ecosystem to process large-scale datasets efficiently. Insights from airline customer feedback and network planning data demonstrate how big data analytics can optimize operational efficiency and enhance customer satisfaction. Key findings include the identification of distinct sentiment patterns in social media data, the efficiency of novel clustering techniques in handling high-volume datasets, and the utility of advanced visualization methods to convey complex data. these results have significant implications for industries ranging from social media platforms to the airline sector, providing valuable tools for enhancing decision-making processes and improving user experiences across diverse domains. the study highlights the potential of big data analytics to drive innovation and operational excellence in dynamic environments. © 2024 ieee.

关键词： Airline networks big data analytics Clustering algorithms data visualization Sentiment analysis Social media

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Proceedings of the 14th IADIS international conference Computer Graphics, Visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and Proceedings of the 5th IADIS international conference big data analytics, data Mining and Computational Intelligence 2020, bigDaCI 2020 and Proceedings of the 9th IADIS international conference theory and Practice in Modern Computing 2020, TPMC 2020 - Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020

Proceedings of the 14th IADIS International Conference Compu...

引用

14th IADIS international conference Computer Graphics, Visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and 5th IADIS international conference big data analytics, data Mining and Computational Intelligence 2020, bigDaCI 2020 and 9th IADIS international conference theory and Practice in Modern Computing 2020, TPMC 2020, Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020

ISBN: (纸本)9789898704214

the proceedings contain 35 papers. the topics discussed include: data-driven approach for generating colormaps of scientific simulation data;a 3D-shockwave volume rendering algorithm based on feature boundary detection;using reorderable matrices to compare risk curves of representative models in oil reservoir development and management activities;laser spot detection and characteristic analysis in plasma interaction simulation;hybrid sort a pattern-focused matrix reordering approach based on classification;data interpolation based on contextual analysis for generating tomographic images in concrete specimen;graphical user interface personalization: user study of image frequency preferences;evaluation of color spaces for unsupervised and deep learning skin lesion segmentation;and repeated pattern extraction with knowledge-based attention and semantic embeddings.

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Harnessing the Power of Right data Over big data for Autonomous Driving using data analytics 5

Harnessing the Power of Right Data Over Big Data for Autonom...

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5th ieee international Transportation Electrification conference, ITEC-India 2023

作者： Selvaraj, Surendhar Banerjee, Jaydeep Continental Automotive India Data Solutions Bengaluru India

ISBN: (纸本)9798350337808

Autonomous Driving is becoming increasingly complex, requiring the continuous tuning of different perception models for a variety of road scenarios, from simple to critical. To achieve the best performance, 'data' plays a crucial role in every stage of product development, simulation, and validation of models for autonomous vehicles. Is 'big data' (petabytes) alone sufficient to attain better performance? Or it is important to find the 'right data' for the 'right use cases' at the 'right time' over 'big data'. this paper represents the importance of 'data analytics' for autonomous driving where 'right data' is more important. In the context of autonomous driving, data analytics can be applied at two levels: active analytics (techniques to collect the right data for the right use cases - more direct and saves cost) and passive analytics (techniques to find the right data among petabytes of collected data - incurs more costs and time). © 2023 ieee.

关键词： Autonomous vehicles

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