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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Rissa Rahmania Yaya Heryadi Lukas Lukas Wayan Suparta Ilvico Sonata Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Group (CEG) Faculty of Engineering Universitas Katolik Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

The existence of fine-grained image classification supporting smart retail provides effectiveness in recognizing products with high similarity. However, the generic classification method performs poorly in identifying products from a subordinate category. This paper aims to identify augmentation techniques to leverage the Vision Transformer (ViT) model to classify the fine-grained grocery product, which involves embedding patches and transformer encoders to extract the main features. First, we develop a fine-grained image dataset with ColorJitter, CutOut, and combining both augmentations. Secondly, we perform experiments and analysis of ViT size, embedded patch size and image size in the patch embedding process. Lastly, the ViT model are evaluated according to the image sizes 224, 384, and 512 in accuracy, loss, and confusion matrix. The highest accuracy was obtained at 0.9922. The ColorJitter and CutOut improved the confusion matrix in ViT-B/16 and ViT-L/16 with an image size of 384 and 512. The results show that both augmentations in the ViT model are able to distinguish fine-grained grocery products.

关键词： Surveys computer vision Accuracy Image recognition Transformers Feature extraction Data augmentation Artificial intelligence Image classification

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A Dynamic Model for Pauses in the Synthesized Speech of Mathematical Expressions in MathML 14

A Dynamic Model for Pauses in the Synthesized Speech of Math...

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14th International Conference on Education Technology and computers, ICETC 2022

作者： Souza, Adriana Freitas, Diamantino Bahia Federal Institute of Education Science and Technology Porto Seguro Bahia Brazil Doctoral Program in Digital Media Faculty of Engineering Faculty of Engineering of University of Porto Porto Portugal Department of Electrical and Computer Engineering Faculty of Engineering of University of Porto Porto Portugal

ISBN: (纸本)9781450397766

Voice synthesizers still present several challenges in the speech of mathematical content, as spoken mathematics has quite peculiar rules. In the synthesized speech, pauses help blind and visually impaired students identify the limits of mathematical operators and subexpressions. However, most studies on pauses define them uniformly or use simple punctuation marks to force the synthesizer to introduce pauses in certain parts of the expression. Speech is a dynamic process and pauses in expressions also need to be dynamic to make the synthetic speech of expressions more natural, as this can help in memorizing this type of content. This work proposed a dynamic model of pauses for mathematical expressions. Collected math expressions spoken by teachers were used to create the model. These expressions were useful for identifying patterns and creating a linear regression model. Blind and visually impaired students evaluated the model. Some improvements were observed when we compared the synthesized mathematical expressions with the model and Audiomath, the parameter tool used in this study. © 2022 ACM.

关键词： Dynamic models

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Lightweight Image Inpainting By Stripe Window Transformer With Joint Attention To CNN

Lightweight Image Inpainting By Stripe Window Transformer Wi...

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IEEE Workshop on Machine Learning for Signal Processing

作者： Bo-Wei Chen Tsung-Jung Liu Kuan-Hsien Liu Department of Electrical Engineering and Graduate Institute of Communication Engineering National Chung Hsing University Taiwan Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taiwan

Image inpainting is an important task in computer vision. As admirable methods are presented, the inpainted image is getting closer to reality. However, the result is still not good enough in the reconstructed texture and structure based on human vision. Although recent advances in computer hardware have enabled the development of larger and more complex models, there is still a need for lightweight models that can be used by individuals and small-sized institutions. Therefore, we propose a lightweight model that combines a specialized transformer with a traditional convolutional neural network (CNN). Furthermore, we have noticed most researchers only consider three primary colors (RGB) in inpainted images, but we think this is not enough. So we propose a new loss function to intensify color details. Extensive experiments on commonly seen datasets (Places2 and CelebA) validate the efficacy of our proposed model compared with other state-of-the-art methods. The source code and pretrained models are available at https://***/RzD11n.

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Image Inpainting by Mscswin Transformer Adversarial Autoencoder

Image Inpainting by Mscswin Transformer Adversarial Autoenco...

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IEEE International Conference on Image Processing

Image inpainting has been researched for years. From deeper and larger models to models that focus on global information, all of them aim to obtain results closer to reality. In this paper, we combine the stripe window and line-by-line feature shift to modify the Vision Transformer (ViT) to reduce the computation cost and obtain global information from the oblique attention. In addition, we design a new loss function to enhance the texture and colors for inpainting. At last, to validate the efficacy of our proposed model, we conduct extensive experiments on commonly seen datasets (Places2 and CelebA) compared with other state-of-the-art methods. The source code and pretrained models are available at https: //***/bobo0303/MSCS-Net.

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Citizen science "Thundercloud Project" – multi-point radiation measurements of gamma-ray glows from accelerated electrons in thunderstorms 38

Citizen science "Thundercloud Project" – multi-point radiat...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Enoto, Teruaki Tsurumi, Miwa Ikkatai, Yuko Wu, Ting Wang, Daohong Shinoda, Taro Nakazawa, Kazuhiro Tsuji, Naoki Diniz, Gabriel Sousa Kataoka, Jun Kamogawa, Masashi Takagaki, Toru Miyake, Shoko Morimoto, Takeshi Nakamura, Yoshitaka Tsuchiya, Harufumi Department of Physics Graduate School of Science Kyoto University Kyoto Japan Extreme Natural Phenomena RIKEN Hakubi Research Team Cluster of Pioneering Research RIKEN Saitama Japan Graduate School of Science and Engineering Aoyama Gakuin University Kanagawa Japan Institute of Human and Social Sciences Kanazawa University Ishikawa Japan Department of Electrical Electronic and Computer Engineering Gifu University Gifu Japan Institute for Space-Earth Environmental Research Nagoya University Aichi Japan Kobayashi-Maskawa Institute for the Origin of Particles and the Universe Nagoya University Aichi Japan Faculty of Science and Engineering Waseda University Tokyo Japan Global Center for Asian and Regional Research University of Shizuoka Shizuoka Japan TAC Inc. Kyoto Japan Ibaraki College Ibaraki Japan Faculty of Science and Engineering Kindai University Osaka Japan Department of Electrical Engineering Kobe City College of Technology Hyogo Japan Nuclear Science and Engineering Center Japan Atomic Energy Agency Ibaraki Japan

It has been a long-standing question whether cosmic rays promote the triggering of lightning and how cosmic-ray air showers interact with the electric field of thunderclouds. The strong electric field in the thunderclouds accelerates electrons to the relativistic regime, of which seed electrons are thought to be supplied from cosmic-ray air shower. Such relativistic electrons emit bremsstrahlung photons in gamma rays, which have been detected by on-ground measurements called gamma-ray glows. Low-altitude winter thunderstorm in Japan provides an ideal environment for observations of gamma-ray glows. We newly launched the citizen science "Thundercloud Project" to construct a multi-point radiation mapping campaign for glows from winter thunderstorms around Kanazawa, Japan. We developed a new handy radiation monitor and shipped about 60 detectors to citizen supporters. The radiation data are stored in the microSD cards in the detectors, and a part of them is remotely sent to the web server so that researchers and supporters can watch the real-time data. In addition, an automatic alert is sent to public Twitter from the server when a glow is detected. The purpose of this project is (1) to characterize the methodological condition of electron acceleration, (2) to investigate whether accelerated relativistic electrons can enhance the chance of the initiation of lightning discharges, and (3) to find a new way of the citizen science to join in the cutting edge science in the physics field. Here we report this growing citizen science project and examples of successful gamma-ray glow observations. Our first scientific result from this citizen science project was published in Tsurumi et al., GRL 2023 [1], where we reported lightning discharges started in or near the electron acceleration site of a gamma-ray glow. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Gamma rays

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Lightning flash started near the electron acceleration region in the thundercloud 38

Lightning flash started near the electron acceleration regio...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Tsurumi, Miwa Enoto, Teruaki Ikkatai, Yuko Wu, Ting Wang, Daohong Shinoda, Taro Nakazawa, Kazuhiro Tsuji, Noki Gabriel, Diniz Kaoataoka, Jun Iwashita, Ryoji Koshikawa, Nanase Kamogawa, Masashi Takagaki, Toru Miyake, Shoko Tomioka, Dai Morimoto, Takeshi Nakamura, Yoshitaka Tsuchiya, Harufumi Department of Physics Graduate School of Science Kyoto University Kyoto Japan Graduate School of Science and Engineering Aoyama Gakuin University Kanagawa Japan Extreme Natural Phenomena RIKEN Hakubi Research Team Cluster of Pioneering Research RIKEN Saitama Japan Institute of Human and Social Sciences Kanazawa University Ishikawa Japan Department of Electrical Electronic and Computer Engineering Gifu University Gifu Japan Institute for Space-Earth Environmental Research Nagoya University Aichi Japan Kobayashi-Maskawa Institute for the Origin of Particles and the Universe Nagoya University Aichi Japan Faculty of Science and Engineering Waseda University Tokyo Japan Global Center for Asian and Regional Research University of Shizuoka Shizuoka Japan TAC Inc. Kyoto Japan Ibaraki College Ibaraki Japan Faculty of Science and Engineering Kindai University Osaka Japan Department of Electrical Engineering Kobe City College of Technology Hyogo Japan Nuclear Science and Engineering Center Japan Atomic Energy Agency Ibaraki Japan

The interaction between cosmic rays and thunderclouds has attracted much attention in recent years. Cosmic rays have been considered as one possible cause of the trigger of lightning flashes: e.g., a possible correlation between the number of observed lightning and cosmic ray flux (e.g.,Themis G. Chronis, journal of Climate,2009). In thunderclouds, electric fields are thought to cause relativistic acceleration of electrons as an interaction with cosmic ray air shower and emit bremsstrahlung photons, known as gamma-ray glows. One unresolved is that such electron acceleration, and thus gamma-ray glows, may be related to initiating lightning flashes. To verify this hypothesis, we conducted winter thundercloud observations using mapping radiation measurements in Japan. At 04:06–04:08 JST on December 30, 2021, five radiation detectors recorded a gamma-ray glow, terminated with the lightning flash recorded by two lightning mapping systems (FALMA and DALMA). Our multi-location observation revealed that the gamma-ray glow region had a horizontal size of about 2 km×2.5 km. The XRAIN radar observation showed that the high reflectivity area, presumably corresponding to the electron acceleration region, reaches more than 2 km above the gamma-ray detected radiation detectors. The initiation of this lightning discharge started from 1.6 km altitude from the ground around the gamma-ray glow region [1]. This result indicates that the lightning flash began in the vicinity of the electric field region and a possible connection between the cosmic ray interaction with the electric fields in thundercloud and the triggering of the lightning flash. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Gamma rays

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Data Alignment Design for Robotic programming by Demonstration Based on IMU and Optical Tracker

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IEEE Transactions on Instrumentation and Measurement 2023年 72卷 1页

作者： Song, Kai-Tai Li, Bing-Yi Ou, Szu-Chen National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering College of Electrical and Computer Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Graduate Degree Program of Robotics Hsinchu300093 Taiwan

This study proposes a data alignment design for sensor fusion of an optical target (OT) and an inertial measurement unit (IMU) to track the trajectory of a handheld tool for robot programming by demonstration (PbD). A novel method is proposed for coordinate and temporal alignment between the OT and the IMU sensor to increase tracking accuracy. The IMU measurements are aligned with the corresponding angular velocities and accelerations derived from the OT to calibrate the IMU-OT relationship. Global and local optimizations are combined to reduce the computation time for the temporal alignment and coordinate calibration. Experimental results show that the proposed method provides improved calibration results with shorter calculation time compared with the two existing methods. The sensor fusion experiments verify the accuracy of trajectory tracking of 1.3 mm using the calibration result, an improvement from 1.4 mm of the data alignment using ruler measurement. Integrated PbD experiments using a 6-DOF manipulator were carried out to evaluate the proposed method. The manipulator imitated the hand motion of a bottle transfer task with a trajectory error of 0.66 mm. Practical robotic experiments demonstrate that the method is suitable for robot programming applications. © 1963-2012 IEEE.

关键词： Calibration

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The Impact of Different Modes of Augmented Reality Information in Assisted Aircraft Cable Assembly 1

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

作者： Ariansyah, Dedy Xi, Khaizuo Erkoyuncu, John Ahmet Pardamean, Bens Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta11480 Indonesia School of Aerospace Transport and Manufacturing Cranfield University BedfordMK43 0AL United Kingdom Centre of Digital Engineering and Manufacturing School of Aerospace Transport and Manufacturing Cranfield University BedfordMK43 0AL United Kingdom Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Aircraft avionics systems are complicated systems which involves high number of components and complex cable assembly procedure. To deal with this challenge, Augmented Reality (AR) has been proposed to be an effective method to improve assembly efficiency and to reduce error rates. In this paper, the authors developed AR-based guidance cable assembly and compare the impact of different modes of AR information. The results show that although AR outperformed the paper document assembly guidance, the design of AR information has distinct influence on the successful completion of the cables assembly process. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Augmented reality

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Hybrid Full-Bridge Phase-Shift and Half-Bridge LLC Resonant Converter Based on Dual Transformers

Hybrid Full-Bridge Phase-Shift and Half-Bridge LLC Resonant ...

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International Conference on Applied System Innovation (ICASI)

作者： Chih-Chiang Hua Ching-Chun Chuang Min-Rui Hong Jian-Min Wang Department of Electrical Engineering National Yunlin University of Science and Technology Douliou Taiwan R.O.C. Department of Electrical Engineering National Kaohaiung University of Science and Technology Kaohsiung City Taiwan Computer Science and Information Engineering National Formosa University Taiwan Graduate Institute of Vehicle Engineering National Formosa University Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

This paper proposes a hybrid full-bridge phase-shift and half-bridge LLC resonant converter based on dual transformers with different output voltages. In the proposed LLC resonant circuit, the power switches can achieve zero-voltage switching, which reduces power losses caused by traditional hard switching. Additionally, the converter continuously operates at the resonant frequency, enabling zero-current switching for the rectifier diodes and enhancing overall converter efficiency. The prototype circuit operates at an input voltage of 400V and fixed frequency with a constant duty ratio. By adjusting the phase shift between PWM square waves to change the output power, the proposed converter achieves a wide range of output voltages from 250V to 450V and a rated capacity of 1kW. The experimental results show that the proposed converter achieves a maximum conversion efficiency of 92.01% at an output voltage of 250V and a maximum conversion efficiency of 93.78% at an output voltage of 450V.

关键词： Legged locomotion Technological innovation Resonant frequency Rectifiers RLC circuits Switches Resonant converters

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Predicting Human Activity with LSTM Face Detection on Server Surveillance System

Predicting Human Activity with LSTM Face Detection on Server...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Alexander Nurenie Yaya Heryadi Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Indonesia

Surveillance server technology was growth with new technology, effective, extra new features, human friendly, and human deals with big amount data, can't view and collect the data in the short time, and took time to analyze, playback video/picture to determine machine, human, vehicle or environment issues or performance, Surveillance Server Systems now which has the ability to face recognition, face detection, human detection, motion detection, license plate recognition, The authors perform this study that still new this research has never been done before to determine the efficacy of the LSTM in predicting human behavior (Long Short Term Memory) Face Detection on Server surveillance system, by taking log view data with a total of 91501 Face detection data downloaded from 10/18/2022~11/9/2022, the data will be processed using Python programming and training so that it can be used to predict the future regarding human activities that vary utilizing time series prediction LSTM include the number of daily activities, the highest and lowest numbers of days, and the maximum and minimum numbers of days. from the results of this study it was found to help to find out the days with the lowest number of humans and the days with the highest number of human activities, so that the owner can predict with sequence of the data the service would be provided when human activity is high in certain area or certain day, it can also can find out the maximum or minimum amount human counting day by day, and compare able some different date and location, the author will continue to do more in-depth research the others data related with prediction with deep learning server surveillance machine system interaction with human, vehicle behavior in the future studies.

关键词： Training Surveillance Time series analysis programming Behavioral sciences Servers Face detection

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