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检索条件"任意字段=International Conference on Intelligent and Smart Computing in Data Analytics, ISCDA 2020"

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smart data Collection in Mobile Edge computing Environment

Smart Data Collection in Mobile Edge Computing Environment

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作者： Tikito, Iman Souissi, Nissrine Mohammed v University in Rabat EMI-SIWEB Team Rabat Morocco Mines-Rabat School Computer Sciences Department Rabat Morocco

ISBN: (纸本)9781728180410

With the digital transformation, businesses and public administrations must change the place of data in the value chain to serve all areas of the business and open up information systems. The value of the knowledge extracted from this data is directly linked to the quality of data collection. Mobile devices are particularly suitable for reporting data. They are very widespread, very suitable and can be used at any time. These characteristics mean that the use of mobile support for data collection corresponds to a paradigm shift more than a simple new additional technology compared to the panoply of existing tools. The explosion of information sharing and data, which stems from our daily by these devices is stored mostly in the cloud servers. Thus, to reduce the number of data transferred and generated by mobile devices to the cloud servers, the edge computing allows to process data at the network edge where they are generated directly reducing certain characteristics of Big data. Big data involves the collection of complex data on the 'V' dimensions which describe the quantity and type of data collected, as well as their importance and relevance to the challenges of the requester. However, the smart data goes a step further and consist to extract from the data collected only the most relevant information for the client in order to make predictions. Our results show that using an intelligent data collection process in mobile computing could generate savings in terms of data storage and analysis at the cloud level. © 2020 IEEE.

关键词： Information management

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Identification of solenoid parameters based on fiber squeezer and neural network for smart control 4

Identification of solenoid parameters based on fiber squeeze...

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4th international conference on intelligent computing in data Sciences (ICDS)

作者： Abedallah, Zahidi Said, Amrane Nawfel, Azami Naoual, Nasser Natl Inst Posts & Telecommun Rabat Morocco Fac Sci & Tech Settat Morocco

ISBN: (数字)9781728180847

ISBN: (纸本)9781728180847

Solenoids are low-cost high-speed nonlinear actuators commonly used in switching mode in many applications. However, fluctuations on the performances of solenoid are a major problem, particularly in industrial applications. These fluctuations are essentially due to changes in the spring constant, in the coefficient of friction, in the inductance and the resistance of the coil. This paper proposes a new methodology for controlling the effect of solenoid parameters variation on the PID corrector coefficients. First at all,the effect of solenoid parameters variation on the PID corrector coefficients is analyzed, Then, the algorithm based on artificial neural networks (ANN) coupled with optical fiber polarization squeezer based on solenoid for polarization scrambling is used to monitor the solenoid parameters from the coefficients of the transfer function, these coefficient are determined from the step response of the squeezer fiber. the parameters identified are used to automatically adjust the coefficients of the PID correctors. The results of the simulation show the validity for monitoring the solenoid parameters for keeping an optimized dynamic response.

关键词： solenoids fluctuations PID polarization controller ANN

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smart real time data transfer surveillance with edge computing and centralized remote monitoring system

Smart real time data transfer surveillance with edge computi...

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international Petroleum Technology conference 2020, IPTC 2020

作者： Nugraha, Budhi Nair, Ragesh Muhammad, Kashif Petrolink

ISBN: (纸本)9781613996751

High-quality and completeness of real time drilling data have become critical factors to capitalize the improvement of data analysis for decision making. This paper proposes a combined architecture that supports edge computing technology with high frequency real time data to produce smart alerts as well as for the remote monitoring of real time data status for large number of rigs in a centralized location to enhance the surveillance of real time drilling data transfers. Unlike the traditional real time data surveillance method that monitors the data in the WITSML town server, this innovative technique analyzes the real time data quality right on the edge device. It offers smart computation to produce rule-based intelligent alarms for effective decision-making. This method delivers flexibility and effectiveness in WITSML real time data monitoring as it is fully independent from direct access to the WITSML Store. The biggest advantage of this approach is that it handles the remote surveillance of numerous rigs and gives absolute control over data aggregation. Managing sensitive drilling data has started to play a key role in cost optimization and critical decision-making, especially when running an active mission critical operation. The new approach of edge computing to analyze the WITSML data from its activity file at the rig site is a breakthrough in the real time data monitoring concept. A rule-based smart alarm system to check the statistics of real time data on the edge increases the confidence of the decision-making process as any data transfer issue can be detected faster. Further analysis and active monitoring of multiple rigs data transmission can be done by a centralized control panel, accessed from the real time operations center in town. Having a system with a precise method to actively monitor the status of real time data transfers on multiple rig sites and smartly generate alerts, assures end users to manage their well efficiently. Emphasizing the requi

关键词： data transfer

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intelligent analysis of big data for the preventing of external force destruction on high-voltage transmission lines 6

Intelligent analysis of big data for the preventing of exter...

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6th Annual international conference on Computer Science and Applications, CSA 2020

作者： Wu, Peng Department of Information Engineering Zibo Vocational Institute Shandong Zibo255000 China

By constructing an intelligent analysis network, we can analyze autonomously and at the same time interact with the data. It makes the analysis more accurate, and it can construct a systematic model of the results. It can share to each smart terminal through the collation and analysis of the cloud computing library. The process will be transmitted to the background. Through the integration of big data the background collates a model of analysis and share to all the terminals. This will upgrade the ability of thinking on the terminals. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Big data

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Remaining Useful Life Prediction of Power MOSFETs Using Model-Based and data-Driven Methods

Remaining Useful Life Prediction of Power MOSFETs Using Mode...

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international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Wu, Jinjing Xu, Zheng Wei, Xiao Minist Publ Secur Key Lab Informat Network Secur Res Inst 3 339 Bisheng Rd Shanghai Peoples R China Guangxi Key Lab Cryptog & Informat Secur Guilin Peoples R China Shanghai Univ Shanghai Peoples R China

ISBN: (纸本)9783030152352;9783030152345

Prognostics and health management has become an advanced engineering technology in avionics systems which can implement condition monitoring and reduce unnecessary downtime. A prognostic application to power MOSFETs is developed in this paper. Firstly, failure mechanism of the power MOSFETs under power cycling aging tests is analyzed. Then, the drain-source on-state resistance is considered as a leading precursor of failure as it exhibits a decaying trend. Finally, a degradation model is established to predict the remaining useful life based on Kalman filter and LS-SVM, respectively. Several results are analyzed to demonstrate the feasibility and effectiveness of these methods.

关键词： Prognostics and health management Remaining useful life Least square support vector machine Kalman Filter

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A distributed IoT system for modelling dynamics in smart environments

A distributed IoT system for modelling dynamics in smart env...

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2020 international conference Engineering Technologies and Computer Science, EnT 2020

作者： Radenkovic, Bozidar Despotovic-Zrakic, Marijana Bogdanovic, Zorica Barac, Dusan Labus, Aleksandra Naumovic, Tamara University of Belgrade Faculty of Organizational Sciences Belgrade Serbia

ISBN: (纸本)9781728180908

This paper studies the possibilities of fusing the concepts of smart environments and continuous and discrete systems simulation into a single system where identification of parameters, dynamics modelling and the choice of adequate control actions can be performed in real-time. The goal is to develop a model of a distributed IoT system capable of intelligent and dynamic adjusting of structure and system parameters with respect to the set goals. This goal is achieved in two phases. In the first phase, the modelling of the nodes in the smart environment is performed through defining interconnected IoT devices that can gather data via sensors, perform control actions via actuators, and perform basic computing operations. In the second phase, hierarchical modelling of smart environments is performed by developing complex mathematical models that use collected data to calculate performance indicators, perform simulations, initiate control actions and support decision making. Both phases are supported by specific software components, some running in the cloud and some distributed on the edge devices. The developed approach is applied for modelling the system for traffic noise monitoring in a smart city. © 2020 IEEE.

关键词： Internet of things

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Design of higher vocational education auxiliary platform based on cloud computing technique

Design of higher vocational education auxiliary platform bas...

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

作者： Yu, Miao Chongqing Three Gorges Vocational College Chongqing China

ISBN: (纸本)9789811525674

Along with the popularity of cloud computing technique today, it has been realized to help people get rid of pen and paper writing and cumbersome report calculation, get rid of the limitation of time and space, as long as you have a network, you can use cloud computing technology to accomplish a variety of tasks quickly and efficiently. Higher professional education is an significant link in the higher education institution. How to effectively run the country’s higher vocational education is related to the overall development of China’s education cause an important topic. This paper starts from the major problems and development direction in the construction of teaching resources in China’s higher vocational colleges, explore the use of modern cloud computing and mesh resources, USES the information technology of cloud computing service mode, service architecture of high quality teaching resource sharing platform in higher vocational colleges is proposed, implementation maximize the use of teaching resources in higher vocational colleges, crack education teaching resources problem such as "gaps between the rich and the poor", promote the level of education modernization, for the cloud platform repository construction goals provide beneficial theoretical support and technical guarantee. The research results of this paper show that in process of design teaching at the higher vocational schools, the advantages of cloud computing can be fully utilized to create a good cloud computing education environment and give full play to teaching assistance function of cloud computing, which is conducive to more effective learning for learners. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Cloud computing

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Traffic Incident Detection from Massive Multivariate Time-Series data 4th

Traffic Incident Detection from Massive Multivariate Time-Se...

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4th international conference on Cognitive computing, ICCC 2020, held as part of Services conference Federation, SCF 2020

作者： Sterling, Nicholas Miller, John A. Department of Computer Science University of Georgia AthensGA United States

ISBN: (纸本)9783030595845

Automatic incident detection (AID) aims to programatically detect vehicle traffic incidents from real-time traffic data, and improvements in AID are vital for future technology such as smart-city traffic planning. In this research we use a simple machine learning model (AdaBoost) applied to freely available traffic data from the Caltrans Performance Measurement System (PeMS) to develop a state of the art AID mechanism. In addition we discuss related work in AID to date, introduce and explore the data we use in our experiments, present our methods and results, and discuss conclusions and future work. © 2020, Springer Nature Switzerland AG.

关键词： data analytics

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Optimization of Logistics Warehouse Location Based on Genetic Algorithm

Optimization of Logistics Warehouse Location Based on Geneti...

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international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Wang, Xu Xia, Qing City Univ Macau Inst Data Sci Macau Peoples R China Guangdong Univ Educ Sch Management Guangzhou Guangdong Peoples R China

ISBN: (纸本)9783030152352;9783030152345

With the continuous progress and development of the global economy, our requirements for the quality of goods and services provided by service providers and suppliers are becoming higher and higher. In order to meet the needs of our customers, many enterprises expand their market share. We need to evolve to respond and adjust quickly to a highly changeable market. Nowadays, social competition is no longer just product competition between enterprises in simple industries, but gradually evolved into joint competition between social supply chains and supply chains. Logistics has always been a crucial link in the development of supply chain, so warehousing management, as the core part of logistics, especially logistics warehousing center, has attracted more and more attention from the public. In many logistics enterprises, how to effectively improve the warehouse location optimization rate is regarded as the top priority. Nowadays, in the logistics warehouse center, it is an effective way to improve the efficiency of warehouse location optimization to optimize its original warehouse location effectively. Whether the warehouse location is allocated reasonably will affect the efficiency of the overall warehousing operation of the logistics warehouse center, and then affect the rate of profits for enterprises.

关键词： Genetic Repository optimization Warehouse management

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Performance Analysis of the State-of-the-Art Neural Named Entity Recognition Model on Judicial Domain 1

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3rd international conference on Soft computing: Theories and Applications, SoCTA 2018

作者： Thomas, Anu Sangeetha, S. Text Analytics & NLP Laboratory Department of Computer Applications National Institute of Technology TiruchirappalliTamil Nadu620015 India

ISBN: (数字)9789811507519

ISBN: (纸本)9789811507502

Extracting named entities out of unstructured text data is an important problem in natural language processing, with applications in tasks such as sentiment analysis, information retrieval and answer selection in question answering. For identifying named entities, many methods have been developed ranging from knowledge-based methods to supervised machine learning methods. Recently, deep learning models have shown better performance than conventional methods in Named Entity Recognition (NER) tasks. However, it remains unclear how the state-of-the-art neural NER models that have shown superior performance on benchmark datasets perform on other domains. This paper aims to analyze the performance of a state-of-the-art neural NER model in identifying the named entities from judicial text data. The experimentally obtained results show that the model achieved very good results in identifying person names, location names and average result in organization names. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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