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4th IFAC Workshop on Distributed Estimation and Control in Networked Systems, NecSys 2013

作者： Borri, A. Dimarogonas, D.V. Johansson, K.H. Di Benedetto, M.D. Pola, G. Rome Italy KTH Royal Institute of Technology School of Electrical Engineering Stockholm Sweden Center of Excellence DEWS Department of Information Engineering Computer Science and Mathematics University of L'Aquila Italy

ISBN: (纸本)9783902823557

This work aims at extending some concepts of symbolic control design to decentralized control structures, with an approximate simulation approach. Symbolic models and controllers are based on abstractions of continuous dynamics where one symbol corresponds to an aggregate of continuous states. We consider a serial interconnection of continuous nonlinear systems and we address the decentralized design of local controllers to accomplish a given specification on the overall system. The results are applied to a vehicle platooning problem, where we jointly fulfill a safety constraint (collision avoidance) and reduce the fuel consumption. Copyright © 2013 IFAC.

关键词： Decentralized control

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A novel method for Centromere and length detection in microscopic images of human chromosomes

A novel method for Centromere and length detection in micros...

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2011 18th Iranian Conference of Biomedical engineering, ICBME 2011

作者： Jahani, Sahar Setarehdan, S. Kamaledin Faculty of Biomedical Engineering Science and Research Branch Islamic Azad University Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781467310055

Many genetic disorders or abnormalities that may occur in the future generations can be predicted through analyzing the shape and morphological characteristics of the human chromosomes. This is usually carried out by an expert, inspecting the Karyotype of the patients. A Karyotype is a particular table that presents the chromosome images in a standard format. To generate a Karyotype, it is necessary to identify each of the 23 pairs of the chromosomes within the microscopic images first. The main step to automate this procedure is the definition of some morphological features for each chromosome. The most common features used for chromosomes identification includes the location of the Centromere and the length of the chromosome. Many other important features, such as Centromeric Index, are usually extracted from the Centromere and length. In this paper, a novel and effective algorithm for Centromere locating and length calculation for the human chromosomes is presented. The proposed algorithm uses the fact that the centromere is the narrowest part of the chromosome. By defining a gray level mask (GLM), which is a linearly varying gray level image along the chromosome longitudinal direction and multiplying it to the binary version of the chromosome image, it is shown that the global minimum in the histogram of the resulted image indicates the location of the centromere. The data set used in this work was provided by the Tesi-Imaging srl in Milan, Italy. A mean value of the absolute error of 3.6 and 5.2 pixels was obtained in identification of the chromosome centromere and length respectively by the proposed method. © 2011 IEEE.

关键词： Chromosomes

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Hybrid Optimization Algorithm in the Photometric Inversion of Periods for Asteroids

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Research in Astronomy and Astrophysics 2023年第5期23卷 66-77页

作者： Xin-Ran Li Yong-Xiong Zhang Hai-Bin Zhao Xiaoping Zhang Xiao-Ping Lu State Key Laboratory of Lunar and Planetary Sciences Macao University of Science and TechnologyMacao 999078China School of Computer Science and Engineering Macao University of Science and TechnologyTaipaMacao 999078China Key Laboratory of Planetary Sciences Purple Mountain ObservatoryCASNanjing 210023China CAS Center for Excellence in Comparative Planetology CASHefei 230026China

Asteroids,as the primitive building blocks for the formation of our solar system,could reveal its evolution mechanism,and have attracted more and more attention from the public and professional institutions in recent *** physical properties,such as rotational period,spin axis and overall shape,can be inverted from ground-and space-based photometric *** the inversion process is very time-consuming,this paper combines the genetic algorithm with the Levenberg–Marquardt(LM) algorithm,and presents a hybrid optimization algorithm based on a Cellinoid shape model for the inversion of rotational periods,which greatly improves the inversion *** proposed hybrid algorithm is applied to the synthetic lightcurves generated for an assumed Cellinoid shape model and the inverted rotational period results are consistent with the preset ones with a reduced search time,compared with the LM ***,multiple numerical experiments on the periods are performed on lightcurves and sparse observations of real asteroids to confirm that the proposed method can perform well in improving computational efficiency.

关键词： astrometry-methods numerical-planets and satellites fundamental parameters

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Automated heart disease prediction using improved explainable learning-based technique

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Neural Computing and Applications 2024年第26期36卷 16289-16318页

作者： Bizimana, Pierre Claver Zhang, Zuping Hounye, Alphonse Houssou Asim, Muhammad Hammad, Mohamed El-Latif, Ahmed A. Abd School of Computer Science and Engineering Central South University Changsha410083 China School of Mathematics and Statistics Central South University Changsha410008 China EIAS Data Science Lab College of Computer and Information Sciences and Center of Excellence in Quantum and Intelligent Computing Prince Sultan University Riyadh11586 Saudi Arabia School of Computer Science and Technology Guangdong University of Technology Guangzhou510006 China Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom Egypt Information Technology Department Faculty of Computers and Information Menoufia University Shebin El-Koom Egypt

Heart disease (HD) stands as a major global health challenge, being a predominant cause of death and demanding intricate and costly detection methods. The widespread impact of heart failure, contributing to increased rates of morbidity and mortality, underscores the urgency for accurate and timely prediction and diagnosis. This is crucial for effective prevention, early detection, and treatment, thereby reducing the threat to individual health. However, the early and precise prediction of HD remains a significant challenge. The complexity of medical data poses a considerable challenge for healthcare professionals, who are required to interpret and utilize this information swiftly for effective intervention. Addressing this gap, our study introduces a novel Improved Explainable Learning-Based Technique (IELBT) for HD prediction. This technique harnesses a strategic combination of feature selection, Venn diagrams, data normalization methods, optimized parameters, and machine learning algorithms, specifically tailored for predicting HD. We evaluated the performance of our model using the Alizadeh Sani HD dataset, aiming to accurately detect the presence or absence of the condition. Our results demonstrate that the IELBT, employing a support vector machine with a robust scaling approach, optimal parameterization, and a data split ratio of 70:30, achieves an impressive accuracy rate of 96.00%. Beyond achieving high accuracy, the IELBT outperforms similar models in existing literature and provides significant interpretability and explanation, essential elements in the field of medical diagnosis. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Forecasting

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The connection between meridians and physiological functions:A quantum principle

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Nano Research 2023年第11期16卷 12817-12820页

作者： Xiang-Yu Kong Min Xiang Jiancheng Fang Dong Han Bo Song Lei Jiang CAS Key Laboratory of Bio-inspired Materials and Interfacial Science Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China Science and Technology Center for Quantum Biology National Institute of Extremely-Weak Magnetic Field InfrastructureHangzhou 310051China CAS Center for Excellence in Nanoscience National Center for Nanoscience and TechnologyBeijing 100190China School of Optical-Electrical Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Future Technology University of Chinese Academy of SciencesBeijing 100049China

In the long history of traditional Chinese medicine(TCM),meridians play essential roles as the critical network to regulate the normal physiological functions of the human *** are regarded to be the channels connecting the internal organs with the body surface and various parts of the *** there are many studies and doctrines trying to reveal the nature of meridians for their validation in TCM,the mechanism underlying the meridians remains ***,based on our macroscopic quantum state concept of ion channels(i.e.,sub-nanometer scale channels),we propose a quantum principle of *** acupoints and organ symptom are in a macroscopic coherence state of the ion channels in *** applying TCM treatments(e.g.,TCM massage,acupuncture,moxibustion,and electroacupuncture)on the acupoint,the corresponding organ symptom could be well regulated with help of quantum meridian state.

关键词： traditional Chinese medicine meridians macroscopic quantum state external stimulation

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Non-linear feature extraction from HRV signal for mortality prediction of ICU cardiovascular patient

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Journal of Medical engineering and Technology 2016年第3期40卷 87-98页

作者： Moridani, Mohammad Karimi Setarehdan, Seyed Kamaledin Motie Nasrabadi, Ali Hajinasrollah, Esmaeil Department of Biomedical Engineering Science and Research Branch Islamic Azad University Tehran Iran Control and Intelligent Processing Centre of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Departments of Biomedical Engineering Shahed University Tehran Iran Loghman Medical Center Shahid Beheshti University of Medical Sciences Tehran Iran

Intensive care unit (ICU) patients are at risk of in-ICU morbidities and mortality, making specific systems for identifying at-risk patients a necessity for improving clinical care. This study presents a new method for predicting in-hospital mortality using heart rate variability (HRV) collected from the times of a patients ICU stay. In this paper, a HRV time series processing based method is proposed for mortality prediction of ICU cardiovascular patients. HRV signals were obtained measuring R-R time intervals. A novel method, named return map, is then developed that reveals useful information from the HRV time series. This study also proposed several features that can be extracted from the return map, including the angle between two vectors, the area of triangles formed by successive points, shortest distance to 45° line and their various combinations. Finally, a thresholding technique is proposed to extract the risk period and to predict mortality. The data used to evaluate the proposed algorithm obtained from 80 cardiovascular ICU patients, from the first 48 h of the first ICU stay of 40 males and 40 females. This study showed that the angle feature has on average a sensitivity of 87.5% (with 12 false alarms), the area feature has on average a sensitivity of 89.58% (with 10 false alarms), the shortest distance feature has on average a sensitivity of 85.42% (with 14 false alarms) and, finally, the combined feature has on average a sensitivity of 92.71% (with seven false alarms). The results showed that the last half an hour before the patients death is very informative for diagnosing the patients condition and to save his/her life. These results confirm that it is possible to predict mortality based on the features introduced in this paper, relying on the variations of the HRV dynamic characteristics. © 2016 Taylor & Francis.

关键词： Forecasting

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Detection of False Information in Digital Media Using Blockchain Technology 3

Detection of False Information in Digital Media Using Blockc...

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3rd Odisha International Conference on Electrical Power engineering, Communication and Computing Technology, ODICON 2024

作者： Kilaru, Aswini Prasad, L V Narasimha Ghantasala, G S Pradeep Ananthanagu, U. Kallam, Suresh Rajesh Sharma, R. Institute of Aeronautical Engineering Department of Cse Telangana Hyderabad India Alliance College of Engineering and Design Alliance University Department of Computer Science and Engineering Bengaluru India Center of Excellence in Immersive Technologies Alliance University Bengaluru India School of Computer Science and Engineering Jain Deemed to Be University Bengaluru India

ISBN: (纸本)9798350354379

The spreading of false information over the internet, highly impacts society and causes social and economic loss to the nation. One of the most important factors for the increase in the number of misleading information is that all the users of any particular digital platform usually do not verify the authenticity of the information. The principal impartial of this proposed work is to afford a solution to society to reduce the social and economic losses caused by spreading false information circulated digitally. Blockchain is a disseminated, decentralized network that conducts peer-to-peer transactions, meaning that it does not have a central entity to operate. Here we present a literature survey on various approaches towards this problem statement and investigate a Blockchain-based solution that focuses on all types of digital content by providing the end user to validate the information along with the evidence for data that was collected at each step. © 2024 IEEE.

关键词： Distributed ledger

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Multi-Modal Domain Adaptation Variational Autoencoder for EEG-Based Emotion Recognition

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1612-1626页

作者： Yixin Wang Shuang Qiu Dan Li Changde Du Bao-Liang Lu Huiguang He the Research Center for Brain-inspired Intelligence National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of ScienceBeijing 100190 the University of Chinese Academy of Sciences Beijing 100049 the Beijing Institute of Control and Electronic Technology Beijing 100038China the School of Mathematics and Information Sciences Yantai UniversityYantai 264003China the Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of ScienceBeijingChina the Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Traditional electroencephalograph(EEG)-based emotion recognition requires a large number of calibration samples to build a model for a specific subject,which restricts the application of the affective brain computer interface(BCI)in *** attempt to use the multi-modal data from the past session to realize emotion recognition in the case of a small amount of calibration *** solve this problem,we propose a multimodal domain adaptive variational autoencoder(MMDA-VAE)method,which learns shared cross-domain latent representations of the multi-modal *** method builds a multi-modal variational autoencoder(MVAE)to project the data of multiple modalities into a common *** adversarial learning and cycle-consistency regularization,our method can reduce the distribution difference of each domain on the shared latent representation layer and realize the transfer of *** experiments are conducted on two public datasets,SEED and SEED-IV,and the results show the superiority of our proposed *** work can effectively improve the performance of emotion recognition with a small amount of labelled multi-modal data.

关键词： Cycle-consistency domain adaptation electroencephalograph(EEG) multi modality variational autoencoder

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3D automatic segmentation of coronary artery based on hierarchical region growing algorithm (3D HRG) in CTA data-sets

3D automatic segmentation of coronary artery based on hierar...

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2013 20th Iranian Conference on Biomedical engineering, ICBME 2013

作者： Turani, Zahra Zoroofi, Reza A. Shirani, Shapoor Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395/515 Iran Department of Radiology School of Medicine Tehran University of Medical Science Tehran Iran

ISBN: (纸本)9781479932320

Nowadays one of the most important causes of mortality is cardiovascular disease, especially coronary artery stenosis. Therefore, it is important to find an accurate and fast way to diagnose them. Computed tomography angiography is a non-invasive imaging method for the heart and its vessel, which can be used instead of angiography in many cases. Indeed, the main focus is on developing an automatic method which can be as accurate as angiography with the least user's contribution. Automatic coronary artery segmentation is considered as the first step to reach this goal. Therefore, a hierarchical region growing algorithm is proposed in which the whole heart region vessels, aorta, left ventricle and other cardiovascular vessels are segmented for the purpose of coronary artery segmentation. Our method validation is assessed by a radiologist through comparing the results with manual segmentation of him. Proposed method's results are 86.81% in average similar to radiologist's segmentation in kappa statistic and its label consistency with radiologist's segmentation is 90.23%. Comparing to other methods, our method is automatic and both left and right coronary can be segmented in all data-sets. It also segments important branches of coronary artery. According to the radiologist comments and high similarity measure, proposed method is reliable and applicable. © 2013 IEEE.

关键词： Heart

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Performance enhancement of IEEE 802.1 le WLAN by dynamic adaptive contention window

Performance enhancement of IEEE 802.1 le WLAN by dynamic ada...

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16th International Conference on Advanced Communication Technology: Content Centric Network Innovation!, ICACT 2014

作者： Achary, Rathnakar Vaithiyanathan, V. Raj, Pethur Nagarajan, S. School of Computing SASTRA University India Infrastructure Architect IBM Global Cloud Center of Excellence IBM India Bangalore India Department of Computer Science and Engineering SASTRA University India

ISBN: (纸本)9788996865032

The service differentiation and adaptation are the important mechanisms for enhancing the performance of IEEE 802.11 wireless local area networks (WLANs). However, all these mechanisms will have limitations for dealing high bandwidth streaming applications. The service differentiation technique proposed in IEEE 802.11e [4] mainly considers the signal with higher priority values to access the wireless channel. Signals with lower priority values have to wait in the queue for a longer time to get an access to the channel. Also as the number of high priority frames in the access categories (ACs) increases, results internal collisions. This degrades the performance of 802.11 WLAN. In this research paper we developed an approach to improve the quality of service (QoS) of WLAN by maximizing the channel throughput and minimizing the internal collision, by adaptively changing the contention window (CW) size based on their priority values and the service requirements of the signals in the queue. The proposed algorithm enables the ACs to share the channel and maximize the channel performance and minimize the collision. © 2014 Global IT Research Institute (GIRI).

关键词： IEEE Standards

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