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intelligent monitoring and simulation of the whole life cycle of coal mining process and water quantity and quality in coal and water coordinated development under large data

Intelligent monitoring and simulation of the whole life cycl...

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

作者： Zhang, Yu-zhe Wu, Xiong Zhu, Ge Wu, Chu Mu, Wen-ping Mei, Ao-shuang School of Water Resource and Environment China University of Geosciences Beijing100083 China

ISBN: (纸本)9789811525674

Coal is China’s main energy, and this situation in the future in a long period of time is unlikely to have fundamental changes. As an underground activity, coal mining inevitably causes local damage and pollution to underground water cut system due to improper application of coal mining technology. And a large number of mine drainage, not only need to spend a lot of drainage costs, increase the cost of coal production, but also waste very valuable water resources. In this paper, based on the water - coal, on the basis of coordination development, through big data analysis methods, proposes the establishment process of coal mining and mine water quality, and the whole life cycle of the coal - water coordination development precision control technology system, through a series of research on the laws of the evolution of time and space and nonlinear multiobjective model building and simulation development plan, research and development of the evaluation method of mine water resource utilization efficiency and benefit, help to realize the coordinated development of the coal - water control in whole life cycle of technology. So as to realize the exploitation and utilization of mine drainage and turn waste into treasure, it can not only relieve the tight situation of water supply in coal mines, but also reduce the environmental pollution caused by coal mining to the mining areas and surrounding cities, and realize the unity of economic and environmental benefits. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Coal

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Creative Thinking Design of Visual Communication Under Big data

Creative Thinking Design of Visual Communication Under Big D...

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international conference on Cyber Security Intelligence and analytics, CSIA 2020

作者： Zhan, Yihong Jilin Engineering Normal University ChangchunJilin130052 China

ISBN: (纸本)9783030433055

With the continuous development of digitalization and informatization in the 21st century, we have ushered in the big data era. The advent of the big data era has brought about subversive changes in many fields. With the tide of the big data era, how visual communication design can more accurately and intuitively convey the information content to be expressed and can stand out among many visual communication media is the concern of every designer. Only when visual communication design is creative can the information receiver be impressed with the visual design content, so creative thinking is particularly important in visual communication design. This paper analyzes the opportunities and challenges faced by visual communication design under big data environment in detail, and puts forward several strategies for developing creative thinking in visual communication design according to the current situation. © Springer Nature Switzerland AG 2020.

关键词： Big data

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A scalable heterogeneous big data framework for e-learning systems

A scalable heterogeneous big data framework for e-learning s...

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2020 international conference on Artificial Intelligence, Big data, computing and data Communication Systems, icABCD 2020

作者： Otoo-Arthur, David van Zyl, Terence L. School of Computer Science and Applied Mathematics University of the Witwatersrand Johannesburg South Africa

ISBN: (纸本)9781728167701

—The adoption of e-learning systems in higher education is a remarkable phenomenon that has redefined teaching and learning. Initially, it was proposed to allow people to learn for personal accomplishment without physically attending any traditional university or academic settings. While these systems continue to provide an efficient and flexible approach for teaching and learning, the rapid integration of ICTs and the expansion of data from these systems remain much concern to the education community. In this study, we propose a smart and secure data flow architectural framework for e-learning that uses a rich set of big data tools within a distributed and parallel analysis platform. Reference Model of Open Distributed Processing (RM-ODP) reference model guided the development of this Big data framework for e-learning analytics. Using the RM-ODP model as a benchmark, we classify the educational institution’s architecture in terms of existing elements, functions and processes to understand stakeholders’ views for the development of the framework. Our approach uses an existing distributed computing environment and of fers an adaptable standard framework to improve the data acquisition, storage, processing, analysis, security and virtualization for e-learning systems. We implement a scalable and adaptable big data framework for e-learning (BiDeL) and point out how big data concept could integrate into online learning systems to improve teaching and learning in higher education using Apache Spark as a case. The proposed framework was applied to both batch and streaming dataset of students online activities on moodle LMSs. BiDel framework performance shows improved data integration and data governance. This big data framework and the general view of the current state of the art in "big data" technologies will serve as a guide for the creation of e-learning systems, which create new value from existing but underused data. The acquired value will provide decision-makers i

关键词： data acquisition

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Comparative Analysis of Time Series databases in the Context of Edge computing for Low Power Sensor Networks 20th

Comparative Analysis of Time Series Databases in the Context...

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20th Annual international conference on Computational Science (ICCS)

作者： Grzesik, Piotr Mrozek, Dariusz Silesian Tech Univ Dept Appl Informat Ul Akad 16 PL-44100 Gliwice Poland

ISBN: (纸本)9783030867973;9783030504250

Selection of an appropriate database system for edge IoT devices is one of the essential elements that determine efficient edge-based data analysis in low power wireless sensor networks. This paper presents a comparative analysis of time series databases in the context of edge computing for IoT and smart Systems. The research focuses on the performance comparison between three time-series databases: TimescaleDB, InfluxDB, Riak TS, as well as two relational databases, PostgreSQL and SQLite. All selected solutions were tested while being deployed on a single-board computer, Raspberry Pi. For each of them, the database schema was designed, based on a data model representing sensor readings and their corresponding timestamps. For performance testing, we developed a small application that was able to simulate insertion and querying operations. The results of the experiments showed that for presented scenarios of reading data, PostgreSQL and InfluxDB emerged as the most performing solutions. For tested insertion scenarios, PostgreSQL turned out to be the fastest. Carried out experiments also proved that low-cost, single-board computers such as Raspberry Pi can be used as small-scale data aggregation nodes on edge device in low power wireless sensor networks, that often serve as a base for IoT-based smart systems.

关键词： Time series PostgreSQL TimescaleDB InfluxDB Edge computing Edge analytics Raspberry Pi Riak TS SQLite

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Application research of big data technology in cross-border e-commerce store operation

Application research of big data technology in cross-border ...

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

作者： Feng, Zhitan School of Commercial Nantong Institute of Technology NantongJiangsu226002 China

ISBN: (纸本)9789811525674

The development of the Internet has brought rapid development of e-commerce in China, while traditional foreign trade transactions have encountered new opportunities and challenges. Cross-border e-commerce has flourished in China. This model changes the product sales model and sales targets. More extensive, involving more technology and people. However, in the process of cross-border e-commerce development, enterprise stores are faced with problems such as product selection and construction, attracting traffic, store maintenance and cross-border logistics and distribution. Based on the analysis of the problem, this paper deals with various aspects from the perspective of big data technology. In the near future, big data technology will be more deeply applied in the cross-border field. This kind of application will face greater pressure on enterprises. As long as the data analysis is continuously improved and the essence of data analysis is achieved, accurate customer sales can be achieved. In order to ensure the long-term development of the store. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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An Integrated Technique to Ensure Confidentiality and Integrity in data Transmission Through the Strongest and Authentic Hotspot Selection Mechanism 3rd

An Integrated Technique to Ensure Confidentiality and Integr...

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

作者： Bhattacharjee, Shiladitya Chakkaravarthy, Divya Midhun Chakkaravarthy, Midhun Bin Ab Rahim, Lukman Univ Teknol PETRONAS High Performance Cloud Comp Ctr HPC3 Seri Iskandar Perak Darul Rid Malaysia Wisma Lincoln Fac Comp Sci & Multimedia Petaling Jaya Selangor Darul Malaysia

ISBN: (纸本)9789811393648;9789811393631

Wireless technology has consistently been a popular resolution for handling the growing demand of data receiving in mobile linkages as the availability of high-speed internet is increasing rapidly. Although, the legacy of such technology shortages of seamless inter-communication amid the wireless link as well as mobile cellular linkages on one individual pointer as well as among thewireless hotspots conversely. Subsequently, data confidentiality and integrity are also primary concerns in data transmission through any network. There can be various weak and strong hotspots, since it is also possible to have fake hotspot in any network. A number of researches have been conducted to ensure data security by selecting the strong and authentic hotspot in wireless network infrastructure. However, the present literature fails to offer any security mechanism that can select the strongest, authentic hotspot and secure data confidentiality as well as integrity at the same time. Hence, this research aims to build an integrated technique that can offer adequate level of data confidentiality and integrity along with the selection of a strongest and most authentic hotspot. The proposed integrated technique comprises a unique hotspot selection and a SDES-based authentication mechanism to establish a secure communication link by picking the strongest hotspot. It encrypts the input data with SDES to assure confidentiality and uses an idle error checking technique with a backup scheme for fortuitous information loss to protect data integrity during transmission. The experimental results show its superiority over other existing techniques by improving QoE demands and fairness matrices. It offers higher avalanche effect and entropy values which justify its capacity to offer adequate data confidentiality. The capacity to offer lower percentage of information loss proves its efficiency in offering data integrity.

关键词： Avalanche effect and entropy values Backup system for accidental data loss data confidentiality and integrity Strongest and authentic hotspot SDES-based authentication SNR and percentage of information loss QoE demands and fairness matrices

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3rd international conference on Advanced computing and intelligent Engineering, ICACIE 2018

3rd International Conference on Advanced Computing and Intel...

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3rd international conference on Advanced computing and intelligent Engineering, ICACIE 2018

ISBN: (纸本)9789811510809

The proceedings contain 54 papers. The special focus in this conference is on Advanced computing and intelligent Engineering. The topics include: Wavelet Transform Domain Methods for Resolution Enhancement of Satellite Images;improving Query Results in Ontology-Based Case-Based Reasoning by Dynamic Assignment of Feature Weights;a Survey on Representation for Itemsets in Association Rule Mining;efficient Clustering Using Nonnegative Matrix Factorization for Gene Expression dataset;design of Random Forest Algorithm Based Model for Tachycardia Detection;detection of Spam in YouTube Comments Using Different Classifiers;deep Learning Architectures for Named Entity Recognition: A Survey;effect of Familiarity on Recognition of Pleasant and Unpleasant Emotional States Induced by Hindi Music Videos;early Detection of Breast Cancer Using Support Vector Machine With Sequential Minimal Optimization;the Case Study of Brain Tumor data Analysis Using Stata and R;predictive data analytics for Breast Cancer Prognosis;a Semantic Approach of Building Dynamic Learner Profile Model Using WordNet;prioritizing Public Grievance Redressal Using Text Mining and Sentimental Analysis;an Automatic Summarizer for a Low-Resourced Language;printed Odia Symbols for Character Recognition: A database Study;importance of data Standardization Methods on Stock Indices Prediction Accuracy;Feature Relevance Analysis and Feature Reduction of UNSW NB-15 Using Neural Networks on MAMLS;video Summarization Based on Optical Flow;Decision Support System for Black Classification of Dental Images Using GIST Descriptors;clustering Performance Analysis;Pattern Analysis of Brain Functional Connectivity Parameters After Removal of Artifactual Motifs from EEG During Meditation;Hyper-heuristic Image Enhancement (HHIE): A Reinforcement Learning Method for Image Contrast Enhancement.

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Recognition of Wheat Pests 10

Recognition of Wheat Pests

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10th IEEE international conference on intelligent Systems, IS 2020

作者： Toskova, Asya Toskov, Borislav Uhr, Zlatina Doukovska, Lyubka University of Plovdiv "paisii Hilendarski" Dept. of Computer Systems Plovdiv Bulgaria Institute of Plant Genetic Resources "k. Malkov" Dept. of Breeding and Genetics Sadovo Bulgaria Institute of Information and Communication Technologies Dept. of Intelligent Systems Sofia Bulgaria

ISBN: (纸本)9781728154565

This article introduces a model of an intelligent system for the recognition of wheat crops pests. The recognition allows us to define the species of weeds, their density, the various diseases and vermin of beneficial plants, as well as the exact location of objects in the field. The recognition technology is based on a convolutional neural network and on the independent work of a drone. © 2020 IEEE.

关键词： Convolutional neural networks

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Mobile-based smart District Holistic Values And Social Dimensions: a Citizen-centric Perspective 5

Mobile-based Smart District Holistic Values And Social Dimen...

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5th international conference on Informatics and computing, ICIC 2020

作者： Kisnu Darmawan, Aang Oranova Siahaan, Daniel Dwi Susanto, Tony Hoiriyah Akramul Umam, Busro Walid, Miftahul Dewi Puspasari, Betty Subiyakto, A'Ang Nizar Hidayanto, Achmad Universitas Islam Madura Department of Information System Pamekasan Indonesia Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Information System Surabaya Indonesia Universitas Islam Madura Department of Information Technology Pamekasan Indonesia Universitas Islam Madura Department of Informatics Pamekasan Indonesia Sekolah Tinggi Teknik Atlas Nusantara Department of Informatics Malang Indonesia Uin Syarif Hidayatullah Jakarta Department of Information System Jakarta Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9781728180472

At present, almost every country struggles to implement city management with the concept of smart cities. Previous studies have produced several models by exploring social values on the adoption and acceptance of technology in the application of the idea of a smart city. However, there is still little research that explores social values in the form of a relational relationship between the dimensions of builders in the smart District, which is very different from the concept of smart cities that are common and popular so far. This study aims to explore and evaluate the relationship of social dimensions of the application of smart mobile-based districts or districts. The model and approach used is an exploration of the building dimensions in the theory of Expectation Confirmation Model, Quality of Experience (QoE), Quality of Service (QoS), Trust, Commitment, Use Intention, Satisfaction, and Recommendation Intention. data collection was carried out from two hundred seventeen respondents who were successfully collected using online survey methods and offline data processing using smartPLS software v.3.2.8. The research findings indicate that there is a positive and significant relationship for the relational pattern of the proposed dimensions of intelligent district service builders. This research contributes to the modeling of the relational relationships of the aspects of the building of smart districts, which is still rarely done. This study confirms that local governments and policymakers should pay more attention to the relationship of critical social dimensions in technology adoption that affects the quality of service performance of smart-based mobile districts. © 2020 IEEE.

关键词： smart city

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Architecture for Visualizing Indoor Air Quality data with Augmented Reality Based Cognitive Internet of Things 34th

Architecture for Visualizing Indoor Air Quality Data with Au...

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34th international conference on Advanced Information Networking and Applications, AINA 2020

作者： Hadj Sassi, Mohamed Saifeddine Chaari Fourati, Lamia Digital Research Center of Sfax LT2S Laboratory Sfax Tunisia

ISBN: (纸本)9783030440404

Today’s generation is witnessing a monumental development in terms of smart devices. Due to the availability of various services at our fingertips, people tend to stay indoors. Thus, it is essential to provide Indoor Air Quality (IAQ) monitoring that improves indoor environments using technological advancements. Accordingly, Internet of Things (IoT) and Augmented Reality (AR) are considered as the major indispensable aspects of computing technologies and immersive virtual technologies by individuals and broadly applied in our daily transactions. Hence, merging these technologies is a big prominence in order to achieve interactive visualization for the smart IAQ system. In this context, we propose a new IAQ architecture based on Cognitive Internet of Things (CIoT) using AR. The proposed architecture shows great potential to integrate IoT for IAQ data with AR visualization. It enables intuitive interaction between users and IoT devices and further enhances the visualization of the data collected from IoT sensors, which effectively contribute to improving the user experience and usability. © 2020, Springer Nature Switzerland AG.

关键词： data visualization

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