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international conference on Data Science and Advanced Analytics (DSAA)

作者： Caireann Kennedy Josephine Griffith National University of Ireland Galway Galway Ireland

ISBN: (数字)9781728182063

ISBN: (纸本)9781728182070

the aim of this research is to develop a more accurate method to detect unreliable news articles without considering the article content. Fake news articles are defined here as those articles which consist entirely of intentionally fabricated unreliable news. the approach taken in this work to detect fake news articles was to consider the type and frequency of HTML tags used in articles. By comparing the counts for HTML tags used in reliable and unreliable online articles, it was found that there are distinct differences between the HTML tags used in the two types of article sources (unreliable or reliable). Two datasets were used with different labelling of ground truth. the first dataset used, NELA 2017 (News Landscape 2017), comprises 136,000 news articles, obtained from 92 different news sources, dated between April 2017 and October 2017. the sources of the articles in NELA 2017 were categorized as either reliable or unreliable, using a media bias fact-checker resource and this was used to label the articles as either reliable or unreliable. the FakeNewsNet dataset is comprised of over 15000 news articles and tweets obtained from a fact-checking website, Gossip Cop, and has preassigned ground truth labels (fake or real). After analysis of NELA 2017, it was found that unreliable articles have 166 tags that were never used by the reliable articles and that there are 8 HTML tags that are used only in the reliable articles. Based on these findings, classification algorithms were employed on the extracted HTML tags. Experimental results show that the KNN classifier (k-nearest neighbors) and the CART classifier (classification and regression tree) give the best performance, having accuracies of around 97% when 10-fold cross-validation was implemented on the NELA 2017 dataset. Accuracies of around 72% were found when the same techniques were applied to the FakeNewsNet dataset. Using the NELA dataset, a comparison was also carried out between this new approach and two o

关键词： Reliability Media Social networking (online) Information integrity HTML Feature extraction programming

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Data-Driven Economic analysis of hydrogen-power coupled integrated energy system

Data-Driven Economic analysis of hydrogen-power coupled inte...

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Data Science and Information Technology (DSIT), international conference on

作者： Zhang Yan Yuan Zi Zhu Zhentao Jin Zhenqiang Wang Mulan Xu Hao Wang Hairong Tan Wenyi School of Economics and Management Nanjing Institute of Technology Nanjing China School of Electric Power Engineering Nanjing Institute of Technology Nanjing China Ministry of Industry and Technology Jiangsu Power Transmisson & Transformation Co.Ltd Nanjing China School of Management Engineering Nanjing Institute of Technology Nanjing China School of Environmental Engineering Nanjing Institute of Technology Nanjing China

ISBN: (数字)9798350384093

ISBN: (纸本)9798350384109

Energy system choices for zero-carbon parks are challenged by the drive towards a low-carbon transition. Traditional wind-power-gas integrated energy systems centred on natural gas and combined heat and power (CHP) are limited by high carbon capture and storage costs. the aim of this study is to assess the economic viability of an innovative hydrogen-electricity coupled integrated energy system centred on hydrogen production from renewable energy sources and to conduct a comparative analysis with conventional systems. the study begins with the collection of historical data on wind speed and solar radiation in the park over a number of years, which is used to analyse the output characteristics of the wind and photovoltaic systems in depth, providing a solid data base for the optimal design of the hydrogen-electric coupled system. Next, a techno-economic model was constructed to meet the park's demand for electricity, heat and transport energy. the capacity of each component in both systems was optimally configured to reduce the annualised cost of the system through a mixed integer linear programming (MILP) approach. Based on this, a comprehensive techno-economic analysis was conducted to compare the economic indicators of the two systems. the results of the analyses show that the hydrogen-electric coupling system has significant economic advantages, including a higher net present value (improved by 70.79%), a shorter payback period (reduced by 6.61%), and a higher internal rate of return. Sensitivity analyses further revealed the main factors affecting the economics of the hydrogen-electric coupling system, including the demand for hydrogen from vehicles in the park, electrolyser costs and wind turbine costs. the findings of this study provide an important reference for planning and decision-making on the energy system of a zero-carbon park and highlight the potential of hydrogen in the future energy supply of the park.

关键词： Economics Couplings Renewable energy sources Costs Hydrogen Data science Wind turbines Mixed integer linear programming Solar radiation Wind forecasting

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GENERATING STYLISTICALLY CONSISTENT PRODUCT FORM DESIGNS USING INTERACTIVE EVOLUTIONARY PARAMETRIC SHAPE GRAMMARS

GENERATING STYLISTICALLY CONSISTENT PRODUCT FORM DESIGNS USI...

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the 7th international conference on Computer-Aided Industrial Design and Conceptual Design (CAID&CD’2006)

作者： Ho Cheong Lee Design Technology Research Centre School of Design The Hong Kong Polytechnic University

Interactive grammar based design systems (IGBDS) are capable of generating large numbers of alternative designs. Prior to the application of IGBDS, a set of rules should be defined based on the theoretical theories and practical experiences in designing the objects, or by analysing the existing sets of objects. However, due to the time constraints in developing theoretical theories, gaining the practical skills of experts is of qualitative in nature and stylistically inconsistent designs to be analysed, it is difficult to systematically derive a set of shape grammar rules in generating designs which fulfil specific requirements. To address this problem, this paper presents an IGBDS enhanced by evolutionary computing to evolve a set of grammar rules for product form design. In this research, the forms of a product are analysed to derive shape features in the form of shape grammar (SG) rules. the rules are then encoded as the code scripts of a genetic algorithm (GA) representation in order to generate new shape grammar rules. the parameters in GA representation are modified by genetic programming (GP) which is regulated by control planning strategies named "GP-GA-SG". the "GP-GA-SG" control planning strategy first defines ways on how the control variables in GP should modify the variables in GA representation. the "GP-GA-SG" control planning strategy then defines ways on how the control variables in GA should modify the variables in SG representation. the SG rules modified by the GA variables define a new combination of shape features for alternative designs. In this way, traditional shape grammar is extended to an interactive context in which generative and evolutionary computing methods are combined. Both product component design as well as product configuration are supported in this framework. In this paper, we describe how this framework is formulated and discuss its potentials in supporting product design, with initial examples showing how the system is intended

关键词： evolutionary shape grammars, product form design, genetic programming, genetic algorithm

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Various Modulation Types Classification on the Air by Convolutional Neural Network 23

Various Modulation Types Classification on the Air by Convol...

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Proceedings of the 7th international conference on Future Networks and Distributed Systems

作者： Yousif I Hammadi Mokhalad Abdulameer Kadhim Alsaeedi Omar Abdulkareem Mahmood Aws Zuhair Sameen Mohammed Saleh Ali Muthanna Ahmed Aziz Ammar Muthanna Dep. of Medical Instruments Engineering Techniques Bilad Alrafidain University College Iraq Department of Communications Engineering University of Diyala Iraq Department of Medical Instrumentation Engineering Techniques Al-Farahidi University Iraq Institute of Computer Technologies and Information Security Southern Federal University Russia Department of computer science Benha university Egypt and International Business Management Department Tashkent State University of Economics Uzbekistan Department of Telecommunication Networks and Data Transmission The Bonch Bruevich Saint Petersburg State University of Telecommunications Russia and Department of Applied Probability and Informatics Peoples Friendship University of Russia Russia

ISBN: (纸本)9798400709036

Deep learning (DL), a relatively recent AI technique, has been successfully applied to the problem of automated modulation categorization (AMC), with promising results. An essential part of developing the spectrum-sensing capabilities needed by software-defined radio is carrying out radio signal classification jobs, which we did in this research by introducing a better deep neural architecture. Different detection techniques were utilized in the literature; however, DL neural networks are recently utilized in this field. Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM) which is one variation of the RNN network, and other techniques are some of the employed DL architectures in the field of AMC. In this paper, Convolutional Neural Network (CNN) model has been built to automatically classify ten-modulation formats correctly. the suggested CNN network is constructed mainly of six-Convolutional layers. the overall number of trainable parameters in the proposed network is 1,757,962. thus, the network accuracy, which was achieved during the training reached more than 90%. Python programming packages have been used to implement the suggested approach using *** platform, which provides wide-range of facilities.

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Address code and arithmetic optimizations for embedded systems

Address code and arithmetic optimizations for embedded syste...

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Asia and South Pacific Design Automation conference

作者： J. Ramanujam S. Krishnamurthy J. Hong M. Kandemir Department of Electrical and Computer Engineering Louisiana State University Baton Rouge LA USA Department of Computer Science and Engineering The Pennsylvania State University University Park PA USA

ISBN: (纸本)0769514413

An important class of problems used widely in both the embedded systems and scientific domains perform memory intensive computations on large data sets. these data sets get to be typically stored in main memory, which means that the compiler needs to generate the address of a memory location in order to store these data elements and generate the same address again when they are subsequently retrieved. this memory address computation is quite expensive, and if it is not performed efficiently, the performance degrades significantly. In this paper, we have developed a new compiler approach for optimizing the memory performance of subscripted or array variables and their address generation in stencil problems that are common in embedded image processing and other applications. Our approach makes use of the observation that in all these stencils, most of the elements accessed are stored close to one other in memory. We try to optimize the stencil codes with a view of reducing both the arithmetic and the address computation overhead. the regularity of the access pattern and the reuse of data elements between successive iterations of the loop body means that there is a common sub-expression between any two successive iterations; these common sub-expressions are difficult to detect using state-of-the-art compiler technology. If we were to store the value of the common sub-expression in a scalar, then for the next iteration, the value in this scalar could be used instead of performing the computation all over again. this greatly reduces the arithmetic overhead. Since we store only one scalar in a register, there is almost no register pressure. Also all array accesses are now replaced by pointer dereferences, where the pointers are incremented after each iteration. this reduces the address computation overhead. Our solution is the only one so far to exploit both scalar conversion and common sub-expressions. Extensive experimental results on several codes show that our approac

关键词： Arithmetic Embedded system Optimizing compilers Random access memory Embedded computing Registers programming profession Computer architecture Information retrieval Degradation

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Templated growth of fullerene C₆₀ crystals by triptycene in polymer blend films

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SUPRAMOLECULAR CHEMISTRY 2012年第7期24卷 526-531页

作者： Lomas, Cole R. Hodgkiss, Justin M. Victoria Univ Wellington Sch Chem & Phys Sci MacDiarmid Inst Adv Mat & Nanotechnol Wellington New Zealand

Supramolecular hosts offer the ability to template the macroscopic assembly of functional guests like fullerene C-60 for electronic device applications. Herein, we investigate the effect of triptycene (TPC) addition to polymer/C-60 blend films. When a transparent polymer matrix is used, we can clearly identify the formation of C-60-TPC co-crystals via fluorescence microscopy, in which blue-shifted fluorescence spectra are observed, and UV-Vis spectroscopy, in which intermolecular charge-transfer bands are suppressed. When C-60 and TPC are blended within a fluorescent-conjugated polymer film that undergoes photo-induced electron transfer to C-60, the composition-dependent evolution of fluorescence quenching shows that TPC organises the nanoscale phase separation of the polymer and fullerene. Our results highlight the potential for supramolecular additives to enhance the properties of organic electronic devices such as solar cells.

关键词： fullerene triptycene polymer film morphology conjugated polymers host-guest complex

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JParEnt: Parallel entropy decoding for JPEG decompression on heterogeneous multicore architectures

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2017年第15期29卷

作者： Sodsong, Wasuwee Jung, Minyoung Park, Jinwoo Burgstaller, Bernd Yonsei Univ Dept Comp Sci Seoul South Korea

the JPEG format employs Huffman codes to compress the entropy data of an image. Huffman codewords are of variable length, which makes parallel entropy decoding a difficult problem. To determine the start position of a codeword in the bitstream, the previous codeword must be decoded first. We present JParEnt, a new approach to parallel entropy decoding for JPEG decompression on heterogeneous multicores. JParEnt conducts JPEG decompression in two steps: (1)an efficient sequential scan of the entropy data on the CPU to determine the start-positions (boundaries) of coefficient blocks in the bitstream, followed by (2)a parallel entropy decoding step on the graphics processing unit (GPU). the block boundary scan constitutes a reinterpretation of the Huffman-coded entropy data to determine codeword boundaries in the bitstream. We introduce a dynamic workload partitioning scheme to account for GPUs of low compute power relative to the CPU. this configuration has become common with the advent of SoCs with integrated graphics processors (IGPs). We leverage additional parallelism through pipelined execution across CPU and GPU. For systems providing a unified address space between CPU and GPU, we employ zero-copy to completely eliminate the data transfer overhead. Our experimental evaluation of JParEnt was conducted on six heterogeneous multicore systems: one server and two desktops with dedicated GPUs, one desktop with an IGP, and two embedded systems. For a selection of more than 1000JPEG images, JParEnt outperforms the SIMD-implementation of the libjpeg-turbo library by up to a factor of 4.3x, and the previously fastest JPEG decompression method for heterogeneous multicores by up to a factor of 2.2x. JParEnt's entropy data scan consumes 45% of the entropy decoding time of libjpeg-turbo on average. Given this new ratio for the sequential part of JPEG decompression, JParEnt achieves up to97% of the maximum attainable speedup (95% on average). On the IGP-based desktop platform,

关键词： JPEG decoding entropy decoding prefix codes heterogeneous multicores GPU programming

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Denoising of Magnetic Resonance Images with Deep Neural Regularizer Driven by Image Prior

Denoising of Magnetic Resonance Images with Deep Neural Regu...

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international conference on Data Science and Advanced Analytics (DSAA)

作者： Yazhou Zhu Xiang Pan Jing Zhu Lihua Li Yuan Liu School of Artificial Intelligence and Computer Science Jiangnan University Wuxi China Wuxi China School of Artificial Intelligence and Computer Science Jiangnan University Wuxi China College of Life Information Science and Instrument Engineering Hangzhou Dianzi University Hangzhou China

ISBN: (数字)9781728182063

ISBN: (纸本)9781728182070

Magnetic resonance imaging (MRI) is an important medical diagnosis technique in clinical diagnosis, while the quality of MR images is always damaged by the noise which is caused in the image acquisition process. In the classic image denoising methods, how to design an excellent regularizer with the prior knowledge of image is the key to solve the denoising problem. In this work, we introduce the deep neural regularizer for the MRI denoising tasks, the deep neural regularizer is made up of neural network structure and objective function, similar to the classic regularizer, both of these two parts are designed with the prior knowledge of image. the proposed neural network has three main parts: encoder network, decoder network and skip connections, the encoder network which consists of five down-sampling blocks is enforced to deeply extract low-resolution or highly-abstract MR image features, similar to the encoder network architecture, the decoder network is made up of five up-sampling blocks and is enforced to restore high-resolution MR image features. To generate more finer image features, we also use skip connections to transmit the abstract information from encoder to decoder directly. the objective function consists of data fidelity term and image quality penalty term, specifically, to enforce the capability of data fidelity term, we add the self-designed image structural consistency calculation to data fidelity term besides only calculating the image consistency over image pixels with mean squared error. Meanwhile, to guide the network generate more clearer image and reduce noise information, with the prior knowledge of image sharpness, an image quality penalty term which calculates the MR image sharpness is also added to the objective function. Experimental results over the simulated MRI data and real clinical data demonstrate the proposed network can achieve superior performance compared with other methods in terms of peak signal to noise ratio, structure simi

关键词： Linear programming Neural networks Noise reduction Magnetic resonance imaging Decoding Task analysis Knowledge engineering

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Preface

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2000年 1955卷

作者： Parigot, Michel Voronkov, Andrei CNRS - Université de Paris 7 case 7012 2 place Jussieu Paris Cedex 05 France University of Manchester Computer Science Department Oxford Rd Manchester United Kingdom

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2020年 12071 LNCS卷 vi页

作者： Méry, Dominique Raschke, Alexander Houdek, Frank Institute of Software Engineering and Programming Languages Ulm University Ulm Germany LORIA Campus Scientifique Université de Lorraine Vandoeuvre-les-Nancy France Research and Development Mercedes-Benz AG Sindelfingen Germany

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