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2023 International Conference on electrical engineering and Informatics, ICEEI 2023

作者： Pranowo, Samuel Raymond Sukra, Zener Lie Asy'ari, Muhammad Zacky Paryasto, Marisa Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Telkom University Computer Engineering Program Electrical Engineering Department Bandung Indonesia

ISBN: (纸本)9798350381290

Agriculture is a vital industry for the people of Indonesia, but there are several obstacles, including limited space in urban areas and inefficient conventional sorting and harvesting methods. Using computer vision to choose hydroponic lettuce that is ready to be harvested and a robotic arm to bring the selected lettuce yields, the produced system aims to solve this problem. The system's computer vision algorithms include color space conversion, intensity transformation, and an algorithm for following borders. This project's research methodology combines a quantitative approach with an experimental approach, which consists of conducting several trials on the built system. Several trials demonstrated that the computer vision software was able to accomplish the specified objectives. The average success rate of the developed computer vision system is 93%, while the average success rate of the robot arm is 85%. © 2023 IEEE.

关键词： Lettuce

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Building a Brain computer Interface (BCI) Using Electroencephalogram (EEG) Signals' Classification 7

Building a Brain Computer Interface (BCI) Using Electroencep...

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7th International Conference on Advances in Biomedical engineering, ICABME 2023

作者： Younis, Mohammad Nabil Sleiman, Sary Haj Khadra, Salma Zaylaa, Amira Daher, Alaa Ayache, Mohammad Beirut Arab University Biomedical Program Depatment of Electrical and Computer Engineering Debbieh Lebanon

ISBN: (纸本)9798350325850

Development of Brain computer Interface (BCI) has been rapid since the mid 1990's. There are three criteria for BCI, (i) comfortability and possession of a suitable signal acquisition device, (ii) system validation and dissemination, and (iii) reliability and potentiality. As there are no BCI possessing the optimal criteria, it was essential to consider building a new one. Thereby, the paper investigates building BCI based on the utilization of EEG signals to translate brainwave patterns into actionable commands. The primary objective is to enhance communication capabilities for individuals afflicted with neurological disorders, empowering them to command external devices and engage more effectively with their surroundings. We built our model on EEG online dataset for the purpose of feature extraction and classification. Statistical features and Discrete Wavelet Transform (DWT) have been applied for feature selection. Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) were the classifiers involved. Results showed that the proposed architecture of MLP and RBF were able to classify the EEG signals into two classes (open eye and closed eye). Results also showed that the proposed approach, which is based on the combination of statistical features and DWT for features selection using AF3 and AF4 channels by the application of MLP, has 98% succession rate. BCI system based on Arduino circuit has been built after the classification Further algorithms and system evaluation need to be considered as future work. © 2023 IEEE.

关键词： Discrete wavelet transforms

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A Pulse Width Modulation-Based Spike Generator to Eliminate Timing Errors in Spiking Neural Networks

A Pulse Width Modulation-Based Spike Generator to Eliminate ...

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2025 International Conference on Electronics, Information, and Communication, ICEIC 2025

作者： Jo, Jungkook Sim, Keonhee Sim, Sangwoong Jun, Jaehoon Inha University Dept. of electrical and computer engineering and program in semiconductor convergence Incheon Korea Republic of Inha University Dept. of electrical engineering Incheon Korea Republic of

ISBN: (纸本)9798331510756

This paper proposes a novel spike generator for processing in memory (PIM) technology. Most of the electronics today utilize a von Neumann architecture. The von Neumann architecture suffers from the separation of memory and processor. This architecture delays data transfer between memory and processor. To overcome the issues, we utilize the spiking neural network (SNN) that combines memory and processor. SNN can be classified into voltage-based, current-based, and time-based architectures, each with its own pros and cons. Time-based SNN suffers from timing issues. To address the timing sensitivity of time-based neuron SNN, this paper proposes a PWM-based SNN. The PWM-based SNN utilizes pulse width-based logic to overcome timing sensitivity. © 2025 IEEE.

关键词： Pulse width modulation

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Algorithmic optimization of quantum optical storage in solids

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Physical Review Research 2024年第3期6卷 033153-033153页

作者： Yisheng Lei Haechan An Zongfeng Li Mahdi Hosseini Department of Electrical and Computer Engineering and Applied Physics Program Elmore Family School of Electrical and Computer Engineering

Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use passive optimization and algorithmic optimization techniques to demonstrate nearly a sixfold enhancement in quantum memory efficiency. In this regime, we demonstrate coherent and single-photon-level storage with a high signal-to-noise ratio. The optimization technique presented here can be applied to most solid-state quantum memories to significantly improve the storage efficiency without compromising the memory bandwidth.

关键词： Quantum communication

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A Low-Noise Capacitively-Coupled Chopper Instrumentation Amplifier with SAR-Assisted Low Current Ripple Reduction Technique 21

A Low-Noise Capacitively-Coupled Chopper Instrumentation Amp...

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21st International System-on-Chip Design Conference, ISOCC 2024

作者： Jo, Jungkook Jun, Jaehoon Inha University Department of Electrical and Computer Engineering Korea Republic of Inha University Program in Semiconductor and Device Korea Republic of

ISBN: (数字)9798350377088

ISBN: (纸本)9798350377088

This paper presents a novel design technique for reducing ripple in various sensor read-out integrated circuits (IC) by calibrating the amplifier offset through current control in bias resistors. Traditional methods for reducing ripple often involve complex amplifiers consuming static power. In contrast, the proposed ripple reduction technique employs successive-approximation register (SAR) logic to control the current flowing through the bias resistor, thus minimizing static power consumption. Experimental results obtained through simulations in a 28 nm CMOS process demonstrate significant ripple reduction to 8.94 μVpp from 2 mVpp. This approach is suitable for low-power design, particularly in wearable device applications, and can potentially extend to other amplifier configurations utilizing chopping technique. © 2024 IEEE.

关键词： Chopper amplifiers

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Distance Measurement of Tunnel Facilities for Monocular Camera-based Localization

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Journal of Institute of Control, Robotics and Systems 2023年第1期29卷 7-14页

作者： Kim, Jongkwang Kim, Hyoungrae Oh, Jangsub Li, Xingyou Jang, Kyeongjun Kim, Hakil Department of Electrical and Computer Engineering Inha University Korea Republic of Program in Future Vehicle Engineering Inha University Korea Republic of Department of Smart Mobility Engineering Inha University Korea Republic of

The GNSS signal used for vehicle localization exhibits a shaded area such as a tunnel. To accurately estimate the location in the shaded area, the accumulated position error must be compensated with information obtained from a separate sensor. When a monocular camera is selected as an additional sensor, the process of measuring the relative distance after detecting objects in a tunnel should be performed before using these data as an indicator. This paper presents a modified inverse perspective transformation model that projects image pixels to the plane parallel to the ground. The image pixels are projected to the plane accounting for the distance and the height of the facility in the tunnel. Then, through the transformation model, the distance of the facility in the tunnel can be measured using a single camera sensor. The Samsungsan Tunnel located on National Highway 110 in South Korea was chosen for the experiment. The estimated distance results by the proposed method were compared with the LiDAR measurements obtained real-time time by computing the position errors for the longitudinal and lateral directions, separately. This study demonstrates the possibility of estimating a distance with only a monocular camera for precise positioning even in a tunnel. © ICROS 2023.

关键词： Optical radar

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Early Diagnosis of Osteoporosis: An Artificial Intelligence-Based Framework 7

Early Diagnosis of Osteoporosis: An Artificial Intelligence-...

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7th International Conference on Advances in Biomedical engineering, ICABME 2023

作者： Zaylaa, Amira J. Daher, Alaa Ayache, Mohammad Omeirat, Niveen Mahmoud, Razane Hawili, Bader Abou Beirut Arab University Biomedical Engineering Laboratory Biomedical Engineering Program Electrical and Computer Engineering Faculty of Engineering Lebanon

ISBN: (纸本)9798350325850

Osteoporosis is a common disease characterized by low bone density and structural deterioration of bone tissue. For a successful course of treatment and fracture avoidance, early diagnosis of this disease is essential. The aim was to provide a novel method for osteoporosis prediction using Artificial Intelligence (AI)-based framework. The purpose was to predict the likelihood of osteoporosis based on the Bone Mineral Density (BMD), along with other characteristics such as age, weight, height, gender, and Body Mass Index (BMI) extracted from medical reports and images collected from a comprehensive medical center in Lebanon. Three machine-learning algorithms were implemented and tested, Logistic Regression (LR), Support Vector Machines (SVM), and Decision Trees (DT). Variety of quantitative statistical metrics were used to evaluate the performance of our framework, upon training and testing our algorithms. The metrics that were employed to evaluate our results included accuracy, precision, sensitivity, and F-score, in addition to the Receiver Operating Characteristic (ROC) Curve and the Area Under the Curve (AUC). Experimental Results demonstrated that both the SVM and LR algorithms achieved the highest accuracy of detection of osteoporosis as compared to existing algorithms applied in this field, with an accuracy of 89%. The sensitivity of diagnosis obtained was 98% by LR and 97% by SVM and surpassed the sensitivity obtained by DT. As such LR showed the best performance. The output of the algorithms could help medical doctors assess patients automatically. These findings demonstrated the potential of AI in osteoporosis prediction and thus prevention, highlighting the significance of early diagnosis. Thereby as a future prospect, choosing carefully the framework is crucial and additional algorithms have to be considered and tested. © 2023 IEEE.

关键词： Decision trees

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Real Time Chest X-Ray Interpretation Applying Vision Transformer for Tuberculosis Detection

Real Time Chest X-Ray Interpretation Applying Vision Transfo...

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2024 International Conference on computer engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Irhamsyah, Muhammad Roslidar Yunidar Al Lail Qadrillah, M. Nasaruddin Arnia, Fitri Munadi, Khairul Universitas Syiah Kuala Post Graduate Program in Engineering Banda Aceh2311 Indonesia Faculty of Engineering Department of Electrical and Computer Engineering 2311 Indonesia

ISBN: (纸本)9798350368802

Tuberculosis (TB) is an infectious disease that can attack the lungs and other organs. In the diagnosis of TB, the interpretation of X-ray radiological images requires special skills from medical specialists. However, the lack of experience of medical personnel and focus on X-ray examinations can be a challenge for radiologists because it has the potential to cause diagnostic errors in image interpretation. Therefore, we proposed a web-based application of real-time chest X-ray interpreter by integrating the deep learning model of Vision Transformer (ViT) to interpret chest X-ray images. The inference model was trained and tested on 652 normal and 652 tuberculosis X-ray images. The data preprocessing of Contrast Adaptive Histogram Equalization (CLAHE) was implemented to increase chest X-ray image contrast as well as inference model performance. The proposed real time system can inteprete the tested chest x-ray images with an accuracy of 95% and with simulation duration time of 4.7 seconds. © 2024 IEEE.

关键词： Diagnosis

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A Discontinuous Galerkin Time-Domain Method to Simulate Metasurfaces using Generalized Sheet Transition Conditions

A Discontinuous Galerkin Time-Domain Method to Simulate Meta...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Chen, Liang Ozakin, Mehmet Burak Zhao, Ran Bagci, Hakan Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

The generalized sheet transition conditions (GSTCs) are incorporated into a discontinuous Galerkin time-domain (DGTD) method to efficiently simulate metasurfaces. The numerical flux for GSTCs is derived for the first time using the Rankine-Hugoniot jump conditions. This numerical flux includes time derivatives of fields and therefore explicit time integration schemes that are traditionally used with DGTD do not yield a stable time marching method. To alleviate this bottleneck, a new time marching scheme, which solves a local matrix system for the unknowns of the elements touching the same GSTC face, is developed. Numerical results, which validate the accuracy of the proposed method against analytical solutions and demonstrate its applicability to the simulation of curved and space/time-varying metasurfaces, are presented. © 2022 IEEE.

关键词： Numerical methods

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Multiphysics Analysis of Screening Effects on Terahertz Photoconductive Devices

Multiphysics Analysis of Screening Effects on Terahertz Phot...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Chen, Liang Dong, Ming Bagci, Hakan Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

Output saturation observed for high power levels of input optical pump is a well-known bottleneck in the operation of terahertz photoconductive devices (PCDs). This saturation is a result of various screening effects that stem from the interactions between electromagnetic fields and semiconductor charge carriers. To simulate these effects, this work uses a time-domain multiphysics approach that solves a coupled system of the Maxwell and the drift-diffusion equations to rigorously take into account the two-way nonlinear coupling between fields and carriers. Furthermore, an optical absorption-based model is used to correctly compute the carrier generation rate. The resulting multiphysics solver is used to simulate realistic PCDs, and excellent agreement is observed between the simulation and experimental results. © 2022 IEEE.

关键词： Multiphysics

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