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Numerical simulation Study on Air-side of Diesel Locomotive Finned Tube Double Channel Radiator 3

Numerical Simulation Study on Air-side of Diesel Locomotive ...

引用

2020 3rd international conference on modeling, simulation and Optimization technologies and applications, MSOTA 2020

作者： Guan, Ying Cui, Hongjiang Li, Minghai School of Locomotive and Vehicle Engineering Dalian Jiaotong University Dalian Liaoning China

Based on the heat transfer and flow resistance of diesel locomotive radiator, the influence was studied about the cooling air inlet speed on heat transfer coefficient and pressure loss of finned tube double channel radiator with louver by using CFD method. Temperature field, speed field and pressure field distribution of radiator calculation results were analyzed. The radiator was tested at different cooling air inlet speed, compared test results with simulation results, the greatest relative error of the heat transfer coefficient and pressure loss were 7.21% and 7.72%, respectively. © Published under licence by IOP Publishing Ltd.

关键词： Tubes (components)

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UAV-Mounted Intelligent Reflecting Surface-Assisted Edge Content Delivery Networks Maximized Sum Rate with Deep Learning

UAV-Mounted Intelligent Reflecting Surface-Assisted Edge Con...

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IEEE international conference on Research, Innovation and Vision for the Future

作者： Thanh-Hieu Nguyen Van-Ca Phan Viet-Thanh Le Long D. Nguyen Quang-Nhat Tran Nguyen-Son Vo HCMC University of Technology and Education Ho Chi Minh City Vietnam Vietnam Aviation Academy Ho Chi Minh City Vietnam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Vietnam Department of Engineering Dong Nai University Dong Nai Vietnam Faculty of Information Technology Van Lang University Ho Chi Minh City Vietnam Institute of Fundamental and Applied Sciences Duy Tan University Ho Chi Minh City Vietnam

ISBN: (数字)9798331505073

ISBN: (纸本)9798331505080

Unmanned aerial vehicles (UAV) and intelligent reflecting surfaces (IRS) have become the important parts besides the emerging technologies, architectures, and advanced applications and services (A&S) required to meet the groundbreaking key performance indicators and goals in 6G networks. This paper studies a system of UAV-mounted IRS (UI) assisted edge content delivery networks in which the contents of advanced A&Ss are originally transmitted from the base stations (BS) to mobile users (MU) via the UIs. The system is formulated to propose a phase-shift and altitude (PSA) optimization problem. The PSA problem is solved for the optimal values of phase-shift of reflecting elements and the optimal altitudes of the UIs to maximize the sum rate received at the MUs. A convolutional neural network based deep learning (CNN-based DL) model is designed to capture the rapid changes of the environment and derive the optimal working parameters immediately to serve the MUs the contents at the maximum sum rate. simulation results demonstrate not only the convergence and accuracy of the CNN-based DL model but also the benefits of PSA solution compared to other benchmarks.

关键词： Deep learning Accuracy Content distribution networks simulation Computational modeling Key performance indicator Autonomous aerial vehicles Convolutional neural networks Optimization Convergence

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Interplay of Cyber Physical Systems for Space technologies with Emphasis on Space Crop Farming

Interplay of Cyber Physical Systems for Space Technologies w...

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international conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Carey Louise B. Arroyo Newton John O. Suganob Ronnie S. Concepcion Robert Kerwin C. Billones Department of Manufacturing Engineering and Management De La Salle University Manila Philippines

ISBN: (数字)9798350381177

ISBN: (纸本)9798350381184

Space farming refers to the practice of growing plants and cultivating crops in outer space. This practice is being researched due to its potential in addressing the need for sustainable food production, especially for long-duration space missions wherein plants hold a vital role in life support systems of the spacecraft. There are many challenges associated with cultivating crops in the harsh and resource-constrained environments of space. Cyber-physical systems hold potential as a solution to many of these problems as they combine the physical world with the virtual world of information and computation. As such, this study focuses on providing a comprehensive review of the Augmented Reality (AR), Virtual Reality (VR), and Digital Twin (DT) technologies that show potential in space farming applications. It was found that augmented reality holds promising potential for guided planting and maintenance, real-time data visualization, digital crop simulation. Similarly, virtual reality shows potential for training and education as well as for simulation and modeling space farming conditions. Lastly, digital twin can be used for remote control and monitoring of space farming systems, and for the predictive analytics and decision-making support. This study also proposes an integrated cyber-physical system with VR, AR, and Digital Twin components for a multi-faceted approach to improving ground-based space farming research and training as well as the space farming capabilities in the international Space Station.

关键词： Training Solid modeling Reviews Decision making Crops Aerospace electronics Real-time systems

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Geoinformation components of sunflower yield simulation in arid climate using the model aquacrop 20

Geoinformation components of sunflower yield simulation in a...

引用

20th international conference Geoinformatics: Theoretical and Applied Aspects

作者： Krukivska, A. Hrechana, N. Snizhko, S. Shevchenko, O. Matviienko, M. Taras Shevchenko National University of Kyiv Ukraine

ISBN: (纸本)9789462823815

In Ukraine the crop losses associated with adverse weather and climatic conditions in agriculture can range from 10 to 70%. The main reason for these losses is the drought. In the last decade, the repetition and the duration of hot weather periods in Ukraine increased significantly. The consequences of climate change for agriculture will be related to changes in temperature and humidity conditions, but also to the reduction of soil fertility, desertification, etc. In the conditions of climate change, when water is a key limiting factor in crop production, it is necessary to use modern methodologies of agrometeorological research based on numerical multiparameter models with using a wide range of geographic information resources and technologies. This paper presents the methodology and results of modeling the conditions of heat and moisture supply of sunflower and their impact on the formation of crop productivity in the Kherson region using the model AquaCrop. Correct use of geoinformation parameters, soil and vegetation characteristics allows to obtain reliable results that can be used for early regulation of soil water balance by irrigation. © 2021 20th international conference Geoinformatics: Theoretical and Applied Aspects. All rights reserved.

关键词： Climate change

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A Novel Technique for Well-Optimized Content Replication in Fog Computing

A Novel Technique for Well-Optimized Content Replication in ...

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Disruptive technologies (ICDT), international conference on

作者： Khushi Joshi Rohini Sharma Department Of Information Technology JSS Academy of Technical Education Noida

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

A fog computing architecture processes huge amount of data by using edge devices. The cloud computing paradigm's fog layer helps to improve quality of service (QoS) in time-sensitive applications. Because devices at the edge of the cloud are very diverse and dynamic, content replication is vital. Replication is essential for consistent service delivery in fog computing. Time-sensitive requests received scant consideration in many of the early approaches. To improve fog computing replication, this research suggests a novel content replication mechanism using KNN and Naïve Bayes classification models. The recommended approach consists of two steps: The first assigns a failure risk classification to the fog servers that are available for replication. In the second phase, we suggest size-based content replication, in which the file or content is replicated on the less likely-to-fail fog server. We have evaluated the performance using metrics like utilization, throughput, and latency. The usefulness of the proposed strategy is validated by simulation results comparing it with the Replica-3 method. Comparing this to the Replica-3 technique, better resource usage, higher throughput, and lower latency are therefore attained. By allowing the system to handle more queries in parallel across multiple computers or processors, KNN's parallel processing capabilities of CPUs and GPUs ensures better resource utilization and greatly increasing throughput as compared to Naïve Bayes model. Additionally, KNN classification offers a useful data structure that significantly reduces latency by minimizing the time required to find the nearest neighbours.

关键词： Cloud computing Computational modeling Quality of service Nearest neighbor methods Throughput Data models Bayes methods Servers Resource management Edge computing

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Machine Learning based Intelligent Diagnosis of Orthodontics: a comprehensive review

Machine Learning based Intelligent Diagnosis of Orthodontics...

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international conference on Computational Intelligence and Knowledge Economy (ICCIKE)

作者： Iwin Thanakumar Joseph S Velliangiri Sarveshwaran Vijayakumar K S Benson Edwin Raj Ahmed A Elngar Anand Devadurai Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur Andhrapradesh India Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Campus Chennai India Department of Computer Information Sciences Higher Colleges of Technology Fujairah United Arab Emirates Faculty of Computers and Artificial Intelligence Beni-Suef University Beni-Suef City Egypt Department of Computer Science King Khalid University Gregar Abha

An effective prediction of orthodontics treatment outcome is highly essential for further scheme of clinical treatment for the patient with the simplified cost. An appropriate utilization of information technology simplifies the treatment for teeth irregularities and misaligned jaws in an effective manner. Lot of research works carried out in the area of dentistry to come out with an optimistic result. With the advent of artificial intelligence and machine learning methodologies in recent years, lot of clinical problems and difficulties can be efficiently managed and overcome by orthodontists. This research article provides the complete insight about the impact of intelligent technologies in the field of orthodontics. It provides a complete overview of futuristic applications in the field of orthodontic clinical diagnosis, planning of treatment for various cases and the correct prediction of outcome of clinical treatment which regularly faced by an orthodontist in the health care sector.

关键词： Deep learning Costs Biological system modeling System performance Teeth Data models Planning

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Survey on micro-nano cluster applications and its guidance, navigation and control technology status 7

Survey on micro-nano cluster applications and its guidance, ...

引用

2020 7th international conference on Computer-Aided Design, Manufacturing, modeling and simulation, CDMMS 2020

作者： Gao, Wanying Li, Kehang Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing100190 China

Nearly 3000 micro-nano satellites have been launched worldwide, and the resulting micro-nano clusters have attracted extensive attention from the international aerospace community. In order to better understand the development level of micronano clusters, this paper investigates some typical satellite swarm missions, summarizes the current status of guidance, navigation and control technologies for clusters, and looks forward to the development of China's micro-nano cluster missions. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Nanosatellites

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Software Reliability Evaluation using a Hybrid Soft Computing Approach for Battery Management System

Software Reliability Evaluation using a Hybrid Soft Computin...

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Sustainable Energy and Future Electric Transportation (SEFET), international conference on

作者： Shrddha Sagar Avadhesh Kumar Garima Shukla Sofia Singh Dipak Raskar School of Computer Science and Engineering Galgotias University Uttar Pradesh India Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Mumbai Maharashtra Department of Artificial Intelligence Amity School of Engineering and Technology Amity University Uttar Pradesh Noida

ISBN: (数字)9798350383997

ISBN: (纸本)9798350384000

Predicting faults in a software system can be performed using software reliability models. Reliability is a real- world aspect that is related to several real-life issues which depends on several factors. Different algorithms and methodologies are present to predict software reliability, still the exploration of hybrid soft computing approaches is required to predict software reliability inefficient way. The reason is soft computing algorithms are able to deal with uncertainties and real time issues. The objective of this study is to propose a reliability assessment model using hybrid approach of GeneticAlgorithm and Self-Organizing Map (SOM) for Component Based Software System (CBSS). The reason for selecting CBSS is the reusability aspects of components, which makes software development process cheaper and faster. This paper is an attempt to identify most reliable components based on three reliability factors (cohesion, coupling, and component dependency) from a software project that can be reused for developing other applications efficiently. simulation of Battery Management System software package components is completed by the use of MATLAB which were having 37 components out of which 6 most reliable components are selected using proposed method.

关键词： Self-organizing feature maps Couplings Computational modeling Software algorithms Battery management systems Software systems Prediction algorithms Software reliability MATLAB Genetic algorithms

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Intelligence and intelligent simulation 1

Intelligence and intelligent simulation

引用

1st international conference on Novelties in Intelligent Digital Systems, NIDS 2021

作者： Meytus, V.Yu. International Research and Training Center for Information Technologies and Systems The National Academy of Sciences of Ukraine Ukraine

ISBN: (纸本)9781643682044

The work presents a new approach to the study of problems associated with the initial definition of the concept of 'intelligence'. In work, intelligence is a property that ensures, at some level, the successful interaction of a subject or system with their environment, which is specified in the form of a subject area. For this, the subject area is modeled (smart modeling). modeling is the process of representing a domain in which the subject must solve the corresponding problems. The domain model is presented as a body of knowledge covering the constituent elements of this domain. Knowledge is a means of describing this model and is determined using a language that includes the logic of describing the corresponding entities of the subject area. Language properties are used to model some abstract formal structure in the form of a mathematical representation. The modeling process consists in a sequential transition from the description of the subject area to an interconnected structure of knowledge, associated with the constituent elements of this area, which are highlighted in the modeling process. © 2021 The authors and IOS Press.

关键词： Intelligent systems

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Structured planning of hardware and software Co-simulation testing of smart grids 10

Structured planning of hardware and software Co-simulation t...

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10th international conference on simulation and modeling methodologies, technologies and applications, SIMULTECH 2020

作者： Elshinawy, Rami Ramírez Acosta, Rebeca P. Schwarz, Jan Sören Lehnhoff, Sebastian OFFIS Institute Escherweg 2 Oldenburg Germany

ISBN: (纸本)9789897584442

The traditional electricity grid is ought to become a smart grid. One reason is the integration of volatile renewable energy generation, which poses the demand for advanced communication and control technology. This results in a change of the overall system dynamics, which in turn require testing to be done in early stages and with a more holistic approach. However, there is a gap in the transition from system specification and static analysis to an experimental setup validating these specification. This paper demonstrates first steps towards a structured methodology for deriving validation experiments for smart grids from initial system requirements. Our approach aims to fill the introduced gap by integrating Smart Grid Architecture Model (SGAM) for static analysis, Holistic Testing Description (HTD) for experimental analysis, and additional tools in a new workflow. Initial assessment of the workflow has been validated on its ability to select the most suitable components and test beds to perform an experiment. Therefore, two case studies were selected, one in the electricity power domain and another in the electricity market domain. © 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved

关键词： Smart power grids

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