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检索条件"任意字段=International Conference on Computer Modeling and Simulation"

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Analysis of Schedules for Rural First and Last Mile Microtransit Services 12th

Analysis of Schedules for Rural First and Last Mile Microtra...

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12th international conference on Computational Logistics (ICCL)

作者： Truden, Christian Ruthmair, Mario Kollingbaum, Martin J. Lakeside Labs GmbH Lakeside 04b A-9020 Klagenfurt Austria Alpen Adria Univ Klagenfurt Dept Math Univ Str 65-67 A-9020 Klagenfurt Austria

ISBN: (纸本)9783030876722;9783030876715

Low and infrequent demand in rural areas poses a problem for public transport providers to run cost-effective services and individual car use is usually the main means of transportation. We investigate how microtransit services can be integrated with existing public transport solutions (bus, train) as a flexible shared mobility alternative in rural areas and how to make them attractive alternatives to individual car use. We combine large neighborhood search with agent-based modeling and simulation to validate generated schedules for a microtransit service in terms of vulnerability to tardiness in passenger behavior or service provision. This includes the study of how disturbances, such as delays in service provision or late arrivals of passengers affect the stability of a transport schedule concerning a reliable timely delivery to transfer stops. We explore how simulation can be utilized as a means to fine-tune provider policies, e.g., how long vehicles may wait for late passengers before they depart.

关键词： Mobility Agent-based simulation Ride-sharing

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A study of replication of Qing Dynasty dragon robes based on CLO3D technology 7

A study of replication of Qing Dynasty dragon robes based on...

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2021 7th international conference on Mechanical Engineering, Materials and Automation Technology, MMEAT 2021

作者： Xu, Wang Yue, Li Xiaogang, Wang Wuhan Textile University School of Fashion Hubei Wuhan China Wuhan Textile University School of Computer Science and Artificial Intelligence Hubei Wuhan China Research Center of Wuhan Textile and Garment Digital Engeering and Technology

So far, the research on Chinese historical costumes has stayed on the discussion of culture, shape, pattern and social background. There is a big gap in the research on the reproduction of historical costumes. In this paper the clothing characteristics of Qing Dynasty dragon robe pattern, craftsmanship, shape and structure are analyzed by referring the literature, with the purpose of realizing the digital virtual display of ancient traditional clothing, and it carries out a comparative analysis of clothing CAD pattern, 3D virtual fitting and replication of samples, which put forward the detailed problems and solutions in the traditional dragon robe virtual simulation process. The research shows that the three-dimensional virtual simulation model can accurately restore the fabric, pattern, color and structure of the dragon robe of the Qing Dynasty. Therefore, this paper provides a reliable patterns and simulation modeling method for the research about the dragon robe, which offer an innovative research method for inheritance of traditional Chinese clothing. © Published under licence by IOP Publishing Ltd.

关键词： computer aided design

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A Performance modeling of Dynamic Vehicular Clouds: Job Completion Time of Concurrently Executed Tasks

A Performance Modeling of Dynamic Vehicular Clouds: Job Comp...

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international conference on Distributed Computing Systems Workshop

作者： Chinh Tran Mustafa Mehmet-Ali Department of Electrical and Computer Engineering Concordia University Montréal Canada

New vehicular applications demand more computing power and real-time processing. As modern vehicles are equipped with computationally powerful but often redundant and under-utilized onboard units for autonomous driving, a network of connected vehicles can form a vehicular cloud (VC) that can provide computing services among themselves or to other devices. In this paper, we evaluate the computing performance of a VC on a highway in congested traffic. We assume that the vehicles join and leave VC at random times. Thus, the number of vehicles in the VC will be time-varying. The residency times of the vehicles in the VC will be correlated because of traffic congestion. To enable the realization of VC in the future, we need to know its computing performance that considers its dynamic nature and concurrent execution of the tasks. In this work, we determine the completion time of a job with multiple tasks with random execution times. More specifically, we derive the probability density function of the job completion time as a function of the system parameters. We provide numerical results to demonstrate the utilization of the analysis and simulation results to confirm the correctness of the analysis.

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A Novel Non-Inverting Quadratic Double Switch Buck Boost Converter for Charging Lithium-ion Batteries in Electrical Vehicles

A Novel Non-Inverting Quadratic Double Switch Buck Boost Con...

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international conference on computer and Applications (ICCA)

作者： Amr Kamal Mohamed Hany A. Bastawrous Elsewedy Cables Elsewedy Electric Group Cairo Egypt Electrical Engineering Department The British University in Egypt Cairo Egypt

ISBN: (纸本)9781665452953

As the demand for clean energy sources increases on a large global scale, electric vehicles (EVs) are currently witnessing a huge demand to replace gas-powered vehicles. A crucial part in EVs is the battery management system, which utilizes DC-DC converters as essential parts. For this purpose, non-inverting DC-DC converters are the most desirable type. Moreover, these converters need to operate in continuous conduction mode (CCM) to minimize harmonic distortion and keep the load always fed with current. In this paper, we propose a novel design of a DC/DC quadratic non-inverting buck boost converter that has two switches and combines three different converters. A simulation model was constructed to investigate the converter performance for duty cycles from 30% to 80% in the CCM. The simulation results obtained not only revealed good performance in the desired duty cycle range but also confirmed the operation in CCM.

关键词： Lithium-ion batteries simulation Computational modeling Battery management systems DC-DC power converters Electric vehicles Harmonic distortion

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Prediction of Blockchain Transaction Fraud Using a Lightweight Generative Adversarial Network

Prediction of Blockchain Transaction Fraud Using a Lightweig...

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Blockchain Computing and Applications (BCCA), international conference on

作者： Charles Rawlins S. Jagannathan Donald Wunsch Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

Classic blockchain protocol design is centered around a computationally-intense cryptographic scheme, such as Bitcoin's Proof-of-Work (PoW). Network scalability and efficiency are stifled with the computational resources necessary to approve new transactions, thus rendering PoW unsuitable with limited devices like Internet of Things (IoT). As a first step towards alleviating this, a novel lightweight Generative Adversarial Network (GAN) called Vector GAN (VecGAN) is introduced wherein its weights are tuned through a direct error-driven learning approach with a Bayesian estimator for the selection of random noise matrices, called Bayesian Feedback Alignment (BFA), to augment data for improved fraud prediction. The augmented data is subsequently processed by a classifier for prediction. This combination of VecGAN with a classifier is treated as a novel method of blockchain ledger decision-making to approve ground-truth data. By using the two-step process, prediction accuracy using a classifier was improved up to 8% for real-world datasets. Resource consumption comparison to existing IoT blockchain protocols in a realistic simulation environment is also provided, where lightweight approaches for VecGAN in training and noise modeling reduce computation compared to other techniques.

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Wind load electrically controlled automatic assembly through computer BIM model 3

Wind load electrically controlled automatic assembly through...

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3rd international conference on Electrical, Communication and computer Engineering, ICECCE 2021

作者： Liang, Yujia Zhang, Yuxin Wen, Zhe Du, Yalong Chen, Shujin Wuhan University of Science and Technology China

In recent years, many Chinese construction enterprises began to use building information modeling technology (hereinafter referred to as BIM). This is a global trend designed to maximize automation and speed up the design process and document approval. This paper presents the key advantages of the BIM approach and discusses the possibility of using digital building models for wind load simulation (the automation of this process) to expand the "profit margin". At present, it is possible to automate application-based wind impact analysis methods. Possible application scenarios are listed and the advantages of wind load automatic assembly are described. At the same time, a possible method for load analysis in BIM design process is proposed. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Automation

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Turbulence modeling Through Deep Learning: An In-Depth Study of Wasserstein GANs

Turbulence Modeling Through Deep Learning: An In-Depth Study...

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Smart Electronics and Communication (ICOSEC), international conference on

作者： Wajdi Alghamdi S. Mayakannan G A Sivasankar Jagendra Singh B. Ravi Naik Ch. Venkata Krishna Reddy Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Mechanical Engineering Vidyaa Vikas College of Engineering and Technology Tiruchengode Namakkal Tamilnadu Department of Aeronautical Engineering KIT - Kalaignar Karunanidhi Institute of Technology Coimbatore School of Computer Science Engineering and Technology Bennett University Great Noida Uttar Pradesh Department of Mechanical Engineering St. Martin's Engineering College Secunderabad Telangana India Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of Technology Hyderabad

This research study compares the accuracy of different techniques based on deep learning (DL) for predicting turbulent flows. Different types of Generative Adversarial Networks (GANs) are examined in terms of their applicability to the study and simulation of turbulence. Next, we select Wasserstein Gans (WGANs) to produce localized disturbances. Network features including the learning rate and loss function are examined as they pertain to the performance of the WGANs during training on turbulent data gleaned from high-resolution Direct Numerical simulations (DNS). DNS input data and the generated turbulent structures are proven to agree qualitatively well. The projected turbulent fields are evaluated quantitatively and statistically.

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Toward Efficient Physical and Algorithmic Design of Automated Garages

Toward Efficient Physical and Algorithmic Design of Automate...

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IEEE international conference on Robotics and Automation (ICRA)

作者： Teng Guo Jingjin Yu Department of Computer Science Rutgers the State University of New Jersey Piscataway NJ USA

Parking in large metropolitan areas is often a time-consuming task with further implications for traffic patterns that affect urban landscaping. Reducing the premium space needed for parking has led to the development of automated mechanical parking systems. Compared to regular garages having one or two rows of vehicles on each island, automated garages can have multiple rows of vehicles stacked together to support higher parking demands. Although this multi-row layout reduces parking space, it makes parking and retrieval more complicated. In this work, we propose an automated garage design that supports nearly 100% parking density. modeling the problem of parking and retrieving multiple vehicles as a special class of multi-robot path planning problem, we propose associated algorithms for handling all common operations of the automated garage, including (1) optimal algorithm and near-optimal methods that find feasible and efficient solutions for simultaneous parking/retrieval and (2) a novel shuffling mechanism to rearrange vehicles to facilitate scheduled retrieval at rush hours. We conduct thorough simulation studies showing the proposed methods are promising for large and high-density real-world parking applications.

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computer System Breakdown Intelligent Analysis simulation Model Based on Deep Learning

Computer System Breakdown Intelligent Analysis Simulation Mo...

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Mechatronics, IoT and Industrial Informatics (ICMIII), international conference on

作者： Bihua Zhuo Officers College of PAP Department of Information and Communication Chengdu Sichuan China

Massive process measurement message brings great computational complexity and modeling complexity to the traditional breakdown diagnosis algorithm, and the traditional diagnosis algorithm has the disadvantage that it is difficult to make online estimation by using high-order quantities. Modern industrial systems have been developing towards largescale and complexity, which makes the breakdown diagnosis means for industrial systems encounter a series of technical questions. In view of the powerful data representation learning and analysis ability of deep learning technique, breakdown diagnosis based on deep learning has attracted wide attention from industrial and academic circles, and has made intelligent process control more automatic and resultful. The means adopted in this paper is deep learning, which is carried out alternately by convolution and sub-sampling. At last, the algorithm close to the output layer adopts the common multilayer neural network. As a breakthrough in the domain of latter-day artificial intelligence, deep learning can voluntarily learn valuable traits from the original trait set or even the original data. The research in this paper shows that the algorithm in this paper is resultful in breakdown prediction, and it is suitable to be widely applied in practical applications.

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AI-Based Geo Intelligent System for Attack Prediction and Virtual simulation

AI-Based Geo Intelligent System for Attack Prediction and Vi...

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Intelligent Control, Computing and Communications (IC3), international conference on

作者： N Kavya Shruthi Ajit Kumar Singh Yadav Department of Computer Science and Engineering North Eastern Regional Institute of Science and Technology Nirjuli Arunachal Pradesh

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

One of the blooming technologies of AI is the metaverse, The Metaverse is a virtual environment in which users may interact with virtual things and with one another. The Metaverse can be utilized in Military GeoIntelligent systems to build a virtual training environment, allowing Defence personnel to practice in realistic circumstances without the need for costly physical resources. The military personnel can practice in a virtual training environment using the Metaverse that can be created with realistic scenarios. This can aid in enhancing their abilities, judgment, and quickness of response. For instance, pilots can practice flying in various weather conditions, soldiers can hone their tactical skills, and cyber security officials can practice responding to cyberattacks. In this paper, we have focused on AI-based technologies combined with the geo intelligence and metaverse which can jointly help in defence to model and analyse complex geographic situations, allowing defence specialists to explore numerous situations and evaluate the effectiveness of different strategies before deploying resources, with the goal of improving situational awareness, response times, and decision-making capabilities across all security-related agencies. The satellite images obtained from the geo satellites give a brief description of a variety of different types of maps and visualizations, including topographic maps, vegetation maps, and thermal maps. These types of satellite imagery include infrared images, the locations of water bodies, planes, plateaus and a number of other surface structures of earth. The imagery helps in identifying the loopholes of spotting the enemy hiding locations and the risky regions of exposure of the native soldiers. The AI model can identify such locations and predict the possible threat locations. When this kind of model is deployed in the metaverse, it can help the soldiers in being trained for war zone like situations. The predictive outcome can hand

关键词： Training Solid modeling Metaverse Vegetation mapping Surface structures Satellite images Personnel Time factors Intelligent systems computer crime

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