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49th EPS Conference on Plasma Physics, EPS 2023

作者： Pastore, F. Felici, F. Sauter, O. Bosman, T.O.S.J. Galperti, C. Vincent, B. Pau, A. Poels, Y. Ravensbergen, T. Vu, N.M.T. Lausanne Switzerland DIFFER - Dutch Institute for Fundamental Energy Research Energy Systems and Control Group Eindhoven Netherlands Eindhoven University of Technology Dept. of Mechanical Engineering Control Systems Technology Group Eindhoven Netherlands Eindhoven University of Technology Dept. of Mathematics and Computer Science Data Mining Group Eindhoven Netherlands ITER Organization Route de Vinon-sur-Verdon St. Paul Lez Durance13067 Cedex France

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Improved SAR Image Generation with Double Top-K Training Method on Auxiliary Classifier GAN

Improved SAR Image Generation with Double Top-K Training Met...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Hongchen Wang Ming Liu Shichao Chen Mingliang Tao Jingbiao Wei School of Computer Science Shaanxi Normal University Xi’an China Xi’an Modern Control Technology Research Institute Xi’an China School of Electronics and Information Northwestern Polytechnical University Xi’an China Army Aviation Research Institute Beijing China

Synthetic aperture radar (SAR) is a critical imaging technique that is widely used for civil and military tasks, as it is featured with an excellent ability for high resolution imaging. However, due to the severe shortage of SAR images, the performance of automatic target recognition (ATR) is greatly sabotaged. Generative adversarial network (GAN) is often applied for data augmentation of small-sized dataset. In this paper, based on auxiliary classifier GAN (ACGAN) and top-k training technique, we propose double top-k training, which implements a modification during training without any further adjustment on model architecture. The proposed method is to enforce generator to only optimize on generated images that perform well in both discriminator and auxiliary classifier, and discard images of poor performance. We evaluate the generated images via recognition on the moving and stationary target acquisition and recognition (MSTAR) dataset. Recognition accuracy and Fréchet inception distance (FID) score indicate better generation results of the proposed method compared with original ACGAN.

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Design and Simulation of Nano Scale FIN FET Using Silvaco TCAD

Design and Simulation of Nano Scale FIN FET Using Silvaco TC...

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2021 International Conference Engineering and Telecommunication, En and T 2021

作者： Saurabh, Raman Tripathi, Pramod Narayan Bhasme, Sarang Balasaheb Nazarov, Alexey Moscow Institute of Physics and Technology Department of Radio Engineering and Cybernetics Moscow Russia Federal Research Center Computer Science and Control of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9781728183909

We present design and simulation of a single gate Fin-FET structure on the SOI substrate using Silvaco TCAD. A 45 nm channel length Fin-FET structure is compared with conventional MOSFET structure having same channel length. Different structural and process parameters such as length, width, height, dielectric thickness, doping etc has been optimized for designing the Fin-FET. The simulated structure shows the threshold voltage of 0.37643, lower DIBL, higher drain saturation current and improved parameters as compared to the conventional MOSFET structure. © 2021 IEEE.

关键词： Fins (heat exchange)

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Extracting Stress-Related EEG Patterns from Pre-Sleep EEG for Forecasting Slow-Wave Sleep Deficiency

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IEEE Transactions on Neural Systems and Rehabilitation Engineering 2024年 32卷 1817-1827页

作者： Su, Cheng-Hua Ko, Li-Wei Jung, Tzyy-Ping Onton, Julie Tzou, Shey-Cherng Juang, Jia-Chi Hsu, Chung-Yao Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Department of Biomedical Science and Environmental Biology Kaohsiung807 Taiwan University of California San Diego Swartz Center for Computational Neuroscience La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300 Taiwan University of California San Diego Institute for Neural Computation La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Biological Science and Technology Hsinchu300 Taiwan Kaohsiung Medical University Hospital Sleep Disorders Center Department of Neurology Kaohsiung807 Taiwan Kaohsiung Medical University College of Medicine Department of Neurology Kaohsiung807 Taiwan

Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall health. While stress is known for its detrimental impact on sleep quality, the precise effect of pre-sleep stress on subsequent sleep structure remains unknown. This study introduced a novel approach to study the pre-sleep stress effect on sleep structure, specifically slow-wave sleep (SWS) deficiency. To achieve this, we selected forehead resting EEG immediately before and upon sleep onset to extract stress-related neurological markers through power spectra and entropy analysis. These markers include beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn) and spectral entropy (SpEn). Fifteen subjects were included in this study. Our results showed that subjects lacking SWS often exhibited signs of stress in EEG, such as an increased beta/delta correlation, higher alpha asymmetry, and increased FuzzEn in frontal EEG. Conversely, individuals with ample SWS displayed a weak beta/delta correlation and reduced FuzzEn. Finally, we employed several supervised learning models and found that the selected neurological markers can predict subsequent SWS deficiency. Our investigation demonstrated that the classifiers could effectively predict varying levels of slow-wave sleep (SWS) from pre-sleep EEG segments, achieving a mean balanced accuracy surpassing 0.75. The SMOTE-Tomek resampling method could improve the performance to 0.77. This study suggests that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. Such information can be integrated with existing sleep-improving techniques to provide a personalized sleep forecasting and improvement solution. © 2001-2011 IEEE.

关键词： Entropy

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An Efficient Implementation for Bayesian Manifold Regularization Method

An Efficient Implementation for Bayesian Manifold Regulariza...

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IEEE Conference on Decision and control

作者： Junpeng Zhang Yue Ju Bo Wahlberg Biqiang Mu Tianshi Chen School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Instituite of Technology Stockholm Sweden Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences Beijing China

When applying the Bayesian manifold regularization method to function estimation problem with manifold constraints, the direct implementation has computational complexity $\mathcal{O}(N^{3})$ , where $N$ is the number of input-output data measurements. This becomes particularly costly when $N$ is large. In this paper, we propose a more efficient implementation based on the Kalman filter and smoother using a state-space model realization of the underlying Gaussian process. Moreover, we explore the sequentially semi-separable structure of the Laplacian matrix and the posterior covariance matrix. Our proposed implementation has computational complexity $\mathcal{O}(N)$ and thus can be applied to large data problems. We exemplify the effectiveness of our proposed implementation through numerical simulations.

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A single-cell transcriptomic analysis of Neuroblastomas revealed a selective cGAS-STING pathway suppression in malignant cells

A single-cell transcriptomic analysis of Neuroblastomas reve...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Sibilio, Pasquale Di Giulio, Stefano Funari, Alessio Paci, Paola Veschi, Veronica Giannini, Giuseppe Sapienza University of Rome Department of Computer Control and Management Engineering Rome Italy National Research Council Institute for Systems Analysis and Computer Science 'Antonio Ruberti' Rome Italy Sapienza University of Rome Department of Molecular Medicine Rome Italy Sapienza University of Rome Department of Translational and Precision Medicine Rome Italy Karolinska Institutet Stockholm17177 Sweden San Gallicano Dermatological Institute Irccs Microbiology and Virology Rome Italy Istituto Pasteur-Fondazione Cenci Bolognetti Rome Italy

ISBN: (纸本)9798350337488

Neuroblastoma is a disease of disordered development accounting for 15% of childhood cancer deaths. The "cold"immunophenotype frequently occurring of these tumors is likely to contribute to its aggressiveness and refractoriness to treatments, including immune checkpoint blockade, observed in high risk neuroblastoma. The mechanisms that contribute to the cold immunostate have not been elucidated, yet. However, recent studies have reported the involvement of MYCN amplification in reducing the immune infiltrate in high-risk Neuroblastoma tumors. Its action mainly concerns suppressed interferon responses and pro-inflammatory pathways. An important pathway deputed to the activation of type I interferon responses and pro-inflammatory cytokines release is the cyclic GMP-AMP synthase (cGAS) - stimulator of interferon genes (STING) cytosolic DNA sensing pathway. Recent preclinical studies suggest a promising therapeutic effect of cGAS-STING pathway reactivation in Neuroblastomas. However, very little is known about the regulation of the cGAS-STING pathway in Neuroblastoma malignant cells, and its relationship with the MYCN amplification state. To this end, we performed a single-cell transcriptomic analysis of primary human Neuroblastoma cells compared with their normal fetal and embryonic progenitors. The results of the high-resolution analysis of cGAS-STING pathway showed that Neuroblastomas malignant cells have a much lower expression of this pathway compared to normal progenitors and other cell phenotypes populating the tumor microenvironment, possibly acquiring an evolutionary advantage. Moreover, the cGAS-STING pathway anticorrelated with MYCN expression suggesting a putative regulatory mechanism of the STING pathway. © 2023 IEEE.

关键词： immunotherapy Neuroblastoma single-cell transcriptomic

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Towards Automated Detection of Adversarial Attacks on Tabular Data 18

Towards Automated Detection of Adversarial Attacks on Tabula...

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18th Conference on computer science and Intelligence Systems, FedCSIS 2023

作者： Biczyk, Piotr Wawrowski, Lukasz Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka Gliwice44-100 Poland Ukasiewicz Research Network Institute of Innovative Technologies Emag Ul. Leopolda 31 Katowice40-189 Poland Qed Software Sp. Z O.o. Mazowiecka 11/49 Warsaw00-052 Poland

ISBN: (纸本)9788396744784

The paper presents a novel approach to investigating adversarial attacks on machine learning classification models operating on tabular data. The employed method involves using diagnostic parameters calculated on an approximated representation of a model under attack and analyzing differences in these diagnostic parameters over time. The hypothesis researched by the authors is that adversarial attack techniques, even if attempting a low-profile modification of input data, influence those diagnostic attributes in a statistically significant way. Thus, changes in diagnostic attributes can be used for detecting attack events. Three attack approaches on real-world datasets were investigated. The experiments confirm the approach as a promising technique to be further developed for detecting adversarial attacks. © 2023 Polish Information Processing Society.

关键词： Information use

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End-to-End Lip Reading in Romanian with Cross-Lingual Domain Adaptation and Lateral Inhibition

arXiv

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arXiv 2023年

作者： Mănescu, Emilian-Claudiu Smădu, Razvan-Alexandru Avram, Andrei-Marius Cercel, Dumitru-Clementin Pop, Florin Faculty of Mathematics and Computer Science University of Bucharest Romania Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania National Institute for Research and Development in Informatics - ICI Bucharest Romania

Lip reading or visual speech recognition has gained significant attention in recent years, particularly because of hardware development and innovations in computer vision. While considerable progress has been obtained, most models have only been tested on a few large-scale datasets. This work addresses this shortcoming by analyzing several architectures and optimizations on the underrepresented, short-scale Romanian language dataset called Wild LRRo. Most notably, we compare different backend modules, demonstrating the effectiveness of adding ample regularization methods. We obtain state-of-the-art results using our proposed method, namely cross-lingual domain adaptation and unlabeled videos from English and German datasets to help the model learn language-invariant features. Lastly, we assess the performance of adding a layer inspired by the neural inhibition mechanism. © 2023, CC BY.

关键词： Speech recognition

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End-to-End Lip Reading in Romanian with Cross-Lingual Domain Adaptation and Lateral Inhibition

End-to-End Lip Reading in Romanian with Cross-Lingual Domain...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Emilian-Claudiu Mănescu Răzvan-Alexandru Smădu Andrei-Marius Avram Dumitru-Clementin Cercel Florin Pop Faculty of Mathematics and Computer Science University of Bucharest Romania Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania National Institute for Research and Development in Informatics - ICI Bucharest Romania

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Single-channel ultrahigh frequency moisture meter with direct measurement of moisture content of bulk materials

Single-channel ultrahigh frequency moisture meter with direc...

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Automatics and Informatics (ICAI), International Conference

作者： Palvan I. Kalandarov Shakhnoza R. Ubaydullayeva Mirhalil A. Ismailov Nikola N. Nikolov Mariela Alexandrova Department "Automation and Control of Technology Process in Production" «Tashkent Institute of Irrigation and Agricultural Mechanization Engineers» National Research University Tashkent Uzbekistan Department of Automation Faculty of Computer Science and Automation Technical University of Varna Varna Bulgaria

ISBN: (数字)9798350353907

ISBN: (纸本)9798350353914

The article discusses the theoretical foundations of the design of a single-channel ultrahigh frequency moisture meter with direct measurement of the moisture content of bulk materials. In accordance with the requirements of the methodology for selecting efficiency criteria, it is necessary to develop structural diagrams of measuring devices. For these purposes, the standard deviation of the random error is determined, characterizing the accuracy. It includes the main components: sensitivity error, zero error and additive component. Mathematical models of structures are constructed and the standard deviation of random errors, which are caused by certain parameters and additive fluctuations, is calculated. A single-parameter ultrahigh-frequency method for determining the moisture content is proposed. This method provides high accuracy of a single-channel ultrahigh frequency moisture meter with direct measurement of the moisture content of bulk materials. The measuring device can be used in the agricultural industry, where humidity is one of the important parameters, starting with harvesting and ending with the release of finished products.

关键词： Meters Additives Accuracy Sensitivity Moisture UHF measurements Mathematical models Frequency measurement Informatics Standards

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