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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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A Blockchain-based and Privacy-Protected Method for Sharing of BIM big data 7

A Blockchain-based and Privacy-Protected Method for Sharing ...

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7th international conference on Cloud computing and big data Analytics, ICCCBDA 2022

作者： Wang, Hongwei Hao, Xiaohan Yin, Lian Gong, Peisong Xiong, Feng Ren, Wei Wuhan Municipal Road and Bridge Co. Ltd Wuhan430050 China School of Software University of Technology Sydney UltimoNSW2007 Australia School of Computer Science China University of Geosciences Wuhan430074 China School of Economics and Management China University of Geosciences Wuhan430074 China School of Business Administration Zhongnan University of Economics and Law Wuhan430073 China Hubei Key Laboratory of Intelligent Geo-Information Processing Wuhan430074 China

ISBN: (纸本)9781665487115

Currently, cloud computing and big data are largely applied in smart construction, or so-called industrial Internet of Things 4.0. Building Information Model (BIM) performs as an elemental information and data unit, which is extensively employed in entire construction processes (lifespan) and inter-Acted with various entities including investors, employers, design institutes, construction companies, and monitors. They thus can achieve quantitative computing, measurement, and managements by sharing BIM data. The accumulation of BIM data will finally approach to a big data for construction intelligence. However, sharing BIM big data may be subtle in terms of privacy leakage, since BIM data may enclose the critical infrastructure information, homeland security data, structure parameters, and design intellectual property. It thus is of urgent importance to protect privacy in the BIM data sharing. In this paper, we propose a blockchain based method to protect data privacy in BIM data sharing, which can be applied for guaranteeing the information security in next generation industrial Internet of Things for smart construction. © 2022 IEEE.

关键词： data privacy Cloud computing Computational modeling Information security big data data models Blockchains

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3D Gaze Estimation via Binocular Disparity and Feature Refinement 10

3D Gaze Estimation via Binocular Disparity and Feature Refin...

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10th international conference on big data computing and Communications, bigCOM 2024

作者： Wang, Chengxin Chen, Qiuxia Tian, Ying Yang, Jinfeng School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan China Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong-Macao Greater Bay Area Shenzhen Polytechnic Shenzhen China

ISBN: (纸本)9798331509538

The eyes are the windows to the soul and are crucial for studying human behavior. Therefore, gaze estimation has attracted much attention in the field of computer vision. In recent years, convolutional neural networks have driven significant progress in gaze estimation research. Despite the remarkable achievements of gaze technology based on full-face images, the inability to obtain full-face images in specific scenarios makes research based on eye images particularly important. This paper proposes a three-dimensional gaze estimation model that takes binocular images as input, using VGG16 as the backbone network for feature extraction. To enhance the feature extraction capability, we have embedded channel attention and spatial attention mechanisms. Meanwhile, to improve the stability of gaze estimation, we classify real gaze angles. First, we perform a preliminary screening of gaze direction through a classification task, and then perform linear regression with the true angle. Finally, we optimize gaze features using binocular vision differences to finetune the gaze estimator. Experiments have shown that our method performs well on three public datasets. © 2024 IEEE.

关键词： Convolutional neural networks

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Research on Power Grid Condition Monitoring Method Based on big data

Research on Power Grid Condition Monitoring Method Based on ...

引用

2022 international conference on Artificial intelligence, Information Processing and Cloud computing, AIIPCC 2022

作者： Jian, Yanhong Zhang, Haifeng Wang, Honggang Ma, Hanmei Big Data Center of State Grid Corporation of China China

ISBN: (纸本)9781665462877

With the continuous development of social economy, the requirements of the society for the continuity and stability of power grid operation are also constantly improving. As a new type of intelligent power transmission medium, intelligent power grid can effectively improve the monitoring and management effect of power grid and ensure the continuous, safe and stable operation of power network. Under this background, in order to meet the requirements of power grid condition detection and fault analysis, combined with the characteristics of smart grid architecture, this paper will propose a power grid condition monitoring method based on big data analysis technology. This method mainly includes four aspects: data preprocessing, data fusion, data analysis and state visualization, and fault determination and processing. Finally, in order to test the effectiveness of the power grid condition monitoring method, this method is applied to engineering practice, and it is confirmed that the power grid condition monitoring method based on big data can realize the intelligent monitoring of power grid condition and the rapid judgment and treatment of abnormal power grid operation. This can provide support for ensuring the stable operation of smart grid and promoting the intelligent, automatic and information development of power grid. © 2022 IEEE.

关键词： big data

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Applications of Artificial intelligence and big data for Strengthening the Role of intelligence in Human Security 8

Applications of Artificial Intelligence and Big Data for Str...

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

作者： Mubarok, Ahmad Shahrul Susandi, Armi Mantoro, Teddy State Intelligence College Medical Intelligence Post-Graduate Program Bogor Indonesia Sampoerna University Media-Tech Lab Departement of Computer Science Jakarta Indonesia

ISBN: (纸本)9781665453899

The state, through the government, should ensure national security and stability through the policies taken. For this reason, fast and accurate information and data are needed to form the basis for policymaking. intelligence actors have an essential role in gathering information to identify and prevent threats within and outside the country. Technological advances affect changes in threats and increase the classification of these threats. Covid-19 is a real example of the threat in this era because almost all countries feel its impact. In addition to affecting health, the Covid-19 pandemic also impacts the global economic sector. The economic impact is felt by small and medium industries, goods and services products, and also the tourism sector. The method that is used in this study is a literature review from various national and international journals. AI and big data can be used to track viruses in real time, collect adequate public health data, and integrate vaccine use. Also, AI and big data can provide local decision and policy-makers with informed, evidence-based predictions. the threat of the Covid-19 pandemic and other infectious diseases that disrupt public health and have a broad impact must be anticipated and addressed in order to achieve the safety and existence of the nation and state. The author wants to emphasize the importance of the role of intelligence in anticipating threats from the visible to the invisible. © 2022 IEEE.

关键词： Artificial intelligence

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Application of Soft computing Technique based on ANN Model Prediction in Diverse Area of Mining Blasting Operations 5

Application of Soft Computing Technique based on ANN Model P...

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5th international conference on Artificial intelligence, big data, computing and data Communication Systems (ICABCD)

作者： Gidiagba, Joachim Osheyor Tartibu, Lagouge Okwu, Modestus O. Univ Johannesburg Dept Mech & Ind Engn Johannesburg South Africa

ISBN: (数字)9781665484220

ISBN: (纸本)9781665484220

The mining industry is a big business globally, blasting is carried out with high explosive energy for massive rock disintegration. South Africa as a country makes a significant contribution to mining in terms of GDP. For a competitive mining industry to be achieved in South Africa and globally, there is a need for increased efficiency in blasting operations, optimization of process parameters, and others. Creative algorithm is required as a computing technique that plays a quintessential role in environmental analysis, exploration, and exploitation process. It has been observed in recent times that one of the major challenges of this industry is the problem of uncertainty which exist because of the nature of the sub-surface during blasting operations. This study makes contribution in that direction. Firstly, a detailed study on relevant areas of application of ANN in mining operation was exposed, focusing on rock fragmentation;blast-induced ground vibration and peak-particle velocity;blast-induced air-blast;cost analysis, and equipment selection during blasting. Secondly, the ANN model was applied to achieve the optimal results using dataset obtained during blasting operations. 70% of the dataset was sectioned for training and 30% for testing and validation. The statistical indicators produced highly satisfactory results. It was concluded that the ANN model is a suitable technique for unraveling the problem of uncertainties in diverse areas of mining operations.

关键词： Artificial Neural Network Mining Operation Blasting Operation Ground Vibration

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2nd international Workshop on big data driven Edge Cloud Services, BECS 2022, 1st international Workshop on the Semantic WEb of Everything, SWEET 2022 and 1st international Workshop on Web Applications for Life Sciences, WALS 2022 held in conjunction with 22nd international conference on Web Engineering, ICWE 2022

2nd International Workshop on Big Data driven Edge Cloud Ser...

引用

2nd international Workshop on big data driven Edge Cloud Services, BECS 2022, 1st international Workshop on the Semantic WEb of Everything, SWEET 2022 and 1st international Workshop on Web Applications for Life Sciences, WALS 2022 held in conjunction with 22nd international conference on Web Engineering, ICWE 2022

ISBN: (纸本)9783031253799

The proceedings contain 15 papers. The special focus in this conference is on big data driven Edge Cloud Services. The topics include: Semantic Matchmaking for Argumentative intelligence in Ubiquitous computing;smart District 4.0 Project: Validation of Results and Exploitation Perspectives;citrusGenome: A Bioinformatics Tool to Characterize, Visualize, and Explore Large Citrus Variant datasets;the Laniakea Dashboard and Storage Encryption Components: A Foundation for Developing On-Demand Cloud Services for Life Science;Integration and Visual Analysis of Biomolecular Networks Through UNIPred-Web;a Novel Hybrid Approach for Localization in Wireless Sensor Networks;an Empirical Analysis on Just-In-Time Defect Prediction Models for Self-driving Software Systems;knowledge Sharing in Proactive WoT Multi-environment Models;multivariate Time Series Anomaly Detection Based on Reconstructed Differences Using Graph Attention Networks;a Decentralized Environment for Biomedical Semantic Content Authoring and Publishing;AI for Food Waste Reduction in Smart Homes;Cowl: A Lightweight OWL Library for the Semantic Web of Everything;features and Capabilities of a Blockchain-Based Ridesharing Enhanced with Semantics.

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The Design of Computer Network based Intelligent Tourism System 6

The Design of Computer Network based Intelligent Tourism Sys...

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6th international conference on Intelligent computing and Control Systems, ICICCS 2022

作者： An, Ying Jiangsu Maritime Institute Nanjing210000 China

ISBN: (纸本)9781665410359

As the tourism industry enters the era of "tourism + Internet", the tourism industry is showing a trend of high-quality development. The integration of cultural and tourism forms an industrial linkage, and e-commerce technology has become an important path for rapid development. Today, when network informatization, big data, and tourism e-commerce are all the rage, scenic spots, as service providers, must promote their integration with information technology and Internet technology, and transform from a traditional service industry to a modern smart service industry. This paper studies the design of modern tourism intelligent system based on computer network technology, and proposes a system for artificial intelligence to guide tourism. © 2022 IEEE.

关键词： big data

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Research on Knowledge Service System of Land big data Based on Knowledge Graph

Research on Knowledge Service System of Land Big Data Based ...

引用

2022 international conference on Cloud computing, big data and Internet of Things, 3CBIT 2022

作者： Liu, Chang Guo, Wei Guo, Wang Sun, Xiang Peng, Cheng Beijing Academy of Agriculture and Forestry Sciences Information Technology Research Center Beijing China Ministry of Agriculture and Rural Affairs Key Laboratory of Digital Village Technology Beijing China

ISBN: (纸本)9781665492256

In the context of the rapid development of artificial intelligence and big data technology, the efficient use and integration of data are essential. As a tool for information carrying and knowledge reasoning in the context of big data, a knowledge graph helps to improve the utilization of land resources in villages and towns and the accurate supply of knowledge services. To effectively solve services such as land cultivation guidance, business guidance, and policy consultation, a land big data knowledge service system based on a knowledge graph is proposed. The construction framework and content of the land big data knowledge service system are studied from the technical and functional levels and applied to the land knowledge service platform to provide service functions such as intelligent retrieval, online consultation, land purchase and sale, and personalized recommendation. This service system is expected to provide reference and reference for the research, development, and technological innovation of villages and towns in the era of big data. © 2022 IEEE.

关键词： big data

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Multimodal Learning Approach for Multi-Topic Twitter Summarization 7

Multimodal Learning Approach for Multi-Topic Twitter Summari...

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7th international conference on Cloud computing and big data Analytics, ICCCBDA 2022

作者： Cao, Yangyang Wu, Yanmin Qi, Jinli Chen, Zizhong Chongqing Key Lab. of Compl. Intelligence Chongqing University of Posts and Telecommunications Chongqing400065 China ChongQing College of Electronic Engineering Department of Artificial Intelligence and Big Data ChongQing401331 China University of California Riverside Department of Computer Science and Engineering RiversideCA United States

ISBN: (纸本)9781665487115

Twitter summary is designed to filter out the content summary from lots of noisy tweets, which can be used for Twitter search, public opinion analysis, hot topic discovery, etc. But the existing Twitter summary methods mostly focus on individual topics or hot events, and there are few studies on Twitter summary with multi-Topic posts. For the sake of resolve this problem, we propose a Twitter summary method based on social network information and manifold learning, which can extract tweets covering multiple topics, and better integrates the topic information and structural information of the tweets. First, the multi-modal manifold learning method is improved, and the social network information is integrated. Second, in order to test the relevance of the tweet summary and the topic, a test method of topic membership is designed. What's more, due to the lack of evaluation data sets, the author built a manual evaluation dataset. Our experiments on large-scale real tweets demonstrate the effectiveness of our framework. © 2022 IEEE.

关键词： Cloud computing Social networking (online) Blogs Manuals big data Manifold learning Noise measurement

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Spiking Spatio-Temporal Channle 7

Spiking Spatio-Temporal Channle

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7th international conference on Cloud computing and big data Analytics, ICCCBDA 2022

作者： Mo, Yan Yang, Yuanlei Duan, Shukai Wang, Lidan Southwest University College of Artificial Intelligence ChongQing China

ISBN: (纸本)9781665487115

Spiking neural network is known as the third generation artificial neural network because of its rich temporal and spatial dynamic characteristics and reasonable bionic properties. It has great prospects in the fields of artificial intelligence and brain like neural computing. However, at present, the accuracy of Spiking neural network in text classification and image recognition is not satisfactory. Researchers hope to improve the performance of spiking networks from all aspects. Although the previous SNNS tried their best to mine the characteristic information of time and space, they focused on the encoding and expression of information. In this paper, a novel concept of Spiking Spatio-Temporal Channel is proposed. The time dimension is introduced in the direction of information transmission, which means the connection between neurons is expanded. Combined with the popular surrogate gradient method, a concise and beautiful spiking neural network training algorithm is deduced. Finally, it is verified that without adding additional neuron overhead and affecting the training and inference speed, after introducing the Spiking Spatio-Temporal Channel, the trainable parameters of the new spiking neural network are increased, the convergence speed is improved, and the recognition accuracy get better performance. © 2022 IEEE.

关键词： Training Gradient methods Image recognition Neurons Text categorization Information processing Inference algorithms

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