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IEEE International Conference on Orange Technologies (ICOT)

作者： An-Chao Tsai Yu-Min Hsu Jhing-Fa Wang International Master Program of Information Technology and Application National Pingtung University Taiwan Department of Electrical Engineering National Cheng-Kung University Tainan Taiwan

ISBN: (数字)9798331523602

ISBN: (纸本)9798331523619

In recent years, advancements in training methods using large-scale text-image datasets and the development of diffusion models have significantly improved the quality and efficiency of image generation from text prompts. Despite these strides, text-to-image generation models still face challenges in producing realistic images that accurately reflect the specified details in the prompts. A common issue with diffusion-based models is their difficulty in generating the precise number of objects described in the text. For instance, a prompt like "six tomatoes in a basket" may often result in an image with an incorrect number of tomatoes. To address this problem, this paper proposes an algorithm designed to enhance the accuracy of object quantity in generated images. The algorithm employs an object counting network to assess the number of objects in a given image and calculates the error between this predicted count and the expected count. This error gradient is then used to guide the predictions of the diffusion model, improving its ability to generate the specified number of objects accurately.

关键词： Training Adaptation models Accuracy Image synthesis Text to image Diffusion models Prediction algorithms Social implications of technology Faces

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Precision Rice Vending Machine by Using Multiple Load Cell and IoT Based

Precision Rice Vending Machine by Using Multiple Load Cell a...

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Computer Science, Information technology and engineering (ICCoSITE), International Conference on

作者： Herman Yuliandoko Farisqi Panduardi Nuraini Lusi Sapto Wibowo Information Technology Program Study Politeknik Negeri Banyuwangi Banyuwangi Indonesia Mechanical Engineering Program Study Politeknik Negeri Banyuwangi Banyuwangi Indonesia Electrical Engineering Program Study Politeknik Negeri Malang Malang Indonesia

Indonesia has the world's largest Muslim population, so the potential for Zakat, Infaq, and Sadaqah (ZIS) funding is enormous. The existence of ZIS in the current Covid-19 pandemic is of extreme importance, as issues such as economic crisis, social inequality, and the rise of dhuafa (poor) are becoming more and more visible. However, in the presence of coronavirus, ZIS has become more challenging to manage and distribute. Bans on gatherings, distancing rules, and other restrictions to prevent the spread of the coronavirus make ZIS more challenging to manage. Therefore, we need innovations to build bridges between people in need and supporters. The Internet of Things (IoT) is one system that can bridge this. In this system, IoT enables machine-to-machine communication and reduces human interaction. This research uses IoT to support Rice Vending Machine with high accuracy. The accuracy is achieved using five load cells and a good rice way-out valve mechanism. In previous machines using a single load cell or open the valve according to a certain time. Based on its test results analysis and MAPE values, we found the machine's accuracy facing obtained very well, and the website monitoring was also very effective. This research provides innovation in ZIS management and dramatically benefits society.

关键词： COVID-19 Bridges Technological innovation Machine-to-machine communications Pandemics Sociology Valves

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Towards the Improvement of the Cognitive Process of the Synthesized Speech of Mathematical Expression in MathML: An Eye-Tracking 2

Towards the Improvement of the Cognitive Process of the Synt...

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2nd International Conference on Interactive Media, Smart Systems and Emerging Technologies, IMET 2022

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

ISBN: (数字)9781665470162

ISBN: (纸本)9781665470162

Being one essential part of the solutions we are developing to provide accessibility for blind persons, synthesized speech of mathematical content, although having evolved in naturalness in recent years, still keeps a characteristic of generating very long outputs, which makes it difficult for a person who uses a screen reader to memorize. Eye-gaze tracking has been useful for studying cognitive processes and student's effort in performing tasks therefore it seems attractive as a means to understand how people analyze, process, and break down extensive math expressions into smaller ones. This understanding can help to build a similar model of auditory rendering of MathML capable of avoiding cognitive overload. Therefore, we carried out an experiment to do a gaze-based analysis of reading and memorizing mathematical expressions. Our sample consisted of fourteen participants, and seven mathematical expressions were used in the experiment. The results showed that the computed complexity of the expressions and the average duration of eye-gaze fixations have a strong and significant relationship. Therefore, we conclude that the complexity variable must always be considered in the speech synthesis process of mathematical expressions. However, when considering why participants requested the repetition of an expression with not larger complexity during the memorization process, a tentative interpretation based on the number of MathML tree nodes and the computed complexity of the expressions was not enough to explain it, indicating that other factors need to be investigated. Although some answers to the research questions were not yet conclusive, we consider this research relevant because it points to directions for the work in order to minimize the cognitive processing and mental load of the synthesized speech rendering of mathematical expressions. © 2022 IEEE.

关键词： Eye tracking

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On the Impact of Knowledge Distillation for Model Interpretability 40

On the Impact of Knowledge Distillation for Model Interpreta...

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40th International Conference on Machine Learning, ICML 2023

作者： Han, Hyeongrok Siwon, Kim Choi, Hyun-Soo Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul Korea Republic of ZIOVISION Inc. Chuncheon Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Korea Republic of

Several recent studies have elucidated why knowledge distillation (KD) improves model performance. However, few have researched the other advantages of KD in addition to its improving model performance. In this study, we have attempted to show that KD enhances the interpretability as well as the accuracy of models. We measured the number of concept detectors identified in network dissection for a quantitative comparison of model interpretability. We attributed the improvement in interpretability to the class-similarity information transferred from the teacher to student models. First, we confirmed the transfer of class-similarity information from the teacher to student model via logit distillation. Then, we analyzed how class-similarity information affects model interpretability in terms of its presence or absence and degree of similarity information. We conducted various quantitative and qualitative experiments and examined the results on different datasets, different KD methods, and according to different measures of interpretability. Our research showed that KD models by large models could be used more reliably in various fields. The code is available at https://***/Rok07/KD_***. © 2023 Proceedings of Machine Learning Research. All rights reserved.

关键词： Distillation

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Evaluating Conveyor Belt Health With Signal Processing Applied to Inertial Sensing

Evaluating Conveyor Belt Health With Signal Processing Appli...

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2023 Symposium on Internet of Things, SIoT 2023

作者： Matos, Saulo Neves Coletti, Otavio Ferracioli Filho, Fernando Ugucioni De Carvalho, Ricardo C. C. L. Pinto, Thomas V. B. De Barros, Luiz G. D. Ranieri, Caetano Mazzoni Lopes, Bruno Eduardo Ueyama, Jo Pessin, Gustavo Institute of Mathematics and Computer Science University of Sao Paulo Brazil Sao Carlos School of Engineering University of Sao Paulo Brazil Vale Institute of Technology Ouro Preto Brazil Universidade Federal of Minas Gerais Graduate Program in Electrical Engineering MG Belo Horizonte Brazil Vale -SA Vitoria Brazil

ISBN: (纸本)9798350329438

Conveyor belts are commonly used in the mining industry for efficient material transport. However, they are prone to failures such as idler anomalies, belt tears, and misalignment. Current monitoring systems only evaluate the conveyor or idle belt's condition at the installation point. This study proposes a method to detect faults in conveyor belts, specifically idler anomalies and belt deviation, using two IMUs installed at the lateral extremities of the belt to evaluate its health along its route. In a reduced-scale conveyor belt, we conducted experiments by collecting gyroscopes and accelerometer data in various scenarios, including normal conditions and anomaly situations. We modified the idlers' physical structure or changed the belt tracks to create these scenarios. We used similarity analysis techniques to compare the data collected and performed statistical hypothesis analysis to observe the influence of the anomaly scenarios on the gyroscope and accelerometer data. We used Dynamic Time Warping (DTW) for gyroscope data to compare ground truth with anomaly scenarios. For the acceleration data, we performed vibration analysis by converting the time domain data to the frequency using Fast Fourier Transform (FFT) and evaluating the difference in spectral density between the reference and anomaly data. Statistical hypothesis analysis revealed that anomaly scenar-ios influenced the gyroscope x-axis and z-axis more. According to the spectral density analysis of the accelerometer, it was revealed that belt misalignment on the y-axis may be detected. © 2023 IEEE.

关键词： Belt conveyors

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Exponential Curve-Based Control Strategy for Auxiliary Equipment Power Supply Systems in Railways

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Processes 2023年第4期11卷 1285-1285页

作者： Farooqui, Shoeb Azam Lin, Chang-Hua Lu, Shiue-Der Liu, Hwa-Dong Sarwar, Adil Huang, Liang-Yin Department of Electrical Engineering National Taiwan University of Science and Technology Taipei106 Taiwan Department of Electrical Engineering National Chin-Yi University of Technology Taichung411 Taiwan Undergraduate Program of Vehicle and Energy Engineering National Taiwan Normal University Taipei106 Taiwan Department of Electrical Engineering ZHCET Aligarh Muslim University Aligarh202002 India Graduate Institute of Manufacturing Technology National Taipei University of Technology Taipei106 Taiwan

An exponential curve-based (ECB) control strategy has been proposed in this paper. The proposed ECB control strategy is based on the growth and decay of charge in the series RC circuit and the harmonic elimination by detecting the Fourier expansion series of the auxiliary equipment power supply system’s (AEPSS) three-phase output voltage level. It can quickly adjust each duty cycle to the best value for driving the isolated three-phase inverter (ITPI) and produce a three-phase 380 VAC/60 Hz output. A comparison of the AEPSS output performance using the traditional voltage cancellation method (VCM) and the proposed ECB control strategy was performed. The hardware implementation of the system was performed on the prototype developed in the laboratory. These control strategies are tested under three conditions, i.e., (i) Vi = 550 VDC. (ii) Vi = 750 VDC. (iii) Vi = 800 VDC. The total harmonic distortion (THD) is 13.7%, 14.5%, and 14.9%, and the output voltage Vo is 372.3 VAC, 377.3 VAC, and 385.3 VAC using the traditional control strategy at three test conditions, respectively. However, the THD is 7.2%, 7.8%, and 8.0%, and the output voltage Vo is 382.2 VAC, 381.2 VAC, and 381.9 VAC using the proposed ECB control strategy under the test conditions. It is obvious from the hardware results that the output voltage harmonics and output voltage level for the proposed ECB control strategy are superior to the traditional VCM. The voltage produced from the AEPSS using the proposed ECB control strategy is more stable and has better quality. In addition, the filter size is also reduced. © 2023 by the authors.

关键词： Auxiliary equipment

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Smart Home Security System Using Face Recognition Based on IoT- CNN 2

Smart Home Security System Using Face Recognition Based on I...

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2nd International Conference on Information technology Research and Innovation, ICITRI 2023

作者： Febriantono, M. Aldiki Zuhair, Alvin Khaeruddin School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia University of Islam Blitar Electrical Engineering Department Blitar Indonesia University of Muhammadiyah Malang Diploma III Electronic Technology Vocational Study Program Malang Indonesia

ISBN: (纸本)9798350324945

Home security is a crucial aspect that requires careful attention, particularly when it comes to addressing theft concerns. Hence, implementing smart door technology equipped with facial recognition holds promising potential for enhancing home security. This study aims to develop a more secure and regulated home entry system by leveraging Internet of Things (IoT) technology and Machine Learning Computer Vision for facial recognition. The system integrates IoT devices, such as cameras and automatic doors, wherein facial image data is captured by the camera and processed using the Convolutional Neural Network (CNN) algorithm to identify individuals. Once an individual is recognized, the system grants access to the home through an automated door. By relying on facial features, the system effectively restricts unauthorized access and safeguards homes against theft risks. Therefore, the advancement of a safer and more controlled home entry system utilizing IoT technology and Machine Learning Computer Vision holds tremendous benefits for homeowners. © 2023 IEEE.

关键词： Face recognition

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Unveiling Multivariate EEG Features: A Novel Approach to Enhancing ADHD Diagnosis Through Visual and Auditory Attention Tests

Unveiling Multivariate EEG Features: A Novel Approach to Enh...

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2023 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2023

作者： Fan, Zuo-Cian Lin, Ro-Wei Tsai, Ching-Shu Chou, Wen-Jiun Li, Chia-Jung Huang, Zih-Jun Shih, Bin-Yu Wang, Liang-Jen Ko, Li-Wei Department of Biological Science & Technology Hsinchu300 Taiwan National Yang Ming Chiao Tung University International Ph.D. Program in Interdisciplinary Neuroscience Hsinchu300 Taiwan Kaohsiung Chang Gung Memorial Hospit Department of Child and Adolescent Psychiatry National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Department of Electronics and Electrical Engineering Hsinchu300 Taiwan

ISBN: (纸本)9798350305791

We sought to revolutionize the classification of Attention-Deficit/Hyperactivity Disorder (ADHD) by pioneering an innovative approach that seamlessly integrated auditory and visual tests with electroencephalogram (EEG) coherence analysis, forming the foundation for our Support Vector Machine (SVM) models. Our primary objective was to achieve precise differentiation between individuals with ADHD and those without, aiming to reshape the landscape of ADHD diagnosis and early intervention. We constructed an SVM model based on CATA coherence, incorporating a carefully selected set of 180 features, and another grounded in CPT coherence with 70 features. Astonishingly, our exploration uncovered that a model incorporating CATA's coherence and Power Spectral Density (PSD) as features achieved an astounding accuracy rate of 97.7%, using only half the number of features. This revelation hints at untapped potential for multivariate advancements in the realm of ADHD classification. The landscape of ADHD diagnosis and intervention is perpetually evolving, most notably with the FDA's approval of game therapy for ADHD. Leveraging the transformative power of our findings, we envision the development of user-friendly game therapies for in-home use, empowering both clinicians and parents alike. This marks a paradigm shift in the realm of ADHD intervention, offering objective, data-driven tools for the early management of ADHD. Gamified therapy not only enhances accessibility but also fosters engagement and compliance, all of which are pivotal in the long-term care of individuals with ADHD. In summary, our study represents a significant advancement in our comprehension and classification of ADHD. By fusing auditory and visual tests with EEG coherence analysis, fortified by state-of-the-art machine learning techniques, we have achieved an unprecedented level of accuracy in identifying individuals with ADHD. Our findings, aligned with the FDA-approved game therapy, offer a glimpse into a

关键词： Electroencephalography

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Computational Network-on-Chip as Convolution Engine

Computational Network-on-Chip as Convolution Engine

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technology, Systems and Applications (VLSI-TSA/VLSI-DAT), International VLSI Symposium on

作者： Zhonghai Lu Mingrui Liu Department of Electrical Engineering School of EECS KTH Royal Institute of Technology Stockholm Sweden Embedded Systems master program School of EECS KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9798350360349

ISBN: (纸本)9798350360356

Inspired by PiN, Processing in Network-on-Chip (NoC), we propose a computational NoC as a convolution engine for accelerating convolutional neural networks in hardware. In contrast to traditional compute architectures where computation and communication are conducted serially and in separation, our computational NoC enables in-transit computation, meaning that computation is performed while packets are transferred in the network. In the paper, we present the router architecture that supports the novel in-transit computation concept, and use a running example to detail the entire convolution process in the computational NoC. Finally, we show simulated performance results in comparison with traditional NoC-based convolution engine.

关键词： Convolution Simulation Computer architecture Network-on-chip Very large scale integration Hardware Pins

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A Novel Strategy for Fault Diagnosis in Photovoltaic Systems Using Multiple Regression Analysis and Support Vector Machines

SSRN

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SSRN 2024年

作者： Lu, Shiue-Der Liu, Hwa-Dong Wang, Meng-Hui Wu, Chia-Chun Department of Electrical Engineering National Chin-Yi University of Technology Taichung411 Taiwan Undergraduate Program of Vehicle and Energy Engineering National Taiwan Normal University Taipei106 Taiwan

This study focuses on analyzing common fault types in photovoltaic (PV) modules, employing fault diagnosis methods based on machine learning technology to enhance the accuracy and efficiency of diagnosing faults in solar power systems. Initially, we collected relevant data from the solar power system and used data analysis techniques to identify system faults, designing a human-machine monitoring interface for practical application. Furthermore, the experimental results proved that the system could accurately identify eight major types of faults, including solar panel output circuits, energy storage batteries, maximum power point tracking (MPPT) controllers, inverters, dust accumulation, loosening of mounting rack screws, damage to the mounting rack foundation, and deformation of the mounting rack structure. Particularly in the detection of dust accumulation, we developed a new method of estimating power generation from multiple regression analysis (MRA), which closely aligns the estimated power output with the actual power output, highlighting the significant impact of dust accumulation on the efficiency of solar power systems. Ultimately, by integrating voltmeters and support vector machines (SVM) into the solar PV array modules, we were able to quickly and accurately measure and locate short-circuit and open-circuit faults in bypass diodes. These innovative monitoring and fault diagnosis techniques can be effectively applied to the daily monitoring and fault diagnosis of solar power systems, significantly improving the system’s operational stability and efficiency. © 2024, The Authors. All rights reserved.

关键词： Failure analysis

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