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4th International Conference on High Voltage engineering and Power Systems, ICHVEPS 2023

作者： Maeda, Haruka Sitompul, Sandro Fujita, Goro Shibaura Institute of Technology Graduate School of Engineering and Science Department of Electrical Engineering and Computer Science Tokyo Japan Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798350318678

The use of high-penetration solar photovoltaics (PV) to transmission networks is complicated by voltage rise. Infractions of voltage occur when voltage levels surpass the permitted limits. Several solutions have been suggested to avoid voltage breaches, including volt-VAR control on inverters. In this research, the impact of utilizing dynamic volt-VAR control as opposed to static volt-VAR control in a high-penetration photovoltaic (PV) system is compared to the impact of applying static VAR compensator (SVC). With dynamic volt-VAR control, which takes into account the inverter's available reactive power capacity, it is possible to adjust the reactive power contribution of the PV inverter. The quantity of available capacity will affect the force of the control, as expressed by the droop gain. The transmission system's controls are evaluated for one year to determine the number of uncompensated voltage occurrences. The number of violations that the control cannot compensate for affects how much reactive power the SVC must provide. © 2023 IEEE.

关键词： Reactive power

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Byzantine Distributed Quickest Change Detection Based on Bounded-Distance-Decoding

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IEEE Signal Processing Letters 2023年 30卷 1532-1536页

作者： Saputra, Bagus Aris Lin, Shih-Chun National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei106 Taiwan National Taiwan University Department of Electrical Engineering and Graduate Institute of Communication Engineering Taipei106 Taiwan

Byzantine distributed quickest change detection (BDQCD) is a crucial problem in cyber-physical security. The challenge of this problem is that an AI plus IoT (AIoT) network needs to detect the change as quickly as possible, subject to a false alarm rate, to prevent device damage. In the BDQCD problem, dealing with compromised meters also becomes a challenge since these meters can collaboratively form an attack to lengthen the detection delay in an IoT network. Here we consider the network where a fusion center monitors the occurrence of an abrupt event through a bunch of distributed meters that may be compromised. To solve the challenge, a new coded framework for BDQCD utilizing bounded distance decoding at the fusion center is proposed. First, under sufficient meter-to-fusion-center link capacity, we achieve a theoretical result that the detection delay of our scheme can be asymptotically optimal in special cases. Next, new codebooks under insufficient link capacities are designed based on the theoretical result. Through the simulation results, our coded BDQCDs outperform the state-of-the-art works by achieving significantly shorter detection delay under various attacks. © 1994-2012 IEEE.

关键词： Probability density function

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Dynamic Sampling-Based Meta-Learning Using Multilingual Acoustic Data for Under-Resourced Speech Recognition

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IEEE Access 2024年 12卷 106070-106083页

作者： Hsieh, I-Ting Wu, Chung-Hsien Zhao, Zhe-Hong National Cheng Kung University Graduate Program of Multimedia Systems and Intelligent Computing Tainan70101 Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan

Under-resourced automatic speech recognition (ASR) has become an active field of research and has experienced significant progress during the past decade. However, the performance of under-resourced ASR trained by existing methods is still far inferior to high-resourced ASR for practical applications. In this paper, speech data from languages that share the most phonemes with the under-resourced language are selected as supplementary resources for meta-training based on the Model-Agnostic Meta-Learning (MAML) strategy. Besides supplementary language selection, this paper proposes a dynamic sampling method instead of the original random sampling method to select support and query sets for each task in MAML to improve meta-training performance. In this study, Taiwanese is selected as the under-resourced language, and the speech corpus of five languages, including Mandarin, English, Japanese, Cantonese, and Thai, are chosen as supplementary training data for acoustic model training. The proposed dynamic sampling approach uses phonemes, pronunciation, and speech recognition models as the basis to determine the proportion of each supplementary language to select helpful utterances for MAML. For evaluation, with the selected utterances from each supplementary language for meta-training, we obtained a Word Error Rate of 20.24% and a Syllable Error Rate of 8.35% for Taiwanese ASR, which were better than the baseline model (26.18% and 13.99%) using only the Taiwanese corpus and other methods. © 2013 IEEE.

关键词： Speech recognition

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Temperature Sensor Circuit for a Wearable Perspiration Monitoring System

Temperature Sensor Circuit for a Wearable Perspiration Monit...

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2023 International Symposium on Devices, Circuits and Systems, ISDCS 2023

作者： Ichimura, Yuichiro Goto, Kenta Johguchi, Koh Graduate School of Science and Technology Shinshu University Electrical and Computer Engineering Division Department of Engineering Nagano Japan Shinshu University Faculty of Engineering Department of Electrical and Computer Engineering Nagano Japan

ISBN: (纸本)9798350315042

In this work, a prototype system has been designed with a 0.18-μm CMOS technology to capture perspiration rate in daily life. To calculate an amount of perspiration, a temperature sensor is necessary concurrently with a relative humidity sensing. The designed temperature sensor consists of 8-bit binary digital-to-analog converter and an analog front-end circuit for thermistors. The designed circuits for temperature and humidity sensors have successfully verified. © 2023 IEEE.

关键词： Humidity sensors

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN) 7

Development of Detection Lung Disease Stand Alone System Bas...

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7th International Conference of computer and Informatics engineering, IC2IE 2024

作者： Liewarnata, Edgar Caesar Mariana, Yosica Tan, Sofyan Liawatimena, Suryadiputra Astuti, Winda Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Aso School of Engineering Product Design Program Industrial Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Automotive and Robotics Program Computer Engineering Department Binus Aso School of Engineering Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331505530

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification. © 2024 IEEE.

关键词： Lung cancer

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Restoration of Time-Varying Graph Signals using Deep Algorithm Unrolling 48

Restoration of Time-Varying Graph Signals using Deep Algorit...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Kojima, Hayate Noguchi, Hikari Yamada, Koki Tanaka, Yuichi Tokyo University of Agriculture and Technology Department of Electrical Engineering and Computer Science Japan Tokyo University of Science Department of Electrical Engineering Japan Osaka University Graduate School of Engineering Japan

ISBN: (纸本)9781728163277

In this paper, we propose a restoration method of time-varying graph signals, i.e., signals on a graph whose signal values change over time, using deep algorithm unrolling. Deep algorithm unrolling is a method that learns parameters in an iterative optimization algorithm with deep learning techniques. It is expected to improve convergence speed and accuracy while the iterative steps are still interpretable. In the proposed method, the minimization problem is formulated so that the time-varying graph signal is smooth both in time and spatial domains. The internal parameters, i.e., time domain FIR filters and regularization parameters, are learned from training data. Experimental results using synthetic data and real sea surface temperature data show that the proposed method improves signal reconstruction accuracy compared to several existing time-varying graph signal re- construction methods. © 2023 IEEE.

关键词： deep algorithm unrolling graph signal processing Time-varying graph signals

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Sentiment Analysis in Indonesian Trading using Lexicon-based and Support Vector Machine

Sentiment Analysis in Indonesian Trading using Lexicon-based...

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2023 International Conference on computer science, Information Technology and engineering, ICCoSITE 2023

作者： Oetama, Raymond Sunardi Yanfi, Yanfi Ikhsan Assiddiq Up, Masagus M. Muhamad Isa, Sani Universitas Multimedia Nusantara Information System DepartmentFaculty of Engineering and Informatics Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350320954

Many individuals now trade online utilizing trading software in the digital world. Binomo is one of Indonesia's most popular trading platforms. This is because some influencers made several promises to Binomo customers. Since many customers were deceived, this case became quite popular. This study was executed to see how Indonesians felt about the Binomo application after the case went viral. The solution taken was in the form of sentiment analysis because there had been no previous research on sentiment analysis that discussed the Binomo case. The data was scanned using Netlytic tools, a cloud-based text and social network analyzer capable of identifying any talks on social media sites such as Twitter. The sentiment analysis of Binomo trading tweets by using the Multi-Perspective Question Answering lexicon utilized the KNIME tool. But unfortunately, the accuracy of sentiment analysis results is low. Furthermore, the Support Vector Machine technique is also being conducted. The Term Frequency-Inverse Document Frequency method is applied to perform feature extraction whilst the chi-square approach is utilized to identify features that are thought to be useful for inclusion in the classification process and to exclude features that are irrelevant to the target class. The obtained accuracy is 86%. The study proposes that words from the algorithm's outputs can be utilized to improve the quality of sentiment analysis using the lexicon. As an outcome of the algorithm, positive and negative terms are added to the lexicon, increasing the accuracy of sentiment analysis using the new vocabulary from 58.984% to 71.146%. © 2023 IEEE.

关键词： Support vector machines

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Frequency Bandwidth Reduction of High-Frequency Intra-Body Propagation Characteristics Used for Attacker's Touch Detection in Fingerprint Authentication 12

Frequency Bandwidth Reduction of High-Frequency Intra-Body P...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Tomura, Shunichi Yamada, Koki Yoshida, Takahiro Tokyo University of Science Graduate School of Engineering Department of Electrical Engineering Tokyo Japan Tokyo University of Agriculture and Technology Department of Electrical Engineering and Computer Science Tokyo Japan Tokyo University of Science Faculty of Engineering Department of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798350340181

In previous studies, we have proposed the attacker's touch detection method in fingerprint authentication using high-frequency intra-body propagation characteristics to detect attacks in that an attacker holds the user's finger/wrist and presses the user's finger to a fingerprint scanner. However, the previous method used a wide range of frequency bands from 300 kHz to 10 MHz, and this caused problems in the circuit scale, cost, and size of the device in development for practical use. Therefore, we searched effective frequency bands and applied K-nearest neighbor with data augmentation in this study. As results, we achieved a 99.1 % touch detection rate with a single frequency and a 99.9 % touch detection rate with a combination of two frequencies. We achieved a significant reduction in the frequency bandwidth of the propagation characteristics. © 2023 IEEE.

关键词： Bandwidth

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The Effect of Viewpoint Change Strategies on Multi-View Video and Audio Transmission QoE Over ICN/CCN 38

The Effect of Viewpoint Change Strategies on Multi-View Vide...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Nunome, Toshiro Takada, Yoshiyuki Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350302196

In this paper, we exploit caches on intermediate nodes for QoE enhancement of multi-view video and audio transmission over ICN/CCN by controlling the content request start timing of consumers. We assume the selected single viewpoint transmission method;a consumer receives video and audio streams of a requested viewpoint. We perform a simple experiment with two consumers. When the consumers play video and audio with the time difference, we assess the effect of cached content by the former consumer's request on the output quality of the latter consumer. We deal with two types of viewpoint change strategies for the former consumer, which affect the efficiency of cache utilization. From the assessment results, we see that cache utilization has an important factor in enhancing QoE. © 2023 IEEE.

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QoE Assessment of Audiovisual Streaming over a Full-Duplex Wireless LAN with Interference Traffic

QoE Assessment of Audiovisual Streaming over a Full-Duplex W...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Nunome, Toshiro Deguchi, Daiki Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350324174

This paper evaluates the QoE of video and audio transmission over a full-duplex wireless LAN with interference traffic through a computer simulation and a subjective experiment. We employ a simulation environment with a pair of audiovisual transmission and reception terminals and a pair of interference traffic transmission and reception ones. We investigate the effect of the transmission rate of interference traffic and communication distance in a wireless channel on the output quality of the video and audio stream at the reception terminal. We perform a subjective experiment with the output timing of video and audio obtained by the simulation. © 2023 IEEE.

关键词： Wireless local area networks (WLAN)

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