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检索条件"任意字段=10th International Workshop on Algorithms and Data Structures"

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Cognitive parameter adaption in regular control structures using process knowledge for parameter adaption

Cognitive parameter adaption in regular control structures u...

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10th international Conference on Informatics in Control, Automation and Robotics, ICINCO 2013

作者： Schmid, Martin Berger, Simon Reinhart, Gunther Project Group RMV of Fraunhofer IWU Beim Glaspalast 5 Augsburg Germany Institute for Machine Tools and Industrial Management Technical University Munich Munich Germany

ISBN: (纸本)9789898565709

the colour control system of an offset printing machine is one example, where modern information processing technologies allow an improved process control and higher resource efficiency. It is not possible to measure the printing quality during production start. So no regular closed loop control can be used. For better system behaviour a simulation model is integrated to calculate the printing quality at any time. To get an optimal process performance, a high simulation quality must be ensured, which includes a compensation of process simulation inaccuracies as well as variable influences. therefore a cognitive system is installed, which measures the most important influences like the used paper and many other process parameters. After each production the right model parameters will be calculated by identification algorithms. So a data set with influences and parameters is available. For the next production run the best-fitting parameters for the simulation model can be calculated by a Neural Network. Additionally wear and deposits, which change the machine's performance, can be compensated. the simulation accuracy and the process control quality rises, which enables a faster run-up. Savings of paper, ink, energy and time allow an economic application of this control concept.

关键词： Process control

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Alignability equivalence of synchronous sequential circuits 7

Alignability equivalence of synchronous sequential circuits

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7th Annual IEEE international workshop on High-Level Design Validation and Test

作者： Rosenmann, A Hanna, Z Intel IDC Log & Validat Technol Design Technol Div Haifa Israel

ISBN: (纸本)0780376552

Sequential verification is a well known research framework that has attracted many researchers in the academic and industrial worlds during the last few decades. In this framework, initialization of synchronous models is one of the fundamental and challenging research topics that is difficult to solve, especially when talking about large industrial strengths hardware models. Many researchers in this domain such as [10] [8] [9] and others tried to analyze and propose solutions to this problem, however the majority of the,approaches used were based on BDDs and classical reachability analysis methods, which by nature suffer from capacity and complexity limits. When talking about hardware formal, equivalence verification, the initialization issue becomes even more complex especially when trying to verify the logic equivalence of two large industrial circuits. In this note we propose a new adaptive and iterative approach that combines various symbolic simulation techniques and bounded model checking algorithms to initialize sequential circuits for the alignability equivalence verification. the novelty of our method has been employed on complex real life sequential models from Intel lead Pentium processor designs. these methods are already implemented in Intel's sequential verification engine, Insight.

关键词： Boolean functions Circuit simulation data structures Hardware Iterative algorithms Iterative methods Logic circuits Process design Reachability analysis Sequential circuits

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Index structures for information filtering under the vector space model

Index structures for information filtering under the vector ...

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Proceedings of the 10th international Conference on data Engineering

作者： Yan, Tak W. Garcia-Molina, Hector Stanford Univ Stanford United States

ISBN: (纸本)0818654007

With the ever increasing volumes of electronic information generation, users of information systems are facing an information overload. It is desirable to support information filtering as a complement to traditional retrieval mechanism. the number of users, and thus profiles (representing users' long-term interests), handled by an information filtering system is potentially huge, and the system has to process a constant stream of incoming information in a timely fashion. the efficiency of the filtering process is thus an important issue. In this paper, we study what data structures and algorithms can be used to efficiently perform large-scale information filtering under the vector space model, a retrieval model established as being effective. We apply the idea of the standard inverted index to index user profiles. We devise an alternative to the standard inverted index, in which we, instead of indexing every term in a profile, select only the significant ones to index. We evaluate their performance and show that the indexing methods require orders of magnitude fewer I/Os to process a document than when no index is used. We also show that the proposed alternative performs better in terms of I/O and CPU processing time in many cases.

关键词： Signal filtering and prediction

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10th international workshop on Artificial Intelligence and Security (AISec 2017) 17

10th International Workshop on Artificial Intelligence and S...

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24th ACM-SIGSAC Conference on Computer and Communications Security (ACM CCS)

作者： Biggio, Battista Freeman, David Miller, Brad Sinha, Arunesh Univ Cagliari Cagliari Italy Facebook Inc Menlo Pk CA USA Google Inc Mountain View CA USA Univ Michigan Ann Arbor MI 48109 USA

ISBN: (纸本)9781450349468

Artificial Intelligence (AI) and Machine Learning (ML) provide a set of useful analytic and decision-making techniques that are being leveraged by an ever-growing community of practitioners, including many whose applications have security-sensitive elements. However, while security researchers often utilize such techniques to address problems and AI/ML researchers develop techniques for Big data analytics applications, neither community devotes much attention to the other. Within security research, AI/ML components are usually regarded as black-box solvers. Conversely, the learning community seldom considers the security/privacy implications entailed in the application of their algorithms when they are designing them. While these two communities generally focus on different directions, where these two fields do meet, interesting problems appear. Researchers working in this intersection have raised many novel questions for both communities and created a new branch of research known as secure learning. the AISec workshop has become the primary venue for this unique fusion of research.

关键词： Adversarial Learning Secure Learning Malware Detection

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SE-UXNet: A medical imaging segmentation network based on attention mechanism 10

SE-UXNet: A medical imaging segmentation network based on at...

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2020 10th international workshop on Computer Science and Engineering, WCSE 2020

作者： Huang, Zhongyu Hu, Wenxin Zheng, Wei School of Data Science and Engineering East China Normal University China Information Technology services East China Normal University China

ISBN: (纸本)9789811447877

Automatic medical image segmentation is an important part of medical image analysis, and plays an indispensable role in computer-aided diagnosis. Recently, FCN (Fully Convolutional Network) and U-Net have become the main frameworks for image segmentation task. Based on U-Net, the U-Net++ is proposed to predict robust segmentation maps. However, it is difficult for both U-Net and U-Net++ to obtain better results as the model depth grows. In this paper we propose a new medical image segmentation network SE-UXNet using attention mechanism. this model bridges the encoder-decoder models of two different structures to increase model capacity, and recalibrates the weight of the features in the bridge process by SE blocks. Using the Dice coefficient and mIoU as evaluation criteria, we evaluate our model by performing nuclei, liver, prostate, polyps and pulmonary nodule segmentation tasks. the results show that, the Dice coefficients of the above segmentation tasks using SE-UXNet were 92.75%, 90.49%, 90.34%, 95.33% and 73.44%, respectively, all higher compared to results of the U-Net and U-Net++. the experimental results also show that the method we proposed improves the accuracy of medical image segmentation. © WCSE 2020.

关键词： Image segmentation

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data-centric simulation interoperability using the DeST simulation platform

Data-centric simulation interoperability using the DeST simu...

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10th Conference of the international-Building-Performance-Simulation-Association

作者： Yi, Yun Kyu Lee, Jaime Malkawi, Ali M. Wang, Chuang Jiang, Yi Yan, Da Univ Penn TC Chan Ctr Bldg Simulat & Energy Studies Philadelphia PA 19104 USA Tsinghua Univ TC Chan Ctr Bldg Simulat & Energy Studies Beijing 100084 Peoples R China

ISBN: (纸本)9780977170630

though architects are increasingly using building simulation, limitations in the interoperability of simulation domains remain a challenge. Independent simulations often have unique database structures. Incompatibilities between these structures render it difficult to share input and output data with other simulations, making it difficult for a designer to predict multiple aspects of building performance at the same time. the integration of algorithms provides one means of overcoming some of these limitations and of increasing the efficiency and prediction accuracy of performance tools. DeST (Designer's Simulation Toolkit) is a custom environment in which multiple simulation engines are integrated into one system. this paper presents a newly developed IFC (Industry Foundation Classes)-based common database, the advantages and limitations of integration with DeST database structure and its object expansion to various domain integration will be discussed.

关键词： DeST IFC XML integration coupling

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10th international Conference on Similarity Search and Applications, SISAP 2017

10th International Conference on Similarity Search and Appli...

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10th international Conference on Similarity Search and Applications, SISAP 2017

ISBN: (纸本)9783319684734

the proceedings contain 23 papers. the special focus in this conference is on Similarity Search and Applications. the topics include: Cost models and scheduling policies for quality-controlled similarity queries;cache and priority queue based approximation technique for a stream of similarity search queries;a benchmarking tool for approximate nearest neighbor algorithms;sketches with unbalanced bits for similarity search;an extreme-value-theoretic foundation for similarity applications;multivariate analysis and distributional support;high-dimensional simplexes for supermetric search;improving k-NN graph accuracy using local intrinsic dimensionality;dynamic time warping and the (windowed) dog-keeper distance;fast similarity search with the earth mover's distance via feasible initialization and pruning;a new perspective on the tree edit distance;good and bad neighborhood approximations for outlier detection ensembles;scalable similarity search for molecular descriptors;self-indexed motion planning;practical space-efficient data structures for high-dimensional orthogonal range searching;semantic similarity group by operators for metric data;succinct quadtrees for road data;on competitiveness of nearest-neighbor-based music classification;dataset proximity mining for governing the data lake;similarity-based browsing through large lists (extended abstract).;malware discovery using behaviour-based exploration of network traffic and concepts and challenges for effective retrieval considering users, tasks, and data.

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structures of covariance matrix in handwritten character recognition

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Joint IAPR 10th international workshop on Structural and Syntactic Pattern Recognition, SSPR 2004 and 5th international workshop on Statistical Techniques in Pattern Recognition, SPR 2004

作者： Raudys, Šarūnas Iwamura, Masakazu Vilnius Gediminas Technical University Saul tekio 11 Vilnius Lithuania Tohoku University Aoba 05 Aramaki Aoba-ku Sendai980-8579 Japan

ISBN: (纸本)9783540225706

the integrated approach is a classifier established on statistical estimator and artificial neural network. this consists of preliminary data whitening transformation which provides good starting weight vector, and fast training of single layer perceptron (SLP). If sample size is extremely small in comparison with dimensionality, this approach could be ineffective. In the present paper, we consider joint utilization of structures and conventional regularization techniques of sample covariance matrices in order to improve recognition performance in very difficult case where dimensionality and sample size do not differ essentially. the techniques considered reduce a number of parameters estimated from training set. We applied our methodology to handwritten Japanese character recognition and found that combination of the integrated approach, conventional regularization and various structurization methods of covariance matrix outperform other methods including optimized Regularized Discriminant Analysis (RDA). © Springer-Verlag Berlin Heidelberg 2004.

关键词： Covariance matrix

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10th international Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006

作者： Jiyuan, An Chen, Yi-Ping Phoebe School of Information Technology Deakin University Vic. 3125 Australia Australian Research Council Centre in Bioinformatics Australia

ISBN: (纸本)3540465375

Accurate prediction of protein structures is very important for many applications such as drug discovery and biotechnology. Building side chains is an essential to get any reliable prediction of the protein structure for any given a protein main chain conformation. Most of the methods that predict side chain conformations use statistically generated data from known protein structures. It is a computationally intractable problem to search suitable side chains from all possible rotamers simultaneously using information of known protein structures. Reducing the number of possibility is a main issue to predict side chain conformation. this paper proposes an enumeration based similarity search algorithm to predict side chain conformations. By introducing "beam search" technique, a significant number of unrelated side chain rotamers can easily be eliminated. As a result, we can search for suitable residue side chains from all possible side chain conformations. © Springer-Verlag Berlin Heidelberg 2006.

关键词： algorithms

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Make evolutionary multiobjective algorithms scale better with advanced data structures: Van emde boas tree for non-dominated sorting 10th

Make evolutionary multiobjective algorithms scale better wit...

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10th international Conference on Evolutionary Multi-Criterion Optimization, EMO 2019

作者： Buzdalov, Maxim ITMO University 49 Kronverkskiy Avenue Saint Petersburg197101 Russia

ISBN: (纸本)9783030125974

We improve the worst-case time complexity of non-dominated sorting, an operation frequently used in evolutionary multiobjective algorithms, to O(n·(log n)k-2 log log n), where n is the number of solutions, k is the number of objectives, and the random-access memory computation model is assumed. this improvement was possible thanks to the van Emde Boas tree, an "advanced" data structure which stores a set of non-negative integers less than n and supports many queries in O(log log n). this is not only a theoretical improvement, as we also provide an efficient implementation of the van Emde Boas tree, which resulted in a competitive algorithm that scales better than other algorithms when n grows, at least for small numbers of objectives greater than two. © Springer Nature Switzerland AG 2019.

关键词： Forestry

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