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A Dynamic Adaptive Search Algorithm for CoSpace Rescue Robot 6

A Dynamic Adaptive Search Algorithm for CoSpace Rescue Robot

引用

6th international conference on Robotics and Automation Engineering, ICRAE 2021

作者： Chengbo, Li Xiaoming, Wang Zixi, Huang Guangyao, Pang Xinyu, Han Yaguang, Lin Dalian Free Trade Zone No. 1 High School Dalian China Key Laboratory of Modern Teaching Technology Ministry of Education Xi'an China School of Computer Science Shaanxi Normal University Xi'an710119 China Shenzhen Middle School Shenzhen China Wuzhou University School of Data Science and Software Engineering Wuzhou China Singapore Polytechnic Advanced Robotics and Intelligent Control Centre Singapore

ISBN: (纸本)9781665406970

The application of robots to assist humans in earthquake rescue has always been an important topic that researchers are constantly studying. CoSpace Rescue is an abstract modeling and simulation of earthquake rescue and a simulation platform for studying robot rescue search algorithms. Its mathematical model is a multi-objective optimization problem. In this paper, we propose a search algorithm design framework for the CoSpace Rescue robot. Based On this framework and the idea of the heuristic search algorithm, we design and implement the 'Multi-objective Optimal Dynamic Adaptive On-Demand Search Algorithm'. The results of the experiment show that the algorithm can dynamically adapt to the changes in the environment and significantly improve the search efficiency of the rescue robot. © 2021 IEEE.

关键词： Earthquakes

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Optimizing the classroom Space Design for Intellectually Disabled Students Based on the Analysis of the Acoustic Environment

Optimizing the classroom Space Design for Intellectually Dis...

引用

international conference on Communication Engineering and Technology (ICCET)

作者： Tawfiq Jebril Yang Chen Heena M Shirahatti Syed Far Abid Hossain School of Human Settlements and Civil Engineering Xi’an Jiaotong University Xi’an China KLE Technological University Hubli Karnataka BRAC Business School BRAC University Dhaka BD.

The present study focuses primarily on the effects of designing a rounded corner classroom for intellectually disabled students in primary schools based on the reverberation time and noise level. Usually, straight 90-degree edges are used for classroom corners, but rounded edges for walls and furniture are more comfortable and help to ensure students safety. Therefore, this study examines how a rounded-edge classroom design for walls and furniture affects additive babble and environmental noise level conditions in primary school classrooms for intellectually disabled students. The study compares the two classroom designs (rounded and right-angle corners) covering the same area with different variable factors to improve students’ performance. The computer software program ODEON and the MATLAB programming language were primarily used to investigate the two models. These models were used to predict five design scenarios’ impact to assess acoustic behavior with and without furniture on intellectually disabled students learning. The findings reveal that the proposed model with rounded corner walls and furniture and a high and sloped ceiling performs better than the regular classroom model. The study also confirms that a better study environment can be created for intellectually disabled students to study alongside regular students.

关键词： Analytical models Computational modeling Working environment noise simulation Predictive models Software Behavioral sciences

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Short-Term Wind Speed Forecasting Using Meta Learningbased Elman Neural Network 4

Short-Term Wind Speed Forecasting Using Meta Learningbased E...

引用

2021 4th international conference on Applied Mathematics, modeling and simulation, AMMS 2021

作者： M.Madhiarasan Department of Computer Science and Engineering Indian Institute of Technology

Adequate power provision to the customer and wind energy penetration into the electrical grid is necessitated for accurate wind speed forecasting in the short-term horizon to realize the scheduling, unit commitment, and control. According to the various meteorological parameters, the wind speed and energy production from wind energy are affected. Therefore,the author performs the multi-inputs associated Meta learning-based Elman Neural Network(MENN) forecasting model to overcome the uncertainty and generalization problem. The proposed forecasting approach applicability evaluated with real-time data concerning wind speed forecasting on a short-term time scale. Performance analysis reveals that the meta learning-based Elman neural network is robust and conscious than the existing methods, with a least mean square error of 0.0011.

关键词： Meta-learning elman neural network generalization forecasting wind speed

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Adversarial Technique Validation & Defense Selection Using Attack Graph & ATT&CK Matrix

Adversarial Technique Validation & Defense Selection Using A...

引用

international conference on Computing, Networking and Communications (ICNC)

作者： Md Ariful Haque Sachin Shetty Charles A. Kamhoua Kimberly Gold Computational Modeling and Simulation Engineering Old Dominion University Norfolk VA USA Network Security Research The U.S. Army Research Laboratory Adelphi MD USA Naval Surface Warfare Center Crane Division Crane IN USA

Today cyber adversaries utilize advanced techniques to victimize target assets. To tackle the adversaries, it is of utmost importance to understand potential techniques they may use to exploit network vulnerabilities. Attack graph has always been a crucial tool for network vulnerability analysis. However, the current state-of-the-art attack graph can not predict adversarial techniques. To overcome the gap, we utilize the MITRE ATT&CK matrix in this work and map the techniques with the attack graph node descriptions. We first formulate a comprehensive dataset from ATT&CK consisting of all the adversarial strategies, subtechniques, associated tactics, and mitigation for the enterprise network. We then capture the attack graph node descriptions and apply the term frequency-inverse document frequency (TF-IDF) algorithm to map the attack techniques with the available node descriptions. Next, we generate the cosine similarity to determine an adversary’s top methods to attack a network. We then map those techniques with the associated tactics and mitigation strategies as enumerated in the ATT&CK matrix. Finally, we illustrate the analysis using a networked system’s attack graph. This proposed method would help identify and validate adversarial techniques and guide in selecting mitigation mechanisms for security enhancement.

关键词： Bit error rate Transformers Security computer crime

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Secured Node Identification Approach Based on Artificial Neural Network Infrastructure for Wireless Sensor Networks

Secured Node Identification Approach Based on Artificial Neu...

引用

international conference on Electrical Energy Systems (ICEES)

作者： S Caleb. S.John Justin Thangaraj Department of Computer Science and Engineering Saveetha School of Engineering Saveetha institute of medical and technical Sciences(SIMATS) Chennai India

It can detect ambient conditions and convey data for processing purposes; In recent years, the wireless sensor network has surpassed all other networks in popularity. The implementation of WSNs is fraught with several significant obstacles, such as concerns over energy usage and safety. WSNs are potentially vulnerable to a wide variety of assaults, any one of which might compromise their capacity for reliable communication or lead to the loss of sensitive data. Consequently, as the network deployment gets more extensive and intricate, there is a massive increase in the requirement for intrusion detection-based energy-efficient approaches. The effectiveness of the networks may be evaluated via the use of Qualnet simulation. Using an artificial neural network and a MATLAB Simulink model, this study intends to improve the effectiveness of a power-based intrusion detection strategy. The results reveal that WSN’s detection of intrusions is enhanced by using an ideal technique inspired by biological nervous systems. Not only that, but the unguarded nodes are having a negative effect on network performance and producing disturbances in the network’s behavior. Both methods use regression analysis to distinguish between fully protected and partially protected nodes. Therefore, the packet delivery ratio and the power consumption of the network may be used for accurate node identification in an artificial neural network.

关键词： Wireless sensor networks Software packages Biological system modeling Intrusion detection Artificial neural networks Energy efficiency Regression analysis

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Research on Safety of Operation and Maintenance of Utility Tunnel based on BIM and computer Technology 2

Research on Safety of Operation and Maintenance of Utility T...

引用

2020 2nd international conference on computer, Communications and Mechatronics Engineering, CCME 2020

作者： Huang, Ping Deng, Xi Huang, Wei Lin, Qiuhui College of Environment and Resources Fuzhou University Fuzhou Fujian China Department of Business Administration Straits Institute of Minjiang University Fuzhou Fujian China Institute of Cross-Strait Higher Education Cooperation and Exchange Minjiang University Fuzhou Fujian China Co. Ltd. Fuzhou Fujian China

The purpose of this study is to ensure the safety of operation and maintenance of utility tunnel. First of all, the framework of safety management system in operation and maintenance phase of utility tunnel is constructed by combining BMI technology, and the Access database tool integrates the operation and maintenance data of utility tunnel with BIM technology to establish a BIM-based utility tunnel operation and maintenance database. On this basis, the BIM model of an utility tunnel is constructed by using Autodesk Revit modeling software. Finally, the application of the safety management model in visualization, safety education and fire simulation of operation and maintenance system of utility tunnel is verified. © Published under licence by IOP Publishing Ltd.

关键词： Maintenance

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An Efficient Lane Line Detection Method Based on computer Vision 7

An Efficient Lane Line Detection Method Based on Computer Vi...

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

作者： Zhu, H.G. China Highway Engineering Consulting Corporation Beijing China

Current approaches of using neural networks in lane departure warning systems are expensive. And it is difficult for neural networks to process 2K and 4K images. In this paper, we use a series of image preprocessing techniques such as perspective transformation, threshold processing and mask operation to process high-resolution images and the optimized sliding window method to fit the lane lines. Compared with neural network method, we can not only reduce hardware cost, but also quickly process high-resolution images. In addition, compared with the traditional lane line detection algorithm, we extract the region of interest through perspective transformation, which not only greatly reduces computation, but also converts images into an aerial view for subsequent processing. Especially, we carry out threshold operation and mask operation after perspective transformation, which greatly improves the performance of our algorithm in a strongly interfering environment. As can be seen from the experimental results, our method has good detection effect and can be applied to various road sections in different environments. © Published under licence by IOP Publishing Ltd.

关键词： Antennas

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Research on Image Super-resolution Reconstruction Based on Deep Learning 7

Research on Image Super-resolution Reconstruction Based on D...

引用

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

作者： Zhang, Yaobin Zhang, Zhiheng Li, Tingle Computer Science and Engineering South China University of Technology Guangzhou Guangdong510006 China Department of Electrical Engineering Shandong University of Science and Technology Jinan Shandong250031 China College of Computer Science and Technology Tianjin Polytechnic University Tianjin300387 China

Image super-resolution processing technology refers to the technology of reconstructing high-resolution images by using low-resolution images with mutual displacement of multiple frames of the same scene. At present, image super-resolution processing technology is widely used in image reconstruction in various fields, such as: medical images, remote sensing images, robot vision, etc. In recent years, deep learning has also been widely used in various fields, especially in computer vision and speech processing. Since image super-resolution reconstruction the method of deep learning is introduced into the technology. Due to the good performance advantages of the deep learning method, it has become an important method for the research of image superresolution reconstruction technology. In this paper, the current status of domestic and foreign research on image super-resolution reconstruction is first simplified. Then, the theory of deep learning was explained, mainly the artificial neural network theory, the related theory of super-resolution reconstruction based on deep learning, and the method of image super-resolution reconstruction based on deep learning. © Published under licence by IOP Publishing Ltd.

关键词： Image reconstruction

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Extended Urban Cell Transmission Model Using Agent-based modeling 11

Extended Urban Cell Transmission Model Using Agent-based Mod...

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11th international conference on Ambient Systems, Networks and Technologies (ANT) / 3rd international conference on Emerging Data and Industry 4.0 (EDI)

作者： Kim, Yeeun Choi, Seongjin Yeo, Hwasoo Korea Adv Inst Sci & Technol KAIST 291 Daehak Ro Daejeon South Korea New York Univ Abu Dhabi Abu Dhabi U Arab Emirates

In this study, we propose an extended Urban Cell Transmission Model (UCTM) that uses the agent concept to handle complex traffic behavior such as signalized intersections in urban arterial traffic. In particular, the proposed model accounts for the turning and traffic signal modeling in intersections, and the lane-changing behavior. The proposed model replicates the periodical queue generation and dissipation caused by the traffic signal at the intersection. For a realistic lane-changing behavior, we define two types of lane-changing depending whether to follow the route or to obtain additional benefits from the travel time. The model is validated with the NGSIM arterial dataset and the results show that the performance of the proposed model replicates the overall urban traffic phenomena adequately. (C) 2020 The Authors. Published by Elsevier B.V.

关键词： urban traffic simulation mesoscopic traffic simulation cell transmission model agent-based modeling

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Tactile Network Resource Allocation Enabled by Quantum Annealing Based on ILP modeling

Tactile Network Resource Allocation Enabled by Quantum Annea...

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Quantum Computing and Engineering (QCE), IEEE international conference on

作者： Arthur Witt Christopher Körber Andreas Kirstädter Thomas Luu Institute of Communication Networks and Computer Engineering University of Stuttgart Stuttgart Germany Institute of Theoretical Physics II Ruhr-University Bochum Bochum Germany Fraunhofer Research Institution for Energy Infrastructures and Geothermal Systems IEG Bochum Germany Forschungszentrum Jülich Institute for Advanced Simulation (IAS-4) & JARA HPC Jülich Germany

Agile networks with fast adaptation and reconfiguration capabilities are required for on-demand provisioning of various network services. We propose a new methodical framework for short-time network optimization based on quantum computing (QC) and integer linear program (ILP) models, which has the potential of realizing a real-time network automation. We define methods to map a nearly real-world ILP model for resource provisioning to a quadratic unconstrained binary optimization (QUBO) problem, which is solvable on quantum annealer (QA). We concentrate on the three-node network to evaluate our approach and its obtainable quality of solution using the state-of-the-art quantum annealer D-Wave Advantage™ 5.2/5.3. By studying the annealing process, we find annealing configuration parameters that obtain feasible solutions close to the reference solution generated by the classical ILP-solver CPLEX. Further, we studied the scaling of the network problem and provide estimations on quantum annealer's hardware requirements to enable a proper QUBO problem embedding of larger networks. We achieved the QUBO embedding of networks with up to 6 nodes on the D-Wave Advantage™. According to our estimates a real-sized network with 12 to 16 nodes require a QA hardware with at least 50000 qubits or more.

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