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Full-Text Articles in Computer Sciences

Estonian Internet Voting With Anonymous Credentials, İsa Sertkaya, Peter Roenne, Peter Y. A. Ryan Feb 2022

Estonian Internet Voting With Anonymous Credentials, İsa Sertkaya, Peter Roenne, Peter Y. A. Ryan

Turkish Journal of Electrical Engineering and Computer Sciences

The Estonian Internet voting (EIV) scheme is a unique example of a long-term nation-wide, legally binding electronic voting deployment. The EIV scheme is used in parallel with standard paper-based election day voting, of course invalidating an already cast i-vote. This necessarily requires careful authentication of the eligible voters and makes the Estonian identity card solution a crucial part of the scheme, however, note that Parsovs has recently drawn attention to the security flaws found in Estonian ID-cards. In this study, we propose an e-voting scheme EIV-AC that integrates the EIV scheme with anonymous credentials based on self-sovereign identity. In addition …

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Forming A Decentralized Research Network: Ds4h, Eni̇s Karaarslan, Meli̇h Bi̇ri̇m, Hüseyi̇n Emre Ari Feb 2022

Forming A Decentralized Research Network: Ds4h, Eni̇s Karaarslan, Meli̇h Bi̇ri̇m, Hüseyi̇n Emre Ari

Turkish Journal of Electrical Engineering and Computer Sciences

There is a trend toward decentralized systems, but these systems are developed without conducting enough software tests. Also, the performance, scalability, and sustainability of the decentralized systems are not taken into account. One of the reasons is the time-consuming testing process. The other is the hardware requirements and the complexity of the software installations of the testing environment. Developer communities need stable and secure research networks to test and develop prototypes before releasing the working versions. Cloud-based blockchain test networks are available, but it allows using a specific framework. Also, users are required to learn how to use each framework. …

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Data Immutability And Event Management Via Blockchain In The Internet Of Things, Hakan Altaş, Gökhan Dalkiliç, Umut Can Çabuk Feb 2022

Data Immutability And Event Management Via Blockchain In The Internet Of Things, Hakan Altaş, Gökhan Dalkiliç, Umut Can Çabuk

Turkish Journal of Electrical Engineering and Computer Sciences

The Internet of things (IoT) is the key enabler of the smart systems used in many areas, from agriculture to aviation, industrial automation to autonomous vehicles. Most IoT deployments employ cost-efficient lightweight devices with limited resources (e.g., bandwidth, energy, storage). Although an IoT network must be built in its simplest form, engineers include more sophisticated devices like gateways and servers to provide web-based services and benefit from cloud systems. So, although the nodes can be widely distributed geographically or topologically, the system becomes centralized, which causes bottlenecks and single-points-of-failure. Furthermore, providing data integrity, nonrepudiation, and event management becomes tricky. In …

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Joint Bidding Decision Of Wind Farms And Energy Storage Based On Newsvendor Model, Xinyue Sun, Jian Liu, Meng Ou, Yanyan Liu Feb 2022

Joint Bidding Decision Of Wind Farms And Energy Storage Based On Newsvendor Model, Xinyue Sun, Jian Liu, Meng Ou, Yanyan Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Currently, renewable energy generation has received more and more attention. This article focuses on wind energy generation, one of the renewable energy sources. Aiming at the intermittent and unpredictable wind power problems, according to the day ahead bidding mechanism in the power market, this paper introduces the energy storage system to maximize wind power merchants profit based on the newsvendor model. First, this paper focuses on the wind farms combined with storage system to put forward the optimal bidding decision of selling or buying electricity to the market one day in advance and the optimal bidding amount. Then, we analyze …

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Privacy In Blockchain Systems, Murat Osmanoğlu, Ali̇ Aydin Selçuk Feb 2022

Privacy In Blockchain Systems, Murat Osmanoğlu, Ali̇ Aydin Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Privacy of blockchains has been a matter of discussion since the inception of Bitcoin. Various techniques with a varying degree of privacy protection and complexity have been proposed over the past decade. In this survey, we present a systematic analysis of these proposals in four categories: (i) identity, (ii) transaction, (iii) consensus, and (iv) smart contract privacy. Each of these categories have privacy requirements of its own, and various solutions have been proposed to meet these requirements. Almost every technique in the literature of privacy enhancing technologies have been applied to blockchains: mix networks, zero-knowledge proofs, blind signatures, ring signatures, …

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Permissioned Blockchain Based Remote Electronic Examination, Öznur Kalkar, İsa Sertkaya Feb 2022

Permissioned Blockchain Based Remote Electronic Examination, Öznur Kalkar, İsa Sertkaya

Turkish Journal of Electrical Engineering and Computer Sciences

Recent coronavirus pandemic transformed almost all aspects of daily life including educational institutions and learning environments. As a result, this transformation brought remote electronic examination (shortly e-exam) concepts back into consideration. In this study, we revisit secure and privacy preserving e-exam protocol proposals and propose an e-exam protocol that utilizes decentralized identity-based verifiable credentials for proof of authentication and public-permissioned blockchain for immutably storing records. In regard to the previously proposed e-exam schemes, our scheme offers both privacy enhancement and better efficiency. More concretely, the proposed solution satisfies test answer authentication, examiner authentication, anonymous marking, anonymous examiner, question secrecy, question …

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Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead Jan 2022

Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead

Engineering Faculty Articles and Research

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …

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Hyperparameter Optimization For Covid-19 Chest X-Ray Classification, Ibraheem Hamdi, Muhammad Ridzuan, Mohammad Yaqub Jan 2022

Hyperparameter Optimization For Covid-19 Chest X-Ray Classification, Ibraheem Hamdi, Muhammad Ridzuan, Mohammad Yaqub

Computer Vision Faculty Publications

Despite the introduction of vaccines, Coronavirus disease (COVID-19) remains a worldwide dilemma, continuously developing new variants such as Delta and the recent Omicron. The current standard for testing is through polymerase chain reaction (PCR). However, PCRs can be expensive, slow, and/or inaccessible to many people. X-rays on the other hand have been readily used since the early 20th century and are relatively cheaper, quicker to obtain, and typically covered by health insurance. With a careful selection of model, hyperparameters, and augmentations, we show that it is possible to develop models with 83% accuracy in binary classification and 64% in multi-class …

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Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor Jan 2022

Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor

Faculty Publications

This paper presents a method to estimate the covariances of the inputs in a factor-graph formulation for localization under non-line-of-sight conditions. A general solution based on covariance estimation and M-estimators in linear regression problems, is presented that is shown to give unbiased estimators of multiple variances and are robust against outliers. An iteratively re-weighted least squares algorithm is proposed to jointly compute the proposed variance estimators and the state estimates for the nonlinear factor graph optimization. The efficacy of the method is illustrated in a simulation study using a robot localization problem under various process and measurement models and measurement …

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Transformers In Medical Imaging: A Survey, Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat, Fahad Shahbaz Khan, Huazhu Fu Jan 2022

Transformers In Medical Imaging: A Survey, Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat, Fahad Shahbaz Khan, Huazhu Fu

Computer Vision Faculty Publications

Following unprecedented success on the natural language tasks, Transformers have been successfully applied to several computer vision problems, achieving state-of-the-art results and prompting researchers to reconsider the supremacy of convolutional neural networks (CNNs) as de facto operators. Capitalizing on these advances in computer vision, the medical imaging field has also witnessed growing interest for Transformers that can capture global context compared to CNNs with local receptive fields. Inspired from this transition, in this survey, we attempt to provide a comprehensive review of the applications of Transformers in medical imaging covering various aspects, ranging from recently proposed architectural designs to unsolved …

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Preface To Topic “Build And Strengthen China’S Information Tech-System”, Guojie Li, Ninghui Sun Jan 2022

Preface To Topic “Build And Strengthen China’S Information Tech-System”, Guojie Li, Ninghui Sun

Bulletin of Chinese Academy of Sciences (Chinese Version)

Self-reliance and self-strengthening at high level does not depend on a single technique, but on the formation of an advantageous national tech-system, so called "country-as-a-platform". Information tech-system refers to the whole one that closely connects devices, components, complete machine, system software, middleware, and application software with a series of technical standards and intellectual property rights. We are entering the IT 3.0 era characterized by integration of human-cyber-physical world. The IT 3.0 era will certainly produce a new tech-system different from the IT 1.0 and IT 2.0 eras, which is a rare opportunity for China to build a self-reliance and self-strengthening …

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Thoughts On New It Technique System, Ninghui Sun Jan 2022

Thoughts On New It Technique System, Ninghui Sun

Bulletin of Chinese Academy of Sciences (Chinese Version)

The world is entering a new period of information society dominated by digital economy. To adapt to the requirements of the new development stage of China, and to achieve the key technologies development, it is necessary to accelerate the construction of a new selfreliance and self-improvement IT technique system. The article gives some thoughts on the demand, principle, and key method on above issues, and the new paradigm of research at Institute of Computing Technology, Chinese Academy of Sciences.

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From Chip Design To Chip Learning, Yunji Chen, Zidong Du, Qi Guo, Wei Li, Yijun Tan Jan 2022

From Chip Design To Chip Learning, Yunji Chen, Zidong Du, Qi Guo, Wei Li, Yijun Tan

Bulletin of Chinese Academy of Sciences (Chinese Version)

Chip is the foundation of the modern information society. As the world is entering a new era of human-cyber-physical ternary computing, with diverse intelligent applications over trillions of devices, chip with specialized architecture will be heavily demanded in both numbers and types. However, chip design is very costly, which usually requires a long design cycle, complicated process, and high professional developers. Hence, there is a large gap between the need of tremendous chips and the high cost of chip design in the new era. This study proposes Chip Learning, a learning-based method to perform the entire chip design, including logic …

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Opportunities And Challenges Of Building Cpu Ecosystem With Open-Source Mode, Yungang Bao, Ninghui Sun Jan 2022

Opportunities And Challenges Of Building Cpu Ecosystem With Open-Source Mode, Yungang Bao, Ninghui Sun

Bulletin of Chinese Academy of Sciences (Chinese Version)

RISC-Ⅴ has been obtained huge attentions and extensively invested over the past decade due to its exciting slogan that "Instruction Sets Want to be Free". Based on RISC-Ⅴ, we are able to build a "human community with a shared future" in the CPU chip area, although there are still many challenges. China should explore its capability to make more contributions in building the open-source chip ecosystem.

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Ubiquitous Operating System: Toward The Blue Ocean Of Human-Cyber-Physical Ternary Ubiquitous Computing Mei, Hong Mei, Donggang Cao, Tao Xie Jan 2022

Ubiquitous Operating System: Toward The Blue Ocean Of Human-Cyber-Physical Ternary Ubiquitous Computing Mei, Hong Mei, Donggang Cao, Tao Xie

Bulletin of Chinese Academy of Sciences (Chinese Version)

In response to the new patterns and scenarios of future human-cyber-physical ternary ubiquitous computing, a new kind of operating system named Ubiquitous Operating System (UOS) is emerging and under exploration for further development. The human-cyberphysical ternary ubiquitous computing has many new features, such as open and dynamic environment, diverse requirements, and complex application scenarios. New ubiquitous applications pose special demands on ubiquitous sensing and connection, lightweight computing and artificial intelligence, dynamic adaptation, feedback and control, natural human-computer-interaction, etc. To support these new requirements, a software definition mechanism is in need to flexibly control hardware, data resources, platforms, and applications. This …

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Thoughts On Innovation Of Future Network Architecture, Yunjie Liu, Tao Huang, Shou Wang Jan 2022

Thoughts On Innovation Of Future Network Architecture, Yunjie Liu, Tao Huang, Shou Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Currently, network technology is deeply integrated with the physical world. Traditional network architectures cannot support the differentiated, customizable, and deterministic needs of industrial Internet and other services. Exploring new network architecture and core technology has officially become the strategic commanding heights of the global Internet competition. To this end, the paper reviews the evolution and trends of the network, analyzes how to achieve high-performance, low-cost, intelligent network development strategies for establishing an autonomous and controllable future network. Two conclusions are drawn as follows. (1) Through the exploration of network construction in recent decades, integration, openness, intelligence, customization and integration of …

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Information Superbahn: Towards New Type Of Cyberinfrastructure, Zhiwei Xu, Guojie Li, Ninghui Sun Jan 2022

Information Superbahn: Towards New Type Of Cyberinfrastructure, Zhiwei Xu, Guojie Li, Ninghui Sun

Bulletin of Chinese Academy of Sciences (Chinese Version)

The world is entering a new era of human-cyber-physical ternary computing with diverse intelligent applications over trillions of devices. This calls for a new type of cyberinfrastructure characterized by a planet-scale, high-goodput, low-entropy computing network, colloquially named Information Superbahn. This article highlights the vision of Information Superbahn, including fundamental requirements, key scientific problems, and a candidate system architecture. The goal of building the Information Superbahn is to natively support humancyber-physical systems and low-entropy computing modes, to reduce the effects of systems disorder. Compared with existing network computing systems, such as Internet, cloud computing, big data and Internet of Things, Information …

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Improving Cyberspace Security Situation From Perspective Of “Talent, Finance And Infrastructure”, Binxing Fang Jan 2022

Improving Cyberspace Security Situation From Perspective Of “Talent, Finance And Infrastructure”, Binxing Fang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Cyberspace security has been an important part in ensuring economic development and supporting the progress of modern science and technology. As more and more applications are relying on information technology (IT), it becomes very important to improve the security situation of cyberspace. How to take effective measures to practically improve the cyberspace security situation has become the core problem disscussed in this paper. This paper addresses it from the perspectives of "talent, finance and infrastructure". First, on the premise of insufficient supply of cyberspace security talents, this paper proposes to establish the ability certification of talents transferred from other IT …

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Thinking On New System For Big Data Technology, Xueqi Chegn, Shenghua Liu, Ruqing Zhang Jan 2022

Thinking On New System For Big Data Technology, Xueqi Chegn, Shenghua Liu, Ruqing Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

In recent years, there are such significant improvements on the performance and efficiency of big data technology and system. As it is widely applied in various fields, big data has empowered industrial intelligence, and is the key step into the intelligent stage of information society. Therefore, we are facing greater challenges nowadays, such as the paradox of data flooding and high-value data lacking, the complexity and uncertainty of big data analysis, and the difficulty to balance the data on sharing and circulation, and trustworthiness and security. Moreover, these challenges will not only promote the innovation and change of big data …

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A Surrogate Assisted Quantum-Behaved Algorithm For Well Placement Optimization, Jahedul Islam, Amril Nazir, Moinul Hossain, Hitmi Khalifa Alhitmi, Muhammad Ashad Kabir, Abdul-Halim Jallad Jan 2022

A Surrogate Assisted Quantum-Behaved Algorithm For Well Placement Optimization, Jahedul Islam, Amril Nazir, Moinul Hossain, Hitmi Khalifa Alhitmi, Muhammad Ashad Kabir, Abdul-Halim Jallad

All Works

The oil and gas industry faces difficulties in optimizing well placement problems. These problems are multimodal, non-convex, and discontinuous in nature. Various traditional and non-traditional optimization algorithms have been developed to resolve these difficulties. Nevertheless, these techniques remain trapped in local optima and provide inconsistent performance for different reservoirs. This study thereby presents a Surrogate Assisted Quantum-behaved Algorithm to obtain a better solution for the well placement optimization problem. The proposed approach utilizes different metaheuristic optimization techniques such as the Quantum-inspired Particle Swarm Optimization and the Quantum-behaved Bat Algorithm in different implementation phases. Two complex reservoirs are used to investigate …

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Application Of Gravity Data For Hydrocarbon Exploration Using Machine Learning Assisted Workflow, Oluwafemi Temidayo Alaofin Jan 2022

Application Of Gravity Data For Hydrocarbon Exploration Using Machine Learning Assisted Workflow, Oluwafemi Temidayo Alaofin

LSU Master's Theses

Gravity survey has played an essential role in many geoscience fields ever since it was conducted, especially as an early screening tool for subsurface hydrocarbon exploration. With continued improvement in data processing techniques and gravity survey accuracy, in-depth gravity anomaly studies, such as characterization of Bouguer and isostatic residual anomalies, have the potential to delineate prolific regional structures and hydrocarbon basins. In this study, we focus on developing a cost-effective, quick, and computationally efficient screening tool for hydrocarbon exploration using gravity data employing machine learning techniques. Since land-based gravity surveys are often expensive and difficult to obtain in remote places, …

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Deep Learning-Based Quality Assessment Of Clinical Protocol Adherence In Fetal Ultrasound Dating Scans, Sevim Cengiz, Mohammad Yaqub Jan 2022

Deep Learning-Based Quality Assessment Of Clinical Protocol Adherence In Fetal Ultrasound Dating Scans, Sevim Cengiz, Mohammad Yaqub

Computer Vision Faculty Publications

To assess fetal health during pregnancy, doctors use the gestational age (GA) calculation based on the Crown Rump Length (CRL) measurement in order to check for fetal size and growth trajectory. However, GA estimation based on CRL, requires proper positioning of calipers on the fetal crown and rump view, which is not always an easy plane to find, especially for an inexperienced sonographer. Finding a slightly oblique view from the true CRL view could lead to a different CRL value and therefore incorrect estimation of GA. This study presents an AI-based method for a quality assessment of the CRL view …

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Automatic Segmentation Of Head And Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub Jan 2022

Automatic Segmentation Of Head And Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub

Computer Vision Faculty Publications

Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are used to detect and segment the tumor region. Clinically, tumor segmentation is extensively time-consuming and prone to error. Machine learning, and deep learning in particular, can assist to automate this process, yielding results as accurate as the results of a clinician. In this research study, we develop a vision transformers-based method to automatically delineate H&N tumor, and compare its results to leading convolutional neural network (CNN)-based models. We use multi-modal data …

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Is Contrastive Learning Suitable For Left Ventricular Segmentation In Echocardiographic Images?, Mohamed Saeed, Rand Muhtaseb, Mohammad Yaqub Jan 2022

Is Contrastive Learning Suitable For Left Ventricular Segmentation In Echocardiographic Images?, Mohamed Saeed, Rand Muhtaseb, Mohammad Yaqub

Computer Vision Faculty Publications

Contrastive learning has proven useful in many applications where access to labelled data is limited. The lack of annotated data is particularly problematic in medical image segmenta-tion as it is difficult to have clinical experts manually annotate large volumes of data. One such task is the segmentation of cardiac structures in ultrasound images of the heart. In this paper, we argue whether or not contrastive pretraining is helpful for the segmentation of the left ventricle in echocardiography images. Furthermore, we study the effect of this on two segmentation networks, DeepLabV3, as well as the commonly used segmentation net-work, UNet. Our …

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Is It Possible To Predict Mgmt Promoter Methylation From Brain Tumor Mri Scans Using Deep Learning Models?, Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub Jan 2022

Is It Possible To Predict Mgmt Promoter Methylation From Brain Tumor Mri Scans Using Deep Learning Models?, Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub

Computer Vision Faculty Publications

Glioblastoma is a common brain malignancy that tends to occur in older adults and is almost always lethal. The effectiveness of chemotherapy, being the standard treatment for most cancer types, can be improved if a particular genetic sequence in the tumor known as MGMT promoter is methylated. However, to identify the state of the MGMT promoter, the conventional approach is to perform a biopsy for genetic analysis, which is time and effort consuming. A couple of recent publications proposed a connection between the MGMT promoter state and the MRI scans of the tumor and hence suggested the use of deep …

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Challenges In Covid-19 Chest X-Ray Classification: Problematic Data Or Ineffective Approaches?, Muhammad Ridzuan, Ameera Ali Bawazir, Ivo Gollini Navarrete, Ibrahim Almakky, Mohammad Yaqub Jan 2022

Challenges In Covid-19 Chest X-Ray Classification: Problematic Data Or Ineffective Approaches?, Muhammad Ridzuan, Ameera Ali Bawazir, Ivo Gollini Navarrete, Ibrahim Almakky, Mohammad Yaqub

Computer Vision Faculty Publications

The value of quick, accurate, and confident diagnoses cannot be undermined to mitigate the effects of COVID-19 infection, particularly for severe cases. Enormous effort has been put towards developing deep learning methods to classify and detect COVID-19 infections from chest radiography images. However, recently some questions have been raised surrounding the clinical viability and effectiveness of such methods. In this work, we carry out extensive experiments on a large COVID-19 chest X-ray dataset to investigate the challenges faced with creating reliable solutions from both the data and machine learning perspectives. Accordingly, we offer an in-depth discussion into the challenges faced …

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Modeling And Simulation Of Emergency Medical Resources Allocation In Shanghai During Covid-19, Changjia Fan, Yanqiu Du, Liang Di, Hu Kai, Jiayan Huang Jan 2022

Modeling And Simulation Of Emergency Medical Resources Allocation In Shanghai During Covid-19, Changjia Fan, Yanqiu Du, Liang Di, Hu Kai, Jiayan Huang

Journal of System Simulation

Abstract: Modeling and simulating on the allocation of emergency medical resources in Shanghai with COVID-19 is carried out. Based on the SEIR model of infectious diseases, combined with the process of outpatients visiting and inpatients treatment, a SEIOWHR(susceptible-exposed-infected-outpatients- waiting to hospitalized-hospitalized-removed) system dynamics model is established. If the Wuhan epidemic occurred in Shanghai, based on the model, the amount of emergency medical resources needed, the gap time of medical resources and the disease progression of patients who are waiting to hospitalized under the different supply of medical resources is simulated, and the key factors in the allocation of medical …

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A Fast Simulation Method For Ship Target Sar Signal Echo, Yuan Fei, Jianhong Li, Yin Hao, Yuhao Wang, Hong Sheng Jan 2022

A Fast Simulation Method For Ship Target Sar Signal Echo, Yuan Fei, Jianhong Li, Yin Hao, Yuhao Wang, Hong Sheng

Journal of System Simulation

Abstract: In order to meet the application requirements of synthetic aperture radar (SAR) in ocean remote sensing, a fast simulation method for the ship target SAR echo generation is presented, which carries out the accurate electromagnetic modeling to the important ship targets. “Four paths" model is used to calculate the complex echo between the ship target and sea surface, and the facet model is used to model the sea surface backscattering. After the two parts of echoes being synthesized, the SAR echo of whole scene is gotten, and the echo is processed by spot SAR imaging processing algorithm to verify …

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Study On Bidirectional Coupling Of Human Thermal Comfort Parameters And Cabin Thermal Environment, Jue Qu, Dayan Wang, Wang Wei, Sina Dang Jan 2022

Study On Bidirectional Coupling Of Human Thermal Comfort Parameters And Cabin Thermal Environment, Jue Qu, Dayan Wang, Wang Wei, Sina Dang

Journal of System Simulation

Abstract: At present, for the existing cockpit heat system, are studied more the airflow tissue parameters of the thermal environment and the human heat regulation is taken into account less, which leads to the low accuracy of simulation result evaluating the human thermal comfort. Through CFD (computational fluid dynamics) method, energy equation, RANS (reynolds-average navier-stokes) equation, and N-S(navier-stokes) equation, by combining the human temperature distribution with the cabin thermal environment parameters, the cabin heat system model based on the human heat regulation is established. The model considers the interacting influence of the human thermal regulation and the thermal environmental airflow …

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Time-Varying Output Formation Tracking Control Of Discrete-Time Heterogeneous Multi-Agent Systems, Xiaolong Qi, Xuguang Yang Jan 2022

Time-Varying Output Formation Tracking Control Of Discrete-Time Heterogeneous Multi-Agent Systems, Xiaolong Qi, Xuguang Yang

Journal of System Simulation

Abstract: Aiming at the discrete-time heterogeneous multi-agent systems with different dimensions and parameters, the time-varying output formation tracking control is studied by using the output regulation method. Assuming that the multi-agents system is consisted of multiple followers and multiple leaders, and the followers can't obtain the leaders' states, the distributed observers are designed by using the neighboring relative information. Based on the states of the distributed observers, the time-varying output formation tracking protocols and algorithm are presented by using the states feedback, and the sufficient conditions that guarantee the protocols' effectiveness are also given. The simulation results show that, …

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