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8th International Conference on Information Technology, Information Systems and electrical engineering, ICITISEE 2024

作者： Darabkh, Khalid A. Al-Mistarihi, Mamoun F. Al-Maaitah, Mera Ismail School of Engineering The University of Jordan Computer Engineering Department Amman11942 Jordan Jordan University of Science and Technology Faculty of Engineering Electrical Engineering Department Irbid22110 Jordan

ISBN: (纸本)9798350368970

In this article, we propose a novel protocol that employs different technologies together, such as Software Defined Network (SDN) for the purpose of offering scalability, programmability, and global network information, and Fog computing for the reason of providing location services that meet V ANET standards. Additionally, we propose a novel cluster head selection algorithm for the purpose of enhancing the efficiency of the protocol by considering three different dimensions, namely, lifetime, average distance, and signal-to-interference noise ratio. The novelty of this proposed algorithm comes from reducing the number of control overheads, reducing long-distance communications, and reducing packet loss due to collisions and contentions inside each cluster, respectively. The proposed protocol has been assessed using N s3 simulator whereas its results are so promising and worth publishing. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Quantifying the Effects of Chemotherapy-Induced Toxicity and Knockout of the Transcription Factor c-Myc on Mice Kidney Metabolism Using Optical Imaging

Quantifying the Effects of Chemotherapy-Induced Toxicity and...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Neghabi, Mehrnoosh Nategh, Parisa Ceyhan, Busenur Konjalwar, Shalaka Santana, Aline G. Machi, Jaqueline F. Rodrigues, Claudia O. Ranji, Mahsa Department of Electrical Engineering and Computer Science Florida Atlantic University United States Department of Biomedical Science Florida Atlantic University United States

The study explores knockout of c-Myc and doxorubicin toxicity influence on mouse kidney's metabolism. Cryo-imaging unveils knockout is significantly more oxidized compared to control group while this was not obser... 详细信息

ISBN: (纸本)9781957171395

关键词： Chemical lasers

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Non Linear Homogenization of Laminate Magnetic Material by Computing Equivalent Magnetic Reluctivity 14

Non Linear Homogenization of Laminate Magnetic Material by C...

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19th International Conference on Software Technologies, ICSOFT 2024

作者： Yousfi, Ghania Mohellebi, Hassane Electrotechnics Department Faculty of Electrical Engineering and Computer Science Mouloud Mammeri University Tizi-Ouzou Algeria

ISBN: (纸本)9789897587061

In the present study we present a numerical modeling of a laminate magnetic material using an homogenization technique which exploit an inverse problem resolution. The laminate magnetic material is consisting of an alternate of magnetic and insulates layers. The equivalent magnetic reluctivity is computed for the homogenized domain by considering a non linear behavior of the magnetic layers. A finite element method is used to solve the 2D non-linear electromagnetic partial differential equation. An optimization problem is constructed and solved with the association of the 2D finite element resolution and a conjugate bi-gradient algorithm. The computation of the equivalent magnetic reluctivity is then performed for different excitation field value according to B-H curve. The comparison of the obtained B-H curves of the laminate and the homogenized domains to the theoretical B-H curve (experimental data) show a good agreement of laminate results. © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Inverse problems

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Characterization of Traffic in the Internet of Vehicles Using Microscopic Modelling

Characterization of Traffic in the Internet of Vehicles Usin...

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2024 IEEE International Conference on Advanced Telecommunication and Networking Technologies, ATNT 2024

作者： Obeng, Kobby Asare Ariffin, Sharifah H.S. Muhammad, Nor Aishah Baharudin, Muhammad Ariff Universiti Teknologi Malaysia Faculty of Electrical Engineering Malaysia Koforidua Technical University Department of Computer Science Ghana Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor Malaysia

ISBN: (纸本)9798350353501

The emergence of the Internet of Vehicles (IoV) as a driver for the new age of Intelligent Transportation Systems (ITS) provides an opportunity for a wide range of services and applications driven by the various interactions that exist between a vehicle and its environment. However, the nature of road networks affects real-time vehicular movements with respect to the departure, delay, speed and arrival of vehicles. In this paper, we present a data-driven, traffic theory and microscopic traffic simulation approach that can be used in modelling the underlying vehicular network of the IoV. Using the traffic status from the A4 highway dataset in Luxembourg, we obtain vehicular volumes from the vehicle flow rate, define thresholds for traffic status using data scaling and employ microscopic modeling to create traffic scenarios. The analysis from the results of the traffic scenarios shows unique vehicular patterns due to the nature of the road network providing insights that ultimately affect the design and implementation of IoV-based services and applications. © 2024 IEEE.

关键词： Internet of things

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Software design and FPGA implementation of optimized medical image fusion techniques

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Multimedia Tools and Applications 2025年 1-31页

作者： Elshazly, E.A. El-Shafai, Walid El-Hoseny, Heba El-Rabaie, El-Sayed M Zahran, O. Abdelwahab, Safey A. S. El-Halawany, M.M. Fikry, R.M. Elaraby, S.M. Faragallah, Osama S. Mohamed, Wael A. Mahmoud, Korany R. Abd El-Samie, Fathi E. Cairo Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Faculty of Computer Studies Arab Open University 11681 Riyadh Saudi Arabia Department of Information Technology College of Computers and Information Technology Taif University 11099 Taif21944 Saudi Arabia Department of Electrical Engineering Faculty of Engineering Benha University Benha Egypt Electronics and Communications Engineering Department Faculty of Engineering Helwan University Helwan Egypt Giza Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Nowadays, medical image fusion plays a crucial role in enhancing the diagnosis accuracy and the clinical decision-making process in various healthcare applications. This research work presents a comprehensive study of the design and implementation of optimized medical image fusion techniques using a combination of software and Field-Programmable Gate Array (FPGA) technologies. The proposed medical image fusion strategy is based on the utilization of Discrete Wavelet Transform (DWT) and Modified Central Force Optimization (MCFO). The implementation of the proposed technique as well as the traditional medical image fusion techniques is considered using an appropriate software design and FPGA. The presented techniques aim to overcome the limitations of traditional fusion techniques by integrating advanced image processing algorithms, optimization algorithms, and parallel computing capabilities offered by FPGA platforms. The first step in the proposed framework is to match the histogram of one of the images with that of the other, so that both images will have the same dynamic range. After that, the DWT is used to decompose the images that should be fused together. Based on some constraints, the MCFO optimization algorithm is used to evaluate the optimum level of decomposition and the optimum parameters for the best fusion quality. Finally, to improve the obtained visual quality and reinforce the information in the fusion result, an additional contrast enhancement step using adaptive histogram equalization is applied to the fusion result. Comparative study between the proposed optimized DWT-based fusion framework, the traditional Principal Component Analysis (PCA), Additive Wavelet Transform (AWT), and DWT-based fusion techniques is presented. Various metrics of fusion quality are considered, including average gradient, standard deviation, local contrast, entropy, edge strength, Peak Signal-to-Noise Ratio (PSNR), Qab/f, and processing time. The proposed optimized DWT-ba

关键词： MATLAB

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The Optimum Switching Bilateral of Various Mix Noise Filters to reduce Medical X-Ray Images 12

The Optimum Switching Bilateral of Various Mix Noise Filters...

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12th International electrical engineering Congress, iEECON 2024

作者： Langampol, Kriengkri Prayote, Akara Lee, Wilaiporn Srisomboon, Kanabadee Rajamangala University Of Technology Phra Nakhon Faculty Of Engineering Department Of Computer Engineering Thailand King Mongkut's University Of Technology North Bangkok Faculty Of Applied Science Department Of Computer And Information Science Thailand King Mongkut's University Of Technology North Bangkok Faculty Of Engineering Department Of Electrical And Computer Engineering Thailand

ISBN: (纸本)9798350383591

In the past few years, image processing has been widely adopted for symptom diagnosis of medical application. To achieve accurate analysis, the medical applications require high quality image for applying to the symptom diagnosis applications. However, the medical image quality may drop due to the imperfection of devices and the environment. Noise is one of the most critical factors that reduces the image quality where the noise may form by combining two types of noises. In this paper, we considered four well-known mixed noise filters including TF, BM3D, NCSR and OSBF filters. Since the OSBF filter is the alternative version of SBF filter that requires to determine the optimal weights, therefore we first determine the optimal weights for the medical image under the combination of Gaussian noise and salt-and-pepper noise. Then, we evaluate the filtering performance under three metrics including PSNR, SSIM and filtering time. As a result, OSBF filter achieves the best filtering performance since it can reduce the noise effect, preserve image details and consumes the short filtering time. On the other hand, the filtering performance of the TF filter suffers from the combining of salt-and-pepper noise. © 2024 IEEE.

关键词： Salt and pepper noise

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Dual-Channel MEMS Actuated Tunable Optical Filter Based on Polarization Insensitive Compound Ring Resonator for DWDM Networks 11th

Dual-Channel MEMS Actuated Tunable Optical Filter Based on P...

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11th EAI International Conference on Advancement of science and Technology, ICAST 2023

作者： Ayalew, Hailu Dessalegn Talabattula, Srinivas Annamalai, Pushparaghavan Electrical and Computer Engineering Faculty Bahir Dar University-Institute of Technology Bahir Dar Ethiopia Department of Electrical Communication Engineering Indian Institute of Science Bangalore India

ISBN: (纸本)9783031641503

One of the key components of wavelength division multiplexing (WDM) networks is tunable optical filters (TOFs). This paper focused on the theoretical analysis and design of a new dual-channel micro-electromechanical system (MEMS) actuated tunable optical filter based on polarization insensitive compound ring resonators (PICRRs) for dense wavelength division multiplexing (DWDM) optical networking applications. It is basically structured on an optimally designed capacitive type microcantilever beam, which is fixed at both ends, with built-in PICRRs, which are placed at both fixed ends of the beam to gain linearly varying longitudinal strain and stress on the resonators. Also, the dimensions of the rings are properly chosen to achieve a full width at half maximum (FWHM) of 0.4078 nm with a flat pass band at 1 dB of 0.3626 nm and a good shape factor for both channels. It also shows a free spectral range of about 20.05 nm for the first channel and 20.046 nm for the second channel, with a high extinction ratio that allows filtering of adjacent channels of 50 GHz DWDM systems. Thus, when the electrostatic attraction force (EAF) is applied, the beam will bend, which induces strain and stress in the rings, which brings a change in effective refractive index of the rings and also affects the perimeter and coupling coefficients of the rings that leads to a change in the output spectrum shift, providing the tunability as high as 4.779 nm/μN, and it is capable of tuning up to 355 GHz with negligible variations of FWHM and channel spacing within the tunability range of the two channels. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Dense wavelength division multiplexing

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Optimizing Optical Attocells Positioning of Indoor Visible Light Communication System

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computers, Materials & Continua 2023年第2期74卷 3607-3625页

作者： Mohammed S.M.Gismalla Asrul I.Azmi Mohd R.Salim Farabi Iqbal Mohammad F.L.Abdullah Mosab Hamdan Muzaffar Hamzah Abu Sahmah M.Supa’at School of Electrical Engineering Faculty of EngineeringUniversiti Teknologi MalaysiaSkudai81310Malaysia Lightwave Communications Research Group(LCRG) Faculty of Electrical EngineeringUniversiti Teknologi Malaysia(UTM)SkudaiJohorMalaysia Department of Electronics and Electrical Engineering Faculty of EngineeringInternational University of AfricaKhartoum12223Sudan Department of Communication Engineering Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Parit RajaBatu Pahat86400JohorMalaysia Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Department of Computer Science University of São PauloSão PauloBrazil

Visible light communication(VLC),which is a prominent emerging solution that complements the radio frequency(RF)technology,exhibits the potential to meet the demands of fifth-generation(5G)and beyond *** random movement of mobile terminals in the indoor environment is a challenge in the VLC *** model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio(SNR).As such,the optical attocells positions were optimized in this study with a developed try and error(TE)*** optimized optical attocells were examined and compared with previous *** novel approach had successfully increased minimum received power from−1.29 to−0.225 dBm,along with enhanced SNR performance by 2.06 *** bit error rate(BER)was reduced to 4.42×10−8 and 6.63×10−14 by utilizing OOK-NRZ and BPSK modulation techniques,*** optimized attocells positions displayed better uniform distribution,as both received power and SNR performances improved by 0.45 and 0.026,*** the results of the proposed model are optimal,it is suitable for standard office and room model applications.

关键词： Visible light communication(VLC) optical attocell received power signal-to-noise ratio(SNR) bit error rate(BER) coefficient of variation(CV)

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Alzheimer’s Disease and Frontotemporal Dementia: Differential Diagnosis Using Electroencephalogram Signal 1

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13th National Technical Symposium on Unmanned System Technology, NUSYS 2023

作者： Rostamikia, Mehran Sarbaz, Yashar Farzamnia, Ali Biomedical System Modeling Lab Biomedical Engineering Department Electrical and Computer Engineering Faculty University of Tabriz Tabriz Iran Faculty of Engineering Universiti Malaysia Sabah Sabah Kota Kinabalu Malaysia School of Computing and Engineering University of Huddersfield Huddersfield United Kingdom

ISBN: (数字)9789819720279

ISBN: (纸本)9789819720262

Dementia is a neurological disorder that affects a person’s cognitive and social skills, leading to a decline in their overall mental functioning. Frontotemporal dementia (FTD) and Alzheimer’s disease (AD) are two common types of dementia. Frontotemporal dementia mostly affects the frontal and temporal lobes of the brain. These areas are responsible for executive functions, decision-making, language, behavior regulation, and personality traits. Alzheimer’s disease primarily damages the cerebral cortex, which is responsible for higher cognitive functions such as memory, language, and perception. The electroencephalogram (EEG) signal has many advantages in diagnosing these disorders, including low cost and high temporal resolution. This study compares AD and FTD patients with healthy subjects by extracting specific features from EEG signals. Two machine learning algorithms were used for the separation, Support Vector Machines (SVMs) and k-Nearest Neighbors (KNNs), and 10-Fold Cross-Validation was applied to validate the performance of this method and an accuracy of 91.2% (sd = 7.8) was achieved using the SVM classifier for diagnosing the disease and 71.1% (sd = 8.6) for classifying AD and FTD. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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A Comprehensive Two-Step Methodology for Automated Segmentation of Architectural Distortion in Mammograms 6

A Comprehensive Two-Step Methodology for Automated Segmentat...

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6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Ibrahim, Sameh E. Elnokrashy, Ahmed F. Mohamed, Wael A. Benha University Benha Faculty of Engineering Department of Electrical Engineering Benha Egypt Benha University Electrical Engineering Benha Egypt Nile University Computer Science Giza Egypt

ISBN: (纸本)9798350378511

Breast cancer is one of the most prevalent forms of cancer worldwide and a leading cause of mortality among women. Early detection of breast cancer is crucial for effective treatment. Architectural distortion (AD) is an early sign of breast cancer, characterized by a subtle contraction of breast tissue that often goes unnoticed. Traditional methods of detection heavily rely on the expertise of radiologists, making the process more difficult. To address this, we propose a deep learning approach to automate precise and efficient AD segmentation. Our approach involves a two-step process. In the first step, we utilize a Mask R-CNN Detectron2 model to perform AD segmentation across the entire set of mammography images. This initial segmentation provides a baseline for identifying AD regions. The ResNet-18 patch model is incorporated into the Mask R-CNN model's segmentation pipeline in the second stage. The purpose of this combination is to improve AD area localization and precision. By combining the strengths of both models, we achieve improved accuracy in AD segmentation. The evaluation of our fully automated method yielded remarkable outcomes on a diverse test set consisting of private datasets, including the Baheya dataset and the NCI dataset, as well as the publicly available Digital Database for Screening Mammography (DDSM). The results showed a Segmentation Accuracy of 0.852, Classification Accuracy of 0.915, and Mean Average Precision (mAP) of 0.894. These findings demonstrate potential to enhance the efficiency and accuracy of AD detection and segmentation in mammogram images, contributing to early diagnosis and treatment planning for patients at risk of breast cancer. © 2024 IEEE.

关键词： Mammography

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