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14th IEEE International Conference on Electronics Information and Emergency Communication, ICEIEC 2024

作者： Wedaj, Fisseha Teju Hawbani, Ammar Wang, Xingfu Al-Gunid, Haithm M. Yilma, Getinet Farooq Qaisar, Muhammad Umar University of Science and Technology of China School of Computer Science and Technology Hefei China Shenyang Aerospace University School of Computer Science Shenyang China Adama Science and Technology University School of Electrical Engineering and Computing Adama Ethiopia Southern University of Science and Technology School of System Design and Intelligent Manufacturing Shenzhen China

ISBN: (纸本)9798350361889

In wireless sensor networks (WSNs), the coverage hole problem is one of the challenging problems that needs an effective solution. Data routing protocols in WSNs aim to disseminate the sensors' data to the central device with the minimum possible network resource usage. However, suppose there is a coverage hole in the middle of the source and destination nodes, and the source node doesn't have information about the hole. In that case, the data may choose the longer and more repetitive path to reach the destination, increasing resource usage, mainly energy and time. The condition is even more challenging when the network employs a mobile data collector. This paper proposes a Coverage Hole Aware Data Routing (CHADR) protocol for Mobile Sink WSNs that determines the shorter hole bypassing path in advance at the source node using the hole and data collector location information. CHADR evaluates the path efficiency using directional angle and expected hops count. After determining the path, data will be transmitted to the mobile sink using an Opportunistic routing technique. We proved CHADR performance with experimental simulations. © 2024 IEEE.

关键词： Routing protocols

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DENSE-Guided Deep Motion Networks Accounted by Large Rotations to Improve Myocardial Strain Analysis from Routine Cine MRI 22

DENSE-Guided Deep Motion Networks Accounted by Large Rotatio...

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22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025

作者： Lei, Pengcheng Xing, Jiarui Fang, Faming Epstein, Frederick H. Zhang, Miaomiao University of Virginia Department of Electrical and Computer Engineering United States School of Computer Science and Technology East China Normal University Shanghai China University of Virginia Health System Department of Biomedical Engineering United States

ISBN: (纸本)9798331520526

Myocardial strain imaging provides a valuable tool for detecting subclinical left ventricular (LV) dysfunction and adding prognostic value in assessing various types of heart disease. Recent studies have utilized highly accurate strain-dedicated techniques, such as displacement encoding with stimulated echoes (DENSE), to train a deep learning (DL) framework to predict the myocardial displacements/deformations from routine cine balanced steady state free precession (bSSFP) images. However, these methods have shown limited performance in capturing the large rotational motion of the myocardium associated with twist and torsion over time, which are important aspects of myocardial mechanics. To address this gap, this paper introduces a novel DENSE-guided DL network that explicitly accounts for large rotational motion to further improve strain analysis of standard cine bSSFP images. Specifically, our proposed network includes two key components: (i) a time-series rotation estimation network employing a 3D convolutional encoder-decoder architecture to model the large rotational dynamics of the LV myocardium over time, and (ii) a radial motion prediction network based on deformable image registration. The output of these two sub-networks was integrated and refined through a fusion network to predict the final myocardial displacements, supervised by DENSE ground truth. Experimental results show that our method improves the accuracy of myocardial strain with effectively captured large rotations. © 2025 IEEE.

关键词： Rotation

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A Novel Determination of Soluble NPK Nutrient Measurement system Using K-means and SOM Methods Compared with UV Visible Spectrophotometer

A Novel Determination of Soluble NPK Nutrient Measurement Sy...

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2023 International electrical engineering Congress, iEECON 2023

作者： Tipwong, Wallop Sirikham, Adisorn Konpang, Jessada Kirdpipat, Putthiphong Chongjarearn, Yutana Preutisrunyanont, Oradee Rajamangala University of Technology Krungthep Department of Electrical and Telecommunication Engineering Bangkok Thailand Thammasat School of Engineering Thammasat University Faculty of Engineering Department of Electrical and Computer Engineering Pathum Thani Thailand Dhurakij Pundit University Department of Robotic Engineering and Automation System Bangkok Thailand

ISBN: (纸本)9798350332360

Technologies are currently being used in smart farms to improve productivity. Agricultural innovation is also widespread. Therefore, the development of Internet of Things (IoTs) technologies and devices to collect data is important. Finding essential nutrients for growth such as Nitrogen (N), Phosphorus (P) and Potassium (K) are important factors. Competitiveness is the important key for growing vertically or indoors. However, soil testing can be expensive, complicated and time consuming. The development of devices that can effectively measure nutrient NPK levels could be used over time. This paper presents a suitable clustering using the K-means method and a forecasting method using the Self-Organizing Map (SOM) method to enhance the device's ability to analyze nutrients in real time. A total of 50,688 samples were tested using the K-Means clustering algorithm, and the sample data were also analyzed. A SOM was prepared to predict the accuracy of the analysis. A total of 11,486 samples were tested and analyzed, then the results of the soluble NPK nutrient monitoring system were taken. It has an efficiency of 84.15% compared to using a UV Visible spectrophotometer, allowing data to be predicted during nutrient solubility changes and to operate according to the proposed system. Therefore, the unsupervised machine learning will improve the measurement system of future cultivation systems. © 2023 IEEE.

关键词： Nutrients

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Multi-view 3D reconstruction based on speckle correlation 8

Multi-view 3D reconstruction based on speckle correlation

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8th International Conference on Speckle Metrology, Speckle 2023

作者： Zeng, Xiaoxian Jing, Yu Tang, Qijian Liu, Xiaoli Peng, Xiang Key Laboratory of Optoelectronic Devices System of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW2522 Australia

ISBN: (数字)9781510674592

ISBN: (纸本)9781510674585

Three-dimensional (3D) reconstruction based on digital speckle correlation has gained widespread usage in dynamic scenarios due to its ability to achieve single-frame reconstruction. Traditional binocular speckle structured light systems often face challenges such as insufficient surface texture richness and excessive curvature, leading to limitations in the accuracy of corresponding point localization during the matching process. Furthermore, partial point cloud loss caused by varying viewpoints can impact the precision and completeness of 3D reconstruction. This paper introduces a Multiview speckle correlation-based approach for 3D reconstruction. By establishing multi-view stereo camera epipolar rectification, complex speckle matching issues are transformed into one-dimensional searches along unified epipolar lines, simplifying the matching process and enhancing efficiency. Additionally, a digital speckle correlation computational model and subpixel interpolation algorithm based on Newton-Raphson iteration are employed to realize multi-view subpixel-level corresponding point localization. Ultimately, the reconstruction point cloud data is obtained through the intersection of three-ray least squares method. Experimental results demonstrate that this method achieves higher accuracy and better model completeness in 3D data reconstruction. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Speckle

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Three-dimensional reconstruction based on three-dimensional phase mapping using single-pixel imaging

Three-dimensional reconstruction based on three-dimensional ...

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2024 International Conference on Optoelectronic Information and Optical engineering, OIOE 2024

作者： Liu, Yemei Li, Yanfei Yu, Jing Miao, Yupei Liu, Xiaoli Peng, Xiang Tang, Qijian Key Laboratory of Optoelectronic Devices and System of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW2522 Australia

ISBN: (数字)9781510680470

ISBN: (纸本)9781510680463

The single-pixel imaging technique has garnered widespread attention and research due to its low requirements on detector resolution and equipment cost. In this study, a laser point scanning single-pixel imaging system is constructed. It utilizes a grating installed in front of the detector to capture a single-frame deformed fringe pattern, combining Fourier transform profilometry with three-dimensional phase mapping to ultimately achieve three-dimensional data acquisition. Following the calibration of the system, the positions of each light ray are calibrated using the intrinsic and extrinsic parameters obtained through camera calibration. Consequently, this paper proposes a single-pixel three-dimensional reconstruction method based on three-dimensional phase mapping, establishing a correlation between three-dimensional points and phases to realize three-dimensional phase mapping. Experimental results demonstrate that the model can achieve high reconstruction accuracy, presenting a novel solution for the field of single-pixel three-dimensional reconstruction. © 2024 SPIE.

关键词： Calibration

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Innovative fusion of VGG16, MobileNet, EfficientNet, AlexNet, and ResNet50 for MRI-based brain tumor identification

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Iran Journal of computer Science 2024年第1期8卷 185-215页

作者： Kia, Marjan Sadeghi, Soroush Safarpour, Homayoun Kamsari, Mohammadreza Jafarzadeh Ghoushchi, Saeid Ranjbarzadeh, Ramin Department of Business Information System Business Analysis (ISBA) Park University Parkville United States School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Software Engineering University of Szeged Szeged Hungary Faculty of Electrical Engineering Malek-Ashtar University of Technology(MUT) Esfahan Iran Faculty of Industrial Engineering Urmia University of Technology Urmia Iran School of Computing Faculty of Engineering and Computing Dublin City University Dublin Ireland

This study presents a novel approach for brain MRI classification by integrating multiple state-of-the-art deep learning (DL) architectures, including VGG16, EfficientNet, MobileNet, AlexNet, and ResNet50, with an attention mechanism. The primary objective was to accurately detect the presence or absence of brain tumors—a critical challenge in medical diagnosis. The methodology was validated on a comprehensive dataset comprising 3264 brain MRI scans, systematically divided into training, validation, and testing subsets. Preprocessing techniques tailored for MRI data were employed to enhance input quality. Each model was initially developed and evaluated individually to establish a performance baseline before their integration. The proposed ensemble technique capitalized on the complementary strengths of these models to enhance classification accuracy and robustness. The inclusion of an attention mechanism further refined the models by emphasizing critical regions in the MRI scans, thereby boosting predictive performance. In addition, data augmentation techniques were applied to mitigate overfitting and increase dataset resilience. Performance metrics, including precision, accuracy, and recall, demonstrated significant improvements across all evaluations, particularly for the models incorporating the attention mechanism. These findings highlight the potential of combining advanced DL architectures with attention mechanisms as a promising strategy for precise and reliable brain tumor classification in MRI scans. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： AlexNet Attention mechanism Brain tumor classification MobileNet ResNet50

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Multi-state system reliability:An emerging paradigm for sophisticated engineered systems

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Frontiers of engineering Management 2024年第3期11卷 568-575页

作者： Yu LIU Tangfan XIAHOU Qin ZHANG Liudong XING Hong-Zhong HUANG School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Center for System Reliability and Safety University of Electronic Science and Technology of ChinaChengdu 611731China Department of Electrical&Computer Engineering University of Massachusetts DartmouthMA 02747USA

1 Introduction Reliability is defined as the probability that a system or component will perform its required function for a specified period of time under specified operating conditions(Ebeling,2019).Traditional reliability theory assumes that both a system and its components have only two possible states in the operation stage,either perfectly functioning or completely ***,as engineered systems become more sophisticated,involving larger sizes,increased functionality,and greater intelligence,and with advancements in sensing technologies,it has been extensively observed that systems and components exhibit multiple distinct states as they deteriorate over *** failure behavior,damage severity,performance capacity,and operational efficiency of the system and components vary among these states(Lisnianski et al.,2018).It,therefore,necessitates the development of advanced reliability theories and methodologies that are capable of characterizing these systems and components with multi-state nature.

关键词： system state specified

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system Modelling, Numerical Simulations and Experimental Validation of High Capacity FSO Data Transmission in DWDM Communication Employing Optical Frequency Comb 24

System Modelling, Numerical Simulations and Experimental Val...

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24th IEEE International Conference on Numerical Simulation of Optoelectronic Devices, NUSOD 2024

作者： Rajaram, Narmada Avazpour, Mahrokh Barry, Liam Hinzer, Karin Hall, Trevor Atieh, Ahmad School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada School of Electronic Engineering Dublin City University Radio and Optics Communications Laboratory GlasnevinDublin 9 Ireland University of Ottawa Optiwave System Inc 7 Capella Court Ottawa Canada

ISBN: (纸本)9798350390537

Dense Wavelength Division Multiplexing (DWDM) optical technology allows transmission of many wavelengths in a single optical channel. In this paper, system modelling and numerical simulations are demonstrated for high-capacity data transmission using an Optical Frequency Comb (OFC). An OFC is generated using fiber loop modulation technique and simulations are carried out using commercially available simulation software -Optisystem. An OFC with excellent flatness is obtained, which is essential for noise and error reduction. Each comb line is modulated with data and the DWDM multiplexed signal is transmitted over a free-space optical (FSO) channel. The system performance is assessed in terms of Bit Error Rate (BER) and range of the FSO channel. Our experimental results demonstrate that our system aligns well with simulation and can generate an OFC confirming the potential of our approach for applications such as optical communication networks. © 2024 IEEE.

关键词： Bit error rate

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Development of Vehicle-to-Grid systemto Regulate the system Parameters of Microgrid

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Energy engineering 2022年第4期119卷 1261-1298页

作者： Om PrakashMahela Baseem Khan Rupendra Kumar Pachauri Power System Planning Division Rajasthan Rajya Vidyut Prasaran NigamLtd.Vidyut BhawanJapurIndia Department of Electrical and Computer Engineering Hawassa UniversityHawassaEthiopia Electrical Engineering Department School of EngineeringUniversity of Petroleum and Energy StudiesDehradunIndia

This paper proposes a vehicle-to-grid(V2G)system interfaced with a microgrid that is effective at regulating frequency on a microgrid over a 24-h cycle.A microgrid is designed and divided into four *** first component is a diesel generator,which is used to act as the base power *** second component consists of renewable energy(RE)power plants,which include solar photovoltaic(PV)and wind *** third component is a V2G *** last component is the load connected to the microgrid.A microgrid is designed to be of sufficient size to represent a community of one thousand households during the day period of low consumption in the spring or fall seasons.A hundred electric vehicles(EVs)are modeled as base models to realize a 1:10 ratio for cars to households,which indicates a possible scenario in the near *** analysis of the active power,reactive power,voltage,frequency,and current is carried *** is established that the proposed design of the V2G andmicrogrid effectivelymaintains systemparameters such as frequency and voltage within permissible limits with an error of less than 1%.Further,transient deviations in these parameters are limited to within 5%.A microgrid with V2G devices regulates the system frequency by mitigating load demand through coordinated control of conventional generation,solar PV plant generation,wind plant generation,power exchange with the microgrid network,and electric *** proposed microgrid and V2G are efficient for energy management and mitigation of intermittency and variability of RE power with improved *** in system parameters have been investigated by changing the operating scenario,and it has been determined that the error is limited to less than 5%.The study is effectively realized in the MATLAB/Simulink environment.

关键词： Microgrid electric vehicles vehicle-to-grid renewable energy PV wind

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Comprehensive Overview of Multi-agent systems for Controlling Smart Grids

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CSEE Journal of Power and Energy systems 2022年第1期8卷 115-131页

作者： Om Prakash Mahela Mahdi Khosravy Neeraj Gupta Baseem Khan Hassan Haes Alhelou Rajendra Mahla Nilesh Patel Pierluigi Siano Power System Planning Division Rajasthan Rajya Vidyut Prasaran Nigam Ltd.Jaipur-302005India Media Integrated Communication Laboratory Graduate School of EngineeringOsaka UniversityOsakaJapan Computer Science and Engineering Department Oakland UniversityRochesterUSA Department of Electrical and Computer Engineering Hawassa UniversityHawassa 1530Ethiopia Faculty of Mechanical and Electrical Engineering Tishreen UniversityLattakiaSyria Department of Electrical Engineering National Institute of Technology Kurukshetra Department of Management&Innovation Systems University of Salerno84084 SalernoItaly

Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience.A multi-agent system(MAS)contains multiple,intelligent,and interconnected collaborating agents for solving a problem beyond the ability of a single agent.A smart grid(SG)combines advanced intelligent systems,control techniques,and sensing methods with an existing utility power *** controlling smart grids,various control systems with different architectures have already been ***-based control of power system operations has been shown to overcome the limitations of time required for analysis,relaying,and protection;transmission switching;communication protocols;and management of plant *** systems provide an alternative for fast and accurate power network *** paper provides a comprehensive overview of MASs used for the control of smart *** paper provides a wide-spectrum view of the status of smart grids,MAS-based control techniques and their implementation for the control of smart *** of MASs in the control of various aspects of smart grids-including the management of energy,marketing energy,pricing,scheduling energy,reliability,network security,fault handling capability,communication between agents,SG-electrical vehicles,SG-building energy systems,and soft grids—have been critically *** than a hundred publications on the topic of MAS-based control of smart grids have been critically examined,classified,and arranged for fast reference.

关键词： Coordinated control multi-agent systems renewable energy sources smart energy infrastructure smart grid

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