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2024 International Conference on Microelectronics, ICM 2024

作者： El-Tanbadawy, Mariam K. Salem, Mohammed A. Megeed Abd Elghany, Mohamed A. German University in Cairo Computer Engineering Dept. Egypt German University in Cairo Electronics Engineering Dept. Egypt Tu Darmstadt Integrated Electronic Systems Lab Germany

ISBN: (纸本)9798350379396

In the past few decades, Seizure Detection has been a vital cornerstone in biomedical research. Both hardware and software implementations have been explored to improve algorithms, detection performance and resources. In this paper, three handcrafted features composed of Coastline Function, Hurst Exponent and Fractal Dimension are used as training data for supervised learning models to build an efficient and sensitive seizure detector. Random Forest classifier exhibits the best accuracy at 98%. Hardware efficiency, too, is exploited through a modified Feature Extractor that combines the aforementioned features. The features are adjusted to reduce their hardware resources on Virtex-7 FPGA. The area utilization is improved by 10%, power utilization is improved by 20% and latency decreased by 32%. © 2024 IEEE.

关键词： Fractal dimension

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Dynamic Image Deblurring based on Crosshatch Attention Adversarial Network and Hybrid Loss 5

Dynamic Image Deblurring based on Crosshatch Attention Adver...

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5th International Conference on Advancements in Computational Sciences, ICACS 2024

作者： Aslam, Ummama Shaukat, Arslan Azam, Basim Dept. of Computer and Software Engineering H-12 Islamabad Pakistan Institute of Integrated and Intelligent Systems Griffith University Brisbane Australia

ISBN: (纸本)9798350394764

Image deblurring techniques that uses deep learning have shown great potential but due to low generalizability, noise immunity and the correlation among different pixels is not addressed in detail that results in unwanted artifact that appears in the deblurred image. To tackle this problem an end-to-end approach is proposed for the recovery of sharp image from blurred one without the estimation of blur kernel. A special type of attention module known as crosshatch attention is used after Residual Block of Generator model for removing noise and for the collection of correlation of different pixels in an image. Hybrid Loss function is defined which focus on different part of image and improve edges and texture details. The performance of the model for deblurring is measured on GoPro dataset. Our proposed model has slightly higher objective and subjective evaluation i-e PSNR, SSIM value and the visual results. © 2024 IEEE.

关键词： Pixels

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Autonomous Social Amenity, Pothole Detection and Reporting 4

Autonomous Social Amenity, Pothole Detection and Reporting

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4th International Multidisciplinary Information Technology and engineering Conference, IMITEC 2024

作者： Mosela, David Olaifa, Moses Owolawi, Pius Malele, Vusi Tshwane University of Technology Dept. Computer Systems Engineering Tshwane South Africa Tshwane University of Technology Dept. of Computer Systems Engineering Tshwane South Africa

ISBN: (纸本)9798350387988

Challenges faced by traffic management in many developing nations across the globe is a result of the poor quality of road infrastructure. Inadequate and defective road infrastructure are major contributors to this effect. A key element that poses significant risk to road safety and that leads to increased road management cost is the increasing number of potholes and inefficient detection and reporting approach. This study provides an in-dept. exploration of the latest developments in pothole detection systems and examines various methodologies and technologies used in these systems, emphasizing the importance of real-time monitoring for proactive road maintenance. In addition, we proposed a system that addresses the persistent challenge of road infrastructure degradation by adopting cutting-edge technologies, including computer vision, machine learning, and sensor networks (such as ultrasonic and GPIO systems) that are used to identify and assess potholes on road surfaces. To achieve the aim of the study, the system adopts the use of RasberryPi 4 Model B for pothole detection and YOLOv4 for image processing. © 2024 IEEE.

关键词： Highway administration

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THE DIGITAL engineering FACTORY: CONSIDERATIONS, CURRENT STATUS, AND LESSONS LEARNED

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INCOSE International Symposium 2024年第1期34卷 927-943页

作者： Gregory, Joe Salado, Alejandro O'Neal, Sharon Larez, Richardo Reda, C.J. Martell, Niko Martin, Evan Colson, Matthew Masterson, John Armenta, David Dept. of Systems and Industrial Engineering University of Arizona United States Electrical and Computer Engineering University of Arizona United States

In industry, the advancement of digital engineering and the digital thread aims to reduce the impact of knowledge ‘siloes’ by providing a way to integrate data across the entire system lifecycle and across multiple domains. In a typical engineering curriculum, however, courses are still treated as ‘siloes’, and students often do not have the opportunity to experience this industrially relevant approach to engineering. The Digital engineering Factory (DEF) is a digital engineering environment under development at the University of Arizona to support engineering students. The DEF supports students by providing access to multiple engineering tools and is structured using a ‘hub-and-spoke’ approach to consolidate data from these tools. Through this connected architecture, students can transfer data generated in a particular course to tools for use in other courses. Connecting course activities in this way enables students to experience a complete end-to-end system lifecycle. At its ‘hub’, the DEF uses Violet to integrate data from multiple sources, create a digital thread, and generate a graph representation of the dataset. This knowledge graph, written in the Ontological Modeling Language (OML), can be viewed in OML Rosetta and is structured according to the University of Arizona Ontology Stack (UAOS). The use of the UAOS and OML Rosetta allows instructors to leverage semantic web technologies to support teaching activities such as grading. In this paper, the authors review the objectives of the DEF, discuss the status of the project, and highlight current limitations and lessons learned with regards to its deployment. These may be useful to inform similar developments in industrial settings. Copyright © 2024 by Author Name. Permission granted to INCOSE to publish and use.

关键词： Life cycle

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Dynamic Network Optimization with Deep Learning and Deployment of Intelligent Reflecting Surfaces 19

Dynamic Network Optimization with Deep Learning and Deployme...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Jang, Nayeon Bae, Jeonghoon Tianyu, Tao Byun, Gyurin Bui, Phuoc-Nguyen Lee, Tae-Jin Choo, Hyunseung Dept. of AI Systems Engineering Korea Republic of Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798331507817

The proliferation of 5G technologies has presented challenges such as signal attenuation and high energy consumption. This study proposes a novel approach to enhance wireless networks by integrating Intelligent Reflecting Surfaces (IRS) and Artificial Intelligence (AI) to optimize signal propagation and predict the Received Signal Strength Indicator (RSSI). A new framework combines K-means clustering for IRS deployment with a Temporal Convolutional Network-Gated Recurrent Unit (TCN-GRU) model for signal prediction. Using data from 15,000 Wi-Fi access points in Herefordshire, UK, the results demonstrate significant improvements in signal strength, with the proposed model achieving a Mean Squared Error (MSE) of 37% lower than the existing models, indicating higher prediction accuracy. In addition to enhancing signal quality, the framework achieves throughput increases of 21.26% with single-group IRS and 64.91% with multi-group IRS. These results validate the proposed the potential of the framework to improve performance, making it suitable for next-generation wireless networks. © 2025 IEEE.

关键词： 5G mobile communication systems

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Application of Permanent Magnets with Different Magnetization in Magnetic Gear Considering Gear Ratio Conversion

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Transactions of the Korean Institute of Electrical Engineers 2023年第11期72卷 1366-1371页

作者： Byeon, Beom-Seok Park, Eui-Jong Jung, Sang-Yong Kim, Yong-Jae Dept. of Electrical Engineering Chosun University Korea Republic of Dept. of Engineering for Smart Mobility Convergence Systems Chosun University Korea Republic of Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

A permanent magnet was used to improve the torque density of the magnetic gear for gear ratio conversion, and a study was conducted to attach the permanent magnet to the tooth tip of the rotor. Through this, it was found that attaching a permanent magnet to the outer rotor is effective. In addition, in the case of gear ratio conversion, in this method, there is a part where the magnetization direction of the electromagnet and the permanent magnet are opposite, resulting in poor results. Therefore, when applied to teeth with coincident magnetization directions, good results were obtained in all cases even when the gear ratio was converted. Copyright © The Korean Institute of Electrical Engineers.

关键词： Permanent magnets

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Design of a Compact 2-Bit PIN Diode Reflection Type Phase Shifter using Radial Stub

Design of a Compact 2-Bit PIN Diode Reflection Type Phase Sh...

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2024 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2024

作者： Bilawal, Farah Babaeian, Fatemeh Karmakar, Nemai Chandra Dept. of Electrical and Computer Systems Engineering Monash University Melbourne Australia

ISBN: (纸本)9798350379693

The goal of this research is to create an optimized hybrid coupler structure for a PIN diode reflection type phase shifter (RTPS) operating at microwave frequencies. To date, no phase shifter has been reported with the proposed technique, compactness, minimum phase error and balanced amplitude. Another limitation of designing such structures at such high frequency range, is that the 50Ω impedance lines' width approaches its length for given substrate thickness, that is undesirable. This study introduces a new method of developing a module at 100 Ω and translating it back to 50 Ω at the input and output terminals. Moreover, the proposed design is highly resilient to manufacturing constraints owing to the addition of radial stubs instead of lumped components, as reflective loads. Its performance with respect to its bandwidth coverage is better with 15% bandwidth enhancement, insertion loss around 3dB, and reflection co-efficient at all ports is better than -15dB over the whole operating bandwidth. The simulated and measured results validate the proposed design effectively. © 2024 IEEE.

关键词： Bandwidth

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Polarimetric Image Fusion Strategies for Improving Target Shape and Contrast in Remote Sensing Applications 21

Polarimetric Image Fusion Strategies for Improving Target Sh...

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Electro-Optical and Infrared systems: Technology and Applications XXI 2024

作者： Ratliff, Bradley M. Tyo, J. Scott Taylor, Michael Prikkel, Connor Dept. Electrical & Computer Engineering Dayton University DaytonOH United States Electrical & Computer Systems Engineering Dept. Monash University Melbourne Australia

ISBN: (纸本)9781510681088

Images from passive imaging polarimeters are often displayed in terms of their intensity (s0), degree of linear polarization (DoLP), and angle of polarization (AOP). The AOP and DoLP together generally provide information about shape and surface quality of imaged objects;however, the information conveyed in these images are often difficult to interpret, especially to an analyst unfamiliar with polarization phenomenology. Furthermore, it can be challenging to train machine learning approaches with direct polarimetric information due to the limited availability of application-specific data. Augmenting s0 images with polarimetric information in the form of contrast and shape enhancement thus allows for the data to remain in the domain of traditional EO-IR intensity imagery that is more familiar for both humans and trained networks. In this work we explore several strategies for effectively fusing polarimetric information into s0 imagery to improve target shape and contrast for both human and algorithmic consumption, with a particular focus on remote sensing and target detection applications. © 2024 SPIE.

关键词： Image fusion

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Artificial Intelligence (AI) for Improving Performance at the Cutting Edge of Medical Imaging 5

Artificial Intelligence (AI) for Improving Performance at th...

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5th International IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2023

作者： Nour, Samar M. Faculty of Engineering Dept. Computer and Systems Engineering Cairo Egypt

ISBN: (纸本)9798350381030

Artificial intelligence (AI) has achieved great strides in recent years, with applications in a variety of areas of study, including healthcare. Consequently, the integration of artificial intelligence (AI) and medical imaging has ushered in a new era in healthcare diagnosis and therapy. Artificial intelligence (AI) has shown impressive potential in enhancing accuracy, efficiency, and diagnostic performance across a range of medical imaging modalities by using the power of deep learning (DL), machine learning (ML), and computer vision. In this paper, we are trying to investigate the connection between artificial intelligence (AI) and medical imaging, concentrating on how AI-driven strategies are improving performance at the cutting edge of medical imaging technologies through the proposed architecture model. Furthermore, the paper also explores the limitations and opportunities that result from incorporating artificial intelligence (AI) into the use of medical imaging. The potential for artificial intelligence (AI) to transform image-guided therapies and its implications for personalized medicine are investigated. © 2023 IEEE.

关键词： Medical imaging

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Forest Fire Prevention and Detection System 5

Forest Fire Prevention and Detection System

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5th IEEE International Conference on Power, Electronics and computer Applications, ICPECA 2025

作者： Jayakody, Lasitha Edirisinghe, Chamathka Senasinghe, Tharush Dissanayake, Shaminda Gamage, Narmada Pandithage, Dinithi Wijayaraja, Jaliya L. Sri Lanka Institute of Information Dept. of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798331533694

Forest fires pose significant threats to both the environment and human life, necessitating the development of advanced detection and prevention systems. In this study, we propose an integrated IoT (Internet of Things)-based system for early detection and management of forest fires. The system incorporates a range of sensors including heat, gas, and thermal imaging sensors, along with IoT technology for real-Time monitoring and communication. Utilizing image processing techniques and (ML) Machine Learning algorithms, the system can accurately detect fires, predict their spreading patterns, and analyze environmental conditions. Key features include the deployment of disposable heat sensors for temperature monitoring, IoT sensors for gas detection and weather monitoring, and a centralized processing node for data analysis. Alerts are sent to nearby authorities and residents, while automated firefighting devices are activated to suppress fires until backup arrives. Experimental results demonstrate the effectiveness of the proposed system in early detection and prevention of forest fires. © 2025 IEEE.

关键词： Temperature sensors

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