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IEEE International Conference on systems, Man and Cybernetics

作者： Khean-Thye Bea Shih-Shin Hu Wei-Hsuan Lin Da-Zheng Lin Hsin-Hui Hu Xiu-Zhi Chen Ting-Ru Lin Yen-Lin Chen Kun-Ming Chen Wai Khuen Cheng Dep. of Electronic Engineering National Taipei University of Technology Taipei Taiwan Dep. of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan Taiwan Semiconductor Research Institute Hsinchu Taiwan Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Kampar Malaysia

In this study, we proposed a transfer-learning based variational autoencoder model for predicting the electrical characteristics in the parameter tuning process of a-IGZO TFT structure design. The result achieve a high R2 score of 0.9704 with a low-computing-power hardware-friendly method that reduced time consumption significantly compared to prior approaches. The findings have practical implications for mitigating the time-consuming nature of TCAD simulations, and the method can expand to various types of input data while ensuring high performance and generalization. We demonstrated significant improvement in generalization and accuracy through a k-fold validation.

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Algorithms for Enhanced Indoor Positioning and Tracking based on a 60-GHz Radar Platform

Algorithms for Enhanced Indoor Positioning and Tracking base...

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Workshop on Metrology for Industry 4.0 and IoT

作者： F. Shamsfakhr M. Corrà A. Ferrari D. Macii L. Palopoli D. Fontanelli Dep. of Industrial Engineering University of Trento Italy Tretec S.r.L. Trento Italy VNG Ingegneria Trento Italy Dep. of Information Engineering and Computer Science University of Trento Italy

ISBN: (数字)9781665410939

ISBN: (纸本)9781665410946

Wireless technologies are increasingly adopted for indoor localisation and tracking. Among them, radars based on 60 GHz phased-array transceivers are becoming a viable and low-cost solution, which delivers high accuracy with a low computational cost while preserving people privacy. In this paper, we propose two techniques for radar-based people tracking and localisation that tackle important effects such as delayed and spurious detection. We also offer a thorough and scientifically sound experimental analysis of the performance of the proposed techniques using an off-the-shelf phased-array device (i.e., the System-on-Chip (SOC) TI IWR6843).

关键词： Wireless communication Performance evaluation Privacy Target tracking Radar measurements Radar Radar tracking

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Real-time System for Translating American Sign Language to Text Using Robust Techniques

Real-time System for Translating American Sign Language to T...

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Recent Advances in science and engineering Technology (ICRASET), International Conference on

作者： Basel A. Dabwan Mukti E. Jadhav Hamad A. Abosaq Fekry A. Olayah Mohammed Al Yami Yahya A. Abdelrahman Department of Information System AlBaydha University AlBaydha Yemen Department of Computer Science Shri Shivaji Science & Art College India Computer Science Dep. Najran University Kingdom of Saudi Arabia Department of Information System Najran University Kingdom of Saudi Arabia Department of Information Systems Faculty of Computer Science and Information Systems Najran University Kingdom of Saudi Arabia Department of Information System College of Computer Science and Information Systems Najran University Kingdom of Saudi Arabia

Sign language serves as a vital medium of communication for the Deaf and dumb people. We present a real-time system to translate ASL into text, addressing the communication gap between deaf and dumb people and normal people. Our system leverages computer vision and machine learning techniques to accurately recognize ASL gestures. In this study, we introduce a convolutional neural network (CNN) and (LSTM) approaches designed to identify hand gestures associated with human actions as captured through images from cameras. By utilizing the hand's spatial positioning and orientation, we construct the training and testing datasets for the CNN-LSTM model, we were used 4680 skeleton images of the ASL alphabet, from A to Z as a dataset. The hand image undergoes an initial filtering process followed by classification, where a classifier determines the classification of the hand gesture. Subsequently, the refined images are harnessed to train the CNN-LSTM model. Our real-time system provides accurate and reliable results in real-time 99.9%, in addition to generating new datasets that are processed and can be trained on any model.

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Discrete cosine transform as universal sentence encoder

arXiv

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arXiv 2021年

作者： Almarwani, Nada Diab, Mona Dep. of Computer Science The George Washington University Dep. of Computer Science College of Computer Science and Engineering Taibah University Facebook AI Research

Modern sentence encoders are used to generate dense vector representations that capture the underlying linguistic characteristics for a sequence of words, including phrases, sentences, or paragraphs. These kinds of representations are ideal for training a classifier for an end task such as sentiment analysis, question answering and text classification. Different models have been proposed to efficiently generate general purpose sentence representations to be used in pretraining protocols. While averaging is the most commonly used efficient sentence encoder, Discrete Cosine Transform (DCT) was recently proposed as an alternative that captures the underlying syntactic characteristics of a given text without compromising practical efficiency compared to averaging. However, as with most other sentence encoders, the DCT sentence encoder was only evaluated in English. To this end, we utilize DCT encoder to generate universal sentence representation for different languages such as German, French, Spanish and Russian. The experimental results clearly show the superior effectiveness of DCT encoding in which consistent performance improvements are achieved over strong baselines on multiple standardized datasets. Copyright © 2021, The Authors. All rights reserved.

关键词： Discrete cosine transforms

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Usage of Blockchain Technology for Improving computer Security

Usage of Blockchain Technology for Improving Computer Securi...

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Information Technology (ACIT)

作者： Adai Almomani Al Refai Mohammed N Ahmad Aburomman Omar Khair Alla Alidmat Qotadeh Saber Fuad Alshariedeh Mohammed Khouj Department of Computer Science Zarqa University Zarqa Jordan Software Engineering Dep. Zarqa University Zarqa Jordan Department of Data Science and A Zarqa University Zarqa Jordan Department of Electronic Enginnering Univeristy of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Cyber threats have grown increasingly sophisticated, surpassing the capabilities of traditional security measures. Blockchain technology, with its decentralized and immutable structure, offers a potential solution to these challenges. This study examines the role of blockchain tools such as smart contracts, decentralized identity management, and secure data sharing in enhancing cybersecurity. A review of key literature and analysis of survey data from cybersecurity professionals demonstrate blockchain's effectiveness in improving data integrity, access control, and secure communications. The results show significant correlations between the adoption of blockchain technologies and the mitigation of threats like data breaches and unauthorized access. While blockchain presents promising advancements, scalability, regulatory barriers, and energy consumption remain challenges. The study provides valuable insights for researchers, practitioners, and policymakers on how blockchain can be integrated into modern cybersecurity strategies to create more secure digital environments.

关键词： Access control Industries Proof of stake Scalability Smart contracts Data protection Blockchains computer security Identity management systems Business

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Stabilization of THz waves using chaos supremacy

Stabilization of THz waves using chaos supremacy

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2023 International Conference on Smart-Green Technology in Electrical and Information systems, ICSGTEIS 2023

作者： Kuwashima, Fumiyoshi Jarrahi, Mona Cakmakyapan, Semih Wada, Kenji Haraguchi, Masanobu Kawakami, Yuki Moriyasu, Takeshi Morikawa, Osamu Kurihara, Kazuyoshi Kitahara, Hideaki Furuya, Takashi Nakajima, Makoto Tani, Masahiko Fukui University of Technology Dep. of Electr. and Electron. Eng. Fukui Japan Ucla Electrical and Computer Eng. Los AngelesCA90095 United States Osaka Metropolitan University Dep. of Physics and Electronics Osaka Japan Tokushima Univ. Industrial and Social Science Grad. Sch. of Tech. Tokushima Japan Fukui Col. Natl. Inst. of Tech. Dep. of Elec. and Inf. Eng. Fukui Japan University of Fukui Faculty of Engineering Fukui Japan Japan Coast Guard Academy Liberal Arts Kure Japan University. of Fukui School of Education Fukui Japan FIR-UF University of Fukui Fukui Japan Osaka Univ. Inst. of Laser Engineering Osaka Japan

ISBN: (纸本)9798350382822

We apply the chaos supremacy of laser chaos system to the high stabilization of THz waves. Stability was demonstrated by down converting the optical beats between laser longitudinal modes in the THz domain to the radio frequency domain and comparing a conventional free running CW laser diode to a chaotically oscillating laser diode. Because of their exceptional stability, chaotically oscillating lasers are attractive options for optical pump sources in terahertz time-domain spectroscopy systems. © 2023 IEEE.

关键词： Stabilization

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Investigation and Study of the Performance of a DVB over Satellite Link Using M-Ary PSK 2

Investigation and Study of the Performance of a DVB over Sat...

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2nd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer engineering, MI-STA 2022

作者： Bishi, Hager Alshepane, Somya H. Alhaddar, Kheriya F. Alnour, Saaida E. Electronic Technology Collage Communication Dep. Tripoli Libya Higher Institute of Science and Technology EE Department Al Khomes Libya Al-Mergib University Department of Electrical and Computer Engineering Al Khomes Libya Al-Gharefa College of Technical Engineering EE Department Al-Gharefa Libya

ISBN: (数字)9781665479189

ISBN: (纸本)9781665479189

In this paper, the performance of a Digital Video Broadcasting Over Satellite Link, a digital Video second-generation for satellite broadcasting (DVB-S2), was investigated and studied as a case study. The simulation was done by using Matlab in order to evaluate DVB-S2 performance developments in channel coding (LDPC codes) combined with modulation schemes (QPSK and 8-PSK ), code rates, forward error correction (FEC) and transmission channels. The obtained simulation results were graphically presented, where the bit error rate as a function of the signal to noise ratio (S/N) was evaluated as well. © 2022 IEEE.

关键词： Signal to noise ratio

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The Correlation Between Architecture Smells, Package Stability and Reusability: A Case Study

The Correlation Between Architecture Smells, Package Stabili...

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sciences and Techniques of Automatic Control and computer engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Mrwan BenIdris Ehab A. Omar Elfallah Marwa Aslam Cheema Mohammed Salah Addin Alsma Tareq Ziad Kadiki Abdelfattah Elbarsha Dep. of Computer Science Faculty of Information Technology University of Benghazi Dept. of Software Engineering Faculty of Information Technology Libyan International Medical University Health Informatics Department Faculty of Public Health University of Benghazi

ISBN: (数字)9798350372632

ISBN: (纸本)9798350372649

the design decisions made in the architecture of a software system are essential to its maintainability, and thus its quality is of great importance. Architecture smells (ASs) can be used to identify any quality issues within the system. To further explore the relationships between ASs, stability, and reusability, Spearman correlation coefficients will be calculated. This paper seeks to examine the connection between architecture smells, software stability, and reusability. To do this, we utilized a dataset created by other researchers and conducted an empirical study of the associations between five types of architecture smells and software stability and reusability. This research is necessary as there is a lack of in-dep.h research on architecture smells and their relationship to software stability and reusability. We found a relationship between the presence of Feature Concentration in package and the stability and reusability of the package. Also, package's stability is affected by both Cyclic dep.ndency and Unstable dep.ndency. A slight positive correlation has been found between God Class and stability, as well as a very weak negative correlation between Unstable dep.ndency and reusability. Finally, we found a slight negative correlation between package stability and reusability.

关键词： Correlation coefficient Correlation Codes Conferences computer architecture Software systems Software development management

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Reducing Overconfidence Predictions for Autonomous Driving Perception

arXiv

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arXiv 2022年

作者： Melotti, Gledson Premebida, Cristiano Bird, Jordan J. Faria, Diego R. Gonçalves, Nuno Federal Institute of Espirito Santo Brazil The Dep. of Electrical and Computer Engineering University of Coimbra-Portugal Portugal Department of Computer Science Nottingham Trent University United Kingdom School of Physics Engineering and Computer Science University of Hertfordshire United Kingdom Dep. of Electrical and Computer Engineering University of Coimbra-Portugal Portuguese Mint and Official Printing Office Lisbon Portugal

In state-of-the-art deep learning for object recognition, Softmax and Sigmoid layers are most commonly employed as the predictor outputs. Such layers often produce overconfidence predictions rather than proper probabilistic scores, which can thus harm the decision-making of 'critical' perception systems applied in autonomous driving and robotics. Given this, we propose a probabilistic approach based on distributions calculated out of the Logit layer scores of pre-trained networks which are then used to constitute new decision layers based on Maximum Likelihood (ML) and Maximum a-Posteriori (MAP) inference. We demonstrate that the hereafter called ML and MAP layers are more suitable for probabilistic interpretations than Softmax and Sigmoid-based predictions for object recognition. We explore distinct sensor modalities via RGB images and LiDARs (RV: range-view) data from the KITTI and Lyft Level-5 datasets, where our approach shows promising performance compared to the usual Softmax and Sigmoid layers, with the benefit of enabling interpretable probabilistic predictions. Another advantage of the approach introduced in this paper is that the so-called ML and MAP layers can be implemented in existing trained networks, that is, the approach benefits from the output of the Logit layer of pre-trained networks. Thus, there is no need to carry out a new training phase since the ML and MAP layers are used in the test/prediction phase. The Classification results are presented using reliability diagrams, while detection results are illustrated using precision-recall *** Codes 68T10 Copyright © 2022, The Authors. All rights reserved.

关键词： Forecasting

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Real-time Ventilation Detection for Feedback and Guidance During Newborn Resuscitation

Real-time Ventilation Detection for Feedback and Guidance Du...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Øyvind Meinich-Bache Hannah Håland Anita Yeconia Rafal Paprocki Solveig Haukås Haaland Øystein Gomo Thomas Haukland Siren Irene Rettedal Sara Brunner Esto Mduma Hege Ersdal Dep. of Electrical Engineering and Computer Science University of Stavanger Norway Strategic Research Laerdal Medical Stavanger Norway Haydom Lutheran Hospital Tanzania Stavanger University Hospital Norway Faculty of Health Sciences University of Stavanger Norway

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

For a healthcare provider treating a non-breathing newborn baby, timely ventilation of the lungs is the most critical action to save the newborn’s life. However, the guidelines for newborn resuscitation are challenging to follow and a real-time feedback and guidance system may contribute to more optimal treatment. In this study we utilized deep neural networks for detecting ventilation in the audio signal extracted from video recordings of 25 newborn resuscitation episodes. The proposed ventilation detection system utilizes Log Mel Spectrograms for feature generation, audio augmentation for dataset expansion, and 2D Convolutional Neural Networks (CNNs) for ventilation classification. For the task of image classification, we compared two different pretrained backbones suited for real-time inference and a custom-built efficient CNN, called VD-CNN. We found that using MobilenNetV3Large as the feature extractor yielded the best results, achieving a F1-score of 97.21%. Our efficient VD-CNN, with a parameter count one fifth that of MobilenNetV3Large, still achieved a robust F1-score of 95.37%. To demonstrate that the proposed system can perform ventilation detection and provide immediate feedback during newborn resuscitation in real-time, we integrated the ventilation detection system into a newborn resuscitation station called Liveborn Station.

关键词： Pediatrics Computational modeling Tablet computers Medical services Ventilation Feature extraction Real-time systems Convolutional neural networks Video recording Spectrogram

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