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Al-Biruni Earth Radius Optimization for COVID-19 Forecasting

computer Systems Science & engineering 2023年第7期46卷 883-896页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Tatiana Makarovskikh Amal H.Alharbi Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of System Programming South Ural State University454080ChelyabinskRussia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.

关键词： COVID-19 prediction meta-heuristic optimization LSTM Al-Biruni earth radius algorithm

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Studying the Influence of Working Fluid Temperature on the Performance of an Electrohydraulic Servo System in Dynamic Mode

Studying the Influence of Working Fluid Temperature on the P...

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2023 International Conference Automatics and Informatics, ICAI 2023

作者： Yordanov, Stanimir Ormandzhiev, Krasimir Mihalev, Georgi Kostov, Krasen Mitev, Veselin Technical University of Gabrovo Department of Automation Information and Control Systems Gabrovo Bulgaria Technical University of Gabrovo Department of Power Engineering Gabrovo Bulgaria

ISBN: (纸本)9798350312911

The paper examines the influence of the working fluid temperature on power losses in an electro-hydraulic servo system. The behavior of the system has been investigated under Proportional-Integral (PI) control at different working fluid temperatures and various control setpoints. An Adaptive PID controller has been synthesized, utilizing feedback from sensors to measure various system parameters (such as temperature, pressure, and RPM), and then adapting the parameters of the P, I, and D components of the controller based on this data to achieve optimal regulation. © 2023 IEEE.

关键词： controllers

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Asynchronous Learning-Based Output Feedback Sliding Mode control for Semi-Markov Jump Systems: A Descriptor Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1358-1369页

作者： Zheng Wu Yiyun Zhao Fanbiao Li Tao Yang Yang Shi Weihua Gui School of Automation Central South UniversityChangsha 410083China Power Electronics Machines and Control GroupThe University of NottinghamNottingham NG72RDUK Department of Mechanical Engineering University of VictoriaVictoria BC V8W 3P6Canada IEEE

This paper presents an asynchronous output-feed-back control strategy of semi-Markovian systems via sliding mode-based learning *** with most literature results that require exact prior knowledge of system state and mode information,an asynchronous output-feedback sliding sur-face is adopted in the case of incompletely available state and non-synchronization *** holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow *** upon the co-occurrence of two subsystems,the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution ***,a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding ***,the proposed theoretical method is substantia-ted through two numerical simulations with the practical contin-uous stirred tank reactor and F-404 aircraft engine model,respectively.

关键词： Asynchronous switching learning-based control output feedback semi-Markovian jump systems sliding mode con-trol(SMC).

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Some Remarks on Fault-Tolerant Dynamic control Allocation for Weakly Redundant Systems 32

Some Remarks on Fault-Tolerant Dynamic Control Allocation fo...

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32nd Mediterranean Conference on control and automation, MED 2024

作者： Cristofaro, Andrea Faleschini, Michelangelo Sapienza University of Rome Department of Computer Control and Management Engineering Italy School of Science and Technology Mathematics Division University of Camerino Italy

ISBN: (纸本)9798350395440

We consider the problem of control allocation for weakly redundant systems subject to actuator faults. In particular, the design of a suitable allocator will be devised with the aim of compensating for the fault effects while, at the same time, keeping the control burden as low as possible. To this goal, two approaches can be followed for the synthesis of the allocation servomechanism: direct allocation using orthogonal projection and optimization-based allocation. Some numerical examples illustrate and highlight advantages, disadvantages and limitations of both strategies. © 2024 IEEE.

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Video-based Gait Analysis with IMU and Industrial Cameras: A Pilot Study

Video-based Gait Analysis with IMU and Industrial Cameras: A...

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2024 Medical Technologies Congress, TIPTEKNO 2024

作者： Turan, Fatma Maghsoudi, Sanaz İlikçi, Hakan Ayvaz, Bora Ergenç, Ali Fuat Bilgili, Fuat Boğazici University Biomedical Engineering Istanbul Turkey Istanbul University Istanbul Faculty of Medicine Department of Orthopedics and Traumatology Istanbul Turkey Istanbul Technical University Control and Automation Engineering Department Istanbul Turkey İstanbul University Istanbul Turkey

ISBN: (纸本)9798331529819

In this study, we investigated the validity of using a two-dimensional gait analysis system, which employed industrial cameras and a custom-developed Inertial Measurement Unit system, compared to the gold standard three-dimensional Vicon gait analysis system. Four subjects with a mean age of 26.76 (SD: 0.71) were included in the study, and gait data was collected from their 8 limbs. Correlation analyses examined the relationship between the data obtained from the two-dimensional gait analysis system and the three-dimensional Vicon system. The study's results showed a high correlation for the hip and knee joints between the two systems, but a lower correlation for the ankle joint. This pilot study demonstrated the potential of using industrial cameras and IMU systems for practical gait analysis. © 2024 IEEE.

关键词： Joints (anatomy)

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Accurate RGB-D SLAM in dynamic environments based on dynamic visual feature removal

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Science China(Information Sciences) 2022年第10期65卷 256-269页

作者： Chenxin LIU Jiahu QIN Shuai WANG Lei YU Yaonan WANG Department of Automation University of Science and Technology of China Institute of Artificial Intelligence Hefei Comprehensive National Science Center College of Electrical and Information Engineering Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University

Visual localization is considered an essential capability in robotics and has attracted increasing interest for the past few years. However, most proposed visual localization systems assume that the surrounding environment is static, which is difficult to maintain in real-world scenarios due to the presence of moving objects. In this paper, we present DFR-SLAM, a real-time and accurate RGB-D SLAM based on ORB-SLAM2 that achieves satisfactory performance in a variety of challenging dynamic scenarios. At the core of our system lies a motion consensus filtering algorithm estimating the initial camera pose and a graph-cut optimization framework combining long-term observations, prior information, and spatial coherence to jointly distinguish dynamic and static visual features. Other systems for dynamic environments detect dynamic components by using the information from short time-span frames, whereas our system uses observations from a long period of keyframes. We evaluate our system using dynamic sequences from the public TUM dataset, and the evaluation demonstrates that the proposed system outperforms the original ORB-SLAM2 system significantly. In addition, our system provides competitive localization accuracy with satisfactory real-time performance compared to closely related SLAM systems designed to adapt to dynamic environments.

关键词： SLAM dynamic environments indoor localization graph-cut robot navigation

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Decomposition frequency optimization in wavelet-based template matching algorithms to manage P300 latency jitter 46

Decomposition frequency optimization in wavelet-based templa...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Quattrociocchi, Ilaria Caracci, Valentina Riccio, Angela Galiotta, Valentina D'Ippolito, Mariagrazia Cincotti, Febo Toppi, Jlenia Astolfi, Laura Sapienza University of Rome Department of Computer Control and Management Engineering Italy Fondazione Santa Lucia Irccs Neuroelectrical Imaging and Brain Computer Interface Laboratory Rome Italy

ISBN: (纸本)9798350371499

Event-Related Potentials (ERPs) are modifications of the brain activity in response to external sensory stimulation. P300 is a positive ERP component that occurs 300 ms after the presentation of a rare stimulus and indicates conscious perception of an unexpected change in sensory stimulation. Since the amplitude of ERPs is comparable to that of background electroencephalography, the most widespread approach to render ERPs correctly detectable is time-domain averaging. ERPs are physiologically affected by variations in latency, referred to as latency jitter. The most promising techniques to address latency jitter are cross-correlation template matching algorithms, which estimate single-trial latencies and resynchronize them according to a template that best describes the ERP component. Adaptive Wavelet Filtering (AWF) is an algorithm applied in the wavelet domain to provide the optimal compromise of time-frequency resolution in detecting ERPs. The choice of an appropriate decomposition frequency is crucial in the application of AWF, as it is essential for identifying the correct template and estimating single-trial latencies. In this study, we investigated the influence of frequency on the performance of AWF to optimize it. The algorithm was tested on simulated data with varying latency shifts and signal-to-noise ratios as well as for data recorded from 11 healthy subjects during an auditory oddball paradigm. Results on both simulated and real EEG data showed how frequency decomposition of 3 Hz is the most appropriate for P300 waveform detection. © 2024 IEEE.

关键词： Template matching

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Synthesis of Variable Gain Robust State Observer for a Class of Uncertain Nonlinear Systems 6

Synthesis of Variable Gain Robust State Observer for a Class...

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6th International Conference on Electrical, control and Instrumentation engineering, ICECIE 2024

作者： Hirasawa, Kazuhiro Asada, Daiki Nagai, Shunya Oya, Hidetoshi Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Niihama College Department of Electronics and Control Engineering Ehime Japan Tokyo City University The Department of Computer Science Tokyo Japan

ISBN: (纸本)9798350380040

This paper proposes a new variable gain robust state observer for a class of uncertain nonlinear systems. The variable gain robust state observer proposed in this paper consists of fixed observer gain matrices and nonlinear modification functions which are determined by appropriate updating rules. It is shown that sufficient conditions for the existence of the proposed variable gain robust state observer can be reduced to solvability of Linear Matrix Inequalities (LMIs). Finally, we give a simple numerical example. © 2024 IEEE.

关键词： State estimation

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Geometric prior guided hybrid deep neural network for facial beauty analysis

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 467-480页

作者： Tianhao Peng Mu Li Fangmei Chen Yong Xu David Zhang The School of Computer Science and Technology Guizhou UniversityGuiyangChina Department of Automation Moutai InstituteRenhuaiGuizhouChina The School of Computer Science and Technology Harbin Institute of TechnologyShenzhenShenzhenChina The Information and Communication Engineering Department Dalian Minzu UniversityDalianChina The School of Data Science The Chinese University of Hong KongShenzhenShenzhenChina

Facial beauty analysis is an important topic in human *** may be used as a guidance for face beautification applications such as cosmetic *** neural networks(DNNs)have recently been adopted for facial beauty analysis and have achieved remarkable ***,most existing DNN-based models regard facial beauty analysis as a normal classification *** ignore important prior knowledge in traditional machine learning models which illustrate the significant contribution of the geometric features in facial beauty *** be specific,landmarks of the whole face and facial organs are introduced to extract geometric features to make the *** by this,we introduce a novel dual-branch network for facial beauty analysis:one branch takes the Swin Transformer as the backbone to model the full face and global patterns,and another branch focuses on the masked facial organs with the residual network to model the local patterns of certain facial ***,the designed multi-scale feature fusion module can further facilitate our network to learn complementary semantic information between the two *** model optimisation,we propose a hybrid loss function,where especially geometric regulation is introduced by regressing the facial landmarks and it can force the extracted features to convey facial geometric *** performed on the SCUT-FBP5500 dataset and the SCUT-FBP dataset demonstrate that our model outperforms the state-of-the-art convolutional neural networks models,which proves the effectiveness of the proposed geometric regularisation and dual-branch structure with the hybrid *** the best of our knowledge,this is the first study to introduce a Vision Transformer into the facial beauty analysis task.

关键词： deep neural networks face analysis face biometrics image analysis

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Adaptive Neuro-Fuzzy Inference Systems for Cognitive Sensor Communication in Smart Cities

Adaptive Neuro-Fuzzy Inference Systems for Cognitive Sensor ...

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2024 IEEE International Conference on Intelligent Systems and Advanced Applications, ICISAA 2024

作者： Pradhan, Rahul Prathiba, Ch. Kholmukhamedov, Timur Patil, B.N. Mary, S. Suma Christal Raj, I Infant GLA University Department of Computer Engineering and Applications Mathura India Vignana Bharathi Institute of Technology Department of CSM Ghatkesar Hyderabad India Turin Polytechnic University Automatic Control and Computer Engineering Department Tashkent Uzbekistan Yeshwantrao Chavan College of Engineering Department of Applied Physics Nagpur India Panimalar Engineering College Department of Information Technology Poonamalle Chennai India K. Ramakrishnan College of Engineering Department of CSE Tamil Nadu Trichy India

ISBN: (纸本)9798331539948

Modern urban development depends on optimizing cognitive sensor communications in smart cities, which is the focus of this investigation. In the era of expanding sensor networks, efficient data transmission is paramount for the success of smart city initiatives. The current state of sensor communication faces challenges like suboptimal adaptability, inefficient energy usage, and limited fault detection. This study proposes a solution through the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS), identifying these challenges as opportunities for improvement. The novelty lies in ANFIS's introduction as an intelligent and adaptive solution. Its ability to learn from sensor data, adapt to changing conditions, and optimize communication parameters sets it apart in enhancing cognitive sensor communication. The research methodology involves a systematic approach, encompassing data collection, pre-processing, and ANFIS model development. The model is rigorously trained, validated, and tested for real-world effectiveness. Integration into the smart city communication system is explored, emphasizing applications in context-aware communication, energy-efficient protocols, and fault detection. Performance is evaluated using metrics like accuracy, reliability, and efficiency, demonstrating the model's efficacy in addressing drawbacks and enhancing overall sensor communication in smart cities. The findings contribute to advancing intelligent systems for urban infrastructure and services. © 2024 IEEE.

关键词： Fuzzy neural networks

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