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Wide bandgap semiconductor-based integrated circuits

Chip 2023年第4期2卷 105-132页

作者： Saravanan Yuvaraja Vishal Khandelwal Xiao Tang Xiaohang Li Advanced Semiconductor Laboratory(ASL) Electrical and Computer Engineering ProgramComputerElectrical and Mathematical Science&Engineering(CEMSE)DivisionKing Abdullah University of Science andTechnology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia

Wide-bandgap semiconductors exhibit much larger energybandgaps than traditional semiconductors such as silicon,rendering them very promising to be applied in the fields of electronics and *** examples of semiconductors include SiC,GaN,ZnO,and diamond,which exhibitdistinctive characteristics such as elevated mobility and *** characteristics facilitate the operation of awide range of devices,including energy-efficient bipolar junctiontransistors(BJTs)and metal-oxide-semiconductor field-effecttransistors(MOSFETs),as well as high-frequency high-electronmobility transistors(HEMTs)and optoelectronic components suchas light-emitting diodes(LEDs)and *** semiconductorsare used in building integrated circuits(ICs)to facilitate theoperation of power electronics,computer devices,RF systems,andother optoelectronic *** breakthroughs includevarious applications such as imaging,optical communication,*** them,the field of power electronics has witnessedtremendous progress in recent years with the development of widebandgap(WBG)semiconductor devices,which is capable ofswitching large currents and voltages rapidly with low ***,it has been proven challenging to integrate these deviceswith silicon complementary metal oxide semiconductor(CMOS)logic circuits required for complex control *** monolithic integration of silicon CMOS with WBG devices increases thecomplexity of fabricating monolithically integrated smart integrated circuits(ICs).This review article proposes implementingCMOS logic directly on the WBG platform as a ***,achieving the CMOS functionalities with the adoption of WBGmaterials still remains a significant *** article summarizesthe research progress in the fabrication of integrated circuitsadopting various WBG materials ranging from SiC to diamond,with the goal of building future smart power ICs.

关键词： Wide bandgap semiconductors Integrated circuits Transistors Power electronics

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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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Traffic Signs Detection System Using YOLO (You Only Look Once) That Provides Notification 1

Traffic Signs Detection System Using YOLO (You Only Look Onc...

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1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Setiawan, Yosua Puji, Muhammad Nurul Astuti, Winda Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368918

Road accidents have become a problem for many road users in many countries. It may affect human daily activity and tasks, potentially influencing productivity and safety. Therefore, reducing road accidents as swiftly and effectively as possible is critical. For this reason, a Traffic signs detection system has been developed in this work to improve road safety. The detection system can detect traffic signs on the road such as traffic lights, speed limits, and no U-turn signs, and then it will provide users with the corresponding text on an LCD and vibration feedback using a motor. Throughout this work, the You Only Look Once (YOLO) algorithm is proposed for detecting traffic signs on the road. Moreover, a camera is used to extract live videos which serve as an input for the Raspberry Pi 4 model B containing custom YOLOv5 and YOLOv8 models. The system then sends the output to an LCD, a vibration motor, and a radio frequency (RF) module as notifications for users. In the end, the performance of the proposed method has been collected and it is found to produce good accuracy within an inconsiderable amount of 1.677 images and 2.263 annotations. Therefore, the accuracy of 0.69 for YOLOv5 and 0.7 for YOLOv8 were obtained from the training and validation process. Furthermore, the system accurately detects the traffic signs on the road. © 2024 IEEE.

关键词： Traffic signs

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A Classifiers Experimentation with Quantum Machine Learning

A Classifiers Experimentation with Quantum Machine Learning

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2023 International Electrical engineering Congress, iEECON 2023

作者： Khemapatapan, Chaiyaporn Thepsena, Thammanoon Jeamaon, Aomduan College of Innovative Technology and Engineering Dhurakij Pundit University Computer Engineering Program Bangkok Thailand

ISBN: (纸本)9798350332360

Quantum Computing is a new way to create a different type of computer system from Quantum Mechanics. Quantum machine learning is one of the applications took the benefit from qauntum computers. In this experiment, we use the IBM Qiskit library to study how well a quantum machine learning classifier works. We made two different colored dots to represent the two-class dataset. The quantum circuit can be collected from the Qiskit library. The 1st and 2nd order feature map schemes operated by oracle quantum oracle functions are applied before making a classification. Finally, we can call the quantum support vector machine or QSVM function to classify data. Kernel matrix from the studied qauntum model shows that quantum computing can be used to clearly classify classes of the dataset with 100 percent accuracy. © 2023 IEEE.

关键词： Support vector machines

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Pedestrian Lane Control System with Alert System 6th

Pedestrian Lane Control System with Alert System

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6th International Conference on Mechanical engineering Research, ICMER 2021

作者： Galang, Emmanuel V. Portillo, Noel R. Adtoon, Jetron J. Computer Engineering Program College of Engineering Education University of Mindanao Davao City8000 Philippines

ISBN: (纸本)9789811915765

Pedestrian accidents are inevitable despite the inclusion of pedestrian lanes. Vehicle users tend to neglect pedestrian lanes unless law enforcers are watching. On the other hand, pedestrian users also have lapses in the use of the lanes. This innovative study aims to secure the people and vehicles who are crossing the road. With image processing, a new pedestrian lane system can distinguish pedestrians and cars as inputs for the system to work. The algorithm of the system could process the matching scenarios provided in the fuzzy logic decision table. A prototype design of the project was fabricated along with traffic lights and cameras. The accuracy of the whole system yielded a result of 96.67% for the entire system, with 30 samples covering six scenarios simulated randomly. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy logic

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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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Correntropy-Based Data Selective Adaptive Filtering

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IEEE Transactions on Circuits and Systems I: Regular Papers 2024年第2期71卷 754-766页

作者： Chien, Ying-Ren Wu, Sheng-Teng Tsao, Hen-Wai Diniz, Paulo S.R. Adaptive and Autonomous Communication Laboratory Department of Electrical Engineering National Ilan University Yilan City260007 Taiwan College of Electrical Engineering and Computer Science Graduate Institute of Communication Engineering National Taiwan University Taipei10617 Taiwan Program of Electrical Engineering Department of Electronics and Computer Engineering COPPE/Poli Universidade Federal do Rio de Janeiro Rio de Janeiro68504 Brazil

Data selection can be used in conjunction with adaptive filtering algorithms to avoid unnecessary weight updating and thereby reduce computational overhead. This paper presents a novel correntropy-based data selection method as an alternative to conventional data selection mechanisms based on squared error values. We developed a variable correntropy sensing algorithm to maximize the instantaneous correntropy function for the Gaussian kernel function to mitigate the impact of impulse noise and other forms of noise that can be disregarded in data selection. The proposed data selection mechanism can be implemented with any adaptive filtering algorithm. In simulations, the proposed method (implemented with the least mean squared algorithm) outperformed comparable error-based data selection schemes in terms of hit rate and miss rate, and the resulting weight updating ratio was close to the expected weight updating ratio. © 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.

关键词： Adaptive filters

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FPGA implementation of low cost and low power chaotic encryption scheme based on a discrete-space chaotic map

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Multimedia Tools and Applications 2025年 1-22页

作者： Moreira Bezerra, João Inácio Machado, Gustavo Iankowski Soares, Rafael Valduga de Almeida Camargo, Vinícius Molter, Alexandre Post Graduate Program in Computer Science Universidade Federal de Pelotas Rio Grande do Sul Pelotas96010610 Brazil Graduate Program in Computer Engineering Universidade Federal de Pelotas Rio Grande do Sul Pelotas96010610 Brazil Post Graduate Program in Mathematical Modeling Universidade Federal de Pelotas Rio Grande do Sul Capão do Leão96160000 Brazil

The exponential growth of the number of devices connected to the Internet and the use of IoT applications increases the amount of data exchange over public channels in low-cost and low-power embedded systems. Images are the most widely shared files, and standard symmetric algorithms such as the Advanced Encryption Standard (AES) are optimized for text but not image encryption. Consequently, new approaches like chaotic encryption have attracted researchers’ interest. Chaotic encryption schemes have been analyzed mostly from a software standpoint, but recent advancements in the field, through the use of discrete chaotic maps, enabled the development of simpler hardware implementations of ciphers with promising reductions in power and cost and increased performance. This work presents the Field-programmable Gate Array (FPGA) implementation of a simultaneous permutation-diffusion chaotic encryption scheme utilizing a discrete-space chaotic map. The FPGA implementation of the cipher is analyzed considering area, maximum frequency, and power consumption, and comparisons are made with the AES. The proposed algorithm has a satisfactory trade-off between area, power and performance, obtaining a peak throughput 59% higher than state-of-the-art symmetric ciphers in the literature. Thus, the proposed cipher shows that chaotic ciphers are viable for both high-performance and low-power embedded devices. Tests verified the security of the proposed cipher against statistical, differential, brute-force, and chosen plain-text attacks. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Cryptography

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Dictionary-based Sentiment Analysis at Subword Level

Dictionary-based Sentiment Analysis at Subword Level

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2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024

作者： Yang, Janghoon Computer Science Program Division of Science and Engineering Penn State Abington AbingtonPA United States

ISBN: (纸本)9798350353464

While deep learning can offer a promising approach to sentiment analysis, it often presents challenges in complexity and explainability. Alternatively, sentiment analysis based on dictionaries has been explored. In this paper, subword-level dictionaries in English are considered to address performance degradation resulting from domain mismatches. To work at subword level, a framework based on naïve bayes machine learning algorithm is exploited. Furthermore, stopwords at the subword level have been proposed to remove additional interference intrinsic to subword tokenization. Numerical experiments demonstrate that the proposed method achieves higher accuracy and F1 scores compared to the conventional dictionary-based method when there is a mismatch between the dictionary and the corpus of documents while performing marginally worse than state-of-the-art deep learning methods when applied to datasets from the same domain. ©2024 IEEE.

关键词： Contrastive Learning

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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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