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European Control Conference (ECC)

作者： Xuehui Mal Yutong Chen Shiliang Zhang Yushuai Li Fucai Qian Zhiyong Sun School of Automation and Information Engineering Xi'an University of Technology Xi'an China Department of Electronic Engineering Tsinghua University Beijing China Department of Informatics University of Oslo Oslo Norway Department of Computer Science Aalborg University Aalborg Denmark Department of Electrical Engineering Eind-hoven University of Technology Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Despite the celebrated success of linear quadratic Gaussian control (LQG) for stochastic systems, LQG approaches are inefficient in handling systems with non-Gaussian noises. This paper is concerned with linear quadratic control of discrete-time systems with bounded noises and unobservable system states. We describe such noises and system states by ellipsoidal sets, enabling the establishment of boundaries for those uncertainties in the control. Further, we learn and update the ellipsoidal sets for the system states by an ellipsoidal set-membership filter. With the learned ellipsoidal sets, we derive a robust state-feedback optimal control law by solving a rendered semidefinite programming problem. Simulation results demonstrate the enhanced control performance by the proposed method.

关键词： Robust control Linear systems Discrete-time systems Semidefinite programming Uncertainty Stochastic systems Simulation

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Design and implementation of a deep neural network approach for intrusion detection systems

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e-Prime - Advances in electrical engineering, Electronics and Energy 2024年 7卷

作者： Osa, Edosa Orukpe, Patience E. Iruansi, Usiholo Department of Electrical and Electronics Engineering Faculty of Engineering University of Benin P.M.B. 1154 Benin City Nigeria Department of Computer Engineering Faculty of Engineering University of Benin P.M.B. 1154 Benin City Nigeria

Due to the increased reliance of many a human system on cyber infrastructures, there is the continuous need for intelligent protection schemes to be developed as the spate of cyber-attacks is on the rise. Such intelligent systems that could easily detect both existing and zero-day attacks are highly sought in the complex and fast evolving cyberspace. In this regard, machine learning as well as deep learning models have been very effective. However, there is the need for better performing models than the existing ones. This work is aimed at the design and implementation of a Deep Neural Network model for detecting intrusions in computer networks. Techniques such as SMOTE and Random Sampling were applied to handle data imbalance in the CICIDS 2017 dataset. The entire experiment was carried out on a single Jupyter notebook in the Google Colaboratory environment where relevant software libraries such as seaborn, pandas, matplotlib, keras, and Tensor Flow were imported and thereafter implemented as required. Performance metrics of accuracy and loss at both training and validation of the model were considered. Results show that the deep learning model was excellent at predicting attacks with the CICIDS 2017 dataset, achieving accuracy score of 99.68 % and loss of 0.0102. © 2024 The Author(s)

关键词： Deep learning Machine learning Neural network Tensor flow

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Research on the Flux-weakening Capability of the Reverse-salient Permanent Magnet Synchronous Motor

Research on the Flux-weakening Capability of the Reverse-sal...

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International Conference on electrical Machines and Systems (ICEMS)

作者： Xiaokun Zhao Cheng Zhang Weinan Wang Baoquan Kou Liangkuan Zhu College of Computer and Control Engineering Northeast Forestry University Harbin China Department of Electrical and Automation Harbin Institute of Technology Harbin China

Permanent magnet synchronous motors (PMSMs) offer the benefits of high torque density and a superior power factor. Nevertheless, the challenge lies in the inherent difficulty of adjusting the permanent magnet flux. To address this issue, this paper analyzes the influence of electromagnetic parameters on the constant-power speed range (CPSR). First, the analysis focuses on the influence of d-axis inductance and saliency ratio, aiming to establish a design method for achieving a wide CPSP in PMSMs. Second, based on the electromagnetic parameter requirements, a reverse-salient PMSM is proposed and its working principle is explained. Finally, the electromagnetic characteristics, including torque and the CPSP, are determined through the application of the finite element method (FEM). The obtained results confirm that the reverse-salient PMSM achieves a CPSP of 7:1, thus validating the accuracy of the theoretical analysis.

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A novel model for efficient cluster head selection in mobile WSNs using residual energy and neural networks

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Measurement: Sensors 2024年 33卷

作者： Jalili, Ahmad Gheisari, Mehdi Alzubi, Jafar A. Fernández-Campusano, Christian Kamalov, Firuz Moussa, Sherif Department of Computer Engineering Gonbad Kavous University Gonbad Kavous Iran Santiago8370451 Chile Department of Electrical Engineering Canadian University Dubai Dubai United Arab Emirates Faculty of Engineering Al-Balqa Applied University Salt Jordan

Wireless Sensor Networks (WSNs) are essential for monitoring operational environments. Efficient selection of cluster heads is crucial in minimizing energy consumption. This study introduces an innovative model for determining the positions of cluster heads in a WSN, using the residual energy of each sensor node as a selection metric. The sensor incorporates a neural network model that has been trained using different significant models to determine the best location for the cluster head. Our model is compared with the Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm to showcase its effectiveness, particularly in mobile node scenarios. We employ a feed-forward multilayer network, specifically Multilayer Perceptrons (MLPs), as the neural network technique. The proposed method comprises two stages: the training stage, where the neural network is trained with appropriate models, and the execution stage, where the trained network suggests the cluster head's location based on the sensor's conditions. The results demonstrate that the proposed method can accurately identify suitable locations for cluster heads in a sensor network and is capable of adapting to new models despite environmental changes and variations in input configurations. © 2024 The Authors

关键词： Location

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Automated Deep Learning Pipeline for Accurate Segmentation of Aortic Lumen and Branches in Abdominal Aortic Aneurysm: A Two-Step Approach

Automated Deep Learning Pipeline for Accurate Segmentation o...

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Intelligent Methods, Systems, and Applications (IMSA)

作者： Fatma N. Hassan Ahmed M. Mahmoud Ahmed F. Elnokrashy Ashraf Y. Hassan Department of Electrical Engineering Benha Faculty of Engineering Benha University Benha Egypt Department of Biomedical Engineering and Systems Cairo University Giza Egypt Astute Imaging Kirkland WA US Department of Computer Science Technology and Computer Science Nile University Giza Egypt Benha University Benha Egypt

ISBN: (数字)9798350362633

ISBN: (纸本)9798350362640

Abdominal Aortic Aneurysm (AAA) is a serious medical condition characterized by the abnormal enlargement of the abdominal aorta. If left untreated, AAA can have life-threatening consequences. Accurate segmentation of the aorta in Computed Tomography Angiography (CTA) images plays a vital role in treatment planning for AAA. However, manual and semi-automatic segmentation methods suffer from limitations in terms of time and accuracy. This study presents a deep learning pipeline that aims to fully automate the precise and efficient segmentation of the aorta and its branches within CTA images. A two-step approach is proposed for the segmentation of the aorta and its branches in contrast-enhanced CTA scans. The first step involves utilizing a UNet++ model to perform aortic segmentation across the entire set of CTA axial slices. In the second step, a post processing algorithm is employed to track the continuity of the segmented aorta while effectively discarding false positive (FP) objects. The assessment of the fully automated method revealed remarkable outcomes, with a mean Dice coefficient of 0.941 on a test set consisting of 10 CTA scans. The automated segmentation results are utilized to create a comprehensive 3D model. The study results indicate that the utilization of the proposed deep learning-based pipeline is highly effective in achieving accurate segmentation of the aortic lumen and its branches. The practical implications of this approach extend to pre-operative planning. This highlights the valuable contribution of the proposed method in improving the management and treatment of patients diagnosed with aortic aneurysm.

关键词： Image segmentation Solid modeling Accuracy Three-dimensional displays Pipelines Surgery Aneurysm

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Design of Dual Frequency Coupled Resonators Using DGS and Microstrip Resonators for Dual Band WPT Applications

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Applied Computational Electromagnetics Society Journal 2021年第1期36卷 75-81页

作者： Atallah, Hany A. Alzubi, Musallam Hussein, Rasha Abdlerhman, Adel B. Electrical Engineering Department Faculty of Engineering South Valley University Qena83523 Egypt Ministry of Communications Po Box 318 Safat11111 Kuwait School of Electronics Communications and Computer Engineering Egypt-Japan University of Science and Technology Alexandria21934 Egypt

This paper introduces a new design for a highly efficient and more compact size dual frequency wireless power transfer (WPT) system, which can operate at both 0.65 GHz and 1.56 GHz bands. The idea of the structure depends on designing a symmetrical system containing Tx and Rx. Each Tx and Rx has a feed line on the top layer with two stubs;each stub has different dimensions than the other one. The bottom layer contains two C-shaped defected ground structures (DGS). By changing the dimensions of one stub, the frequency resonance corresponds to this stub is changed without any change on the other resonance. The system has a size of 20 × 20 mm2. Further, the system achieves efficiencies of 72 % and 89 % at 0.65 GHz and 1.56 GHz, respectively with a transmission distance of 8 mm. The proposed dual frequency WPT is implemented and verified. Good concurrences among electromagnetic (EM) simulations and the measurements have been attained. The system is suitable for recharging short-range applications. © ACES

关键词： Defected ground structures

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EmoSyn: Adaptive Emotion Framework for Sentiment Analysis and Internet of Medical Things

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Awan, Kamran Ahmad Alqahtani, Abdullah M. Cengiz, Korhan Alshammari, Alya Alrashdi, Ibrahim The University of Haripur Faculty of Information Technology and Numerical Sciences Department of Information Technology Khyber Pakhtunkhwa Pakistan Jazan University Department of Electrical and Electronic Engineering Collage of Engineering and Computer Science Saudi Arabia Prince Mohammad Bin Fahd University Department of Electrical Engineering Al Khobar31952 Saudi Arabia Princess Nourah bint Abdulrahman University Department of Applied Linguistics College of Languages Riyadh11671 Saudi Arabia Jouf University Department of Computer Science College of Computer and Information Sciences Al-Jouf Sakaka73211 Saudi Arabia

Sentiment analysis, or more specifically, the integration of IoMT into healthcare systems, requires frameworks that must adapt at runtime with high precision. Most existing methods have several limitations of either latency or accuracy issues, and therefore perform less effectively in dynamic scenarios. This study aims to address these challenges by proposing EmoSyn, a novel framework that incorporates Emotion Wave Modulation (EWM), Neuro-Cognitive Language Dynamics (NCLD), and the Sentient IoMT Interaction Protocol (SIP). EWM generates dynamic emotional waveforms using high-dimensional feature vectors and kernelized mappings, while NCLD employs synthetic neural mappings and adaptive linguistic modeling to capture semantic transitions. SIP facilitates real-time IoMT recalibration through bidirectional sentiment-driven feedback. Implemented using mathematical frameworks and a custom Emotion-Aware Predictive Synthesis Algorithm (EAPSA), EmoSyn ensures precise sentiment interpretation and efficient IoMT interactions. The framework was evaluated using MOSEI and MIMIC-III datasets in a Python-based simulation environment. The results showed EmoSyn achieving 91% precision for MOSEI and 86% for MIMIC-III, with average latencies of 29 ms and 27 ms. © 2013 IEEE.

关键词： Semantics

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Automated Speech Recognition System to Detect Babies’ Feelings through Feature Analysis

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computers, Materials & Continua 2022年第11期73卷 4349-4367页

作者： Sana Yasin Umar Draz Tariq Ali Kashaf Shahid Amna Abid Rukhsana Bibi Muhammad Irfan Mohammed A.Huneif Sultan A.Almedhesh Seham M.Alqahtani Alqahtani Abdulwahab Mohammed Jamaan Alzahrani Dhafer Batti Alshehri Alshehri Ali Abdullah Saifur Rahman Faculty of Computing University of OkaraOkara57000Pakistan Department of Computer Science University of SahiwalSahiwal57000PunjabPakistan Computer Science Department COMSATS University IslamabadLahore Campus57000Pakistan Department of Computer Science CUISahiwal CampusSahiwal57000Pakistan Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Pediatric Department Medical CollegeNajran University Saudi ArabiaNajran61441Saudi Arabia Consultant of ORL&HNs and Facial Plastic Surgery College of MedicineNajran University Saudi ArabiaNajran61441Saudi Arabia

Diagnosing a baby’s feelings poses a challenge for both doctors and parents because babies cannot explain their feelings through expression or *** the emotions of babies and their associated expressions during different sensations such as hunger,pain,etc.,is a complicated *** infancy,all communication and feelings are propagated through cryspeech,which is a natural *** clinical methods can be used to diagnose a baby’s diseases,but nonclinical methods of diagnosing a baby’s feelings are *** such,in this study,we aimed to identify babies’feelings and emotions through their cry using a nonclinical *** in the cry sound can be identified using our method and used to assess the baby’s *** considered the frequency of the cries from the energy of the *** feelings represented by the infant’s cry are judged to represent certain sensations expressed by the child using the optimal frequency of the recognition of a real-world audio *** used machine learning and artificial intelligence to distinguish cry tones in real time through feature *** experimental group consisted of 50%each male and female babies,and we determined the relevancy of the results against different *** application produced real-time results after recognizing a child’s cry *** novelty of our work is that we,for the first time,successfully derived the feelings of young children through the cry-speech of the child,showing promise for end-user applications.

关键词： Cry-to-speak machine learning artificial intelligence cry speech detection babies

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Design of S-band CubeSat Antenna 9

Design of S-band CubeSat Antenna

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9th International electrical engineering Congress, iEECON 2021

作者： Thunyakaset, N. Ratanacharoen, S. Namsang, A. Lerdwanittip, R. Chomtong, P. Akkaraekthalin, P. Civil Aviation Training Center Aeronautical Engineering Division Thailand Faculty of Technical Education Department of Teacher Training in Electrical Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9781728195841

A design of S-band planar monopole antenna suited for CubeSat communication system is presented. The antenna design uses two-layer printed circuit board based on the patch antenna. The patch is cut at the corners to make the surface currents circularly flow and is designed to have a maximum gain suitable for CubeSat configuration. The patch antenna is also designed by using CST software, which simulation results shows that the antenna provides great impedance matching in the S-band at 2.36-2.48 GHz, a bandwidth of 120 MHz, and a directional radiation pattern with maximum gain of 8.17 dBi. © 2021 IEEE.

关键词： Microstrip antennas

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Compact Null Steering Antenna with Hemispherical Null Coverage Under Feed Position Controlling

Compact Null Steering Antenna with Hemispherical Null Covera...

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IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)

作者： Shi-Tong Wang Lei Zhu Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City Faculty of Science and Technology University of Macau Macau China

ISBN: (数字)9798331520717

ISBN: (纸本)9798331520724

This paper proposes an effective strategy to implement pattern null steering by means of controlling the feed position. To demonstrate this strategy, a circular patch antenna with several shorting pins is developed. Under the simultaneous excitation of TM 11 and TM 02 modes, a pattern null is generated and can be reconfigured on the upper hemisphere by switching the feed position. Based on the theoretical analysis of null formation, the mapping relationship between null direction and feed position is revealed. According to the presented mapping relationship, the required feed position for a randomly given null direction can be conveniently determined. The measurement verification is presented. Moreover, a potential application of the proposed antenna in reducing the grating lobes is discussed in the last part of this paper.

关键词： Radio frequency Antenna measurements Patch antennas Conferences Switches Antenna feeds Pins Feeds Gratings

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