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International Conference on Industrial and Information Systems, ICIIS

作者： Partha Sarkar Abhijit Mallik Chandan Kumar Sarkar V. Ramgopal Rao Department of Electronics & Telecommunication Engineering Jadavpur University Kolkata India Q.I.P. program of AICTE Orissa Engineering College Bhubaneswar Orissa India Department of Electronics & Communication Engineering Kalyani Government Engineering College India Department of Electrical Engineering Indian Institute of Technology Bombay India

In this paper we systematically investigate the effects of the varying tilt angle of the halo implants on the different device performance parameters of 100 nm lateral asymmetric channel (LAC) MOSFETs. The tilt angle is varied from 5deg to 60deg with twist angle 0deg. Substantial reduction of sub-threshold swing is found for large tilt angles as compared to low angles of halo implant. The device structure, known as lateral asymmetric channel with large angle tilt implant (LACLATI), exhibits better reverse short channel effect and I on /I off , and lower junction capacitance

关键词： Implants Los Angeles Council MOSFETs Threshold voltage Industrial electronics Educational institutions Capacitance communication industry electronics industry Information systems

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The Effects of Curvature of Edge Screen on Subjective Feelings in Smartphone Usage

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Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2017年第1期61卷 1269 - 1270页

作者： Yushin Lee Joong Hee Lee Yong Min Kim Jihwan Lee Sanghyun Kwon Hyungmin Sim Myung Hwan Yun Department of Industrial Engineering Seoul National University Seoul 08826 Technology Management Economics and Policy Program Seoul National University Seoul 08826 Mobile Communication Business Samsung Electronics Suwon 16677

As the penetration rate of Smartphone grows high and the market gets saturated, the technological and aesthetic progress for manufacturers are heavily demanded to sustain their market share. To meet such demands, manufacturers continuously improve the design of their products. As the design of smartphone varies by manufacturers, there have been many existing researches to identify the relationships between various physical dimensions of smartphones and how users feel (Chowdhury, A., & Kanetkar, M., 2017; Lee, S., Kyung, G., Lee, J., Moon, S. K., & Park, K. J., 2016; Pereira, A., Miller, T., Huang, Y. M., Odell, D., & Rempel, D., 2013; Sung, K., Cho, J., & Freivalds, A., 2016). Recently, in accordance with the development and improvement of flexible displays, curved displays have been applied on smartphones with various curvatures. The popular one among them is the “edge screen” on smartphones, which refers to curved display implemented either on one single side or both sides. Considering that physical dimensions such as shape and size are the important features for customer satisfaction (Hwang, 2012; Ling, C., Hwang, W., and Salvendy, G., 2007), curvature of edge screen can influence on user comfort when the users carry out their tasks on their smartphones. However, such issue hasn’t been dealt in previous studies. Therefore, as a preliminary study, this study aimed to identify the relationships between curvatures of edge screens and subjective feelings in smartphone usage with various usage patterns using subjective evaluation experiment. In this laboratory study, 47 subjects assessed their subjective feelings (grip comfort, control comfort, stability, front visibility, side visibility) towards given samples with four different kinds of usage patterns. The samples were designed with a 5.5-inch flat display of 16:9 ratio (Samsung Galaxy Note 2) as a main screen along with a curved display of different radii of curvatures (R, unit: mm) on the right edge as an edge sc

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Evolutionary Trends of Intelligent IoT Networking for Commercial and Industrial Use Cases

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中国通信（英文版） 2023年第8期20卷前插1-前插4页

作者： Shuai Han Rong Bo Nadra Guizani Sai Xu Ruoyu Su Liang Xiao Cheng Li Department of Electronics and Communication Engineering Harbin Institute of Technology Communications Research Centre Canada Engineering program and the computing Research Association School of Cybersecurity Northwestern Polytechnical UniversityXi'anChina Nanjing University of Posts and Telecommunications Department of Informatics and Communication Engineering Xiamen Univer- sityFujianChina Department of Electrical and Computer Engineering of Memorial University St.John'sCanada

The intelligent Internet of Things(IIoT)is one of the key enablers for the digital transformation of traditional industries towards Industry *** services have diversified requirements due to the nature of their commercial and industrial *** various devices in IIoT environments have their unique properties in terms of resource limita-tions,network lifetimes,and application Quali-ty-of-Service(QoS)requirements which affect the performance under such applications ***,IoT devices typically have constrained power,storage,computing,high latency,massive multiple access and communications resources which limit the performance of IIoT for commercial and industrial Use *** the other hand,devices used in IIoT were not initially designed with security in mind and they had been considered *** response to the above challenges,domestic and foreign scholars have gradually carried out research on network architecture,collaborative scheduling strategy,energy supply technology,resource man-agement,and ***,the research on IIoT is still in its infancy,and has not yet formed comprehen-sive and systematic theoretical methods and technical standards.

关键词： Special issues and sections Internet of Things Intelligent systems Commercialization Requirements engineering Industrial engineering

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A comparative evaluation of competitive learning algorithms for edge detection enhancement

A comparative evaluation of competitive learning algorithms ...

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European Signal Processing Conference (EUSIPCO)

作者： Tuba Sirin Mehmet Izzet Saglam Isin Erer Muhittin Gokmen Okan Ersoy Informatics Institute Computer Science and Engineering Informatics Institute Satellite Communication and Remote Sensing Program Faculty of Electrical and Electronic Engineering Electronics and Communication Department Faculty of Electrical and Electronic Engineering Istanbul Technical University Maslak Istanbul TURKEY Purdue University School of Electrical and Computer Engineering West Lafayette Indiana USA

Most edge detection algorithms include three main stages: smoothing, differentiation, and labeling. In this paper, we evaluate the performance of algorithms in which competitive learning is applied first to enhance edges, followed by an edge detector to locate the edges. In this way, more detailed and relatively more unbroken edges can be found as compared to the results when an edge detector is applied alone. The algorithms compared are K-Means, SOM and SOGR for clustering, and Canny and GED for edge detection. Perceptionally, best results were obtained with the GED-SOGR algorithm. The SOGR is also considerably simpler and faster than the SOM algorithm.

关键词： Image edge detection Image segmentation Vectors Abstracts Filtering algorithms Erbium Training

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Quantum Wrapper Networking: Investigating the Noise Impact of Classical Headers on the Quantum Payload

Quantum Wrapper Networking: Investigating the Noise Impact o...

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2024 Frontiers in Optics, FiO 2024

作者： Gül, Gamze On, Mehmet Berkay Tan, Shannon G. Proietti, Roberto Kanter, Gregory S. Yoo, S.J. Ben Kumar, Prem Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States Department of Electronics and Telecommunications Engineering Politecnico di Torino Italy

We study the impact in time and frequency domains of classical headers on quantum payloads in quantum wrapper networking. We identify and characterize in-fiber scattering processes that produce noise photons degrading...

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Guava Trees Disease Monitoring Using the Integration of Machine Learning and Predictive Analytics 3

Guava Trees Disease Monitoring Using the Integration of Mach...

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

作者： Elsayed, Mahmoud Hassan, Nourhan Maher, Marina Waleed, Nouran Reda, Rehab Eldin, Haitham Sharaf Mostafa, Hassan The American University of Cairo Mechatronics Department Egypt Nile University Giza12677 Egypt Communication Engineering Alexandria University Egypt Biomedical Engineering Cairo University Egypt Tanta University Egypt Cairo University Faculty of Science Biophysics Department 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)9781665421577

The increase in population, food demand, and the pollution levels of the environment are considered major problems of this era. For these reasons, the traditional ways of farming are no longer suitable for early and accurate detection of biotic stress. Recently, precision agriculture has been extensively used as a potential solution for the aforementioned problems using high resolution optical sensors and data analysis methods that are able to cope with the resolution, size and complexity of the signals from these sensors. In this paper, several methods of machine learning have been utilized in order to study pests, their types, population, and agricultural conditions in terms of soil and climate for some crops such as potatoes, guava, and cotton, which are among the main Egyptian crops. In the process of obtaining a suitable estimate of insects population affecting each of the aforementioned crops, a hardware model control, based on the results provided by the predictive analysis, an estimate of the electromagnetic force is applied to the cultivated areas to get rid of the pests as well as giving a background to farmers about the possibility of infecting a crop such as Potato with Late Blight, according to climatic conditions. © 2021 IEEE.

关键词： Model predictive control

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Exploring Regression and Classification in Big Data with Deep Learning

Exploring Regression and Classification in Big Data with Dee...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Pandey, Ravindra Rongali, Aruna Sri Gopinath, S. Anute, Nilesh Nama, Forda Pund, Sachin Hult International Business School United States University of the Cumberlands Doctoral Information Technology Information Technology Emphasis Information Technology United States Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore India ASM's Institute of Business Management and Research Pune India University of Lampung Doctoral Program of Environtmental Science Department of Informatics Bandar Lampung Indonesia Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India

ISBN: (纸本)9798350357769

Deep gaining knowledge is a synthetic intelligence approach used to recognize complex facts. It uses many facts to recognize the complicated relationships between various factors. With deep learning, models can be built which might be capable of understanding the complicated patterns within big datasets. In this paper, we can explore using deep mastering in regression and type tasks on large datasets. In particular, we can use deep learning strategies to build a regression model that predicts a target value primarily based on the functions in a massive dataset and a classification version that can classify an object into one of the many classes of an extensive dataset. We can then discuss the overall performance of the fashions in comparison to standard models and talk about capability areas for development. Moreover, we will analyze the scalability of deep mastering strategies used on large datasets and discuss exceptional practices for building deep mastering fashions on massive datasets. Finally, we will summarize our findings and offer our conclusions approximately the use of deep studying in regression and type obligations on large datasets. © 2023 IEEE.

关键词： approximately gaining knowledge mastering performance regression

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Multi Inteligent Traffic Light Optimization techniques by appling Modified Component Analysis Algorithm

Multi Inteligent Traffic Light Optimization techniques by ap...

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International Conference on Science Technology engineering and Management (ICONSTEM)

作者： V. Ellappan B. Sindhusaranya Tadesse Hailu Electronics & Communication Eng. Program School of Electrical Engineering & Computing Adama Science and Technology University Adama Ethiopia Center for Research in Image and Signal Processing2 Mahendra Engineering College (Autonomous) Namakkal

ISBN: (纸本)9781728116006

Large cities situated within the developing countries facing one of the most important problems are heavy traffic congestion. It happened because of fast urbanization n. Many modern infrastructures for constructing a traffic signal have been introduced. Due to high maintenance cost and less knowledge of local workers that infrastructure doesn't work well. In this paper, we proposed a new technique for signal control framework, which estimates the traffic flows using the image analysis. For this technique inexpensive Web cameras are required for supporting signal control strategy which is based on traffic volume on that particular time. Traffic volumes can be estimated with few observation points. Based on that, signal controls can be adjusted. Numerical experiments of this proposed work confirmed that average travel time is reduced to 20.6% while comparing to the fixed-time signal control.

关键词： Matlab Graphical user interfaces Traffic control Computational modeling Optimization Timing Real-time systems

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Analysis of Mucilage Levels Build Up in the Sea of Marmara Based on Unsupervised Unmixing of Worldview-3 Data

Analysis of Mucilage Levels Build Up in the Sea of Marmara B...

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Geoscience and Remote Sensing Symposium (M2GARSS), Mediterranean and Middle-East

作者： Gö zdenur Keleş oğ lu Alp Ertü rk Esra Erten Institute of Informatics Satellite Communication and Remote Sensing Program Istanbul Technical University Istanbul Turkey Department of Electronics and Telecommunication Engineering Kocaeli University Turkey Department of Geomatics Engineering Istanbul Technical University Istanbul Turkey

ISBN: (数字)9781665427951

ISBN: (纸本)9781665427968

Increasing uncontrolled industrialization causing untreated wastewater and marine traffic, coupled with specific weather conditions makes the Marmara Sea face major challenges, such as the mucilage outbreak in the summer of 2021. Cleaning up the Sea of Marmara will continue to be critical to the long term survival of the fishing industry and tourism, and new methods and techniques for monitoring its behaviour will be important for benchmarking. In this specific context, this paper discusses the potential of using unmixing approaches for the analysis of multispectral images in order to understand and map the abundance of mucilage coverage, in connection with its chemical compositions related to varying levels of aggregation. A WorldView-3 multispectral image, acquired on May 25, 2021, was chosen for the study due to its high spatial resolution and VIS/NIR spectral region. Unmixing provides the spectral characteristics of endmembers (i.e., water, ship and different types mucilage), and the abundance associated with each endmember. Preliminary results were discussed and some research aspects for understanding mucilage phenomena using EO were put forward.

关键词： Water Toxicology Sea measurements Cleaning Wastewater Spatial resolution Marine vehicles

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Low-Resolution Face Recognition for CCTV and Edge-Powered Smart Attendance Systems

Low-Resolution Face Recognition for CCTV and Edge-Powered Sm...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Nico Surantha Edward Yose Sani Muhamad Isa Department of Electrical Electronics and Communication Engineering Faculty of Science and Engineering Tokyo City University Tokyo Japan Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Attendance systems have become more modern, and one of the biometric systems without physical contact is face recognition. However, many face-based attendance systems still carry out attendance individually and cannot detect multiple faces simultaneously. In addition, capturing facial data in real-time is still a challenge because the relatively large distance between the camera and the individual reduces the ability to recognize faces. The general solution is to use super-resolution to generate better-quality faces while maintaining the main facial recognition features. One technique still being researched is super-resolution generative adversarial networks (SRGAN). SRGAN can enlarge the resolution of captured images and maintain image quality sufficient for face recognition. The attendance system can be easily integrated into edge devices such as the Jetson Nano. This paper proposes automatic and effective attendance systems with the super-resolution technique to detect and recognize faces in low-resolution input. The experimental results show that using face data capture with a resolution of 40 × 40 pixels and a four-fold magnification results in a resolution of 160 × 160 pixels. Combining Face SRGAN with FaceNet architecture as the basis of face recognition can achieve an accuracy rate of 78.19% and an F1-Score of 81.13% with an average processing time of 1.61 seconds per frame on a PC and 14.55 seconds per frame on a Jetson Nano at an average of face recognition per frame of as many as up to 8 faces simultaneously.

关键词： Support vector machines Image quality Accuracy Face recognition Image edge detection Superresolution Generative adversarial networks

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