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Conference on Lasers and Electro-Optics (CLEO)

作者： Diego Tami Douglas A. A. Ohlberg Jhonattan C. Ramirez Cássio Gonçalves Do Rego Gilberto Medeiros-Ribeiro Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Brazil Microscopy Center Universidade Federal de Minas Gerais Brazil Department of Electronic Engineering Universidade Federal de Minas Gerais Brazil Computer Science Department Universidade Federal de Minas Gerais Brazil

In this work, we analyzed numerically a multiscale nanosystem based on sMIM on TBG. Spontaneous formation of a water-meniscus by the approximation between the tip-sample concentrates the microwave fields, reaching res... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Microscopy Masers Lasers and electrooptics Laser modes Numerical models Impedance Electrooptical waveguides

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Erratum to "MiNuGAN: Dual segmentation of mitoses and nuclei using conditional GANs on multi-center breast H&E images" [Journal of Pathology Informatics Volume 13, 2022, 100002]

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Journal of pathology informatics 2025年 17卷 100426页

作者： Salar Razavi Fariba D Khameneh Hana Nouri Dimitrios Androutsos Susan J Done April Khademi Electrical Computer and Biomedical Engineering Ryerson University Toronto Ontario Canada. Laboratory Medicine Program University Health Network Toronto Ontario Canada.

[This corrects the article DOI: 10.1016/***.2022.100002.].

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Hot Carrier Injection (HCI) Reliability of Fabricated Y-gate HEMT with Various Top Length

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ECS Journal of Solid State Science and Technology 2023年第3期12卷 035001-035001页

作者： Chen, Yu-Lin Yeh, Wen-Kuan Chen, Ke-Horng Hsu, Heng-Tung Hsu, Chin-Tsai Godwin Raj, D. Chou, Hung-Ting Wu, Jui-Sheng Yu, Tien-Han Godfrey, D. Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan International College of Semiconductor Technology National Yang Ming Chiao Tung University Hsinchu Taiwan National Applied Research Laboratories Hsinchu Taiwan Dept of ECE Amal Jyothi College of Engineering Kerala India National Chung Shan Institute of Science and Technology Taoyuan Taiwan Deparment of Materials Science and Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Dept of Electronics and Communication Engineering Dayananda Sagar University Bengaluru India

Device degradation due to hot carrier injection (HCI) in different Y-gate HEMT devices is thoroughly analyzed. To further understand the HCI reliability of the Y-gate HEMT devices, the device is fabricated with AlGaN/GaN structure with different top lengths (Ltop). An HCI stress time of 6000 s was conducted on these devices, while V t stability in other stress time domains, leakage current, and transconductance degradation are also discussed. In this work, we have demonstrated that increasing the LTop length could avoid the virtual gate effect and disperse the influence of the electric field under HCI stress. Furthermore, the effects of trapping in various locations, such as in the bulk SiN or AlGaN/GaN interface has been discussed. These trapping effects caused by the HCI stress might be the source of the Vth shift. Overall, The large Y-gate HEMT showed the lowest degradation of DC characteristics after the long HCI stress test. © 2023 The Electrochemical Society ("ECS"). Published on behalf of ECS by IOP Publishing Limited.

关键词： High electron mobility transistors

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JointNET: A Deep Model for Predicting Active Sacroiliitis from Sacroiliac Joint Radiography

arXiv

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arXiv 2023年

作者： Turk, Sevcan Demirkaya, Ahmet Yigit Turali, M. Hepdurgun, Cenk Dar, Salman U.H. Karabulut, Ahmet K. Azizova, Aynur Orman, Mehmet Tamsel, Ipek Aydingoz, Ustun Argin, Mehmet Çukur, Tolga Department of Radiology University of Michigan MI United States Department of Radiology Ege University Izmir Turkey Department of Electrical and Computer Engineering Northeastern University MA United States Bilkent University Ankara Turkey Department of Electrical and Electronics Engineering Bilkent University Ankara Turkey Department of Radiology Hacettepe University Ankara Turkey EMOT Hospital Izmir Turkey Neuroscience Program Aysel Sabuncu Brain Research Center Bilkent University Ankara Turkey Department of Biostatistics Ege University Izmir Turkey

Purpose: To develop a deep learning model that predicts active inflammation from sacroiliac joint radiographs and to compare the success with radiologists. Materials and Methods: A total of 1,537 (augmented 1752) grade 0 SIJs of 768 patients were retrospectively analyzed. Gold-standard MRI exams showed active inflammation in 330 joints according to ASAS criteria. A convolutional neural network model (JointNET) was developed to detect MRI-based active inflammation labels solely based on radiographs. Two radiologists blindly evaluated the radiographs for comparison. Python, PyTorch, and SPSS were used for analyses. P © 2023, CC BY-NC-ND.

关键词： Deep learning

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computer-Aided Lung Auscultation Screening and Radiographic Evaluation of Pediatric Pneumonia

Computer-Aided Lung Auscultation Screening and Radiographic ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Annapurna Kala Daniel Chong Abdullah H. Baqui Salahuddin Ahmed ASMD Ashraful Islam Nabid Chowdhury Arunangshu Roy Eric D. McCollum Mounya Elhilali Dpt. Electrical & Computer Engineering Lab. for Computational Audio Perception Johns Hopkins University Dpt. International Health Bloomberg School of Public Health Johns Hopkins University Projahnmo Research Foundation Dhaka Bangladesh Dpt. Pediatrics Global Program in Pediatric Respiratory Sciences Eudowood Division of Pediatric Respiratory Sciences Johns Hopkins School of Medicine Baltimore USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

While chest auscultations provide an accessible and low-cost tool for pediatric pneumonia diagnosis, its subjectivity and low reliability continues to hinder its inclusion in global pneumonia guidelines; eventhough more robust tools like chest radiography also suffer from cost and accessibility issues. Advances in computer-aided analytics is offering more robust tools for interpreting digital auscultation signals though little has been done to explore variations of lung sounds across different chest positions and the correspondence between auscultations and specific radiographic findings. The present study explores interpretation of lung auscultations across chest positions in a pediatric pneumonia population, using a deep neural network classification of normal and abnormal breathing patterns. The results reveal a strong alignment between computer-aided auscultation findings and radiographic interpretation not only in terms of presence of adventitious lung patterns, but also in terms of localizing the abnormality along the left or right lung. Though evaluated in a small clinical population, this research underscores the potential of computer-aided auscultation analysis as a cost-effective substitute for radiography in resource-limited settings.

关键词： Pneumonia Costs Lungs Artificial neural networks Reliability engineering in medicine and biology Diagnostic radiography Guidelines

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Stakeholder Engagement Strategies to Build Resilience to Compound Hazards: Engaging Community-Based Organizations in Research

SSRN

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SSRN 2024年

作者： Clark, Sarah Guido, Zack Cabrera-Rivera, Laura Teresa Méndez-Lázaro, Pablo McMahan, Ben Moscoso, Federico Cintrón Crespo-Acevedo, Wanda I. Castro-Sitiriche, Marcel Arizona Institute for Resilience University of Arizona TucsonAZ United States Department of Environmental Health University of Puerto Rico Medical Sciences Campus San Juan Puerto Rico El Puente - Latino Climate Action Network Puerto Rico NOAA Climate Adaptation Partnerships Program Puerto Rico Department of Electrical and Computer Engineering University of Puerto Rico Mayagüez Puerto Rico

Climate extremes can generate impacts in one sector that cascade or amplify the impacts in others. Developing strategies that build resilience to these compound hazards requires collaboration among diverse stakeholders to understand hazard dynamics and the synergies and tradeoffs in adaptation activities. In many regions, community-based organizations (CBOs) lead in local climate adaptation, and their engagement in research can help inform research agendas and capacity-strengthening activities that support locally led adaptation. In this paper, we describe a collaborative project that convened stakeholders working in climate adaptation, public health, and energy resilience in Puerto Rico. The goals were to identify knowledge gaps and opportunities for immediate action. Based on interviews, a participatory workshop, and a survey, we report on the CBO activities, their networks and their views on the relationships between climate, public health, and energy. We also describe their perspectives on priorities to address compound hazards. Drawing on these results, we discuss five strategies that can help research projects collaborate with CBOs. They include understanding the network to inform engagement, paying attention to differential impacts and justice, employing flexible planning to accommodate multiple goals and perspectives, focusing on information sharing to advance collaboration, and exploring narratives of change to understand adaptation and maladaptation. This study informs how research can more effectively engage CBOs in climate adaptation, which, in turn, can contribute to building plans and systems that are better equipped to build resilience to compound extreme events. © 2024, The Authors. All rights reserved.

关键词： Public health

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Economics of Semantic Communication System: An Auction Approach

arXiv

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arXiv 2022年

作者： Liew, Zi Qin Du, Hongyang Yang, Wei Lim, Bryan Xiong, Zehui Niyato, Dusit Miao, Chunyan Kim, Dong In Alibaba-NTU Singapore Joint Research Institute Nanyang Technological Univerity Singapore The School of Computer Science and Engineering The Energy Research Institute NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore Nanyang Technological University Singapore639798 Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Semantic communication technologies enable wireless edge devices to communicate effectively by transmitting semantic meaning of data. Edge components, such as vehicles in next-generation intelligent transport systems, use well-trained semantic models to encode and decode semantic information extracted from raw and sensor data. However, the limitation in computing resources makes it difficult to support the training process of accurate semantic models on edge devices. As such, edge devices can buy the pretrained semantic models from semantic model providers, which is called "semantic model trading". Upon collecting semantic information with the semantic models, the edge devices can then sell the extracted semantic information, e.g., information about urban road conditions or traffic signs, to the interested buyers for profit, which is called "semantic information trading". To facilitate both types of the trades, effective incentive mechanisms should be designed. Thus, in this paper, we propose a hierarchical trading system to support both semantic model trading and semantic information trading jointly. The proposed incentive mechanism helps to maximize the revenue of semantic model providers in the semantic model trading, and effectively incentivizes model providers to participate in the development of semantic communication systems. For semantic information trading, our designed auction approach can support the trading between multiple semantic information sellers and buyers, while ensuring individual rationality, incentive compatibility, and budget balance, and moreover, allowing them achieve higher utilities than the baseline method. Copyright © 2022, The Authors. All rights reserved.

关键词： Commerce

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Fast Data-independent KLT Approximations Based on Integer Functions

arXiv

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arXiv 2024年

作者： Radünz, A.P. Coelho, D.F.G. Bayer, F.M. Cintra, R.J. Madanayake, A. Graduate Program in Statistics Universidade Federal de Pernambuco Recife Brazil Calgary Canada Departamento de Estatística and LACESM Universidade Federal de Santa Maria Santa Maria97105-900 Brazil Signal Processing Group Department of Technology Universidade Federal de Pernambuco Caruaru Brazil Department of Electrical and Computer Engineering Florida International University FL33174 United States

The Karhunen-Loève transform (KLT) stands as a well-established discrete transform, demonstrating optimal characteristics in data decorrelation and dimensionality reduction. Its ability to condense energy compression into a select few main components has rendered it instrumental in various applications within image compression frameworks. However, computing the KLT depends on the covariance matrix of the input data, which makes it difficult to develop fast algorithms for its implementation. Approximations for the KLT, utilizing specific rounding functions, have been introduced to reduce its computational complexity. Therefore, our paper introduces a category of low-complexity, data-independent KLT approximations, employing a range of round-off functions. The design methodology of the approximate transform is defined for any block-length N, but emphasis is given to transforms of N = 8 due to its wide use in image and video compression. The proposed transforms perform well when compared to the exact KLT and approximations considering classical performance measures. For particular scenarios, our proposed transforms demonstrated superior performance when compared to KLT approximations documented in the literature. We also developed fast algorithms for the proposed transforms, further reducing the arithmetic cost associated with their implementation. Evaluation of field programmable gate array (FPGA) hardware implementation metrics was conducted. Practical applications in image encoding showed the relevance of the proposed transforms. In fact, we showed that one of the proposed transforms outperformed the exact KLT given certain compression ratios. Copyright © 2024, The Authors. All rights reserved.

关键词： Image compression

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Parallel Approximations of the Tukey g-and-h Likelihoods and Predictions for Non-Gaussian Geostatistics

Parallel Approximations of the Tukey g-and-h Likelihoods and...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Sagnik Mondal Sameh Abdulah Hatem Ltaief Ying Sun Marc G. Genton David E. Keyes Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Kingdom of Saudi Arabia Statistics Program King Abdullah University of Science and Technology Extreme Computing Research Center King Abdullah University of Science and Technology

Maximum likelihood estimation is an essential tool in the procedure to impute missing data in climate/weather applications. By defining a particular statistical model, the maximum likelihood estimation can be used to understand the underlying structure of given geospatial data. The Gaussian random field has been widely used to describe geospatial data, as one of the most popular models under the hood of maximum likelihood estimation. Computation of Gaussian log-likelihood demands operations on a dense symmetric positive definite matrix, often parameterized by the Matérn correlation function. This computation of the log-likelihood requires $\mathcal{O}(n^{2})$ storage and $\mathcal{O}(n^{3})$ operations, which can be a huge task considering that the number of geographical locations, $n$ , now commonly reaches into the millions. However, despite its appealing theoretical properties, the assumptions of Gaussianity may be unrealistic since real data often show signs of skewness or have some extreme values. Herein, we consider the Tukey ${g-}$ and $-h$ (TGH) random field as an example of a non-Gaussian random field that shows more robustness in modeling geospatial data by including two more parameters to incorporate skewness and heavy tail features in the model. This work provides the first HPC implementation of the TGH random field's inference on parallel hardware architectures. Using task-based programming models associated with dynamic runtime systems, our implementation leverages the high concurrency of current parallel systems. This permits to run the exact log-likelihood evaluation of the Tukey g-and-h (TGH) random fields for a decent number of geospatial locations. To tackle large-scale problems, we provide additionally an implementation of the given model using two different low-rank approximations. We compress the aforementioned positive-definite symmetric matrix for computing the log-likelihood and rely on the Tile Low-Rank (TLR) and the Hierarchical Off-Diagon

关键词： Maximum likelihood estimation Symmetric matrices Runtime Computational modeling Linear algebra Tail Predictive models

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Development of Educational Game for Indonesian History Lesson Focusing on Indonesia Pre-Literacy Relics 'Prehistoria' for Grade X High School Student

Development of Educational Game for Indonesian History Lesso...

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2020 International Conference on computer engineering, Network, and Intelligent Multimedia, CENIM 2020

作者： Nugroho, Supeno Mardi Susiki Rahman, Muhammad Daffa Abiyyu Hariadi, Mochamad Arief, Muhammad Faculty of Intelligent Electrical and Informatics Technology Sepuluh Nopember Institute of Technology Computer Engineering Department Surabaya Indonesia Tokyo University of Technology Media Science Program Graduate School of Bionics Computer and Media Sciences Tokyo Japan

ISBN: (纸本)9781728182834

The development of game technology has opened up new possibilities in learning methods through educational games. However, in Indonesia, the application of this concept is lacking. One lesson that can benefit from educational games is Indonesian History in class X, with a focus on history in the pre-literacy period. This study aims to create a puzzle-Adventure type of digital game that can help educate students about the pre-literacy period, developed with Unity, and uses WebGL as a target device while referring to Indonesia's revised 2013 national curriculum. The result of this research is the creation of a digital game that can be played on average of 254.36 seconds, with potential for educational use. A survey result shows that many of the ancient objects and some of the ages are well-recognized. However, the survey also shows many of the gameplay aspects, such as UI, gameplay features, and adventure elements, need improvements. © 2020 IEEE.

关键词： Surveys

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