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26th International Conference on Knowledge-Based and intelligent Information and engineering systems, KES 2022

作者： Tigani, Smail Tadist, Khawla Saadane, Rachid Chehri, Abdellah Chaibi, Hasnae Engineering Unit Euro-Med Research Center Euro-Med University Fez Morocco Laboratory of Intelligent Systems and Applications Faculty of Sciences and Technologies Sidi Mohammed Ben Abdellah University Fez Morocco Electrical Engineering Department Hassania School of Public Labors Casablanca20250 Morocco University of Quebec in Chicoutimi QuébecG7H 2B1 Canada GENIUS Laboratory SUPMTI Rabat Morocco

This paper presents a deep artificial neural network approach based currency market volatility based recommendation engine. Since deep learning classification needs labeled data set that we don't have, an approach is designed specially for that point in order to generate labeled data set from non labeled one. This is a major innovative aspect in this contribution in addition to the recommendation service. It is based on Gaussian kernel density and Monte Carlo simulation. The main goal of the proposed approach is to predict - for each hour of the day - the volatility behaviour of the selected currency pair. The proposed model has a range of applications in financial market specially the algorithmic trading. Deep neural network was trained and evaluated and testing process gave good convergence rate. © 2022 The Authors. Published by Elsevier B.V.

关键词： Recommender systems

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An Efficient Capsule-based Network for 2D Left Ventricle Segmentation in Echocardiography Images

An Efficient Capsule-based Network for 2D Left Ventricle Seg...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： R. Naghne A. Kazemi H. Moghaddasi M. Rahmani P. Farnia A. Ahmadian J. Alirezaie Image-Guided Surgery Group Research Center of Biomedical Technology and Robotics (RCBTR) Advanced Medical Technologies and Equipment Institute (AMTEI) Tehran University of Medical Sciences Tehran Iran Medical Physics and Biomedical Engineering Department Faculty of Medicine Tehran University of Medical Sciences (TUMS) Department of Electrical and Computer Engineering Toronto Metropolitan University Toronto Ontario Canada

The segmentation of cardiac chambers is essential for the clinical diagnosis and treatment of cardiovascular diseases. It is demonstrated that in cardiac disease, the left ventricle (LV) is extensively involved. Therefore, segmentation of the LV in echocardiographic images is critical for the precise evaluation of factors that influence cardiac function such as LV volume, ejection fraction, and LV mass. Although these measurements could be obtained by manual segmentation of the LV, it would be time-consuming and inaccurate because of the poor quality and low contrast of these images. Convolutional neural networks, commonly referred to as CNNs, have emerged as a highly favored deep learning technique for medical image segmentation. Despite their popularity, the pooling layers in CNNs ignore the spatial information and do not consider the part-whole hierarchy relationships. Furthermore, they require a large training dataset and a large number of parameters. Therefore, Capsule Networks are proposed to address the CNNs limitations. In this study, for the first time, an optimized capsule-based network for object segmentation called SegCaps is proposed to achieve accurate LV segmentation on echocardiography images applied to the CAMUS dataset. The result was compared against the standard 2D-UNet. The modified SegCaps and 2D-UNet achieved an average Dice similarity coefficient (DSC) of 84.48% and 83.28% on LV segmentation, respectively. The capabilities of the CapsNet led to an improvement of 1.44% in DSC with 92.77% fewer parameters than the U-Net. The results indicate that the proposed method leads to accurate and efficient LV *** Relevance— From a clinical point of view, our findings lead to more precise evaluations of critical cardiac parameters, including ejection fraction as well as left ventricle volume at end-diastole and end-systole.

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Visuotactile Sensor Enabled Pneumatic Device Towards Compliant Oropharyngeal Swab Sampling

Visuotactile Sensor Enabled Pneumatic Device Towards Complia...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Shoujie Li Mingshan He Wenbo Ding Linqi Ye Xueqian Wang Junbo Tan Jinqiu Yuan Xiao-Ping Zhang Tsinghua Shenzhen International Graduate School Shenzhen China Department of Mechanical Engineering Seoul National University Seoul Korea Department of Intelligent Control Qianyuan Institute of Science Hangzhou China Clinical Research Center The Seventh Affiliated Hospital Sun Yat-sen University Shenzhen Guangdong China Department of Electrical Computer and Biomedical Engineering Ryerson University Toronto ON Canada

Manual oropharyngeal (OP) swab sampling is an intensive and risky task. In this article, a novel OP swab sampling device of low cost and high compliance is designed by combining the visuotactile sensor and the pneumatic actuator-based gripper. Here, a concave visuotactile sensor called CoTac is first proposed to address the problems of high cost and poor reliability of traditional multi-axis force sensors. Besides, by imitating the doctor's fingers, a soft pneumatic actuator with a rigid skeleton structure is designed, which is demonstrated to be reliable and safe via finite element modeling and experiments. Furthermore, we propose a sampling method that adopts a compliant control algorithm based on the adaptive virtual force to enhance the safety and compliance of the swab sampling process. The effectiveness of the device has been verified through sampling experiments as well as in vivo tests, indicating great application potential. The cost of the device is around 30 US dollars and the total weight of the functional part is less than 0.1 kg, allowing the device to be rapidly deployed on various robotic arms.

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An Improved Method for Approximating the Infinite-horizon Value Function of the Discrete-time Switched LQR Problem

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IFAC-PapersOnLine 2023年第2期56卷 4138-4143页

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 U.S.A.

This paper considers the problem of approximating the infinite-horizon value function of the discrete-time switched LQR problem. In particular, we propose a new value iteration method to generate a sequence of monotonically decreasing functions that converges exponentially to the value function. This method facilitates us to use coarse approximations resulting from faster but less accurate algorithms for further value iteration, and thus, our method is capable of achieving a better approximation for a given computation time compared with the existing methods. Two numerical examples are presented in this paper to illustrate the effectiveness of our method.

关键词： Switched linear systems optimal control switched LQR problem

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Drowsy Driver Detection System For Poor Light Conditions

Drowsy Driver Detection System For Poor Light Conditions

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2023 IEEE International Conference on Mechatronics (ICM)

作者： Ahmed Ibnouf Ayman Fadlallah Muaiz Ali Abdelmalek Zidouri Control & Instrumentation Engineering Department King Fahd University of Petroleum and Minerals (KFUPM) Dhahran Saudi Arabia Information & Computer Science Department King Fahd University of Petroleum and Minerals (KFUPM) Dhahran Saudi Arabia Electrical Engineering Department King Fahd University of Petroleum and Minerals (KFUPM) Dhahran Saudi Arabia Electrical Engineering Department Interdisciplinary Research Center for Intelligent Secure System King Fahd University of Petroleum and Minerals (KFUPM) Dhahran Saudi Arabia

In recent years, the number of car accidents has been gradually increasing. A major factor in this increase is the drowsiness of drivers. There are many image recognition research studies on drowsiness detection but tend to neglect the case of low-light conditions. This paper focuses on detecting drowsy drivers in low-light conditions. In this paper, a behavioralbased drowsy driver detection system (DDDS) was proposed. The proposed DDDS applies a preprocessing algorithm that improves illumination and then focuses on detecting the driver’s face and eyes to calculate eye blink duration. A deep neural network model was used for facial recognition, and Haar Cascade classifiers were used for eyes detection. Every single eye was based to a Convolutional Neural Network (CNN) model to predict its state as either ‘‘Open’’ or ‘‘Closed’’. The proposed CNN was developed using a dataset of 1452 samples and gave an accuracy of 97.92% on the testing dataset, 15% of the 1452 samples. Different case scenarios in poor light conditions were implemented to evaluate the proposed DDDS. The system was able to identify the state of the driver even in harsh and severe poor light conditions.

关键词： Deep learning Face recognition Transportation industry Lighting Safety Convolutional neural networks Standards

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On Enlarging the Domain of Attraction for Linear systems Subject to Asymmetric Actuator Saturation

On Enlarging the Domain of Attraction for Linear Systems Sub...

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IEEE Conference on Decision and Control

作者： Wenxin Lai Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA U.S.A.

In this paper, we revisit the problem of enlarging the domain of attraction for linear systems with asymmetric actuator saturation. We partition the state space into several regions according to the sign of each input and rewrite the linear system subject to asymmetric actuator saturation as an equivalent switched system, each subsystem of which is associated with one partition of the state space and is a linear system subject to symmetric actuator saturation. Based on this equivalent representation of the system, we present a Lyapunov function, which is composed of a set of quadratic functions associated with matrices that are not required to be positive definite. We establish sufficient conditions for regional stability and, based on them, formulate optimization problems to enlarge the estimate of the domain of attraction. Simulation results illustrate the effectiveness of the proposed approach.

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Automated Controller Placement for Software-Defined Networks to Resist DDoS Attacks

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computers, Materials & Continua 2021年第9期68卷 3147-3165页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Lee Ching Kwang Rizaludin Kaspin Bhawani Shankar Chowdhry Rajkumar Buyya Satya Prasad Majumder Manoj Gupta Shuaib Memon Faculty of Computing&Informatics Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation CentreCyberjaya63000SelangorMalaysia National Center of Robotics and Automation Mehran University of Engineering&TechnologyJamshoroPakistan Department of Computer Science and Engineering Hanyang UniversitySeoul04763South Korea School of Electrical and Electronic Engineering Nanyang Technological University639798Singapore Cloud Computing and Distributed Systems Laboratory The University of MelbourneMelbourneVIC 3053Australia Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology(BUET)Dhaka1205Bangladesh Department of Electronics and Communication Engineering JECRC UniversityVidhaniJaipur303905India Auckland Institute of Studies Mt AlbertAucklandNew Zealand

In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication *** research has concentrated largely on factors such as reliability,latency,controller capacity,propagation delay,and energy ***,SDNs are vulnerable to distributed denial of service(DDoS)attacks that interfere with legitimate use of the *** ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design,especially in critical applications such as military,health care,and financial services networks requiring high *** propose a mathematical model for planning the deployment of SDN smart backup controllers(SBCs)to preserve service in the presence of DDoS *** a number of input parameters,our model has two distinct ***,it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating ***,it recommends an optimal number of smart backup controllers for use with different levels of DDoS *** goal of the model is to improve resistance to DDoS attacks while optimizing the overall cost based on the *** simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of DDoS attacks while managing the overall cost.

关键词： SDN automated controller placement SBC ILP DDoS attack

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Automatic facial expression recognition in an image sequence using conditional random field

Automatic facial expression recognition in an image sequence...

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International Symposium on Computational Intelligence and Informatics

作者： Mohamad Roshanzamir Mahdi Roshanzamir Abdolreza Mirzaei Mohammad Tayarani Darbandy Afshin Shoeibi Roohallah Alizadehsani Fahime Khozeimeh Abbas Khosravi Department of Computer Engineering Fasa University Fasa Iran Department of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran School of Architecture Islamic Azad University Taft Taft Iran Internship in Health Data Analytics Program AI-enabled Processes (AIP) Research Centre Macquarie University Sydney Australia Institute for Intelligent Systems Research and Innovation (IISRI) Deakin University Victoria Australia

ISBN: (纸本)9798350398830

Facial expression recognition is one of the fields that nowadays has attracted the attention of many researchers. It is possible to automate facial expression recognition using artificial intelligence methods. This will be of great help to researchers, especially in areas such as psychology. Automatic facial recognition can be derived from a static image of facial expression, but a better and more efficient way to do this is through a sequence of images. In this paper, a new method is proposed to automatically detect facial expressions from a sequence of images. Each sequence of facial images begins with a face neutral state and ends with one of the six main emotions. Motion vectors are extracted from the sequence using optical flow algorithm. These vectors are then used to train the conditional random field and finally to automatically determine the emotion. In this paper, in addition to the basic conditional random field, the hidden dynamic conditional random field is also investigated. Additionally, the effect of changing some parameters of these algorithms such as different optimization methods has been investigated. Given that a facial expression is recognized during a sequence of images, random field-based methods can be used for efficient classification of facial expressions reaching accuracy (more than 90%) competitive with the best existing methods for facial expression recognition.

关键词： Image recognition Mechatronics Face recognition Heuristic algorithms Psychology Optimization methods Feature extraction

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Portable System and User Interface for ECG and EMG Acquisition, Conditioning, and Parameters Extraction

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Procedia computer Science 2025年 256卷 1216-1223页

作者： Luiz E. Luiz Wilson J. da Silva Salviano Soares Paulo Leitão João P. Teixeira Research Centre in Digitalization and Intelligent Robotics (CeDRI) Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragança 5300-253 Bragança Portugal Postgraduate Programme in Electrical Engineering and Industrial Informatics - CPGEI Federal Technological University of Paraná 80230-901 Curitíba Paraná Brazil Engineering Department School of Sciences and Technology University of Trás-os-Montes and Alto Douro (UTAD) Quinta de Prados 5000-801 Vila Real Portugal Institute of Electronics and Informatics Engineering of Aveiro (IEETA) University of Aveiro 3810-193 Aveiro Portugal Intelligent Systems Associate Laboratory (LASI) University of Aveiro 3810-193 Aveiro Portugal

electrical signals from the human body are constantly the focus of research, searching for a better understanding of physiological events, discovering early signs of disease, and improving life quality. Developing devices that allow research beyond the usual requirements and allow easy adaptation regarding the system’s acquisition, conditioning, and processing parts could be a step toward better understanding some behaviours. Therefore, this work focused on designing a system that goes from the discrete components to a graphical interface, allowing user control of parameters to set the acquisition in a way that favours the specific signal of interest. The resulting system allows the user to change parameters regarding the analogue and digital filtering, sampling frequency and events detection, namely R-peaks, in the electrocardiogram, to estimate heart rate and its frequency fluctuation, and muscle contraction in electromyogram, to analyse contraction strength and muscle fatigue. The system also allows the data to be stored, aiming to generate datasets to further process the data in AI-based algorithms.

关键词： Graphical User Interface Biosignals Printed Circuit Board EMG processing ECG processing

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A Tutorial on Movable Antennas for Wireless Networks

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IEEE Communications Surveys and Tutorials 2025年

作者： Zhu, Lipeng Ma, Wenyan Mei, Weidong Zeng, Yong Wu, Qingqing Ning, Boyu Xiao, Zhenyu Shao, Xiaodan Zhang, Jun Zhang, Rui National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore National Key Laboratory of Wireless Communications Chengdu611731 China Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Shanghai Jiao Tong University Department of Electronic Engineering Shanghai200240 China Beihang University School of Electronic and Information Engineering Beijing100191 China University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada Beijing Institute of Technology State Key Laboratory of CNS/ATM Miit Key Laboratory of Complex-field Intelligent Sensing Beijing100081 China The Chinese University of HongKong School of Science and Engineering Shenzhen Research Institute of Big Data Guangdong Shenzhen518172 China

Movable antenna (MA) has been recognized as a promising technology to enhance the performance of wireless communication and sensing by enabling antenna movement. Such a significant paradigm shift from conventional fixed antennas (FAs) to MAs offers tremendous new opportunities towards realizing more versatile, adaptive and efficient next-generation wireless networks such as 6G. In this paper, we provide a comprehensive tutorial on the fundamentals and advancements in the area of MA-empowered wireless networks. First, we overview the historical development and contemporary applications of MA technologies. Next, to characterize the continuous variation in wireless channels with respect to antenna position and/or orientation, we present new field-response channel models tailored for MAs, which are applicable to narrowband and wideband systems as well as far-field and near-field propagation conditions. Subsequently, we review the state-of-the-art architectures for implementing MAs and discuss their practical constraints. A general optimization framework is then formulated to fully exploit the spatial degrees of freedom (DoFs) in antenna movement for performance enhancement in wireless systems. In particular, we delve into two major design issues for MA systems. First, we address the intricate antenna movement optimization problem for various communication and/or sensing systems to maximize the performance gains achievable by MAs. Second, we deal with the challenging channel acquisition issue in MA systems for reconstructing the channel mapping between arbitrary antenna positions inside the transmitter and receiver regions. Moreover, we show existing prototypes developed for MA-aided communication/sensing and the experimental results based on them. Finally, the extension of MA design to other wireless systems and its synergy with other emerging wireless technologies are discussed. We also highlight promising research directions in this area to inspire future investigatio

关键词： Antenna arrays

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