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IEEE 25th International conference on Intelligent Transportation Systems (ITSC)

作者： Kacem, Thabet Barreto, Alexandre B. Costa, Paulo Wijesekera, Duminda Univ Dist Columbia Comp Sci Washington DC 20008 USA George Mason Univ C4I & Cyber Ctr Affiliate Fac Fairfax VA 22030 USA

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

The emergence of Automatic Dependent Surveillance-Broadcast (ADS-B) caused a revolution in Air Traffic control (ATC) thanks to the numerous benefits this protocol provides, especially when compared to traditional surveillance technologies. Notably, ADS-B offers improved location accuracy from its use of GPS while reducing operational and maintenance costs. Despite these advantages, ADS-B's open broadcast of clear-text messages resulted in several vulnerabilities that negatively affected its widespread usage. In previous work, we proposed ADS-Bsec as a framework that leverages technologies such as cryptography, location verification and artificial intelligence to address the core of such vulnerabilities while keeping compatibility with the original protocol. However, air traffic services require aircraft crossing different authorities' zones to obtain additional authorization tokens, especially during international flights, thus imposing the need for ADS-Bsec to have a key management scheme that addresses this added layer of complexity. This paper presents a solution for this issue that extends the ADS-Bsec framework with the proposed implementation of a key management module based on our prior work on the key exchange protocol. The proposed module exchanges and manages keys to be used in the message verification process for each Flight Information Region (FIR) the aircraft goes through during its flight. We evaluate our ideas with a simulation of a real-world scenario based on actual data from a flight departing New York JFK airport and landing at Los Angeles LAX airport. We provide an analysis and a discussion of the results.

关键词： Protocols Atmospheric modeling Surveillance Traffic control Airports data models Robustness

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Delay Bound analysis of Wireless Train control and Monitoring System Using Stochastic Network Calculus 25

Delay Bound Analysis of Wireless Train Control and Monitorin...

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IEEE 25th International conference on Intelligent Transportation Systems (ITSC)

作者： Yu, Chengxiao Lin, Siyu Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing Peoples R China Beijing Jiaotong Univ Frontiers Sci Ctr Smart High Speed Railway Syst Beijing Peoples R China

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

Wireless train control and monitoring system (WTCMS) introduces wireless communication technology on the basis of traditional TCMS, which is responsible for monitoring the operation status of train equipment in highspeed trains. The delay of WTCMS has great influence on the operation safety of high-speed trains. In order to ensure the requirement of information transmission in real time, we analyze the stochastic delay bound of WTCMS using stochastic network calculus (SNC). For stochastic arrival curve of WTCMS, periodic traffic model and Poisson traffic model are used to describe process data and message data of WTCMS, respectively. The impairment process model and Markov onoff model are used to denote the stochastic service curve of the wireless channel. And we represent the service curve of wired transmission network by combining the Latency-Rate model and the service priority model. Based on the moment generating function (MGF) method in SNC, the upper delay bounds of WTCMS are derived according to stochastic arrival curve and service curve. The theoretical analysis is validated by simulations, which shows that the delay performance of WTCMS meet the delay requirements.

关键词： WTCMS stochastic network calculus delay analysis high-speed train

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Deep learning algorithm of clustering analysis in IUR teaching system 3

Deep learning algorithm of clustering analysis in IUR teachi...

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3rd International conference on Advanced Algorithms and Signal Image processing, AASIP 2023

作者： Liu, Q.I. Gao, Zheng Zhang, Yun Dongguan City University Dongguan China Nanchang Normal College of Applied Technology Nanchang China Universiti Utara Malaysia Sintok Malaysia

ISBN: (纸本)9781510668522

Optimized data analysis methods can enhance teaching system efficiency. The optimization algorithm has spontaneous recognition of high-dimensional data sparsity in the density peak clustering information. This study proposed a deeplearning algorithm in the density peak clustering analysis of the IUR teaching system, which has the advantages of fast calculation speed and dynamic data update. The research is based on the k-means clustering method to select IUR teaching system loads, and the pheromone parameter is used as an influencing factor in the clustering process. The proposed algorithm can better implement teaching data analysis across systems. In addition, the improved algorithm has low complexity and strong operability. The innovative elements of the IUR teaching systems such as renewable subjects, R&D resource input, and innovative teaching management can be controlled collaboratively. In the experimental analysis, the proposed algorithm can further strengthen the quantitative analysis of the IUR teaching system configuration, improve the refinement method for the effective control and distribution of innovative teaching systems, and fully exploit the data resources for the combination of innovative applications and teaching systems development. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep learning

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Research on Accuracy analysis and Simulation of Visual-Integrated Composite Robots

Research on Accuracy Analysis and Simulation of Visual-Integ...

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Robotics, Artificial Intelligence and Intelligent control (RAIIC), International conference on

作者： Yuanchao Zhu Mingming Liu Nanjing Research Institute of Electronics Technology Nanjing China

ISBN: (数字)9798350352627

ISBN: (纸本)9798350352634

A comprehensive study was conducted on the modeling, analysis, and simulation of overall system errors in response to the complex issue of error propagation and high control difficulty in visual-integrated composite robots. Force analysis was performed to determine the conditions under which the Automated Guided Vehicle (AGV) would not tip over during operation. The current accuracy status and causes of errors in each subsystem were summarized, followed by modeling and analyzing the overall system errors. The impact of static deformation and impact acceleration on composite robots was analyzed using ANSYS. MATLAB was used to perform numerical simulation and modeling of the visual-based robotic arm control system, generating 1000 sets of random data within the range of subsystem errors. The errors produced by the AGV and the robotic arm were combined and compared with the actual errors of the composite robot system, thereby verifying the correctness and effectiveness of the overall system error analysis method and providing theoretical guidance for the error analysis in visual-integrated composite robot systems.

关键词： Analytical models Accuracy Remotely guided vehicles Error analysis Reviews Manipulators Numerical simulation

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Intelligent modeling of Temperature Profile for Sustainable Food Waste Composting 6

Intelligent Modeling of Temperature Profile for Sustainable ...

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6th International conference on Applied Computational Intelligence in Information Systems, ACIIS 2023

作者： Lai, Jia Chi Lung Then, Yi Hwang, Siaw San Swinburne University of Technology Sarawak Campus Faculty of Engineering Computing & Science Sarawak Kuching93350 Malaysia Universiti Malaysia Sarawak Faculty of Engineering Kota Samarahan Sarawak 94300 Malaysia

ISBN: (纸本)9798350317428

The composting process exhibits dynamic changes in environmental variables due to underlying biological and physiochemical mechanisms, adding complexity to its modeling. This work focuses on developing a mathematical model for food waste composting in forced continuous aeration conditions. The model incorporates substrate degradation with microbial kinetics, heat balance, and mass balance to address the complexity. In this study, we compare the performance of nth order kinetics against first-order kinetics in predicting temperature variations during food waste composting. Additionally, a comparison is made between nth order kinetics and Monod kinetics for forecasting temperature variations in manure waste composting. The six-stage with fifth order ODE solver (ode45) in MATLAB is employed to numerically solve the differential equations and generate temperature profiles. The developed model successfully predicts peak temperature and the time taken to reach it, enabling better temperature control during the thermophilic phase. This control is vital for avoiding excessive temperatures that can inhibit microbial activities. Comparison of experimental and simulation data, using RRMSE and MAE validation, demonstrates good agreement in the performance of the nth order model when utilizing experimental heat of reaction and proposed kinetics. To further enhance the predictive model for composting processes, it is suggested to expand the nth order model to incorporate other factors such as oxygen concentration, pH, and moisture content. This expansion can contribute to improved prediction accuracy and performance. By employing intelligent and resilient digital innovations, this research strives to advance sustainable living practices in the domain of food waste composting. © 2023 IEEE.

关键词： Temperature control

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Distributed Blockchain-SDN Models for Robust data Security in Cloud-Integrated IoT Networks

Distributed Blockchain-SDN Models for Robust Data Security i...

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Automation, Computing and Renewable Systems (ICACRS), International conference on

作者： Koya Haritha Sai Srinivas Vellela Roja D Lakshma Reddy Vuyyuru Nallapu Malathi Lavanya Dalavai Dept. of CSE-Data Science Chalapathi Institute of Technology Guntur AP India Dept. of CSE KoneruLakshmaiah Education Foundation Vaddeswaram AP India Dept. of CSE-DS KKR & KSR Institute of Technology and Sciences Guntur AP India

ISBN: (数字)9798331532420

ISBN: (纸本)9798331532437

Blockchain and SDN are combined in the "DistB-SD Cloud" architecture to secure and execute cloud-integrated IoT data. Cloud Computing Management and Services, Distributed Secure Blockchain Methodology, SDN Environment, and data Extraction comprise the architecture. SDN-enabled devices safely gather and process sensor data in the data plane, while OpenFlow and OpenStack handle network component communication in the control plane. The application layer improves network administration with dynamic configuration and data analytics. Distributed nodes and hash chains ensure system integrity in blockchain-based access control and ledger maintenance. Blockchain and SDN improve security, privacy, and scalability by resisting attacks. The architecture outperforms OpenFlow-based SDN models in throughput and bandwidth, proving its stability under different network conditions. The study shows that the suggested "DistB-SD Cloud" achieves increased throughput (22.1 KB/s) and bandwidth (1.9 GB/s) when nodes and packet arrival rates increase, making it a feasible solution for safe and scalable cloud computing in IoT-based systems.

关键词： Cloud computing Renewable energy sources Computational modeling Scalability process control Computer architecture Bandwidth Throughput Stability analysis Blockchains

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modeling OF FORCED AND NATURAL CONVECTION DRYING process OF A COFFEE SEED

JOURNAL OF THE ASABE

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JOURNAL OF THE ASABE 2022年第5期65卷 1061-1070页

作者： Duque-Dussan, Eduardo Villada-Dussan, Andres Roubik, Hynek Banout, Jan Czech Univ Life Sci Prague Fac Trop AgriSci Dept Sustainable Technol Kamycka 129 Prague 16500 Czech Republic Exponent Failure Anal Associates Inc Menlo Pk CA USA

Different coffee drying technologies face complex tasks in ensuring an acceptable final seed moisture content. This research performed a Finite Element analysis (FEA) study, simulating a single coffee bean's drying process as a transient mass diffusion model under mechanical and natural convection conditions, so the drying behavior and data of both case scenarios can be foreseen and controlled by a predictive Finite Element Model (FEM). A wet bean was 3D-scanned and digitized as the FEA simulation geometry;the water diffusion between the grain and the atmosphere was defined by a diffusion coefficient subject to the drying air temperature and the grain's moisture content. Three cases were studied: mechanical grain drying at three different temperatures (50, 45, and 40 degrees C) in a forced convection environment;variable natural convection drying under environmental conditions (wet and dry season);and constant natural convection (wet and dry season), including the variation in day/night temperature and relative humidity. The results agree well with the data found in the literature, obtaining the graphical moisture distribution of the phenomena, predictive drying curves, diffusion coefficients, and isotherms. Both simulated drying scenarios provide essential information for coffee growers to improve and control their drying processes, thus obtaining high-quality grains, reducing contamination by microorganisms, and ensuring the integrity of their products.

关键词： Coffea arabica Coffee Drying Coffee Seed Finite Element Model Moisture Diffusion

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Optimization of the Public Transport System Using data analysis Methods 4

Optimization of the Public Transport System Using Data Analy...

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4th International conference on control Systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2022

作者： Kasatkina, Ekaterina Vavilova, Daiana Ketova, Karolina Institute of Informatics and Computer Engineering Kalashnikov Izhevsk State Technical University Izhevsk Russia Kalashnikov Izhevsk State Technical University Faculty of Mathematics and Natural Sciences Izhevsk Russia

ISBN: (数字)9781665456593

ISBN: (纸本)9781665456593

The system of public transport movement in the urban environment has been investigated using modern methods of data analysis. This approach allows to optimize the work of public transport and thereby improve the quality of population life. When this problem is decided, for the first time, such an interdisciplinary approach is used, which combines elements of linear algebra, graph theory and methods of statistical information processing. Possible problem solutions of planning the topology in public transport system are proposed to overcome the problem of the presence of duplicating routes, depending on their duplication coefficients. The practical task of data analysis of the public transport traffic pattern in order to identify duplicate routes was solved for the system of the city of Izhevsk (Udmurt Republic). The studied transport system includes 323 stopping points and 55 routes of urban public transport. The information presented on the site of the interactive geoinformation system (IGIS) was used in the numerical calculations. The routes duplication coefficients were calculated by the methods of correlation analysis, and their significance was assessed by the Student's criterion. Based on the coefficients and duplicating routes variants, specific methods for solving the problem of planning the topology of a transport network are proposed. Calculations are shown that in order to overcome the problem of duplication of routes in the public transport system of Izhevsk, more than 28 routes should be synchronized, and 6 public transport routes should be replaced by 3 routes as a result of their partial merging. © 2022 IEEE.

关键词： Graph theory

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Research on Risk analysis Method of Industrial Fieldbus Based on data analysis

Research on Risk Analysis Method of Industrial Fieldbus Base...

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2022 International conference on Internet of Things and Machine Learning, IoTML 2022

作者： Lu, Lijun Jin, Weifeng Zhang, Chuangxun Yu, Huafeng Ren, Yilin Zhejiang Chitic Control Engineering Co. Ltd 310018 China Xi'an Jiaotong University 710049 China Hangzhou Pulse Wave Technology. Ltd 310018 China

ISBN: (纸本)9781510664913

As an industrial field bus, CAN bus has the characteristics of high real-time and high reliability. This chapter analyzes the risk situation by using CAN bus through the research on the actual situation of the industrial field. First of all, we understand and analyze the actual situation of industrial field and CAN bus;Secondly, the risk assessment model is designed and applied to the actual risk assessment process;Finally, the risk assessment model is used to analyze the countermeasures and specific suggestions that need to be improved at present. © 2023 SPIE.

关键词： Risk assessment

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A Framework for Cloud Inspection of Complex Mechanical Parts

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IEEE ACCESS 2021年 9卷 12932-12942页

作者： Liu, Rui Duan, Gui-Jiang Beihang Univ Sch Mech Engn & Automat Beijing 100191 Peoples R China

Inspection plays an important role in quality control and trust of manufacturing service in the cloud manufacturing (CMfg) paradigm. To provide an inspection service for complex mechanical parts in CMfg, the concept of cloud inspection was defined as a multi-dimension extension of CMfg. A framework of cloud inspection consisting of the physical resource layer, the cloud inspection platform, and the application layer was constructed. The data model of cloud inspection, including the role model, resource model, and business model was constructed. Besides, a 4-phrase process model was built by integrating digital inspection technology into the cloud manufacturing environment. Inspection resources including hardware resources, software resources, and knowledge resources were connected to the cloud inspection platform. A four-level model was proposed for the encapsulation of inspection services. Enable toolsets for cloud inspection of complex mechanical parts, including the inspection planning toolset, measurement programming toolset, inspection process monitor toolset, and data analysis toolset were encapsulated. A prototype system was developed. A case study was given to verify the effectiveness and feasibility of the proposed framework. The framework for cloud inspection provides a solution for the inspection business of mechanical parts in CMfg.

关键词： Inspection data models Manufacturing Cloud computing Solid modeling Software Licenses Cloud inspection cloud manufacturing data model process model complex mechanical part

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