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7th NAFOSTED Conference on Information and computer science, NICS 2020

作者： Pham, Kha-Luan Dang, Khanh-Mai Tang, Loi-Phat Nguyen, Thanh-Nhan Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Advanced Program in Computer Science Faculty of Information Technology Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Generative Adversarial Networks can generate deceptive portraits of people who do not exist. The misuse of this technology leads to severe security issues such as fake identities and credentials. Since 2017, many works on Deep Learning have focused on detecting GAN synthesized images to prevent the threat against credibility in media. In this work, the authors propose a lightweight VGG-like model to detect state-of-the-art StyleGAN generated portraits. The authors also adopt EfficientNet-B0 to train a classifier on the same StyleGAN architecture. The VGG-like model and EfficientNet-based model achieve 98.9% and 100%, respectively, on the StyleGAN dataset published by Nvidia in 2019. Both models show the potential in generalizing to other GAN architectures and synthetic technologies. © 2020 IEEE.

关键词： Generative adversarial networks

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Pixel-Wise Information in Fake Image Detection 8th

Pixel-Wise Information in Fake Image Detection

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8th International Conference on Future Data and Security Engineering, FDSE 2021

作者： Ngo, Nhat-Khang Cao, Xuan-Nam Advanced Program in Computer Science University of Science Ho Chi Minh City Viet Nam Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9789811680618

In recent years, generative adversarial networks have generated high-quality images that are difficult to differentiate by human eyes. Aside from the positives, improper use of this technology might have severe consequences for society. As a result, digital picture forensic techniques are critical to preventing these damages in our lives. In this paper, we describe a technique for detecting fraudulent face images generated by StyleGAN. Using a U-net-based classifier, we can integrate both global and local information of an image to determine if it is real or fake. A huge testing set of 20,000 pictures is used to confirm the model’s efficacy. For comparison, we do tests on different CNN-based models. The results demonstrate that among the models on the same dataset, the U-net-based classifier has the greatest accuracy (98.43 % ). Finally, prediction maps are shown to demonstrate the relevance of pixel-level information in detecting real/fake images. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Generative adversarial networks

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Highly Flexible Piezoelectric Pressure Sensor at Extremely High-Temperature Range Using Ultrawide-Bandgap III-N Thin Films

Highly Flexible Piezoelectric Pressure Sensor at Extremely H...

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IEEE Electron Devices Technology and Manufacturing Conference (EDTM)

作者： Nam-In Kim Miad Yarali Muhammad Aqib Jae-Hyun Ryou Department of Mechanical Engineering Texas Center for Superconductivity at UH Advanced Manufacturing Institute University of Houston USA Materials Science and Engineering Program University of Houston USA Department of Electrical and Computer Engineering University of Houston USA

Pressure monitoring in extreme conditions, such as in industrial, aerospace, and radioactive atmosphere, is crucial. Our focus is on developing and researching piezoelectric sensors that are highly flexible for detecting gas pressures at extremely high temperatures. We develop the flexible device using epitaxial III -nitride film, which is single-crystalline, by layer-transfer method. The sensor shows a sensitive and stable operation for extended periods. We use software simulation and relevant formulas to support our experimental findings.

关键词： Temperature sensors Pressure sensors X-ray scattering Sensor phenomena and characterization Software Semiconductor process modeling III-V semiconductor materials

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Observation of Photonic Chiral Flatbands

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Physical Review Letters 2025年第10期134卷 103801-103801页

作者： Minho Choi Andrea Alù Arka Majumdar Department of Electrical and Computer Engineering University of Washington Seattle Washington 98195 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA and Physics Program Graduate Center City University of New York New York New York 10031 USA Department of Electrical and Computer Engineering University of Washington Seattle Washington 98195 USA and Department of Physics University of Washington Seattle Washington 98195 USA

Distinct selectivity to the spin angular momenta of photons has garnered significant attention in recent years, for its relevance in basic science and for imaging and sensing applications. While nonlocal metasurfaces with strong chiral responses to the incident light have been reported, these responses are typically limited to a narrow range of incident angles. In this study, we demonstrate a nonlocal metasurface that showcases strong chirality, characterized by circular dichroism (∼0.6), over a wide range of incident angles ±5°. Its quality factor, circular dichroism and resonant frequency can be optimized by design. These findings pave the way to further advance the development of valley-selective optical cavities and augmented reality applications.

关键词： Natural frequencies

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Thermal simulation of microwave kiln based on multiphysics

Thermal simulation of microwave kiln based on multiphysics

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International Technical Conference o Circuits/Systems, computers and Communications (ITC-CSCC)

作者： Thodsaphon Jansaengsuk Sorathon Pattanapichai Piyawong Poopanya Nonthawat Phimphakan Jatuporn Thongsri Computer Simulation in Engineering Research Group College of Advanced Manufacturing Innovation King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Program of Physics Faculty of Science Ubon Ratchathani Rajabhat University Ubonratchatani Thailand

A microwave kiln, made of silicon carbide and ceramic fiber, commonly employs in a household glassware production process. In this process, when the kiln was in a microwave oven, a microwave transmitted to the kiln generating a high temperature to fuse the glass inside. This article presents a thermal simulation to investigate the temperature inside the kiln based on multiphysics consisting of a high-frequency structure simulator (HFSS) and computational fluid dynamics (CFD). The multiphysics results revealed the temperature inside the kiln in a transient state, consistent with the experimental results. As expected, the temperature increased with the increasing time of the process. Significantly, the silicon carbide had higher temperatures than the ceramic fiber; therefore, silicon carbide is a crucial material for generating heat inside the kiln. In addition, the temperature-increasing rate (TIR) inside the kiln depended on the kiln's thickness (Th). As a result, the thinner Th provided better TIR. The research findings can be applied to develop a high-efficacy household glassware production process.

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Learner Action Patterns in the Problem-Solving Process Related to program Code Composition Based on Tracking System Activities 7

Learner Action Patterns in the Problem-Solving Process Relat...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Syahidi, Aulia Akhrian Supianto, Ahmad Afif Hirashima, Tsukasa Watanobe, Yutaka Politeknik Negeri Banjarmasin Smart City Information System Applied Undergraduate Program Banjarmasin City Indonesia Research Center for Data and Information Sciences Bandung City Indonesia Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Learning Engineering Laboratory Higashihiroshima Japan University of Aizu Division of Information Systems Department of Computer Science and Engineering Fukushima AizuWakamatsu Japan

ISBN: (纸本)9798350345711

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the 'if-then' rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process. © 2022 IEEE.

关键词： Data mining

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Spin-orbit-locked hyperbolic polariton vortices carrying reconfigurable topological charges

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eLight 2022年第1期2卷 143-153页

作者： Mingsong Wang Guangwei Hu Saroj Chand Michele Cotrufo Yohannes Abate Kenji Watanabe Takashi Taniguchi Gabriele Grosso Cheng‑Wei Qiu Andrea Alù Photonics Initiative Advanced Science Research CenterCity University of New YorkNew York CityNY 10031USA Department of Electrical and Computer Engineering National University of SingaporeSingapore 116083Singapore Department of Physics and Astronomy The University of GeorgiaAthensGA 30602USA Research Center for Functional Materials National Institute for Materials ScienceTsukubaIbaraki 305‑0044Japan International Center for Materials Nanoarchitectonics National Institute for Materials ScienceTsukubaIbaraki 305‑0044Japan Physics Program Graduate CenterCity University of New YorkNew YorkNY 10016USA

The topological features of optical vortices have been opening opportunities for free-space and on-chip photonic technologies,e.g.,for multiplexed optical communications and robust information *** a parallel but disjoint effort,polar anisotropic van der Waals nanomaterials supporting hyperbolic phonon polaritons(HP2s)have been leveraged to drastically boost light-matter *** far HP2 studies have been mainly focusing on the control of their amplitude and scale *** we report the generation and observation of mid-infrared hyperbolic polariton vortices(HP2Vs)associated with reconfigurable topological ***-shaped gold disks coated with a flake of hexagonal boron nitride are exploited to tailor spin-orbit interactions and realise deeply subwavelength *** complex interplay between excitation spin,spiral geometry and HP2 dispersion enables robust reconfigurability of the associated topological *** results reveal unique opportunities to extend the application of HP2s into topological photonics,quantum information processing by integrating these phenomena with single-photon emitters,robust on-chip optical applications,sensing and nanoparticle manipulation.

关键词： Hyperbolic polariton vortex Light-matter interactions Spin-orbit interaction Topological charge Reconfigurability

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Resilience of Data-Driven Cyberattack Detection Systems in Smart Power Grids

Resilience of Data-Driven Cyberattack Detection Systems in S...

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European Signal Processing Conference (EUSIPCO)

作者： Abdulrahman Takiddin Rachad Atat Hayat Mbayed Muhammad Ismail Erchin Serpedin Department of Electrical and Computer Engineering Florida State University Tallahassee FL USA Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Center for Advanced Power Systems Florida State University Tallahassee FL USA Department of Computer Science Tennessee Technological University Cookeville TN USA Department of Electrical and Computer Engineering Texas A&M University College Station TX USA

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

Data communications within the smart power grid components are susceptible to cyberattacks due to the inter-connected nature of the grid and reliance on communication networks. Such cyberattacks can exploit the integrity of the exchanged data and result in operational instability. Existing data-driven cyberattack detection systems (CDSs) are proposed in the literature but their effectiveness is only verified against one type of cyberattacks. In reality, a smart grid system could encounter more than one attack type at once. Thus, in this paper, we investigate the resilience of state-of-the-art data-driven CDSs against replay false data injection, adversarial evasion, and adversarial data poisoning attacks on a realistic IEEE 118-bus system model. It turns out that a convolutional recurrent graph autoencoder-based CDS offers an attack detection rate of 96 – 97.5%, which outperforms other machine learning and deep learning-based data-driven CDSs by 16 – 54% since it captures the recurrent and spatial aspects of the data without being trained on attack data.

关键词： Deep learning Europe Feature extraction Graph neural networks Data models Smart grids Reliability computer crime Unsupervised learning Resilience

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Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI 41

Position: Bayesian Deep Learning is Needed in the Age of Lar...

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41st International Conference on Machine Learning, ICML 2024

作者： Papamarkou, Theodore Skoularidou, Maria Palla, Konstantina Aitchison, Laurence Arbel, Julyan Dunson, David Filippone, Maurizio Fortuin, Vincent Hennig, Philipp Hernández-Lobato, José Miguel Hubin, Aliaksandr Immer, Alexander Karaletsos, Theofanis Khan, Mohammad Emtiyaz Kristiadi, Agustinus Li, Yingzhen Mandt, Stephan Nemeth, Christopher Osborne, Michael A. Rudner, Tim G.J. Rügamer, David Teh, Yee Whye Welling, Max Wilson, Andrew Gordon Zhang, Ruqi Department of Mathematics The University of Manchester Manchester United Kingdom Eric and Wendy Schmidt Center Broad Institute of MIT and Harvard Cambridge United States Spotify London United Kingdom Computational Neuroscience Unit University of Bristol Bristol United Kingdom Centre Inria de l'Université Grenoble Alpes Grenoble France Department of Statistical Science Duke University United States Statistics Program KAUST Saudi Arabia Helmholtz AI Munich Germany Department of Computer Science Technical University of Munich Munich Germany Munich Center for Machine Learning Munich Germany Tübingen AI Center University of Tübingen Tübingen Germany Department of Engineering University of Cambridge Cambridge United Kingdom Department of Mathematics University of Oslo Oslo Norway Bioinformatics and Applied Statistics Norwegian University of Life Sciences Ås Norway Department of Computer Science ETH Zurich Switzerland Chan Zuckerberg Initiative CA United States Center for Advanced Intelligence Project RIKEN Tokyo Japan Vector Institute Toronto Canada Department of Computing Imperial College London London United Kingdom Department of Computer Science UC Irvine Irvine United States Department of Mathematics and Statistics Lancaster University Lancaster United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Center for Data Science New York University New York United States Department of Statistics LMU Munich Munich Germany DeepMind London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Informatics Institute University of Amsterdam Amsterdam Netherlands Courant Institute of Mathematical Sciences Center for Data Science Computer Science Department New York University New York United States Department of Computer Science Purdue University West Lafayette United States

In the current landscape of deep learning research, there is a predominant emphasis on achieving high predictive accuracy in supervised tasks involving large image and language datasets. However, a broader perspective reveals a multitude of overlooked metrics, tasks, and data types, such as uncertainty, active and continual learning, and scientific data, that demand attention. Bayesian deep learning (BDL) constitutes a promising avenue, offering advantages across these diverse settings. This paper posits that BDL can elevate the capabilities of deep learning. It revisits the strengths of BDL, acknowledges existing challenges, and highlights some exciting research avenues aimed at addressing these obstacles. Looking ahead, the discussion focuses on possible ways to combine large-scale foundation models with BDL to unlock their full potential. Copyright 2024 by the author(s)

关键词： Contrastive Learning

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Design and Implementation of Business Intelligence Dashboard for Project Control at the Port Harbor-Company 12th

Design and Implementation of Business Intelligence Dashboard...

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12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020

作者： Lumban Gaol, Ford Syahir, Arsyan Matsuo, Tokuro Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Information System Bina Nusantara University Jakarta Indonesia Advanced Institute of Industry Technology Tokyo Japan

ISBN: (纸本)9789811533792

This study aims to assist resource management and the project controller at Port Harbor Company. Port Harbor Company is an IT Consulting. Problems that often occur in IT Consulting are related to the project cost, resource management and control of each project. Problems that occur at the Port Harbor Company are poor resource management, spending costs that exceed a predetermined budget and how to see the status of ongoing projects. Using Business Intelligence and the dashboard as a front end will help the project controller and resource management manage resources, manage project costs and monitor ongoing projects. In this study, the development and implementation of Business Intelligence and dashboards using the ASAP method are expected to be more structured and can solve the Port Harbor Company problem. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Project management

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