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International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

作者： Abdulvahit Karaıl Veysel Gökhan Böcekçı İsmail Kiyak Electrical and Electronics Engineering Institute of Graduate Studies in Pure and Applied Sciences Marmara University Istanbul Turkey Department of Electrical and Electronics Engineering Faculty of Technology Marmara University Istanbul Turkey

In communication technologies, it can be solved in systems that are extremely simple, detailed, among the tools for use in the electronic environment, internet-connected, development and integrated systems. With the rapid development of technology, smart led lamps, smart office, smart conference room lighting, road lighting fixtures and therefore smart lighting systems have been the reason why smart lighting systems can enter daily life rapidly. Sensors which are the components of smart lighting systems, feedback from users, cloud services, smart algorithms become more widespread with artificial intelligence in an easier, faster, and more economical way, causing a change in traditional lighting control and improvements in energy saving, functionality, and user centered lighting. In this study, the mediapipe framework is intended to be used for office conference room. MediaPipe is indeed an open-source framework that enables the processing of computer vision data, including video and audio. The lighting system was built using the artificial intelligence supported mediapipe hand recognition solution, and artificial intelligence and image processing algorithms were used. Each hand gesture corresponds to a different command to control the light. There are 3 main menus are determined for the hand and defined to the system. Main menus can be reached with every hand movement. After entering the main menu, intermediate menus are processed. Lighting application can be realized through control commands obtained by hand movements, digital/analog information conversion and Dali control system. It is concluded that the ease of control brought by this method is more advantageous in terms of its purpose than other methods because it is contactless and does not require any hardware device in the hands of the presenter.

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Enhanced Sensitivity of ISFET pH-Sensor Utilizing Reduced Graphene Oxide

Enhanced Sensitivity of ISFET pH-Sensor Utilizing Reduced Gr...

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Microelectronics (IICM), Iranian International Conference on

作者： Hossein Rezaei Estakhroyeh Mahdiyeh Mehran Esmat Rashedi Department of Electrical Engineering RF MEMS and Bio-Nano Electronics Lab Shahid Bahonar University of Kerman Kerman Iran Faculty of Electrical and Computer Engineering Graduate University of Advanced Technology Kerman Iran

ISBN: (数字)9798331511371

ISBN: (纸本)9798331511388

With an emphasis on the sensitivity of various gate-sensing layers, the current work sought to examine how well Ion-Sensitive Field-Effect Transistors (ISFETs) function as pH sensors. Reduced Graphene Oxide (rGO) has been investigated as a potential sensing material for ISFET sensors, however Metal Oxides have historically been the material of choice for the gate-sensing layer because of its stability and dependability. ISFET sensors using rGO as the sensing material and those with traditional Metal Oxide gate layers were thoroughly compared. The performance of the sensors was assessed under a range of operating situations by multiphysics modeling with finite element methods using COMSOL Multiphysics software. The results showed a considerable improvement in sensor performance when rGO was used as the gate-sensing layer. A lower threshold voltage needed to activate the sensor and a higher sensitivity to pH variations were two of these enhancements. In ISFET sensors for pH monitoring, this work emphasizes the benefits of adopting alternate gate materials, such rGO. For the purpose of creating more dependable and efficientpH-sensing instruments for a range of scientific and industrial applications, it is helpful to analyze the fundamental mechanics and performance characteristics of sensors.

关键词： Sensitivity Graphene Metals Logic gates Sensor phenomena and characterization Threshold voltage Stability analysis Software Transistors Monitoring

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Enhanced Light-Matter Interactions for a Single T Center in a Silicon Nanocavity

Enhanced Light-Matter Interactions for a Single T Center in ...

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CLEO: Fundamental Science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Wong, Yu-En Johnston, Adam Felix-Rendon, Ulises Chen, Songtao Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States

We investigate light-matter interactions for a single T center coupled to a silicon photonic crystal cavity. By solving Lindblad master equation, we extract the cavity-QED parameters for the coupled system. © Opt... 详细信息

ISBN: (纸本)9781957171395

关键词： Silicon photonics

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Evaluating an e-Learning Platform at graduate School Based on User Experience Evaluation Technique 3

Evaluating an e-Learning Platform at Graduate School Based o...

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3rd International Conference on electrical, electronics, Informatics, and Vocational Education, ICE-ELINVO 2020

作者： Abubakari, M.S. Nurkhamid Hungilo, G. Department of Electronics Engineering Education Postgraduate Program Universitas Negeri Yogyakarta Indonesia Department of Informatics Engineering Graduate Program University Atma Jaya Yogyakarta Indonesia

This study was aimed to evaluate the e-learning platform in a graduate school by using User Experience Questionnaire (UEQ). The data were collected from 65 respondents and analyzed using an excel data analysis tool. The results indicate that all six scales of the instrument are consistent except the novelty scale. Also, the calculated means of the scales are slightly positive as all values are greater than 0.8 compared to the UEQ benchmark. Although the respondents show a little positive impression with the platform, all scales means are below average category except efficiency scale which is above average as compared to the benchmark. This indicates that the platform needs more improvement in all aspects of user experience for it to be at least in a good category. The findings discussed in this paper are valuable for all academic stakeholders in various educational institutions which implement interactive e-learning systems as well as practitioners of user experience and developers of e-learning systems. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Learning systems

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An Overview of Facial Micro-Expression Analysis: Data, Methodology and Challenge

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IEEE Transactions on Affective Computing 2023年第3期14卷 1857-1875页

作者： Xie, Hong-Xia Lo, Ling Shuai, Hong-Han Cheng, Wen-Huang National Yang Ming Chiao Tung Univresity Institute of Electronics Hsinchu300093 Taiwan National Yang Ming Chiao Tung Univresity Department of Electrical and Computer Engineering Hsinchu300093 Taiwan National Chung Hsing University Artificial Intelligence and Data Science Program Taichung40227 Taiwan

Facial micro-expressions indicate brief and subtle facial movements that appear during emotional communication. In comparison to macro-expressions, micro-expressions are more challenging to be analyzed due to the short span of time and the fine-grained changes. In recent years, micro-expression recognition (MER) has drawn much attention because it can benefit a wide range of applications, e.g., police interrogation, clinical diagnosis, depression analysis, and business negotiation. In this survey, we offer a fresh overview to discuss new research directions and challenges these days for MER tasks. For example, we review MER approaches from three novel aspects: macro-to-micro adaptation, recognition based on key apex frames, and recognition based on facial action units. Moreover, to mitigate the problem of limited and biased ME data, synthetic data generation is surveyed for the diversity enrichment of micro-expression data. Since micro-expression spotting can boost micro-expression analysis, the state-of-the-art spotting works are also introduced in this paper. At last, we discuss the challenges in MER research and provide potential solutions as well as possible directions for further investigation. © 2010-2012 IEEE.

关键词： Surveys

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Clustering Analysis of a Spatiotemporal Dataset with a Novel Kernel Density Estimator

Clustering Analysis of a Spatiotemporal Dataset with a Novel...

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2023 International Conference on Machine Learning and Cybernetics, ICMLC 2023

作者： Yu, Jen-Chien Yang, Chun-Chieh Gilbert, John Reuben Liu, Rou-Jun Oyang, Yen-Jen Yang, Meng-Han National Kaohsiung University of Science and Technology Department of Computer Science and Information Engineering Kaohsiung City807618 Taiwan National Taiwan University Master Program in Statistics Taipei106216 Taiwan National Taiwan University Department of Computer Science & Information Engineering Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan

ISBN: (纸本)9798350303780

A vast number of spatiotemporal datasets collected from a wide range of sources has motivated scientists to develop effective approaches to identify interesting patterns hidden in these datasets. In this respect, kernel density estimators, which belong to a class of non-parametric estimators in statistics, have been widely exploited in recent years. With this background, we have developed a novel kernel density estimator aiming to provide accurate analysis results. According to the evaluation with a real spatiotemporal dataset, which collected emergency medical service records in a county in the United States, the proposed kernel density estimator can approximate the probability density function significantly more accurately than a conventional kernel density estimator. Furthermore, we have exploited the proposed kernel density estimator to identify interesting patterns hidden in the real spatiotemporal dataset. © 2023 IEEE.

关键词： Probability density function

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Zero Sequence Current Detection Method of High Impedance Faults Using Distortion Waveform in Distribution Networks

Zero Sequence Current Detection Method of High Impedance Fau...

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IEEE PES Asia-Pacific Power and Energy engineering Conference (APPEEC)

作者： Jiraphat Manmoh Watcharin Srirattanawichaikul Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Graduate Program in Electrical Engineering Graduate School Chiang Mai University Chiang Mai Thailand Provincial Electricity Authority Bangkok Thailand

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

This paper presents high-impedance faults (HIF) detected in distribution networks with distortion zero sequence current detection methods. The simulation model in this paper is performed on a single branch distribution network with a voltage rating of 22kV, and the simulation is divided into two parts. The first part is the creation of HIF in the system by adjusting the distortion of the HIF current according to the principle of the heat-balanced equation of the material. The second part takes the resulting HIF model, which feeds into the established distribution network and detects distortion zero sequence currents occurring. The simulation results clearly depict the current waveform distortion caused by HIF, which can be adjusted. The presence of zero sequence current can indicate the occurrence of HIF in the distribution network.

关键词： Heating systems Surface impedance Surface waves Simulation Distribution networks Voltage Distortion

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Correlating the Ambient Conditions and Performance Indicators of the LoRaWAN via Surrogate Gaussian Process-Based Bidirectional LSTM Stacked Autoencoder

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IEEE Transactions on Network and Service Management 2023年第3期20卷 3413-3427页

作者： Bhat, Showkat Ahmad Huang, Nen-Fu Hussain, Imtiyaz Sajjad, Uzair National Tsing Hua University College of Electrical and Computer Science Hsinchu1300044 Taiwan National Tsing Hua University Department of Computer Science Hsinchu1300044 Taiwan National Taipei University of Technology Graduate Program in Energy and Opto-Electronic Materials Taipei10608 Taiwan National Taipei University of Technology Department of Energy and Refrigerating Airconditioning Engineering Taipei10608 Taiwan

LoRa's biggest advantage is its flexibility, which is the ability to increase or decrease data rate and range while decreasing or increasing sensitivity. Whenever propagation conditions change frequently, this function allows the spreading factor to be modified accordingly. Despite their efficiency and scalability, adaptive data rate algorithms ignore and fail to factor in the complex correlation between ambient weather parameters influencing the communication channel design. In this research, a Bayesian surrogate Gaussian process-based bidirectional LSTM stacked autoencoder model (BSGP-BLSTM-SAE) is proposed to estimate the channel performance indicators such as received signal strength indicator (RSSI) and signal-to-noise ratio (SNR) and to determine the correlation between the ambient weather conditions and performance indicators for the LoRaWAN network. Bayesian optimization algorithm has been used to optimize the hyper-parameters of the developed model. A LoRaWAN experimental multivariate time series dataset has been used for the evaluation of the developed model, which upon testing and validation produces high accuracy in predicting the channel performance indicators and ambient conditions of the experimental LoRaWAN network. The mean absolute error of the developed model was around 0.45. Thus, the proposed model can predict the link performance indicators and thereby assist in real-time optimization of the transmission parameters to enhance the network performance in LoRaWAN-based systems at different ambient conditions. © 2004-2012 IEEE.

关键词： Internet of things

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Performance Evaluation of Coffee Bean Binary Classification Through Deep Learning Techniques 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Islamy, Fajrul Muchtar, Kahlil Arnia, Fitri Dawood, Rahmad Febriana, Alifya Elwirehardja, Gregorius Natanael Pardamean, Bens Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Master of Computer Science Program BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Coffee beans are one of the high-value commodities in Indonesia, but the sorting method for the quality of coffee beans still uses visual methods and sieves with mechanical machines. This study aims to provide an alternative to classifying coffee beans using Deep Learning algorithms, such as the ResNet-18 and MobileNetV2. The dataset used is USK-COFFEE which consists of two classes, the normal coffee bean class, and the defect coffee bean class. The models were trained using the balanced and imbalanced datasets, meaning that two scenarios were performed. From the results of this study, the accuracy value for the ResNet-18 model was 91.50% when trained on the balanced dataset and 90.87% on the imbalanced dataset. It outperformed the MobileNetV2 architecture, which only achieved 0.8125 and 0.8112 accuracy scores when trained on the balanced and imbalanced datasets, respectively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Computer vision

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Purcell Enhancement of a Single T Center Coupled to a Silicon Nanophotonic Cavity

Purcell Enhancement of a Single T Center Coupled to a Silico...

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CLEO: Fundamental Science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Felix-Rendon, Ulises Johnston, Adam Wong, Yu-En Chen, Songtao Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States

We demonstrate Purcell enhancement of a single T center integrated in a silicon photonic crystal cavity, increasing the fluorescence decay rate by a factor of 6.89 and achieving a photon outcoupling rate of 73.3 kHz. ... 详细信息

ISBN: (纸本)9781957171395

关键词： Silicon photonics

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