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A Study of Brand Power simulation by Time Series Based on Flink and Kafka Framework 2

A Study of Brand Power Simulation by Time Series Based on Fl...

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2nd IEEE international conference on Data Science and computer Application, ICDSCA 2022

作者： Fu, Lianxue Yang, Jing Zhang, Fan China Automotive Technology and Research Center Co. Ltd. Tianjin China Co. Ltd. Tianjin China

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

To build a strong automotive company, it is essential to monitor and calculate each indicator of a brand of car and the score of brand power in real time. In this paper, firstly, the subjective and objective data of research data (subjective data) and sales data of each car(objective data) brand in each year and month are combined to form multi-source heterogeneous data. And then data pre-processing is performed on the basis of multi-source heterogeneous data, and the pre-processing includes the removal of attribute features without contribution, detection and filling of outliers and missing values, etc. Secondly, Introduces the advantages of the Flink framework and Kafka framework respectively, as well as the process of reading, storing, computing and running processing, using distributed computing processing and streaming data computing processing;finally, based on the framework of Flink+Kafka for the eight subjective and objective combination of indicators for the calculation of car brand power. The method can basically monitor and calculate the brand power of each car brand in real time, and give the score of each index at any time. © 2022 IEEE.

关键词： Data handling

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An LSTM-PSO-Based Predictive Strategy and Its Application in the Main Steam Temperature Control in Power Plants 2

An LSTM-PSO-Based Predictive Strategy and Its Application in...

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2023 2nd international conference on Power System and Power Engineering, PSPE 2023

作者： Jin, Fei Hao, Xiaoguang Yin, Zhe Yang, Chunlai Liu, Xuelai Shi, Yijun State Grid Hebei Energy Technology Service Co. Ltd Shijiazhuang050021 China School of Control and Computer Engineering Beijing102206 China

We proposed an LSTM-PSO predictive controller strategy to overcome the large delay and strong disturbance during main steam temperature control. First, the long short-term memory (LSTM) network model was developed to forecast the future trend of mainstream temperature, and the deviation between the model output and the expected value after feedback correction was minimized by the particle swarm optimization (PSO) algorithm. Then, the LSTM-PSO predictive controller was taken as the primary controller to maintain the steam temperature of the coal-fired boiler. A comparative simulation with conventional PID cascade control and dynamic matrix controller strategies was given, and the test calculations indicate that the adjustment time was shortened and the overshoot was reduced. Finally, the LSTM - PSO predictive control strategy was deployed into the actual boiler operation process of a 300 MW coal-fired power plant, within 0.5 °C steady-state error and 2 °C dynamic error. © Published under licence by IOP Publishing Ltd.

关键词： Controllers

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Blockchain-Based Lifecycle Approach towards a Secure Building Information modelling (BIM) Workflow 2

Blockchain-Based Lifecycle Approach towards a Secure Buildin...

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2nd international conference on computers and Automation, CompAuto 2022

作者： Hammi, Assam Belhi, Abdelhak Gasmi, Houssem Bouras, Abdelaziz College of Engineering Qatar University Computer Science and Engineering Department Doha Qatar

ISBN: (纸本)9781665481946

Data safety concerns are critical during the whole lifecycle of any built asset from the design stage until destruction. Information security in Building Information Modeling (BIM) enabled projects represents a key factor for the whole process success. Unsuitable distribution of sensitive information may cause financial loss, lack of trust and even physical security threats. This paper would propose a novel solution to secure BIM workflow through a Blockchain technology-based lifecycle approach. The aim in this solution is to integrate a blockchain-based lifecycle management platform with BIM software. The interactions and system transactions between the two entities will be managed by distributed ledger technology and smart contracts. This will ensure workflow's security by strengthening the transparency, traceability and securing information exchange. © 2022 IEEE.

关键词： Blockchain

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Numerical simulation and Analysis of Structural Dynamic Response of Solid Rocket Motor under Oscillating Internal Pressure 2

Numerical Simulation and Analysis of Structural Dynamic Resp...

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2nd international conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Alkkhayat, A.H. Pandey, Sandeep Ramani, S. Mahaboob Basha, S. Jeyakani, P. Anumula Swarnalatha, A.P. College of Technical Engineering The Islamic University Najaf Iraq Department of Electrical & Electronics Engineering IES College Of Technology MP Bhopal462044 India Department of Electronics and Communication Engineering Sreenidhi Institute of Science & Technology Telangana Hyderabad500029 India Department of Computer Science and Engineering Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Tamilnadu Chennai India New Prince Shri Bhavani College Of Engineering And Technology Tamilnadu India Department Of Aeronautical And Aerospace Engineering KCG College of Technology Tamilnadu Chennai India

ISBN: (纸本)9798350305418

The causes of combustion instability of solid rocket motor are very complex. Studies have shown that structural vibration may be the direct cause of combustion instability, but there are very few reports about structural dynamic response and its effects on grain. In order to study the effects of structural dynamic response of solid rocket motor grain under oscillating internal pressure on combustion process and verify a new method to study combustion instability from the perspective of structural dynamics, the dynamic response of solid rocket motor grain under oscillating internal pressure was numerically simulated in this paper, and the distribution of grain strain was obtained. Meanwhile, the damages of oscillating internal pressure to the grain structure were predicted. The viscoelastic constitutive model of solid propellant was established by WLF equation, and the oscillating process of internal pressure was described by cyclic load. Based on the theories of modal analysis and harmonic response analysis, numerical simulation and comparative analysis were carried out for different pressure, different length diameter ratio and different residual thickness. The results show that when the internal pressure is 8 to 14 MPa, the maximum principal strain of grain increases continuously with the increase of internal pressure, and the local strain values exceed 20\%, which may lead to the increase of combustion rate. The maximum principal strain increases with the increase of length diameter ratio, and the increasing trend is nonlinear. The maximum principal strain increases with the decrease of residual charge thickness. When the thickness of the residual propellant is 1/5 of the initial thickness, the maximum principal strain reach or exceed 40\%, which is higher than the axial tensile elongation of the propellant. In a word, the oscillating internal pressure has some significant effects on the dynamic response of solid rocket motor grain, and the dynamic response is gr

关键词： Combustion Instability Dynamic Response Pressure

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Cloud-based Decentralized Smart Healthcare for Patient Monitoring on Deep Learning 2

Cloud-based Decentralized Smart Healthcare for Patient Monit...

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2nd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Arunachalam, Sripriya Shanthi, H.J. Sivagurunathan, G. Das, Shyamali Anand, D. Raj M, Thanga School of Computing Sciences Vels Institute of Science Technology & Advanced Studies - Vistas Computer Applications- Pg India Amet University Ecr Kanathur India St. Joseph's College of Engineering Omr Department of Electronics and Communication Engineering Chennai600119 India Cmr Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India Koneru Lakshmaiah Education Foundation Department of Cse AP Vaddeswaram India Persistent Systems Limited Pune India

ISBN: (纸本)9781665456302

Over the past few years, there has been a meteoric surge in the quantity of digital information available online for instantaneous sharing, persistent archiving, and inquiring. It has expanded the possibilities for using digital data that is both decentralised and ad hoc in order to make decisions quickly. At present, e-Healthcare is among the most sought-after sectors for EHR and telemedicine communication. Securing electronic health records (EHR) has become a topic of intense interest in recent years, with previous works employing a wide range of methods to better ensure the confidentiality and security of EHR at a reasonable price. There are a number of serious problems with the current research, including computational complexity, increased process time, information leakage, vulnerability to various assaults, scalability difficulty, etc. Clinical data analysis presents several difficulties, but disease prediction is one of the most significant ones. The suggested study aims to apply deep learning (DL) classification algorithms for disease prediction. A technique that utilises cloud computing, fog computing, and IoMT more recently has been presented for diagnosing illness. Fast DL classification analysis is performed in the fog layer. When compared to the alternative proposed model Bi-CNN, the healthcare model's efficiency in the Bi-LSTM simulation yields significantly better results: 97.31% of accuracy, 97.58% of recall, 96.90% of precision, 94.90% of F1-measure, 97.25% of specificity, and 94.80% of G-mean. © 2023 IEEE.

关键词： Fog computing

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Multi-frame Integrated Aero-engine Altitude simulation Test Bench Data Flow Visualization Migration Technology 2

Multi-frame Integrated Aero-engine Altitude Simulation Test ...

引用

2nd international conference on computer Science, Electronic Information Engineering and Intelligent Control Technology, CEI 2022

作者： Zhou, Qi-Fan Zhao, Wanli Wang, Kun Tao, Xinxin Zheng, Fangju Guo, Ying-Qing School of Power and Energy Northwestern Polytechnical University Xi'an710072 China

ISBN: (数字)9781665476164

ISBN: (纸本)9781665476164

As an important method for the aero-engine performance testing, the data collected from each sensor in the process of aero-engine altitude simulation test is extremely valuable and essential. To display the data more intuitively and to explore its deeper meanings and potential value, the development of the real-time migration and visualization technology of the data flow generated from the aero-engine altitude simulation test-bed basing on multi-framework integrationis proposed. Firstly, with the help of the Mybatis-Plus automatic view layer, data stored in the bottom historical database can be visualized in the browser's table structure space using Vue framework's table structure, which provides the convincing testers to check and analyze. Then, data flow technology migration, referring to the JDBC interface based on GateWay's current limiting mechanism, integrating full/incremental data flow, and integrates multi-thread parallel transport flows using Mybatis' load balancing mechanism. Therefore, the essential information in historical database for subsequent algorithm analysis can be synchronized to local database. Finally, with Vue framework, data flow front-end monitoring interface verifies data visualization, integrity, and effectiveness in real-time. © 2022 IEEE.

关键词： Data visualization

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The Acceptance of Machine module in the Hospitality Industry with Prospects and Challenges: A Review

The Acceptance of Machine module in the Hospitality Industry...

引用

Computational modelling, simulation and Optimization (ICCMSO), international conference on

作者： Rohit Kapil Sethi Milan Sharma Amit Gusain School of Hotel Management Airline and Tourism CT University Ludhiana India Computer Science and Engineering Bahra University Solan Himachal Pradesh Faculty of Hotel and Tourism Management SGT University Gurgaon India

In the growth of technology there have been some discussions recently regarding the use of such technology and how they affect hotels function as technology has advanced, the hotel sector has begun using state-of-the-art technologies such as Machine Learning (ML) and robots. Several recent discussions have been held on the use of these technologies and how they affect the cost of running hotels. With these new technologies becoming increasingly important, this paper examines the trend of the hotel industry’s adoption of machine learning and robotics. To determine the fundamental elements that influence ML adoption, we used the TOE framework across three domains: technology, organization, and environment. The finding expose the hotels are using ML and robotics due to the numerous factors that influence their adoption. The study illustrates how machine learning could be implemented in the hospitality sector and is one of the initial efforts to explore the full scope of how it may be applied.

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A Delay-Aware Heartbeat Scheduling Mechanism for Cloud Datacenter 2

A Delay-Aware Heartbeat Scheduling Mechanism for Cloud Datac...

引用

2nd IEEE international conference on Data Science and computer Application, ICDSCA 2022

作者： Tang, Ming Wang, Ling Xu, Chunlei Zou, Haodong Su, Chenwei Ji, Mingtao Information and Telecommunication Branch State Grid Jiangsu Electric Power Co. Ltd Nanjing China State Grid Jiangsu Electric Power Co. Ltd Nanjing China Department of Computer Science and Technology Nanjing University Nanjing China

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

Recently, the existing distributed systems such as big data processing systems (Spark, Hadoop, etc.) and distributed training systems (Pytorch, Parameter Server, Tensorflow, etc.) need to send heartbeat packets to monitor the operation of tasks and detect the status of nodes. This paper studies the problem of how to design an efficient heartbeat mechanism for cloud datacenter, and we provide a new vision for solving this issue through the programmable switch. We firstly analyzed the format of the heartbeat packet and the aggregation process of heartbeat packets. Based on these, we designed an adaptive heartbeat mechanism by establishing an optimization problem with the goal of minimizing the aggregation cost. Furthermore, a heuristic scheduling algorithm is proposed and implemented on the simulation platform. The simulation results show that our proposed algorithm performs much better than the default heartbeat mechanism. That is, our proposed algorithm can effectively reduce the processing overhead and the network load. © 2022 IEEE.

关键词： simulation platform

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Business process (4IR) Centric Optimization modelling 2

Business Process (4IR) Centric Optimization Modelling

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2nd international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Munsamy, Megashnee Telukdarie, Arnesh Univ Johannesburg Johannesburg South Africa

Current best practice methodologies of energy utilization are limited to core production processes, excluding non-core processes. Energy determinations are limited to specialized functions and do not cover the entire business. This research introduces business process modelling to evaluate the holistic business energy demand, inclusive of core production and support functions, of a coal fired power plant. The methodology includes, modelling and statistical techniques, in developing the holistic baseline model, with predictive capacities to forecast the energy impact of changes to the business. Post a validation cycle, the results provide for insights on the impact of optimization, including Cleaner Production, IoT and technology substitution on the coal to energy business. The results include CO2 impact, energy impact and resource (people) impacts as forecast by the model. The model is unique in that it is system agnostic and can be used to forecast any energy production configuration. (C) 2021 The Authors. Published by Elsevier B.V.

关键词： Energy modelling energy optimization Fourth Industrial Revolution CO2 emissions

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An Improved Recycling Folded-Cascode Amplifier with Nested Current Mirror for Front-end Readout ASIC 2

An Improved Recycling Folded-Cascode Amplifier with Nested C...

引用

2nd IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2022

作者： Liu, Dechen Wei, Tingcun Chen, Sijie Chen, Nan Northwestern Polytechnical University School of Microelectronics Xi'an China Northwestern Polytechnical University School of Computer Science and Engineering Xi'an China Northwestern Polytechnical University School of Electronics and Information Xi'an China

ISBN: (数字)9781728181158

ISBN: (纸本)9781728181158

A nested-current-mirror (NCM) recycling folded cascode (RFC) operational transconductance amplifier (OTA) for front-end readout ASIC is designed in this work. The nested current mirror technology is applied to the recycling folded cascode amplifier, which improves the small signal transconductance and output impedance, and significantly improves the DC gain, gain-bandwidth product (GBW) and slew rate (SR). The proposed amplifier has been implemented using HHGrace 0.11μm CMOS process. According to the simulation results, for the same 3pF load, the proposed amplifier improves 26MHz in GBW, 69V/us in slew rate, and 22dB in DC gain compared to the conventional RFC amplifier. © 2022 IEEE.

关键词： Operational amplifiers

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