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2023 IEEE 66th International Midwest Symposium on Circuits and Systems, MWSCAS 2023

作者： El-Zeiny, Ahmed N. Hassan, Adham Mostafa, Hassan Khalil, Ahmed H. Cairo University Electronics and Communications Engineering Department Egypt University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza12578 Egypt

ISBN: (纸本)9798350302103

In this paper, we present an efficient real-time object detector designed for embedded system applications. Although increased memory and power consumption pose significant challenges, our network adopts techniques to overcome them. Depthwise and pointwise separable convolutions are used across the backbone, neck, and head of the network to reduce the number of parameters. To compensate for accuracy loss, we employ several techniques including starting with a larger baseline, using depthwise separable convolution mixed with blueprint separable convolution in the backbone, replacing the SiLU activation function with the Mish activation function, and switching from Adam to SGD optimization algorithms. These techniques help to achieve a state-of-the-art object detection network called Mini-YOLOX, which optimizes YOLOX-S from the YOLOX series and reaches only ∽57% of its parameter size and ∽52% of its floating-point operations with better accuracy. Mini-YOLOX achieves impressive results with only 5.08M parameters and 13.95 GFLOPs, resulting in a 40.9 AP score in just 5.71 ms. © 2023 IEEE.

关键词： convolutional neural network (CNN) embedded applications Real-time object detector YOLOX

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On-chip Optofluidic Structure for Hormonal Detection Using Stable Fabry-Pérot Resonator

On-chip Optofluidic Structure for Hormonal Detection Using S...

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2022 IEEE International Conference on Electrical, Computer, and Energy Technologies, ICECET 2022

作者： Ali, Alaa M. Mansour, Mohamed Abdelsalam Ahmed, Mohamed H. Sayed Gaber, Noha Marty, Frederic Bourouina, Tarik Center for Nanotechnology and Nanotechnology and Nanoelectronics Engineering Program Zewail City of Science and Technology Giza Egypt Nanotechnology and Nanoelectronics Engineering Program Zewail City of Science and Technology Giza Egypt Laboratoire Electronique Systèmes de Communication et Microsystèmes Université Paris-Est ESIEE Paris ESYCOM EA Noisy-le-Grand2552 France

ISBN: (数字)9781665470872

ISBN: (纸本)9781665470872

This work aims to present the numerical simulation of a micro-optical system consisting of a Fabry-Pérot resonator and micro-lenses used for hormonal detection. Ideally, the Fabry-Pérot cavity should have curved shape in 3D to confine the light in all directions inside the resonator. However, this 3D structure is not compatible with the planar microfabrication technology. Therefore, the design introduced in this work consists of an upright cylindrical lens and Fiber rod lens to confine the light in both horizontal and vertical directions before entering the cavity. The fabricated structure also includes a microfluidic channel that holds the fluid to be tested between the mirrors of the cavity. Both fluid mechanics simulations and optical simulations are conducted. The designed chip incorporates different Fabry-Pérot cavities that can be used to characterize different samples on the same chip with different sensitivities and detection ranges. The sensitivity of our device was tested by Estrogen hormone with different concentrations, and it is found to reach up to 400.25 nm/RIU. © 2022 IEEE.

关键词： Optical systems

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SoC-Oriented Implementation of Machine Learning Based Breast Cancer Classification Algorithm 12

SoC-Oriented Implementation of Machine Learning Based Breast...

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12th Mediterranean Conference on Embedded Computing, MECO 2023

作者： Saeed, Abdelrahman Tawfik, Ayman Mostafa, Hassan Khalil, Ahmed Hussein Cairo University Electronics and Communications Engineering Department Giza12613 Egypt Ajman University Department of Electrical and Computer Engineering United Arab Emirates University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza Egypt

ISBN: (纸本)9798350322910

Convolutional Neural Networks (CNN) have drawn the attention of researchers in the medical imaging field. Many researchers have exploited CNN for breast cancer detection. This study provides an Internet of Things (IoT) friendly implementation of CNN for breast cancer detection. To achieve faster time to Market, Deep-learning Processing Unit (DPU) on Field programmable Gate Array (FPGA) is adopted for the CNN hardware implementation. CNN inference on the proposed system achieves a 1.6x speed-up factor and 91.5% reduction in energy consumption compared to the conventional general-purpose multi-core Central Processing Unit (CPU). © 2023 IEEE.

关键词： Convolutional neural networks

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All dielectric compact broadband silicon waveguide mode converters

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Optical and Quantum Electronics 2024年第12期56卷 1-21页

作者： Hassan, Samar Hassan A. Hameed, Mohamed Farhat O. Mahmoud, Korany R. Wageeh, Amr Obayya, S.S.A. Electronics and Communications Engineering Department Faculty of Engineering Helwan University Cairo Egypt Centre for Nanotechnology Zewail City of Science Technology and Innovation October Gardens 6Th of October City Giza12578 Egypt Nanotechnology and Nanoelectronics Engineering Program Zewail City of Science Technology and Innovation October Gardens 6Th of October City Giza12578 Egypt Mathematics and Engineering Physics Department Faculty of Engineering University of Mansoura Mansoura35516 Egypt Cairo Egypt Giza Egypt Centre for Photonics and Smart Materials Zewail City of Science Technology and Innovation October Gardens 6Th of October City Giza12578 Egypt Department of Electronics and Communications Engineering Faculty of Engineering University of Mansoura Mansoura35516 Egypt

Compact mode order converters (MOCs) operating at the mid-infrared regime are reported using silicon-on-calcium fluoride platform. The suggested designs convert the fundamental transverse electric (TE) mode to first and second order TE modes with total device lengths of only 5.89 μm and 5 μm, respectively, at λ = 3.14 µm. The full vectorial 3D finite-deference time-domain is utilized to analyze the TE0 → TE1 and TE0→TE2 MOCs. The proposed designs depend on using dielectric material of Si3N4 inside the Si core region to improve and facilitate the mode conversion process. The conversion efficiencies (inter-modal crosstalks [CTs]) are equal to 93.4% (− 19.2 dB), and 90% (− 17 dB) for TE0: TE1 and TE0:TE2 MOCs, respectively. Moreover, the reported designs have a wide wavelength range of 300 nm, where the conversion-efficiency (CE) and maximum CT are > 86% and 0: TE1 and TE0: TE2 MOCs, respectively, at λ = 1.55 µm. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Silicon photonics

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Mini-YOLOX: A Lightweight Network for Real-Time Embedded Applications

Mini-YOLOX: A Lightweight Network for Real-Time Embedded App...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Ahmed N. El-Zeiny Adham Hassan Hassan Mostafa Ahmed H. Khalil Electronics and Communications Engineering Department Cairo University Zewail City of Science and Technology University of Science and technology Nanotechnology and Nanoelectronics Program Giza Egypt

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ASIC-FPGA Gap for a RISC-V Core Implementation for DNN Applications 3

ASIC-FPGA Gap for a RISC-V Core Implementation for DNN Appli...

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3rd Novel Intelligent and Leading Emerging Sciences Conference, NILES 2021

作者： Hussein, Abdelrahman S. Mostafa, Hassan Cairo University Electronics and Communication Engineering Department Giza12613 Egypt University of Science and technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza12578 Egypt

ISBN: (纸本)9781665421577

Recently, an emerging instruction set called RISC-V has been considered a paradigm in the computer architecture domain, which has easily got the attention of the hardware community. This is because it is fully open-source, which opens wide horizons for development and innovation. As deep learning applications (DL) are becoming more common, it is very important to evaluate the processors' performance handling such tasks. In these lights, a RISC-V core performance executing a DL task is evaluated. Also, the gap between its ASIC and FPGA implementations is measured in terms of power and area. The main finding is that ASIC achieves better optimization in both aspects more than the FPGA. © 2021 IEEE.

关键词： Rockets

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Efficient HLS Implementation for Convolutional Neural Networks Accelerator on an SoC

Efficient HLS Implementation for Convolutional Neural Networ...

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2021 International Conference on Microelectronics, ICM 2021

作者： Sarg, Muhammad Khalil, Ahmed H. Mostafa, Hassan Cairo University Electronics and Communications Engineering Department Giza12613 Egypt University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza12578 Egypt

ISBN: (纸本)9781665408394

Convolutional Neural Networks (CNNs) have achieved high accuracy in many applications such as image recognition and classification. However, due to their large amount of parameters and intensive required operations, general purpose processors cannot achieve the desired inference performance levels. Recently, various hardware accelerators for deep CNNs have been carried out to enhance the throughput of CNNs. Among these accelerators, field programmable gate array (FPGA)-based ones have gained a lot of interest due to their high performance, low power consumption, high reconfigurability, and fast development cycle. Furthermore, the availability of high-level synthesis (HLS) tools lowers the programming burden and increases the productivity of the FPGA-based accelerator designers. In this paper, a C++ HLS implementation for FPGA-based accelerator for the convolutional layers of CNNs is proposed. As a case study, we evaluate the proposed accelerator using Resnet50 CNN on Xilinx Zynq UltraScale+ MPSoC ZCU104 evaluation board using SDSoC development environment, achieving up to 339x inference speedup. © 2021 IEEE.

关键词： Field programmable gate arrays (FPGA)

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FPGA Utilized Implementation of Epileptic Seizure Detection System Based on Wearable Devices using Dynamic Partial Reconfiguration 10

FPGA Utilized Implementation of Epileptic Seizure Detection ...

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10th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2022

作者： Fawzy, Mohamed Hussien, Ahmed Mostafa, Hassan Siemens Digital Industries Software Cairo Egypt Cairo University Electronics and Electrical Communications Engineering Department Giza Egypt University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology October Gardens 6th of October Giza12578 Egypt

ISBN: (纸本)9781665464635

Unplanned seizures are caused by a disorder in the central nervous system known as epilepsy. Although significant advancements have been made in the realm of non-EEG wearable devices, there is still much room for improvement in the field of EEG-based seizure detection and prediction using ML. The management of epilepsy has a lot of promise to be aided by non-invasive wearable technology. The suggested study intends to design and implement a support vector machine (SVM) classification-based epileptic seizure detection system based on various wearable devices. The proposed technique for detecting seizures accomplishes According to data for seizure detection, our system consistently achieves a sensitivity of 100% and an accuracy of 97%. High level MATLAB model creation is part of the design cycle. Despite the fact that high performance cannot be achieved with just one signal. Although a high performance detection system cannot achieve the requisite sensitivity and accuracy with a single signal, we presented various combining techniques. RTL modelling, design optimization, FPGA implementation, and functional verification are all included in the implementation cycle. The capacity of the FPGA's partial dynamic reconfiguration is suggested for implementation in order to make better use of the available resources. Comparing the proposed implementation to relevant earlier work, it demonstrated improved utilization. © 2022 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Radio Optical Network Simulation Tool (RONST)

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Computers, Materials & Continua 2022年第5期71卷 3685-3702页

作者： Yasmine IAbdelhak Fady Kamel Moustafa Hafez Hussein EKotb Haitham AOmran Tawfik Ismail Hassan Mostafa Department of Electronics and Communications Faculty of EngineeringMansoura UniversityDakahlia35516Egypt Nanotechnology and Nanoelectronics Program Zewail City of Science and TechnologyGiza12578Egypt Department of Electronics and Communications Faculty of EngineeringCairo UniversityGiza12613Egypt Department of Electronics and Communications Faculty of EngineeringAin Shams UniversityCairo11566Egypt Laboratory of Micro Optics Faculty of Information Engineering and TechnologyGerman University in Cairo11835CairoEgypt National Institute of Laser Enhanced Sciences Cairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) Nile UniversityGiza12677Egypt

This paper presents a radio optical network simulation tool(RONST)for modeling optical-wireless *** a typical optical and electrical chain environment,performance should be optimized concurrently before system *** a result,simulating such systems turns out to be a multidisciplinary *** governing equations are incompatible with co-simulation in the traditional environments of existing software(SW)*** ultra-wideband(UWB)technology is an ideal candidate for providing high-speed short-range access for wireless *** limited wireless reach of this technology is a significant limitation.A feasible solution to the problem of extending UWB signals is to transmit these signals to endusers via optical *** concept implies the need for the establishment of a dependable environment for studying such ***,the essential novelty of the proposed SW is that it provides designers,engineers,and researchers with a dependable simulation framework that can accurately and efficiently predict and/or optimize the behavior of such systems in a single optical-electronic simulation ***,it is supported by a strong mathematical foundation with integrated algorithms to achieve broad flexibility and low computational *** validate the proposed tool,RONST was deployed on an ultra-wideband over fiber(UWBoF)*** bit error rate(BER)has been calculated over a UWBoF system,and there is good agreement between the experimental and simulated results.

关键词： Optical-wireless systems mathematical modelling techniques opto-electronic software tools ultra-wide band over fiber systems(UWBoF)

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SoC-Oriented Implementation of Machine Learning Based Breast Cancer Classification Algorithm

SoC-Oriented Implementation of Machine Learning Based Breast...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Abdelrahman Saeed Ayman Tawfik Hassan Mostafa Ahmed Hussein Khalil Electronics and Communications Engineering Department Cairo University Giza Egypt Department of Electrical and Computer Engineering Ajman University United Arab Emirates (UAE) University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza Egypt

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