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检索条件"机构=Dep. Computer Engineering Technology"

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Prediction of Electrical Characteristics of a-IGZO TFT Based on Transfer Learning-Based Variational Autoencoder

Prediction of Electrical Characteristics of a-IGZO TFT Based...

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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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Health home-monitoring system based on IoT 7

Health home-monitoring system based on IoT

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7th IEEE International Symposium on Electrical and Electronics engineering, ISEEE 2021

作者： Ionescu, Bogdan Craciun, Marian Petrea, George Epure, Silviu Arama, Catalin Vlad, Ciprian 'Dunarea de Jos' University of Galati Dep. of IT and Digital Communications Romania 'Dunarea de Jos' University of Galati Dep. of Computer Science and Information Technology Romania 'Dunarea de Jos' University of Galati Dep. of Electronics and Telecommunications Romania 'Dunarea de Jos' University of Galati Dep. of Automation and Electrical Engineering Romania

ISBN: (纸本)9781665437998

The recent COVID-19 pandemic highlighted that there is a lot of work to do regarding the integration of digital technologies in healthcare. Actual trending offers the possibility to patients to have permanent knowledge about their health status and not to go to have a general check when some symptoms appear. Internet of Things (IoT) has also reached the medical area and can offer high quality solutions. After this step is taken the data collected and stored locally or remote in the cloud cand be easily reached, analyzed and health monitoring for each patient is much improved. © 2021 IEEE.

关键词： Internet of things

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TIoT: A Trust by Design Architecture for Secure and Private Internet of Things (IoT) 21

TIoT: A Trust by Design Architecture for Secure and Private ...

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21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Alsheakh, H. Mahdi, Tareq Nasser Kadhm, Mustafa S. Al Shammari, Abeer Abdulsahib, Fatimah I. Taher, Hazeem B Algriree, Waleed Alobaidi, Marwa Q. Mohammed, Hayder Dhafer College of Science Mustansiriyah University Department of Computer Science Baghdad Iraq College of Pharmacy Mustansiriyah University Clinical Laboratory Science Baghdad Iraq Ministry of Science and Technology Baghdad Iraq Szechenyi Istvan Egyetem Department of Computer Science Gyor9026 Hungary University of Thi-Qar Department of Computer Science Thi-Qar Iraq University Putra Malaysia Dep. of Wireless Communication and Network Engineering Selangor Malaysia National Engineering School of Sfax Sfax University Sfax Tunisia College of Pharmacy Mustansiriyah University Baghdad Iraq

ISBN: (纸本)9798350374131

The Internet of Things (loT) facilitates the interconnection of a vast array of devices, services, and individuals for data exchange in multi-domain loT ecosystems, the social, physical, and cyber domains. That emerges various security, privacy, and trust issues, such as vulnerabilities, threats, and attacks. Addressing these challenges requires innovative solutions. New controls (solutions) are needed. Trust by design can be one of these controls, supporting security and privacy (among other system components). This paper proposes a Trusted loT (TloT), a trust-by-design model, and highlights the author's principal contributions. First, it advocates for implementing Tlo T through trust services. Second, it outlines an architecture for using trust by design in loT, including the design of its top-level structure and activities. Minor contributions include overviews of loT and trust, as well as looking at security and privacy in terms of security services and privacy services, respectively. © 2024 IEEE.

关键词： Internet of things

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Camera-LiDAR Fusion based Object Segmentation in Adverse Weather Conditions for Autonomous Driving

Camera-LiDAR Fusion based Object Segmentation in Adverse Wea...

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International Baltic Electronics Conference, BEC

作者： Junyi Gu Mauro Bellone Artjom Lind Dep. of Mechanical and Industrial Engineering Tallinn University of Technology Tallinn Estonia FinEst Centre for Smart Cities Tallinn University of Technology Tallinn Estonia Institute of Computer Science University of Tartu Tartu Estonia

ISBN: (数字)9798350365115

ISBN: (纸本)9798350365122

This paper presents the results of a series of machine learning experiments that focus on the domain adaption between different training datasets for autonomous driving. The experiments use a neural network model obtained through transfer learning from the Waymo Open Dataset and then tested with our custom dataset, which was recorded at the TalTech campus in different weather conditions. In this work, we developed a set of tools to extract and process the sensory data from the iseAuto shuttle. The camera and LiDAR sensors of the iseAuto shuttle were calibrated, and the point clouds data of the LiDAR sensor was projected onto the camera plane. We present, here, our publicly available iseAuto dataset which was used for a classification task under adverse weather and low illumination conditions. The iseAuto dataset contains 8000 frames of camera and LiDAR data for traffic object detection and segmentation. We provide ground truth annotations of 2400 frames, in which the object contours were manually labeled out. In addition, we provided the manual-labeled ground-truth segmentations of cars and humans in images, which can be used by the community to test the accuracy of the segmentation of their models. An additional focus of this paper is to demonstrate that with a few custom annotated data, using transfer learning and semi-supervised learning, it is possible to obtain reasonable accuracy on noisy real-world data. The current performance in vehicle segmentation ranges from 65% to 85% in intersection over union (IoU) and between 43% and 60% IoU for pedestrian segmentation in challenging scenarios such as nighttime and rainy weather.

关键词： Point cloud compression Laser radar Accuracy Transfer learning Object segmentation Semisupervised learning Cameras Sensors Autonomous vehicles Meteorology

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CCDF measurement with Multi Impairment of Wi-Fi 6 performance using MATLAB Simulink

CCDF measurement with Multi Impairment of Wi-Fi 6 performanc...

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Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), International Conference on

作者： Fatima Faydhe Al-Azzawi Rasha Hassan Abbas Zainab Faydhe Al-Azzawi Kamal Y. Kamal Electronics Technical Department Institute of Technology Middle Technical University MTU Baghdad Iraq Dep. Computer Technology Engineering AL- Mansour university college Iraq

The current 802.11ac WiFi standard is built upon and improved by WiFi 6, commonly referred to as “AX WiFi” or “802.11ax WiFiIn response to the increasing number of gadgets in the globe, WiFi 6 was first developed. If you have numerous smart home devices, VR equipment, or a lot of other gadgets, WiFi 6 employs a 160 MHz Channel to offer a channel that larger and providing by 1024-QAM to more data with one packed, increasing efficiency. In this paper 802.11 ax design and implemented in MATLAB Simulink where CCDF measurement (Complementary Cumulative Distribution Function measure the probability that a signal's instantaneous power may exceed its target level or average power) with multi-impairment performance illustrated using 1024-QAM to offer a packed signal with increasing data and a channel with160 MHz, 1024 QAM examined with AWGN and Rayliegh fading channel in term of bit error rate.

关键词： Power measurement Phase measurement Quadrature amplitude modulation Software packages Bit error rate Measurement uncertainty IEEE 802.11ax Standard

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Image Encryption using Chaotic Techniques: A Survey Study

Image Encryption using Chaotic Techniques: A Survey Study

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2021 International Conference in Advances in Power, Signal, and Information technology, APSIT 2021

作者： Ayad, Jenan Hasan, Fadhil Sahib Ali, Alaa H. Hussein, Zaid Khudhur Abdulkareem, Hanan J. Jalil, Mustafa A. Ahmed, Ghaidaa Sadiq, Ahmed University of Technology Electrical Engineering Dep. Baghdad Iraq Electrical Engineering Dep. Mustansiriyah University Baghdad Iraq Technical Engineering Al-Esraa University College Medical Instrumentation Baghdad Iraq Al-Esraa University College Computer Technical Engineering Baghdad Iraq

ISBN: (纸本)9781665425063

The sharing of information through unsecured networks like the internet has increased fast recently. This information could be text, audio, image, or video. The security of data transmission is an essential issue. Encryption is one of the most effective techniques to assure safe data transmission. Videos and Images size are very large and have a high correlation between neighboring pixels, so the classical encryption techniques such as RSA, DES, AES, etc., cannot be utilized for image encryption while chaotic image encryption schemes, which use a high level of unpredictability in key generation, can solve this problem. The chaos encryption main properties are pseudorandom number, sensitivity to initial conditions, and large key size. The goal of this study was to find the best chaotic map for picture encryption, this research looks into the use of chaos maps for image encryption, such as the Tent map, Logistic map, Sine map, and others. Arnold's Cat map, and also presents a comparison for their performance. © 2021 IEEE.

关键词： Data transfer

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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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Improving Distribution Systems Maintenance Management, by Predicting Reliability Indices Using Fully Connected Neural Networks

Improving Distribution Systems Maintenance Management, by Pr...

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Smart Grid Conference (SGC)

作者： Mohammad-Hossein Tananaeifar Mahdis Alimadaday SeyedMohammad-Mahdi Ghadamgahi Mohammad Ghafourian-Nasiri Alireza Fereidunian Construction Engineering and Management Dep. Amirkabir University of Technology Tehran Iran Industrial Engineering Dep. Tarbiat Modares University Tehran Iran Computer Engineering Dep. Kharazmi University Tehran Iran Electrical Engineering Faculty K. N. Toosi University of Technology Tehran Iran

ISBN: (数字)9798350333961

ISBN: (纸本)9798350333978

Due to the increasing amount of industrial data worldwide, deep learning solutions have become extensively popular for preventive maintenance programs. Preventive maintenance reduces the costs of equipment failures, thus crafting detailed preventive maintenance programs are very effective. Neural networks are intelligent computing techniques inspired by biological neurons. Neural networks are one of the most common and practical machine learning algorithms that are utilized in many industrial applications. In this research, a fully connected neural network is developed to predict the systems reliability indices, i.e. the number of failures occurring in feeders and the amount of energy not served (ENS) in electricity distribution feeders. As a result, a data-driven improvement is provided for the preventive maintenance program.

关键词： Costs Machine learning algorithms Neurons Energy measurement Organizations Smart grids Reliability

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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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Basic Study for Transfer Learning for Autonomous Driving in Car Race of Model Car 6

Basic Study for Transfer Learning for Autonomous Driving in ...

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6th International Conference on Business and Industrial Research, ICBIR 2021

作者： Chiba, Shohei Sasaoka, Hisayuki National Institute of Technology Asahikawa College Advanced Course of Production System Engineering Asahikawa Japan National Institute of Technology Asahikawa College Dep. of Electrical and Computer Engineering Asahikawa Japan

ISBN: (纸本)9781665433495

Reinforcement learning, deep learning, and deep reinforcement learning can effectively acquire action rules for the autonomous motion of objects. However, some researchers have reported that the machine learning process requires a large amount of learning time. Besides, the process needs to consider the similarity of the environment between the training target and the test target. There is no such thing as driving only on a course learned in advance in actual autonomous driving. In this study, we have used a transfer learning algorithm for autonomous drivings for model cars. The training target for acquiring the learning model and the actual driving courses are changed. In this study, we report on the effectiveness of transfer learning using a model car as the basis for a learning model acquired by reinforcement learning. © 2021 IEEE.

关键词： Deep learning

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