2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI)最新文献_第5页

Design a PLC-Based Automated and Controlled Liquid Filling-Capping System 设计一种plc自动控制的液体灌装封盖系统

2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) Pub Date : 2022-11-06 DOI: 10.1109/EICEEAI56378.2022.10050478

Abdulrahim Mahrez, Abdulrahim Hilmy, Abduelaziz Alasoad, Adel Yahya, Khalid Yahya, A. Amer, Hani H. Attar

引用次数: 0

Simulating a Charging Station for Electric Vehicles (EV) Based on the Concept of the Markov Chain to Analyze the System Performance 基于马尔可夫链的电动汽车充电站仿真系统性能分析

2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) Pub Date : 2022-11-06 DOI: 10.1109/EICEEAI56378.2022.10050450

Sahand Hamzehei, Omid Akbarzadeh Pivehzhani, Nazanin Fasihihour, M. Alzgool, M. Khosravi

引用次数: 0

The Ability of Ultra Wideband to Differentiate Between Hematoma and Tumor Occur in The Brain 超宽带对颅内血肿和肿瘤的鉴别能力

2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) Pub Date : 2022-11-06 DOI: 10.1109/EICEEAI56378.2022.10050471

A. Alqerem, Hani Attar, Waleed Alomoush, Mohand Deif

{"title":"The Ability of Ultra Wideband to Differentiate Between Hematoma and Tumor Occur in The Brain","authors":"A. Alqerem, Hani Attar, Waleed Alomoush, Mohand Deif","doi":"10.1109/EICEEAI56378.2022.10050471","DOIUrl":"https://doi.org/10.1109/EICEEAI56378.2022.10050471","url":null,"abstract":"Undiagnosed intracranial injuries or tumors can result in lifelong brain damage, severe disability, or death. Intracranial hematomas and tumors must be diagnosed and treated promptly to improve patient outcomes. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) detect cerebral bleeding and malignancies. This research aims to study the Ultra Wide Band (UWB) signals' ability to detect hematoma and tumors in the human head. The features of UWB are very vast/fast with very low power density; it gets its input in very narrow pulse ranges from 100ps to a few nanoseconds; consequently, due to the low power density, the tissues don't get ionized. The bandwidth is more than 20% of the center frequency or 500MHz. The average power spectral density should not exceed −41.3dBm/MHz frequency range used in medical applications should be between 3.1 to 10.6 GHz. The head model is divided into seventeen different tissue types, which are: Cerebro-Spinal-Fluid (CSF), Grey matter (GM), Skin, Cerebellum, Bone, Fat, Dura, White matter (WM), Cartilage, Sclera, Tongue, Eye Lens, Vitreous Humor, Blood, Muscles, Spinal Cord (nerve), and Sinuses (air). Each layer in the model is assigned specific dielectric properties (at 3.1 to 9 GHz) according to the tissue types. This model is proposed to study the effect of internal bleeding and tumor of the brain on the characteristics of the reflected and transmitted ultra-wideband waves from the brain model; CST MICROWAVE STUDIO has designed the actual phantom head model.","PeriodicalId":426838,"journal":{"name":"2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134364199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Structural Analysis of Back-Iron for Axial-Flux PM High-Speed Machines 轴向磁通永磁高速机床背铁结构分析

2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) Pub Date : 2022-11-06 DOI: 10.1109/EICEEAI56378.2022.10050459

T. El-Hasan, Mohammed Y. Mosleh, M. Mnati

{"title":"Structural Analysis of Back-Iron for Axial-Flux PM High-Speed Machines","authors":"T. El-Hasan, Mohammed Y. Mosleh, M. Mnati","doi":"10.1109/EICEEAI56378.2022.10050459","DOIUrl":"https://doi.org/10.1109/EICEEAI56378.2022.10050459","url":null,"abstract":"Back-iron plays a vital role in electrical machines as they are normally designed to complete the magnetic circuit. Although laminated steel sheets have been used in traditional machines, they are not appropriate for high-speed rotating structure since they are exposed to high centrifugal forces which may cause mechanical failure. Rigidity, mechanical integrity and robustness are important factors that must be taken into account while designing the back-iron. This paper presents the utilization of annulus disc type back-iron fitted at the back of PM rotor for high rotational speed. Structural integrity of the disc is investigated and realized by performing stress and modal analysis using ANSYS FE modeling. Moreover, natural frequencies, vibration mode shapes, and participation factors are extracted from the FE results. Back-iron size, hence weight is optimized without degrading the flux density levels. Analysis results showed the validity of the proposed back-iron design for the intended application. Stress and vibration analysis results showed safe design structure as stress levels are well below 350 MPa and natural frequencies are all above the operating frequency of 833 Hz.","PeriodicalId":426838,"journal":{"name":"2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127905644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Convolutionally coded Wideband Code Division Multiple Access in 6G LEO Satellite Communication System 6G低轨卫星通信系统中的卷积编码宽带码分多址

2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) Pub Date : 2022-11-06 DOI: 10.1109/EICEEAI56378.2022.10050493

Hani H. Attar, Eman S. Abass, Mohammad Al-Nairat, Ayat Alrosan

{"title":"Convolutionally coded Wideband Code Division Multiple Access in 6G LEO Satellite Communication System","authors":"Hani H. Attar, Eman S. Abass, Mohammad Al-Nairat, Ayat Alrosan","doi":"10.1109/EICEEAI56378.2022.10050493","DOIUrl":"https://doi.org/10.1109/EICEEAI56378.2022.10050493","url":null,"abstract":"The Low Earth Orbit (LEO) network is one of the primary areas of focus for 6G technology. 2020 marked the beginning of 6G research and development, although commercialization may not occur until 2030. LEOs are the ideal choice for 6G due to their lightweight, low cost, and rapid development cycles, which enable them to solve the problem of connectivity in communication-blind places that 5G cannot serve, such as oceans, distant areas, and deserts. This study presents a complete performance evaluation of a convolutionally coded Wideband Code Division Multiple Access (WCDMA) system for the Additive white Gaussian noise (AWGN) channel and the LEO satellite channel. The Bit Error Rate (BER) performance for the proposed system will be formulated and tested using numerical data. Simulation results are demonstrated for a convolutionally coded WCDMA system over an LEO satellite channel for varying numbers of users and coding parameter values. The suggested approach increases the performance of WCDMA-based systems by employing coding gain. Moreover, he results demonstrate that the proposed scheme is superior based on comparing the proposed approach's performance to standard methods without coding.","PeriodicalId":426838,"journal":{"name":"2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116944734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Hybrid Deep Cascade-ResNet Model for Detecting Alzheimer's Stages in MR Images 一种用于检测MR图像中阿尔茨海默氏症分期的混合深度级联- resnet模型

2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) Pub Date : 2022-11-06 DOI: 10.1109/EICEEAI56378.2022.10050454

K. Rezaee, Mohammad Hossein Khosravi, Mohammad Sabri, Khaled E. Al-Qawasmi

{"title":"A Hybrid Deep Cascade-ResNet Model for Detecting Alzheimer's Stages in MR Images","authors":"K. Rezaee, Mohammad Hossein Khosravi, Mohammad Sabri, Khaled E. Al-Qawasmi","doi":"10.1109/EICEEAI56378.2022.10050454","DOIUrl":"https://doi.org/10.1109/EICEEAI56378.2022.10050454","url":null,"abstract":"Neuroimaging is used for diagnosing neuropathological disorders, such as Alzheimer's disease (AD). In this study, a hybrid convolutional neural network (CNN) model is evaluated for its ability to improve AD diagnosis. Accordingly, we determine that using the CascadeNet and ResNet algorithms, we can precisely classify Alzheimer's disease stages in magnetic resonance imaging (MRI). Based on Kaggle datasets, we validate the proposed architecture and compare its performance with that of similar deep learning methods. We achieved 99.02% accuracy using quaternary classification. There was an accuracy of quaternary classification between all AD subtypes in the proposed model. Cascade-ResNet has better classification accuracy and processing complexity than other deep CNNs. The proposed model outperforms the current state-of-the-art deep learning methods when applied to MRI. Furthermore, the hybrid Cascade-ResNet performed well without the need for feature extraction and was insensitive to existing noise in the imaging. Consequently, untrained operators are able to apply the proposed model to digital patient imaging data. By distinguishing between AD patients and healthy individuals, this research can enhance value-based care in clinical settings.","PeriodicalId":426838,"journal":{"name":"2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128483200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual Mode Multicarrier Communication System Based on Discrete Fractional Cosine Transform and Discrete Fourier Transform 基于离散分数余弦变换和离散傅立叶变换的双模多载波通信系统

2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) Pub Date : 2022-11-06 DOI: 10.1109/EICEEAI56378.2022.10050457

A. Solyman, Taisir Ismail, Hani H. Attar

{"title":"Dual Mode Multicarrier Communication System Based on Discrete Fractional Cosine Transform and Discrete Fourier Transform","authors":"A. Solyman, Taisir Ismail, Hani H. Attar","doi":"10.1109/EICEEAI56378.2022.10050457","DOIUrl":"https://doi.org/10.1109/EICEEAI56378.2022.10050457","url":null,"abstract":"In a static channel, using a single-tap equalizer to eliminate inter-symbol-interference (ISI) and channel distortion makes multicarrier systems like Discrete Fourier Transform orthogonal frequency division multiplexing (DFT- OFDM) so attractive. Intercarrier interference (ICI) manifests as a result of OFDM transceivers' inability to diagonalize the channel matrix in doubly selective fading channels. The Discrete Fractional Cosine Transform (DFrCT-OCDM) has been proposed to act as the bases for Orthogonal chirp division multiplexing multicarrier (OCDM) system to perform better than conventional OFDM systems under doubly dispersive channel conditions. It is demonstrated that the DFrCT requires less intricate signal processing to implement than the traditional Fast Fourier Transform. Simulation findings show that the DFrCT offers better performance, spectrum efficiency, and energy concentration features than the conventional FFT technique. We propose an adaptive transmission in those channels utilizing dual-mode transmission of DFrCT-OCDM and DFT-OFDM. Its performances were analyzed using Monte Carlo computer simulations in time-variant and time-invariant channel scenarios","PeriodicalId":426838,"journal":{"name":"2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121880433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0