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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Binh Nguyen Michael Nigro Alice Rueda Venkat Bhat Sri Krishnan Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan Univerity Toronto ON Interventional Psychiatry Program St. Michael’s Hospital Toronto

Digital phenotyping (DP) is a multidisciplinary field of science that quantifies the individual level phenotype through active and passive data. Although DP is a multidisciplinary field, there lacks a technical and a systematic approach to representing DP. This work proposes the development of digital phenotype profile (DPP) to represent a user’s physical and behavioural health baseline through systematic investigations with an emphasis on robustness and explainability. To achieve this, a Statistical, Information Theory, and Data-driven (SID) pipeline will develop the foundation of the DPP. SID evaluates the non-linearity of the signal to offer inference for domain-specific feature extraction, evaluates the information theory to rank the DPP parameters, and imputes missing data for robust analysis, respectively. SID was applied to a 24-hr Multi-Level dataset and was able to represent individual DPPs. The respective DPPs were visualized and clusters of awake and asleep were used for individual specific modelling.

关键词： Systematics Pipelines Data visualization Signal processing Feature extraction Robustness Acoustics

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On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection

arXiv

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arXiv 2023年

作者： Park, Sangha Mok, Jisoo Jung, Dahuin Lee, Saehyung Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

Successful detection of Out-of-Distribution (OoD) data is becoming increasingly important to ensure safe deployment of neural networks. One of the main challenges in OoD detection is that neural networks output overconfident predictions on OoD data, make it difficult to determine OoD-ness of data solely based on their predictions. Outlier exposure addresses this issue by introducing an additional loss that encourages low-confidence predictions on OoD data during training. While outlier exposure has shown promising potential in improving OoD detection performance, all previous studies on outlier exposure have been limited to utilizing visual outliers. Drawing inspiration from the recent advancements in vision-language pre-training, this paper venture out to the uncharted territory of textual outlier exposure. First, we uncover the benefits of using textual outliers by replacing real or virtual outliers in the image-domain with textual equivalents. Then, we propose various ways of generating preferable textual outliers. Our extensive experiments demonstrate that generated textual outliers achieve competitive performance on large-scale OoD and hard OoD benchmarks. Furthermore, we conduct empirical analyses of textual outliers to provide primary criteria for designing advantageous textual outliers: near-distribution, descriptiveness, and inclusion of visual semantics. © 2023, CC BY-NC-SA.

关键词： Forecasting

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An autonomous robotic system for collecting garbage over small water bodies

An autonomous robotic system for collecting garbage over sma...

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作者： Syed Nouman Hasany Saniya Shah Zaidi Syed Ahmad Sohail Muhammad Farhan Electrical Engineering Program Habib University Computer Science Program Habib University Electrical and Computer Engineering Program Habib University

Water pollution is a grave problem requiring utmost attention as it directly affects marine *** freshwater ecosystem,for example,lakes and ponds,a major chunk of water garbage is plastic floating on the surface of water which is labor intensive to collect *** this paper,we present a novel autonomous robotic system capable of navigating small water bodies and is equipped with computer vision that helps it to detect the *** detection is followed by focusing on an area of interest to determine whether the garbage lies in the scope of robot for ***,if WiFi communication is available,the robot has the provision of tracking the detected garbage to determine its *** design of garbage collection unit of the robot ensures the garbage does not move outward once *** robot is tested in two different pools and with plastic bottles as main type of *** results manifest the high degree of control of its locomotion as well as of detection and collection of the *** deep neural network based detector onboard the robot can be retrained after self-collection of appropriate data to detect other types of garbage as well.

关键词： An autonomous robotic system for collecting garbage over small water bodies

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AI-driven Maintenance Tool for Synchronous Power Generator Temperature Monitoring Using Fiber Bragg Gratings

AI-driven Maintenance Tool for Synchronous Power Generator T...

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SBMO/IEEE MTT-S International Conference on Microwave and Optoelectronics (IMOC)

作者： Uilian José Dreyer Erlon V. da Silva Wilian Oliveira Paulo H. R. Mazzo Kleiton de M. Sousa André Biffe Di Renzo Cicero Martelli Jean Carlos Cardozo da Silva Graduate Program in Energy Systems (PPGSE) ENGlE Brasil Energia Universidade Tecnologica Federal do Parana-UTFPR Curitiba Parana Brazil Graduate Program in Electrical and Computer Engineering (CPGEI)

The carbon brushes and slip rings of a hydrogen-erator are the main components guiding the excitation current from the bridge to the rotor windings. The brushes' temperature are crucial to infer their operational condition and, the generator status. This work presents the temperature measurement of six Fiber Bragg Gratings (FBG) sensors installed in a 370 MVA electric generator brushes. The results show the sensors' capacity to monitor the brushes' temperature in accordance with the current flowing through them. Together with the sensors, an Artificial Intelligence (AI) technique was applied to the measured temperature to detect anomalous events regarding the current supplied to the rotor windings. The optical sensors combined with the AI could detect five events of abnormal current behaviour. One is presented in detail in this paper. This sensing system can be further applied to online fault detection using the temperature measured by the FBGs as a brush condition indicator and a generator operation and maintenance tool.

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Neural Diffeomorphic Non-uniform B-spline Flows

arXiv

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arXiv 2023年

作者： Hong, Seongmin Chun, Se Young Department of Electrical and Computer Engineering Seoul National University Korea Republic of INMC Interdisciplinary Program in AI Seoul National University Korea Republic of

Normalizing flows have been successfully modeling a complex probability distribution as an invertible transformation of a simple base distribution. However, there are often applications that require more than invertibility. For instance, the computation of energies and forces in physics requires the second derivatives of the transformation to be well-defined and continuous. Smooth normalizing flows employ infinitely differentiable transformation, but with the price of slow non-analytic inverse transforms. In this work, we propose diffeomorphic non-uniform B-spline flows that are at least twice continuously differentiable while bi-Lipschitz continuous, enabling efficient parametrization while retaining analytic inverse transforms based on a sufficient condition for diffeomorphism. Firstly, we investigate the sufficient condition for Ck−2-diffeomorphic non-uniform kth-order B-spline transformations. Then, we derive an analytic inverse transformation of the non-uniform cubic B-spline transformation for neural diffeomorphic non-uniform B-spline flows. Lastly, we performed experiments on solving the force matching problem in Boltzmann generators, demonstrating that our C2-diffeomorphic non-uniform B-spline flows yielded solutions better than previous spline flows and faster than smooth normalizing flows. Our source code is publicly available at https://***/smhongok/Non-uniform-B-spline-Flow. © 2023, CC BY-NC-ND.

关键词： Interpolation

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Automatic LPI Radar Waveform Recognition Using Vision Transformer

Automatic LPI Radar Waveform Recognition Using Vision Transf...

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IEEE International Conference on Radar

作者： Junseob Kim Sunghwan Cho Sunil Hwang Yeongyoon Choi Department of Electrical Engineering Korea Military Academy Republic of Korea Maneuver System Coordination and Contract Team Defense Acquisition Program Administration Republic of Korea Department of Electrical Engineering and Computer Science GIST Republic of Korea

This paper investigates the classification of low probability of intercept (LPI) radar signals by exploiting the intrinsic advantages of the Vision Transformer (ViT). Due to the characteristics of LPI radar signals, such as intrapulse modulation, wide frequency bands, and low transmission power, these signals are challenging to be detected and classified using traditional analytic methods. This has led to the adoption of various deep learning techniques to overcome these limitations. On the one hand, the ViT, originally developed for natural language processing, has demonstrated outstanding performance in computer vision by replacing the structure of the convolutional neural network (CNN) with the transformer, specifically leveraging self-attention. Therefore, this paper explores a method based on the ViT technique for classifying LPI signal images. The simulation results show that the proposed ViT method outperforms the traditional CNN method by 12.8% at −10dB SNR.

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Efficient Diffusion-Driven Corruption Editor for Test-Time Adaptation

arXiv

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arXiv 2024年

作者： Oh, Yeongtak Lee, Jonghyun Choi, Jooyoung Jung, Dahuin Hwang, Uiwon Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of School of Computer Science and Engineering Soongsil University Korea Republic of Division of Digital Healthcare Yonsei University Korea Republic of

Test-time adaptation (TTA) addresses the unforeseen distribution shifts occurring during test time. In TTA, performance, memory consumption, and time consumption are crucial considerations. A recent diffusion-based TTA approach for restoring corrupted images involves image-level updates. However, using pixel space diffusion significantly increases resource requirements compared to conventional model updating TTA approaches, revealing limitations as a TTA method. To address this, we propose a novel TTA method that leverages an image editing model based on a latent diffusion model (LDM) and fine-tunes it using our newly introduced corruption modeling scheme. This scheme enhances the robustness of the diffusion model against distribution shifts by creating (clean, corrupted) image pairs and fine-tuning the model to edit corrupted images into clean ones. Moreover, we introduce a distilled variant to accelerate the model for corruption editing using only 4 network function evaluations (NFEs). We extensively validated our method across various architectures and datasets including image and video domains. Our model achieves the best performance with a 100 times faster runtime than that of a diffusion-based baseline. Furthermore, it is three times faster than the previous model updating TTA method that utilizes data augmentation, making an image-level updating approach more feasible. ∗ © 2024, CC BY.

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Single-Phase Transformerless UPS with Interleaved Boost Converters for Battery Discharging

Single-Phase Transformerless UPS with Interleaved Boost Conv...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Alan R. A. Pinto Filipe A. C. Bahia Reuben P. R. Souza José R. Pinheiro Fabiano F. Costa Post-Graduate Program in Electrical Engineering PPGEE Federal University of Bahia Salvador Brazil Dept. of Electrical and Computer Engineering DEEC Federal University of Bahia Salvador Brazil Dept. of Electrical Engineering DEE Federal University of Campina Grande Campina Grande Brazil

This paper proposes a reconfiguration for a single-phase, double conversion uninterruptible power supply (UPS). With the addition of two static switches to the original circuit, the UPS mitigates the ripple in the current, through battery discharge performed by two legs. Other than these switches, the circuit topology is preserved. The preliminary results show a satisfactory level of ripples for the inductor current and suitable power quality for the output voltage.

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Digital Technology in Health Education Trend Mapping through Bibliometrics Analysis 4

Digital Technology in Health Education Trend Mapping through...

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4th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Maulana, Fairuz Iqbal Lestari, Dian Widartha, Vandha Pradwiyasma Haidar, Nirwana Dirgantara, Wahyu School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Airlangga University Faculty of Medicine Surabaya60132 Indonesia Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia University of Madura Informatics Engineering Study Program Pamekasan Indonesia University of Merdeka Malang Department of Electrical Engineering Malang Indonesia

ISBN: (纸本)9781665473279

This study examines the mapping of research data on digital technology in the field of health education using bibliometric analysis method. Data was collected by identifying keywords in the Scopus database and sorting them out to sort the studies from the last 10 years (2012-2021). Through this step, a total of 1482 documents were obtained (articles, journals, proceedings, books, and others). The data is then processed using the VOSViewer instrument to obtain a visualization of the mapping analysis. This study also analyzes the network types of authors and co-authors through the VOSViewer instrument. The result of this study indicates that the most document types published within ten years are Articles (66.5%), Review (22.9%), Conference Paper (4.2%), and others. The most studied subjects are Medicine (55.7%), Nursing (9.0%), Health Professions (8.2%), Social Sciences (7.8%), engineering (3.9%), computer Science (2.6%), Environmental Science (2.6%), Biochemistry-Genetics and Molecular Biology (2.2%), Psychology (1.6%), and Dentistry (1.3%). This study offers a written communication process and the nature and direction of developing descriptive means of counting and analyzing the various phases of communication as well as recognizing the authorship and direction of its symptoms in documents on the subject of digital technology in the health sector. © 2022 IEEE.

关键词： Mapping

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A Dual-channel Converter with a Positive Output and a Negative Voltage Output

A Dual-channel Converter with a Positive Output and a Negati...

引用

International Symposium on computer, Consumer and Control (IS3C)

作者： Yau Yeu-Torng Luu Thanh-Phu Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan Department of Electrical Engineering National Chin-Yi University of Technology Taichung Taiwan

In this paper, a dual-channel converter with a positive output and negative voltage output is proposed. It integrates a positive voltage output converter and a negative voltage output converter, and shares the same switches. The number of active components can be reduced. In addition, the circuit can achieve dual output voltage control with a single controller and PWM drive signal by appropriately designing the ratio of the number of windings of the coupling inductor. A regulated positive voltage output and negative voltage output can be achieved.

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