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2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2021

作者： Do Prado, Josue Campos Santos, Marcos Vinicius Ramos, Lucas Feksa Canha, Luciane Neves Konzen, Gabriel School of Engineering Computer Science Washington State University VancouverWA98686 United States School of Engineering Newcastle University Newcastle Upon TyneNE1 7RU United Kingdom Federal University of Rondônia Department of Electrical Engineering Porto Velho Brazil Graduate Program in Electrical Engineering Federal University of Santa Maria Santa Maria Brazil Division of Energy Economics and Environmental Studies Rio de Janeiro Brazil

ISBN: (纸本)9781665444217

The Brazilian state of Amapa=-notable for having 70% of its area consisting of unexplored Amazonian forests-experienced a massive power blackout in November 2020. An internal short-circuit in a transformer led to an explosion followed by a fire at the Macapa substation. This event left about 90% of the Amapa's population without power for several days in the middle of the COVID-19 pandemic, disrupting the lives of hundreds of thousands of people and raising concerns from several electricity sector stakeholders. This paper discusses select lessons learned from the power blackout and presents future opportunities to improve power system reliability and resilience for the grids in Amapá, and other similar Brazilian states, with a special focus on the increasingly important role of of distributed energy resources and smart grid technologies. © 2021 IEEE.

关键词： Outages

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Analysis of a VLC Link under Lighting Conditions in an Indoor Scenario

Analysis of a VLC Link under Lighting Conditions in an Indoo...

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Conference on Lasers and Electro-Optics (CLEO)

作者： David Esteban Farfán Guillén Fernando César Baraviera Tosta Paulo de Tarso Neves Alexandre de Almeida Prado Pohl Graduate Program in Electrical and Computer Engineering (CPGEI) Universidade Tecnológica Federal do Paraná (UTFPR) Curitiba Brazil

Visible light communication transmits data through light-emitting diodes. In this work a commercial lamp consisting of 7 white LEDs is employed in the demonstration of data transmission, obeying the recommended lighti... 详细信息

ISBN: (纸本)9781943580910

关键词： OFDM Electrooptic modulators Lighting Surface emitting lasers Modulation Lasers and electrooptics Light emitting diodes

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Out of Sight, Out of Mind: A Source-View-Wise Feature Aggregation for Multi-View Image-Based Rendering

arXiv

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arXiv 2022年

作者： Cha, Geonho Shin, Chaehun Yoon, Sungroh Wee, Dongyoon Clova AI NAVER Corp. Korea Republic of Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

To estimate the volume density and color of a 3D point in the multi-view image-based rendering, a common approach is to inspect the consensus existence among the given source image features, which is one of the informative cues for the estimation procedure. To this end, most of the previous methods utilize equally-weighted aggregation features. However, this could make it hard to check the consensus existence when some outliers, which frequently occur by occlusions, are included in the source image feature set. In this paper, we propose a novel source-view-wise feature aggregation method, which facilitates us to find out the consensus in a robust way by leveraging local structures in the feature set. We first calculate the source-view-wise distance distribution for each source feature for the proposed aggregation. After that, the distance distribution is converted to several similarity distributions with the proposed learnable similarity mapping functions. Finally, for each element in the feature set, the aggregation features are extracted by calculating the weighted means and variances, where the weights are derived from the similarity distributions. In experiments, we validate the proposed method on various benchmark datasets, including synthetic and real image scenes. The experimental results demonstrate that incorporating the proposed features improves the performance by a large margin, resulting in the state-of-the-art performance. © 2022, CC BY-NC-ND.

关键词： Three dimensional computer graphics

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Anti-Adversarially Manipulated Attributions for Weakly Supervised Semantic Segmentation and Object Localization

arXiv

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arXiv 2022年

作者： Lee, Jungbeom Kim, Eunji Mok, Jisoo Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Interdisciplinary Program in AI AIIS ASRI INMC and ISRC Seoul National University Seoul08826 Korea Republic of

Obtaining accurate pixel-level localization from class labels is a crucial process in weakly supervised semantic segmentation and object localization. Attribution maps from a trained classifier are widely used to provide pixel-level localization, but their focus tends to be restricted to a small discriminative region of the target object. An AdvCAM is an attribution map of an image that is manipulated to increase the classification score produced by a classifier before the final softmax or sigmoid layer. This manipulation is realized in an anti-adversarial manner, so that the original image is perturbed along pixel gradients in directions opposite to those used in an adversarial attack. This process enhances non-discriminative yet class-relevant features, which make an insufficient contribution to previous attribution maps, so that the resulting AdvCAM identifies more regions of the target object. In addition, we introduce a new regularization procedure that inhibits the incorrect attribution of regions unrelated to the target object and the excessive concentration of attributions on a small region of the target object. Our method achieves a new state-of-the-art performance in weakly and semi-supervised semantic segmentation, on both the PASCAL VOC 2012 and MS COCO 2014 datasets. In weakly supervised object localization, it achieves a new state-of-the-art performance on the CUB-200-2011 and ImageNet-1K datasets. © 2022, CC BY-NC-ND.

关键词： Semantic Segmentation

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Intrinsic Parameter Fluctuation and Process Variation Effect of Vertically Stacked Silicon Nanosheet Complementary Field-Effect Transistors

Intrinsic Parameter Fluctuation and Process Variation Effect...

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IEEE International Symposium on Quality Electronic Design

作者： Sekhar Reddy Kola Yiming Li Min-Hui Chuang Parallel and Scientific Computing Laboratory Hsinchu Taiwan Electrical Engineering and Computer Science International Graduate Program Hsinchu Taiwan Institute of Communications Engineering Hsinchu Taiwan Institute of Biomedical Engineering Hsinchu Taiwan Institute of Pioneer Semiconductor Innovation Hsinchu Taiwan Institute of Artificial Intelligence Innovation Hsinchu Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Center for mmWave Smart Radar System and Technologies National Yang Ming Chiao Tung University Hsinchu Taiwan

We study the variability of vertically stacked gate-all-around silicon nanosheet (GAA Si NS) complementary field-effect transistors (CFETs). The process variation effect (PVE), the work function fluctuation (WKF), and the random dopant fluctuation (RDF) of CFETs are statistically estimated using an experimentally validated device simulation technique. Among five factors of PVE, the channel thickness (T Nch /T Pch ), the channel width (W ch ), and the gate length (L G ) are significant. Owing to superior GAA channel control and increased effective gate area, both WKF and RDF are suppressed. Notably, the PVE on both N-/P-FETs of GAA Si CFET induce the largest off-state current fluctuations of 80% and 278%, respectively, because the device characteristic is very sensitive to the layer thickness and width of channel.

关键词： Fluctuations Gallium arsenide Logic gates Electric variables Silicon Resource description framework Semiconductor process modeling

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Automatic facial expression recognition in an image sequence using conditional random field

Automatic facial expression recognition in an image sequence...

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International Symposium on Computational Intelligence and Informatics

作者： Mohamad Roshanzamir Mahdi Roshanzamir Abdolreza Mirzaei Mohammad Tayarani Darbandy Afshin Shoeibi Roohallah Alizadehsani Fahime Khozeimeh Abbas Khosravi Department of Computer Engineering Fasa University Fasa Iran Department of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran School of Architecture Islamic Azad University Taft Taft Iran Internship in Health Data Analytics Program AI-enabled Processes (AIP) Research Centre Macquarie University Sydney Australia Institute for Intelligent Systems Research and Innovation (IISRI) Deakin University Victoria Australia

ISBN: (纸本)9798350398830

Facial expression recognition is one of the fields that nowadays has attracted the attention of many researchers. It is possible to automate facial expression recognition using artificial intelligence methods. This will be of great help to researchers, especially in areas such as psychology. Automatic facial recognition can be derived from a static image of facial expression, but a better and more efficient way to do this is through a sequence of images. In this paper, a new method is proposed to automatically detect facial expressions from a sequence of images. Each sequence of facial images begins with a face neutral state and ends with one of the six main emotions. Motion vectors are extracted from the sequence using optical flow algorithm. These vectors are then used to train the conditional random field and finally to automatically determine the emotion. In this paper, in addition to the basic conditional random field, the hidden dynamic conditional random field is also investigated. Additionally, the effect of changing some parameters of these algorithms such as different optimization methods has been investigated. Given that a facial expression is recognized during a sequence of images, random field-based methods can be used for efficient classification of facial expressions reaching accuracy (more than 90%) competitive with the best existing methods for facial expression recognition.

关键词： Image recognition Mechatronics Face recognition Heuristic algorithms Psychology Optimization methods Feature extraction

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Comparative Study of Deep Learning Methods through Improvement of Skin Image Quality of Basal Cell Carcinoma

Comparative Study of Deep Learning Methods through Improveme...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Ade Miftahul Jannah Kahlil Muchtar Maulisa Oktiana Aulia Rahman Yagus Cahyadi Novi Maulina Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Aceh Indonesia Dept. of Information System Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Doctorate Student of Doctoral Program in Medical Sciences Faculty of Medicine Universitas Syiah Kuala Indonesia Aceh Indonesia

Basal cell carcinoma (BCC) or commonly known as basal cell cancers is the most common non-melanoma skin disease in the world. BCC is the result of an interaction between a combination of genetic and environmental factors that are directly related to prolonged exposure to ultraviolet (UV) rays, such as the neck and head area. This study proposes to use the CLAHE (Contrast Limited Adaptive Histogram Equalization) method on skin images to improve image quality. CLAHE is an image quality improvement method that aims to obtain images with better contrast than the original image without reducing the quality of the image itself. The experimental results show that the CLAHE image are more accurate than the original image. For quantitative measurements, the performance is seen from the value of accuracy, precision, recall, specificity, and F-score. To be more specific, the experiments utilized the well-known public dataset called ISIC 2018 Dataset (for BCC image), while the normal skin used our own USK-Normal Skin dataset. The results for original image using VGG-16 architecture is 98,3%, ResNet-34 is 97,5%, EfficientNetB0 is 98,2%, and EfficientNet-B7 is 99,7%, respectively. Meanwhile, in the CLAHE image, the accuracy values obtained are higher, for the VGG-16 is 100%, ResNet-34 99.5%, EfficientNetB0 100% and EfficientNet-B7 100%, respectively. The normal skin dataset is available through this link: https://***/USK-NORMAL-SKIN-DATASETI.

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Strain-induced formation of self-assembled InGaN/GaN superlattices in nominal InGaN films grown by plasma-assisted molecular beam epitaxy

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Physical Review Materials 2021年第12期5卷 124606-124606页

作者： Kamruzzaman Khan Kai Sun Christian Wurm Kanak Datta Parag B. Deotare Elaheh Ahmadi Department of Materials Science and Engineering University of Michigan Ann Arbor Michigan 48109 USA Department of Electrical and Computer Engineering University of California Santa Barbara California 93106 USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor Michigan 48109 USA Applied Physics Program University of Michigan Ann Arbor Michigan 48109 USA

In this work, we report the spontaneous formation of superlattice structures in nominal InGaN films grown by plasma-assisted molecular beam epitaxy. A 700-nm-thick self-assembled In0.2Ga0.8N/GaN superlattice with excellent structural quality was achieved. Strain was studied as a possible driving force for the formation of self-assembled superlattice (SASL) structure by growth of InGaN on ZnO substrate using similar growth conditions. The SASL structures were optically characterized using photoluminescence spectroscopy. Structural characterization was conducted via transmission electron microscopy and atom probe tomography. High-resolution x-ray diffraction (XRD) and XRD reciprocal space map were utilized to determine the average composition and the degree of relaxation of InGaN films. We propose that the vertical phase separation observed in the SASL structure is caused by high-temperature growth and intensified by strain. This work provides a method for engineering strain and growth of thick InGaN films for a variety of applications including solar cells and photodetectors.

关键词： Nitrides Superlattices Molecular beam epitaxy Photoluminescence Time-resolved photoluminescence X-ray diffraction

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Miniscope3D:optimized single-shot miniature 3D fluorescence microscopy

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Light(Science & Applications) 2020年第1期9卷 367-379页

作者： Kyrollos Yanny Nick Antipa William Liberti Sam Dehaeck Kristina Monakhova Fanglin Linda Liu Konlin Shen Ren Ng Laura Waller UCB/UCSF Joint Graduate Program in Bioengineering University of CaliforniaBerkeleyCA 94720USA Department of Electrical Engineering&Computer Sciences University of CaliforniaBerkeleyCA 94720USA TIPs Department Universite libre de Bruxelles(ULB)1050 BrusselsBelgium

Miniature fluorescence microscopes are a standard tool in systems ***,widefield miniature microscopes capture only 2D information,and modifications that enable 3D capabilities increase the size and weight and have poor resolution outside a narrow depth ***,we achieve the 3D capability by replacing the tube lens of a conventional 2D Miniscope with an optimized multifocal phase mask at the objective’s aperture *** the phase mask at the aperture stop significantly reduces the size of the device,and varying the focal lengths enables a uniform resolution across a wide depth *** phase mask encodes the 3D fluorescence intensity into a single 2D measurement,and the 3D volume is recovered by solving a sparsity-constrained inverse *** provide methods for designing and fabricating the phase mask and an efficient forward model that accounts for the fieldvarying aberrations in miniature *** demonstrate a prototype that is 17mm tall and weighs 2.5 grams,achieving 2.76μm lateral,and 15μm axial resolution across most of the 900×700×390μm^(3) volume at 40 volumes per *** performance is validated experimentally on resolution targets,dynamic biological samples,and mouse brain *** with existing miniature single-shot volume-capture implementations,our system is smaller and lighter and achieves a more than 2×better lateral and axial resolution throughout a 10×larger usable depth *** microscope design provides single-shot 3D imaging for applications where a compact platform matters,such as volumetric neural imaging in freely moving animals and 3D motion studies of dynamic samples in incubators and lab-on-a-chip devices.

关键词： enable resolution narrow

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Giant Thermomechanical Bandgap engineering in Quasi-two-dimensional Tellurium

arXiv

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arXiv 2023年

作者： Hussain, Naveed Ahmed, Shehzad Tep, Hüseyin U. Ullah, Kaleem Shahzad, Khurram Wu, Hui Shcherbakov, Maxim R. Department of Electrical Engineering and Computer Science University of California Irvine IrvineCA92697 United States State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing100084 China College of Physics and Optoelectronic Engineering Shenzhen University Guangdong518060 China Micro and Nano-Technology Program School of Natural and Applied Sciences Middle East Technical University Ankara06800 Turkey Department of Electrical and Computer Engineering University of Delaware NewarkDE19711 United States Department of Physics Middle East Technical University Ankara06800 Turkey

Mechanical straining-induced bandgap modulation in two-dimensional (2D) materials has been confined to volatile and narrow modulation due to substrate slippage and poor strain transfer. We report the thermomechanical modulation of the inherent bandgap in quasi-2D tellurium nanoflakes (TeNFs) via non-volatile strain induction during hot-press synthesis. We leveraged the coefficient of thermal expansion (CTE) mismatch between TeNFs and growth substrates by maintaining a high-pressure enforced non-slip condition during thermal relaxation (623 to 300K) to achieve the optimal biaxial compressive strain of -4.6 percent in TeNFs/sapphire. This resulted in an enormous bandgap modulation of 2.3 eV, at a rate of up to ~600 meV/%, which is two-fold larger than reported modulation rate. Strained TeNFs display robust band-to-band radiative excitonic blue photoemission with an intrinsic quantum efficiency (IQE) of c.a. 79.9%, making it promising for energy efficient blue LEDs and nanolasers. Computational studies reveal that biaxial compressive strain inhibits exciton-exciton annihilation by evading van-Hove singularities, hence promoting radiative-recombination. Bandgap modulation by such nonvolatile straining is scalable to other 2D semiconductors for on-demand nano(opto)-electronics. Copyright © 2023, The Authors. All rights reserved.

关键词： Energy gap

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