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IEEE IVMSP Workshop

作者： Qiqin Dai Emeline Pouyet Oliver Cossairt Marc Walton Francesca Casadio Aggelos Katsaggelos Dpt. of Electrical Engineering and Computer Science Northwestern University Center for Scientific Studies in the Arts (NU-ACCESS) Northwestern University

ISBN: (纸本)9781509019304

X-Ray fluorescence (XRF) scanning of works of art is becoming an increasingly popular non-destructive analytical method. The high quality XRF spectra is necessary to obtain significant information on both major and minor elements used for characterization and provenance analysis. However, there is a trade-off between the spatial resolution of an XRF scan and the Signal-to-Noise Ratio (SNR) of each pixel's spectrum, due to the limited scanning time. In this paper, we propose an XRF image super-resolution method to address this trade-off, thus obtaining a high spatial resolution XRF scan with high SNR. We use a sparse representation of each pixel using a dictionary trained from the spectrum samples of the image, while imposing a spatial smoothness constraint on the sparse coefficients. We then increase the spatial resolution of the sparse coefficient map using a conventional super-resolution method. Finally the high spatial resolution XRF image is reconstructed by the high spatial resolution sparse coefficient map and the trained spectrum dictionary.

关键词： Dictionaries Spatial resolution Image reconstruction Mathematical model Signal resolution Signal to noise ratio

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Mercury: Combining Performance with Dependability Using Self-virtualization

Mercury: Combining Performance with Dependability Using Self...

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International Conference on Parallel Processing (ICPP)

作者： Haibo Chen Rong Chen Fengzhe Zhang Binyu Zang Pen-Chung Yew Parallel Processing Institute Fudan University China Dpt. of Computer Science and Engineering University of Minnesota Twin-Cities USA

There has recently been increasing interests in using system virtualization to improve the dependability of HPC cluster systems. However, it is not cost-free and may come with some performance degradation, uncertain QoS and loss of functionalities. Meanwhile, many virtualization-enabled features such as online maintenance and fault tolerance do not require virtualization being always on. This paper proposes a technique, called self-virtualization, that supports dynamically attaching and detaching a full-fledged virtual machine monitor (VMM) beneath an operating system, without disturbing applications thereon, and rid the system of potential overhead when the virtualization is not needed. This technique enables HPC clusters to reap most benefits from virtualization without sacrificing performance. This paper presents the design and implementation of Mercury, a working prototype based on Linux and Xen VMM. Our performance measurement shows that Mercury incurs very little overhead: about 0.2 ms to complete a mode switch, and negligible performance degradation compared to Linux.

关键词： Degradation Linux Switches Performance loss Fault tolerance Joining processes Virtual machine monitors Operating systems Application virtualization Prototypes

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Different approach to build an uninterruptible power supply system with power factor correction

International Power Electronics Congress - CIEP

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International Power Electronics Congress - CIEP 1998年 119-124页

作者： Vázquez, N. Aguilar, C. Alvarez, J. Cáceres, R. Barbi, I. Arau, J. Inst. Tecnológico de Celaya Computer Science Dpt. Celaya Mexico CENIDET Electronics Engineering Dpt. Cuernavaca Mexico CINVESTAV-IPN Electrical Engineering Dpt. Mexico D.F. Mexico Federal University of Santa Catarina Power Electronics Institute Florianópolis -SC Brazil

In this paper a different approach to build an uninterruptible power supply (UPS) system is presented. The proposed scheme includes features such as high power factor, low total harmonic distortion and good dynamic response at the output voltage. This scheme has the desirable features of high efficiency, simple circuit and low cost compared to a traditional standalone multiple stages UPS with power factor correction. The circuit operation, analysis and experimental results of the proposed UPS scheme are presented. The UPS approach is a good solution for low power applications (&le 500 W).

关键词： Uninterruptible power systems

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Recognition of food-texture attributes using an in-ear microphone

arXiv

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arXiv 2021年

作者： Mars, Monica Diou, Christos Papapanagiotou, Vasileios van den Boer, Janet Delopoulos, Anastasios Multimedia Understanding Group Dpt. Electrical and Computer Engineering Faculty of Engineering Aristotle University of Thessaloniki Greece Department of Informatics and Telematics Harokopio University of Athens Greece Dpt. of Biomedical Signals and Systems Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Division of Human Nutrition and Health Wageningen University Netherlands

Food texture is a complex property;various sensory attributes such as perceived crispiness and wetness have been identified as ways to quantify it. Objective and automatic recognition of these attributes has applications in multiple fields, including health sciences and food engineering. In this work we use an in-ear microphone, commonly used for chewing detection, and propose algorithms for recognizing three food-texture attributes, specifically crispiness, wetness (moisture), and chewiness. We use binary SVMs, one for each attribute, and propose two algorithms: one that recognizes each texture attribute at the chew level and one at the chewing-bout level. We evaluate the proposed algorithms using leave-one-subject-out cross-validation on a dataset with 9 subjects. We also evaluate them using leave-one-food-type-out cross-validation, in order to examine the generalization of our approach to new, unknown food types. Our approach performs very well in recognizing crispiness (0.95 weighted accuracy on new subjects and 0.93 on new food types) and demonstrates promising results for objective and automatic recognition of wetness and chewiness. Copyright © 2021, The Authors. All rights reserved.

关键词： Wearable technology

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Analysis and Detection of Melanoma through Collective Intelligence with AI

Analysis and Detection of Melanoma through Collective Intell...

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Annual IEEE Symposium on computer-Based Medical systems

作者： Enrique Fernández-Morales Carlos L. Sanchez-Bocanegra Rafael Pastor-Vargas José-Juan Pereyra-Rodriguez Juan M. Haut José Alberto Benítez-Andrades Communications and Control Systems Dpt. Computer Science Faculty UNED Madrid Spain Communications and Control Systems Dpt. Computer Science Faculty UNED Malaga Spain Virgen Del Rocio Hospital Universitario Seville Spain School of Tecnology University of Extremadura Cáceres Spain Dept. of Electric Systems and Automatics Engineering Universidad de León León Spain

ISBN: (数字)9798350384727

ISBN: (纸本)9798350384734

Cancer is a widespread global health problem, claiming millions of lives each year, and skin cancer represents a significant threat as it is one of the most common types. Early tumor detection via medical imaging is critical for effective treatment. Leveraging artificial intelligence, particularly novel models like Transformers, presents promising avenues for improved diagnosis. This paper explores the efficacy of a Collective Intelligence approach using AI in classifying cancerous and non-cancerous tumors, aiming to reduce classification errors and support clinical decision-making. We created five different configurations using various datasets to compare the results. The results show solid performance for the CI in the evaluated tasks, reaching up to 75.89% accuracy. The lack of images in certain classes significantly contributes to overfitting. It is suggested to explore data expansion strategies and improve consistency in image capture for future work.

关键词： Accuracy Melanoma Collective intelligence Image capture Transformers Solids Artificial intelligence

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Adaptive filtering of advertisements on web pages 05

Adaptive filtering of advertisements on web pages

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14th International World Wide Web Conference, WWW2005

作者： Esfandiari, Babak Nock, Richard Dpt. of Systems and Computer Engineering Carleton University 1125 Colonel By Drive Ottawa ON K1S5B6 Canada GRIMAAG-DSI/Univ. Antilles-Guyane Campus de Schoelcher B.P. 7209 97275 Schoelcher Cedex Martinique

ISBN: (纸本)1595930515

We present a browser extension to dynamically learn to filter unwanted images (such as advertisements or flashy graphics) based on minimal user feedback. To do so, we apply the weighted majority algorithm using pieces of the Uniform Resource Locators of such images as predictors. Experimental results tend to confirm that the accuracy of the predictions converges quickly to very high levels.

关键词： Websites

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Rough Sets and Intelligent systems Paradigms 1

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丛书名： Lecture Notes in computer science

1000年

作者： Marzena Kryszkiewicz Zbigniew W. Raś Chris Cornelis Davide Ciucci Jesús Medina-Moreno Hiroshi Motoda

ISBN: (数字)9783319087290

ISBN: (纸本)9783319087283

This book constitutes the refereed proceedings of the 23rd Australasian Joint Conference on Rough Sets and Intelligent systems Paradigms, RSEISP 2014, held in Granada and Madrid, Spain, in July 2014. RSEISP 2014 was held along with the 9th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2014, as a major part of the 2014 Joint Rough Set Symposium, JRS 2014. JRS 2014 received 40 revised full papers and 37 revised short papers which were carefully reviewed and selected from 120 submissions and presented in two volumes. This volume contains the papers accepted for the conference RSEISP 2014, as well as the three invited papers presented at the conference. The papers are organized in topical sections on plenary lecture and tutorial papers; foundations of rough set theory; granular computing and covering-based rough sets; applications of rough sets; induction of decision rules - theory and practice; knowledge discovery; spatial data analysis and spatial databases; information extraction from images.

关键词： Artificial Intelligence Data Mining and Knowledge Discovery Mathematical Logic and Formal Languages Information systems Applications (incl. Internet) Information Storage and Retrieval Pattern Recognition

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A review of sentiment computation methods with R packages

arXiv

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arXiv 2019年

作者： Naldi, Maurizio University of Rome Tor Vergata Dpt. of Civil Engineering and Computer Science Via del Politecnico 1 Rome00133 Italy

Four packages in R are analyzed to carry out sentiment analysis. All packages allow to define custom dictionaries. Just one - SentimentR - properly accounts for the presence of negators. Copyright © 2019, The Aut... 详细信息

关键词： Sentiment analysis

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Automatic video colorization using 3d conditional generative adversarial networks

arXiv

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arXiv 2019年

作者： Kouzouglidis, Panagiotis Sfikas, Giorgos Nikou, Christophoros Dpt. of Computer Science and Engineering University of Ioannina Ioannina45110 Greece Information Technologies Institute CERTH Thessaloniki57001 Greece

In this work, we present a method for automatic colorization of grayscale videos. The core of the method is a Generative Adversarial Network that is trained and tested on sequences of frames in a sliding window manner. Network convolutional and deconvolutional layers are three-dimensional, with frame height, width and time as the dimensions taken into account. Multiple chrominance estimates per frame are aggregated and combined with available luminance information to recreate a colored sequence. Colorization trials are run succesfully on a dataset of old black-and-white films. The usefulness of our method is also validated with numerical results, computed with a newly proposed metric that measures colorization consistency over a frame sequence. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

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Thematic labeling of Twitter accounts using DBpedia properties

Thematic labeling of Twitter accounts using DBpedia properti...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Gerasimos Razis Ioannis Anagnostopoulos Petr Saloun Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Czech Republic

ISBN: (纸本)9781509052479

In this paper, we propose an iterative algorithm towards the automatic labeling of Twitter accounts in respect to thematic categories derived from DBpedia properties. We describe the rationale behind the selection of these thematic categories, and discuss their evaluation assessment. Finally, we propose and analyze two generic and adaptable methodologies for discovering the necessary linked data resources for further enhancing the thematic description of Twitter accounts.

关键词： Twitter Labeling Measurement Classification algorithms Tagging Semantics Algorithm design and analysis

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