WorldWideScience

Sample records for pattern proposal florent

  1. Michiel Florent van Langren and Lunar Naming

    NARCIS (Netherlands)

    van der Krogt, P.C.J.; Ormeling, F.J.

    2014-01-01

    Michiel Florent van Langren produced a lunar map in 1645 in order to present a way to mariners to find their position at sea by observing which craters were either illuminated by solar rays or obscured during the waxing or waning of the moon. This required a detailed map of the moon and in order to

  2. Nele Suisalu otsib aktiivset vaatajat / Tiiu Laks

    Index Scriptorium Estoniae

    Laks, Tiiu, 1984-

    2008-01-01

    Lõuna-Prantsusmaal Montpellier's koreograaf Xavier le Roi juures õppiv Nele Suisalu lavastab koos elukaaslase Florent Hamoniga Tallinnas Kanuti Gildi saalis Augusti tantsufestivali raames tantsuetenduse "Ball"

  3. Proposal for the development of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    Energy Technology Data Exchange (ETDEWEB)

    Deptuch, Gregory; Hoff, Jim; Kwan, Simon; Lipton, Ron; Liu, Ted; Ramberg, Erik; Todri, Aida; Yarema, Ray; /Fermilab; Demarteua, Marcel,; Drake, Gary; Weerts, Harry; /Argonne /Chicago U. /Padua U. /INFN, Padua

    2010-10-01

    Future particle physics experiments looking for rare processes will have no choice but to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare process. The authors propose to develop a 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) chip for HEP applications, to advance the state-of-the-art for pattern recognition and track reconstruction for fast triggering.

  4. Chenu F. (2015). L’évaluation des compétences professionnelles. Une mise à l'épreuve des notions et présupposés théoriques sous-jacents

    OpenAIRE

    Wittorski, Richard

    2016-01-01

    Dans son ouvrage intitulé L’évaluation des compétences professionnelles, Florent Chenu s’intéresse à une question « chargée » tant sur le plan scientifique (définitions multiples du terme compétence, souvent aujourd’hui considéré comme un « mot valise ») que sur le plan social (des enjeux et débats sociaux vifs concernant les modalités d’évaluation des compétences et, au-delà, concernant la façon de les reconnaître dans les milieux du travail). Dans ce contexte particulier, proposer une publi...

  5. A proposed heuristic methodology for searching reloading pattern

    International Nuclear Information System (INIS)

    Choi, K. Y.; Yoon, Y. K.

    1993-01-01

    A new heuristic method for loading pattern search has been developed to overcome shortcomings of the algorithmic approach. To reduce the size of vast solution space, general shuffling rules, a regionwise shuffling method, and a pattern grouping method were introduced. The entropy theory was applied to classify possible loading patterns into groups with similarity between them. The pattern search program was implemented with use of the PROLOG language. A two-group nodal code MEDIUM-2D was used for analysis of power distribution in the core. The above mentioned methodology has been tested to show effectiveness in reducing of solution space down to a few hundred pattern groups. Burnable poison rods were then arranged in each pattern group in accordance with burnable poison distribution rules, which led to further reduction of the solution space to several scores of acceptable pattern groups. The method of maximizing cycle length (MCL) and minimizing power-peaking factor (MPF) were applied to search for specific useful loading patterns from the acceptable pattern groups. Thus, several specific loading patterns that have low power-peaking factor and large cycle length were successfully searched from the selected pattern groups. (Author)

  6. Specialization Patterns

    DEFF Research Database (Denmark)

    Schultz, Ulrik Pagh; Lawall, Julia Laetitia; Consel, Charles

    2000-01-01

    Design patterns offer many advantages for software development, but can introduce inefficiency into the final program. Program specialization can eliminate such overheads, but is most effective when targeted by the user to specific bottlenecks. Consequently, we propose that these concepts...... are complementary. Program specialization can optimize programs written using design patterns, and design patterns provide information about the program structure that can guide specialization. Concretely, we propose specialization patterns, which describe how to apply program specialization to optimize uses...... of design patterns. In this paper, we analyze the specialization opportunities provided by specific uses of design patterns. Based on the analysis of each design pattern, we define the associated specialization pattern. These specialization opportunities can be declared using the specialization classes...

  7. Efficient discovery of risk patterns in medical data.

    Science.gov (United States)

    Li, Jiuyong; Fu, Ada Wai-chee; Fahey, Paul

    2009-01-01

    This paper studies a problem of efficiently discovering risk patterns in medical data. Risk patterns are defined by a statistical metric, relative risk, which has been widely used in epidemiological research. To avoid fruitless search in the complete exploration of risk patterns, we define optimal risk pattern set to exclude superfluous patterns, i.e. complicated patterns with lower relative risk than their corresponding simpler form patterns. We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm. We propose an efficient algorithm for mining optimal risk pattern sets based on this property. We also propose a hierarchical structure to present discovered patterns for the easy perusal by domain experts. The proposed approach is compared with two well-known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application. The proposed method discovers more and better quality risk patterns than a decision tree approach. The decision tree method is not designed for such applications and is inadequate for pattern exploring. The proposed method does not discover a large number of uninteresting superfluous patterns as an association mining approach does. The proposed method is more efficient than an association rule mining method. A real world case study shows that the method reveals some interesting risk patterns to medical practitioners. The proposed method is an efficient approach to explore risk patterns. It quickly identifies cohorts of patients that are vulnerable to a risk outcome from a large data set. The proposed method is useful for exploratory study on large medical data to generate and refine hypotheses. The method is also useful for designing medical surveillance systems.

  8. Polyhedral patterns

    KAUST Repository

    Jiang, Caigui

    2015-10-27

    We study the design and optimization of polyhedral patterns, which are patterns of planar polygonal faces on freeform surfaces. Working with polyhedral patterns is desirable in architectural geometry and industrial design. However, the classical tiling patterns on the plane must take on various shapes in order to faithfully and feasibly approximate curved surfaces. We define and analyze the deformations these tiles must undertake to account for curvature, and discover the symmetries that remain invariant under such deformations. We propose a novel method to regularize polyhedral patterns while maintaining these symmetries into a plethora of aesthetic and feasible patterns.

  9. Mathieu Briancourt, Visite au phalanstère, 1848

    OpenAIRE

    2017-01-01

    Introduction par Florent Perrier Malgré plusieurs rééditions de sa Visite au Phalanstère, malgré sa traduction en allemand puis en anglais, avant 1850, rares sont les informations disponibles sur Mathieu Briancourt (1793-1882), ouvrier teinturier, sinon qu’il fut un inlassable propagateur du fouriérisme jusqu’aux années 1870, ne reniant jamais ses engagements premiers auxquels il consacra plusieurs ouvrages fameux, dont L’Organisation du travail et l’Association. Reprenant un mode de descript...

  10. Caching Patterns and Implementation

    Directory of Open Access Journals (Sweden)

    Octavian Paul ROTARU

    2006-01-01

    Full Text Available Repetitious access to remote resources, usually data, constitutes a bottleneck for many software systems. Caching is a technique that can drastically improve the performance of any database application, by avoiding multiple read operations for the same data. This paper addresses the caching problems from a pattern perspective. Both Caching and caching strategies, like primed and on demand, are presented as patterns and a pattern-based flexible caching implementation is proposed.The Caching pattern provides method of expensive resources reacquisition circumvention. Primed Cache pattern is applied in situations in which the set of required resources, or at least a part of it, can be predicted, while Demand Cache pattern is applied whenever the resources set required cannot be predicted or is unfeasible to be buffered.The advantages and disadvantages of all the caching patterns presented are also discussed, and the lessons learned are applied in the implementation of the pattern-based flexible caching solution proposed.

  11. Specialization Patterns

    OpenAIRE

    Schultz , Ulrik Pagh; Lawall , Julia ,; Consel , Charles

    1999-01-01

    Design patterns offer numerous advantages for software development, but can introduce inefficiency into the finished program. Program specialization can eliminate such overheads, but is most effective when targeted by the user to specific bottlenecks. Consequently, we propose to consider program specialization and design patterns as complementary concepts. On the one hand, program specialization can optimize object-oriented programs written using design patterns. On the other hand, design pat...

  12. Post-decomposition optimizations using pattern matching and rule-based clustering for multi-patterning technology

    Science.gov (United States)

    Wang, Lynn T.-N.; Madhavan, Sriram

    2018-03-01

    A pattern matching and rule-based polygon clustering methodology with DFM scoring is proposed to detect decomposition-induced manufacturability detractors and fix the layout designs prior to manufacturing. A pattern matcher scans the layout for pre-characterized patterns from a library. If a pattern were detected, rule-based clustering identifies the neighboring polygons that interact with those captured by the pattern. Then, DFM scores are computed for the possible layout fixes: the fix with the best score is applied. The proposed methodology was applied to two 20nm products with a chip area of 11 mm2 on the metal 2 layer. All the hotspots were resolved. The number of DFM spacing violations decreased by 7-15%.

  13. Design Pattern Canvas: An Introduction to Unified Serious Game Design Patterns

    Directory of Open Access Journals (Sweden)

    Gregor Zavcer

    2014-10-01

    Full Text Available The aim of this article is to start a dialogue and search for a unified game design tool within the game design and research community. As a possible direction, presented paper outlines the practice and importance of design pattern use in serious game development and argues that design patterns can make serious game development more efficient by enabling knowledge exchange and better communication between different stakeholders. Furthermore, the use of design patterns provides a foundation for structured research and analysis of games. In order to help advance the state of game design the paper proposes a new method – the Serious Games Design Pattern Canvas or shorter Design Pattern Canvas (DPC. DPC is a design template for developing new or documenting existing (serious game design patterns. It is a visual chart with elements describing a pattern's purpose, mechanic, audience, consequences, collected data, related research and ethical considerations. It assists game designer in aligning their activities by illustrating patterns characteristics and potential trade-offs. One of the goals of the DPC is to either help break larger game design problems into smaller pieces or assist in a bottom up approach of designing serious games. It is important to note, that the paper proposes the first step for co-creation of a game design tool and further research and validation of the DPC is needed.

  14. Eliciting design patterns for e-learning systems

    Science.gov (United States)

    Retalis, Symeon; Georgiakakis, Petros; Dimitriadis, Yannis

    2006-06-01

    Design pattern creation, especially in the e-learning domain, is a highly complex process that has not been sufficiently studied and formalized. In this paper, we propose a systematic pattern development cycle, whose most important aspects focus on reverse engineering of existing systems in order to elicit features that are cross-validated through the use of appropriate, authentic scenarios. However, an iterative pattern process is proposed that takes advantage of multiple data sources, thus emphasizing a holistic view of the teaching learning processes. The proposed schema of pattern mining has been extensively validated for Asynchronous Network Supported Collaborative Learning (ANSCL) systems, as well as for other types of tools in a variety of scenarios, with promising results.

  15. Domain knowledge patterns in pedagogical diagnostics

    Science.gov (United States)

    Miarka, Rostislav

    2017-07-01

    This paper shows a proposal of representation of knowledge patterns in RDF(S) language. Knowledge patterns are used for reuse of knowledge. They can be divided into two groups - Top-level knowledge patterns and Domain knowledge patterns. Pedagogical diagnostics is aimed at testing of knowledge of students at primary and secondary school. An example of domain knowledge pattern from pedagogical diagnostics is part of this paper.

  16. Un programa iconológico perdido, recuperado : pinturas de la iglesia nueva de Guadalupe, de Juan García de Miranda

    Directory of Open Access Journals (Sweden)

    María Teresa Jiménez Priego

    1992-01-01

    Full Text Available La iglesia nueva de Guadalupe constituyó uno de ios conjuntos más reveladores, desde el punto de vista artístico, programático y significativo, de la influencia y ejercicio del patrocinio de un mecenas. Este conjunto es creado bajo los auspicios económicos e intelectuales de don Pedro Ñuño Manuel Florentín Colón y Portugal, Duque de Veragua, Almirante y Adelantado de las Indias y virrey de Navarra, Sicilia y Cerdeña, además de ser ministro del monarca Felipe V.

  17. Combination of oriented partial differential equation and shearlet transform for denoising in electronic speckle pattern interferometry fringe patterns.

    Science.gov (United States)

    Xu, Wenjun; Tang, Chen; Gu, Fan; Cheng, Jiajia

    2017-04-01

    It is a key step to remove the massive speckle noise in electronic speckle pattern interferometry (ESPI) fringe patterns. In the spatial-domain filtering methods, oriented partial differential equations have been demonstrated to be a powerful tool. In the transform-domain filtering methods, the shearlet transform is a state-of-the-art method. In this paper, we propose a filtering method for ESPI fringe patterns denoising, which is a combination of second-order oriented partial differential equation (SOOPDE) and the shearlet transform, named SOOPDE-Shearlet. Here, the shearlet transform is introduced into the ESPI fringe patterns denoising for the first time. This combination takes advantage of the fact that the spatial-domain filtering method SOOPDE and the transform-domain filtering method shearlet transform benefit from each other. We test the proposed SOOPDE-Shearlet on five experimentally obtained ESPI fringe patterns with poor quality and compare our method with SOOPDE, shearlet transform, windowed Fourier filtering (WFF), and coherence-enhancing diffusion (CEDPDE). Among them, WFF and CEDPDE are the state-of-the-art methods for ESPI fringe patterns denoising in transform domain and spatial domain, respectively. The experimental results have demonstrated the good performance of the proposed SOOPDE-Shearlet.

  18. Optimization of patterns of control bars using neural networks

    International Nuclear Information System (INIS)

    Mejia S, D.M.; Ortiz S, J.J.

    2005-01-01

    In this work the RENOPBC system that is based on a recurrent multi state neural network, for the optimization of patterns of control bars in a cycle of balance of a boiling water reactor (BWR for their initials in English) is presented. The design of patterns of bars is based on the execution of operation thermal limits, to maintain criticizes the reactor and that the axial profile of power is adjusted to one predetermined along several steps of burnt. The patterns of control bars proposed by the system are comparable to those proposed by human experts with many hour-man of experience. These results are compared with those proposed by other techniques as genetic algorithms, colonies of ants and tabu search for the same operation cycle. As consequence it is appreciated that the proposed patterns of control bars, have bigger operation easiness that those proposed by the other techniques. (Author)

  19. A SIMPLE HETERODYNE TEMPORAL SPECKLE-PATTERN INTERFEROMETER

    International Nuclear Information System (INIS)

    Wong, W. O.; Gao, Z.; Lu, J.

    2010-01-01

    A common light path design of heterodyne speckle pattern interferometer based on temporal speckle pattern interferometry is proposed for non-contact, full-field and real-time continuous displacement measurement. Double frequency laser is produced by rotating a half wave plate. An experiment was carried out to measure the dynamic displacement of a cantilever plate for testing the proposed common path heterodyne speckle pattern interferometer. The accuracy of displacement measurement was checked by measuring the motion at the mid-point of the plate with a point displacement sensor.

  20. Completed Local Ternary Pattern for Rotation Invariant Texture Classification

    Directory of Open Access Journals (Sweden)

    Taha H. Rassem

    2014-01-01

    Full Text Available Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP and the Completed Local Binary Count (CLBC, have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP drawbacks. The LBP is sensitive to noise, and different patterns of LBP may be classified into the same class that reduces its discriminating property. Although, the Local Ternary Pattern (LTP is proposed to be more robust to noise than LBP, however, the latter’s weakness may appear with the LTP as well as with LBP. In this paper, a novel completed modeling of the Local Ternary Pattern (LTP operator is proposed to overcome both LBP drawbacks, and an associated completed Local Ternary Pattern (CLTP scheme is developed for rotation invariant texture classification. The experimental results using four different texture databases show that the proposed CLTP achieved an impressive classification accuracy as compared to the CLBP and CLBC descriptors.

  1. Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

    Science.gov (United States)

    Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

    2016-06-01

    Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  2. Chopper model of pattern recognition

    NARCIS (Netherlands)

    van Hemmen, J.L.; Enter, A.C.D. van

    A simple model is proposed that allows an efficient storage and retrieval of random patterns. Also correlated patterns can be handled. The data are stored in an Ising-spin system with ferromagnetic interactions between all the spins and the main idea is to "chop" the system along the boundaries

  3. Fusion of fuzzy statistical distributions for classification of thyroid ultrasound patterns.

    Science.gov (United States)

    Iakovidis, Dimitris K; Keramidas, Eystratios G; Maroulis, Dimitris

    2010-09-01

    This paper proposes a novel approach for thyroid ultrasound pattern representation. Considering that texture and echogenicity are correlated with thyroid malignancy, the proposed approach encodes these sonographic features via a noise-resistant representation. This representation is suitable for the discrimination of nodules of high malignancy risk from normal thyroid parenchyma. The material used in this study includes a total of 250 thyroid ultrasound patterns obtained from 75 patients in Greece. The patterns are represented by fused vectors of fuzzy features. Ultrasound texture is represented by fuzzy local binary patterns, whereas echogenicity is represented by fuzzy intensity histograms. The encoded thyroid ultrasound patterns are discriminated by support vector classifiers. The proposed approach was comprehensively evaluated using receiver operating characteristics (ROCs). The results show that the proposed fusion scheme outperforms previous thyroid ultrasound pattern representation methods proposed in the literature. The best classification accuracy was obtained with a polynomial kernel support vector machine, and reached 97.5% as estimated by the area under the ROC curve. The fusion of fuzzy local binary patterns and fuzzy grey-level histogram features is more effective than the state of the art approaches for the representation of thyroid ultrasound patterns and can be effectively utilized for the detection of nodules of high malignancy risk in the context of an intelligent medical system. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  4. Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment

    Science.gov (United States)

    Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

    2014-01-01

    Context Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. Objective This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. Method The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. Results The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. Conclusion The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns. PMID:25243670

  5. Design pattern mining using distributed learning automata and DNA sequence alignment.

    Directory of Open Access Journals (Sweden)

    Mansour Esmaeilpour

    Full Text Available CONTEXT: Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. OBJECTIVE: This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA and deoxyribonucleic acid (DNA sequences alignment. METHOD: The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. RESULTS: The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. CONCLUSION: The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.

  6. Design pattern mining using distributed learning automata and DNA sequence alignment.

    Science.gov (United States)

    Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

    2014-01-01

    Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.

  7. Procedural generation of aesthetic patterns from dynamics and iteration processes

    Directory of Open Access Journals (Sweden)

    Gdawiec Krzysztof

    2017-12-01

    Full Text Available Aesthetic patterns are widely used nowadays, e.g., in jewellery design, carpet design, as textures and patterns on wallpapers, etc. Most of the work during the design stage is carried out by a designer manually. Therefore, it is highly useful to develop methods for aesthetic pattern generation. In this paper, we present methods for generating aesthetic patterns using the dynamics of a discrete dynamical system. The presented methods are based on the use of various iteration processes from fixed point theory (Mann, S, Noor, etc. and the application of an affine combination of these iterations. Moreover, we propose new convergence tests that enrich the obtained patterns. The proposed methods generate patterns in a procedural way and can be easily implemented on the GPU. The presented examples show that using the proposed methods we are able to obtain a variety of interesting patterns. Moreover, the numerical examples show that the use of the GPU implementation with shaders allows the generation of patterns in real time and the speed-up (compared with a CPU implementation ranges from about 1000 to 2500 times.

  8. Absolute phase map recovery of two fringe patterns with flexible selection of fringe wavelengths.

    Science.gov (United States)

    Long, Jiale; Xi, Jiangtao; Zhu, Ming; Cheng, Wenqing; Cheng, Rui; Li, Zhongwei; Shi, Yusheng

    2014-03-20

    A novel approach is proposed to unwrap the phase maps of two fringe patterns in fringe pattern projection-based profilometry. In contrast to existing techniques, where spatial frequencies (i.e., the number of fringes on a pattern) of the two fringe patterns must be integers and coprime, the proposed method is applicable for any two fringe patterns with different fringe wavelengths (i.e., the number of pixels in a fringe) and thus provides more flexibility in the use of fringe patterns. Moreover, compared to the existing techniques, the proposed method is simpler in its implementation and has better antierror capability. Theoretical analysis and experiment results are presented to confirm the effectiveness of the proposed method.

  9. Mining continuous activity patterns from animal trajectory data

    Science.gov (United States)

    Wang, Y.; Luo, Ze; Baoping, Yan; Takekawa, John Y.; Prosser, Diann J.; Newman, Scott H.

    2014-01-01

    The increasing availability of animal tracking data brings us opportunities and challenges to intuitively understand the mechanisms of animal activities. In this paper, we aim to discover animal movement patterns from animal trajectory data. In particular, we propose a notion of continuous activity pattern as the concise representation of underlying similar spatio-temporal movements, and develop an extension and refinement framework to discover the patterns. We first preprocess the trajectories into significant semantic locations with time property. Then, we apply a projection-based approach to generate candidate patterns and refine them to generate true patterns. A sequence graph structure and a simple and effective processing strategy is further developed to reduce the computational overhead. The proposed approaches are extensively validated on both real GPS datasets and large synthetic datasets.

  10. An algorithm, implementation and execution ontology design pattern

    NARCIS (Netherlands)

    Lawrynowicz, A.; Esteves, D.; Panov, P.; Soru, T.; Dzeroski, S.; Vanschoren, J.

    2016-01-01

    This paper describes an ontology design pattern for modeling algorithms, their implementations and executions. This pattern is derived from the research results on data mining/machine learning ontologies, but is more generic. We argue that the proposed pattern will foster the development of

  11. Pattern Laser Annealing by a Pulsed Laser

    Science.gov (United States)

    Komiya, Yoshio; Hoh, Koichiro; Murakami, Koichi; Takahashi, Tetsuo; Tarui, Yasuo

    1981-10-01

    Preliminary experiments with contact-type pattern laser annealing were made for local polycrystallization of a-Si, local evaporation of a-Si and local formation of Ni-Si alloy. These experiments showed that the mask patterns can be replicated as annealed regions with a resolution of a few microns on substrates. To overcome shortcomings due to the contact type pattern annealing, a projection type reduction pattern laser annealing system is proposed for resistless low temperature pattern forming processes.

  12. A novel approach to describing and detecting performance anti-patterns

    Science.gov (United States)

    Sheng, Jinfang; Wang, Yihan; Hu, Peipei; Wang, Bin

    2017-08-01

    Anti-pattern, as an extension to pattern, describes a widely used poor solution which can bring negative influence to application systems. Aiming at the shortcomings of the existing anti-pattern descriptions, an anti-pattern description method based on first order predicate is proposed. This method synthesizes anti-pattern forms and symptoms, which makes the description more accurate and has good scalability and versatility as well. In order to improve the accuracy of anti-pattern detection, a Bayesian classification method is applied in validation for detection results, which can reduce false negatives and false positives of anti-pattern detection. Finally, the proposed approach in this paper is applied to a small e-commerce system, the feasibility and effectiveness of the approach is demonstrated further through experiments.

  13. Electrode pattern design for GaAs betavoltaic batteries

    International Nuclear Information System (INIS)

    Chen Haiyang; Yin Jianhua; Li Darang

    2011-01-01

    The sensitivities of betavoltaic batteries and photovoltaic batteries to series and parallel resistance are studied. Based on the study, an electrode pattern design principle of GaAs betavoltaic batteries is proposed. GaAs PIN junctions with and without the proposed electrode pattern are fabricated and measured under the illumination of 63 Ni. Results show that the proposed electrode can reduce the backscattering and shadowing for the beta particles from 63 Ni to increase the GaAs betavoltaic battery short circuit currents effectively but has little impact on the fill factors and ideal factors.

  14. Modelling Behaviour Patterns of Pedestrians for Mobile Robot Trajectory Generation

    Directory of Open Access Journals (Sweden)

    Yusuke Tamura

    2013-08-01

    Full Text Available Robots are expected to be operated in environments where they coexist with humans, such as shopping malls and offices. Both the safety and efficiency of a robot are necessary in such environments. To achieve this, pedestrian behaviour should be accurately predicted. However, the behaviour is uncertain and cannot be easily predicted. This paper proposes a probabilistic method of determining pedestrian trajectory based on an estimation of pedestrian behaviour patterns. The proposed method focuses on the specific behaviour of pedestrians around the robot. The proposed model classifies the behaviours of pedestrians into definite patterns. The behaviour patterns, distribution of the positions of the pedestrians, and the direction of each behaviour pattern are determined by learning through observation. The behaviour pattern of a pedestrian can be estimated correctly by a likelihood calculation. A robot decides to move with an emphasis on either safety or efficiency depending on the result of the pattern estimation. If the pedestrian trajectory follows a known behaviour pattern, the robot would move with an emphasis on efficiency because the pedestrian trajectory can be predicted. Otherwise, the robot would move with an emphasis on safety because the behaviour of the pedestrian cannot be predicted. Experimental results show that robots can move efficiently and safely when passing by a pedestrian by applying the proposed method.

  15. Proximity effect on patterning characteristics of hole patterns in synchrotron radiation lithography

    International Nuclear Information System (INIS)

    Somemura, Yoh; Deguchi, Kimiyoshi; Miyoshi, Kazunori

    1994-01-01

    This paper reports the results of analyzing the proximity effect on the patterning characteristics for plural neighboring hole patterns in synchrotron radiation lithography. Fresnel diffraction simulation was used and pattern replication experiments were performed with pattern pitch, proximity gap, and mask contrast as parameters. Even when the pattern pitch (hole:space) is 1:1, pattern sizes down to 0.2 μm can be replicated with a large dose margin under a large proximity gap condition up to 40 μm, irrespective of the mask contrast. A low-contrast (2.5) mask has an advantage over the conventional-contrast (7) mask in that it allows the use of a larger proximity gap when replicating hole patterns with a size of 0.1-0.2 μm. Moreover, the phase-shifting mask we previously proposed improves the exposure latitude and widens the proximity gap, so that it is possible to use a 20-μm gap to replicate 0.1-μm hole patterns for a pitch of 1:1 and to use a 30-μm gap for a pitch of 1:2. (author)

  16. The Reification of Patterns in the Design of Description-Driven Systems

    CERN Document Server

    Le Goff, J M; Kovács, Z; McClatchey, R

    2001-01-01

    To address the issues of reusability and evolvability in designing self- describing systems, this paper proposes a pattern-based, object-oriented, description-driven system architecture. The proposed architecture embodies four pillars - first, the adoption of a multi-layered meta-modeling architecture and reflective meta-level architecture, second, the identification of four data modeling relationships that must be made explicit such that they can be examined and modified dynamically, third, the identification of five design patterns which have emerged from practice and have proved essential in providing reusable building blocks for data management, and fourth, the encoding of the structural properties of the five design patterns by means of one pattern, the Graph pattern. The CRISTAL research project served as the basis onto which the pattern-based meta-object approach has been applied. The proposed architecture allows the realization of reusability and adaptability, and is fundamental in the specification o...

  17. Finger vein recognition using local line binary pattern.

    Science.gov (United States)

    Rosdi, Bakhtiar Affendi; Shing, Chai Wuh; Suandi, Shahrel Azmin

    2011-01-01

    In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as fingerprint and palm print because the features are inside the human body. In the proposed method, a new texture descriptor called local line binary pattern (LLBP) is utilized as feature extraction technique. The neighbourhood shape in LLBP is a straight line, unlike in local binary pattern (LBP) which is a square shape. Experimental results show that the proposed method using LLBP has better performance than the previous methods using LBP and local derivative pattern (LDP).

  18. Stochastic optimization of loading pattern for PWR

    International Nuclear Information System (INIS)

    Smuc, T.; Pevec, D.

    1994-01-01

    The application of stochastic optimization methods in solving in-core fuel management problems is restrained by the need for a large number of proposed solutions loading patterns, if a high quality final solution is wanted. Proposed loading patterns have to be evaluated by core neutronics simulator, which can impose unrealistic computer time requirements. A new loading pattern optimization code Monte Carlo Loading Pattern Search has been developed by coupling the simulated annealing optimization algorithm with a fast one-and-a-half dimensional core depletion simulator. The structure of the optimization method provides more efficient performance and allows the user to empty precious experience in the search process, thus reducing the search space size. Hereinafter, we discuss the characteristics of the method and illustrate them on the results obtained by solving the PWR reload problem. (authors). 7 refs., 1 tab., 1 fig

  19. A novel double patterning approach for 30nm dense holes

    Science.gov (United States)

    Hsu, Dennis Shu-Hao; Wang, Walter; Hsieh, Wei-Hsien; Huang, Chun-Yen; Wu, Wen-Bin; Shih, Chiang-Lin; Shih, Steven

    2011-04-01

    Double Patterning Technology (DPT) was commonly accepted as the major workhorse beyond water immersion lithography for sub-38nm half-pitch line patterning before the EUV production. For dense hole patterning, classical DPT employs self-aligned spacer deposition and uses the intersection of horizontal and vertical lines to define the desired hole patterns. However, the increase in manufacturing cost and process complexity is tremendous. Several innovative approaches have been proposed and experimented to address the manufacturing and technical challenges. A novel process of double patterned pillars combined image reverse will be proposed for the realization of low cost dense holes in 30nm node DRAM. The nature of pillar formation lithography provides much better optical contrast compared to the counterpart hole patterning with similar CD requirements. By the utilization of a reliable freezing process, double patterned pillars can be readily implemented. A novel image reverse process at the last stage defines the hole patterns with high fidelity. In this paper, several freezing processes for the construction of the double patterned pillars were tested and compared, and 30nm double patterning pillars were demonstrated successfully. A variety of different image reverse processes will be investigated and discussed for their pros and cons. An economic approach with the optimized lithography performance will be proposed for the application of 30nm DRAM node.

  20. Output-Sensitive Pattern Extraction in Sequences

    DEFF Research Database (Denmark)

    Grossi, Roberto; Menconi, Giulia; Pisanti, Nadia

    2014-01-01

    Genomic Analysis, Plagiarism Detection, Data Mining, Intrusion Detection, Spam Fighting and Time Series Analysis are just some examples of applications where extraction of recurring patterns in sequences of objects is one of the main computational challenges. Several notions of patterns exist...... or extend them causes a loss of significant information (where the number of occurrences changes). Output-sensitive algorithms have been proposed to enumerate and list these patterns, taking polynomial time O(nc) per pattern for constant c > 1, which is impractical for massive sequences of very large length...

  1. External beam radiation for retinoblastoma: Results, patterns of failure, and a proposal for treatment guidelines

    International Nuclear Information System (INIS)

    Hernandez, J. Carlos; Brady, Luther W.; Shields, Jerry A.; Shields, Carol L.; Potter, Patrick de; Karlsson, Ulf L.; Markoe, Arnold M.; Amendola, Beatriz E.; Singh, Arun

    1996-01-01

    Purpose: To analyze treatment results and patterns of failure following external beam radiation for retinoblastoma and propose treatment guidelines according to specific clinical variables. Methods and Materials: We analyzed 27 patients (34 eyes) with retinoblastoma who received external beam radiation as initial treatment at Hahnemann University Hospital from October 1980 to December 1991 and have been followed for at least 1 year. Of the 34 eyes, 14 were Groups I-II (Reese-Ellsworth classification), 7 were Group III, and 13 were Groups IV-V. Doses ranged from 34.5-49.5 Gy (mean 44.3 Gy, median 45 Gy) in 1.5-2.0 Gy fractions generally delivered through anterior and lateral wedged pair fields. Results: At a mean follow up of 35.2 months (range 12-93 months), local tumor control was obtained in 44% (15 out of 34) of eyes with external beam radiation alone. Salvage therapy (plaque brachytherapy, cryotherapy, and/or photocoagulation) controlled an additional 10 eyes (29.5%), so that overall ocular survival has been 73.5%. Local tumor control with external beam radiotherapy alone was obtained in 78.5% (11 out of 14) of eyes in Groups I-II, but in only 20% (4 out of 20) of eyes in Groups III-V. A total of 67 existing tumors were identified prior to treatment in the 34 treated eyes and local control with external beam radiation alone was obtained in 87% (46 out of 53) of tumors measuring 15 mm or less and in 50% (7 out of 14) of tumors measuring more than 15 mm. When analyzing patterns of failure in the 19 eyes that relapsed, a total of 28 failure sites were identified and consisted of progression of vitreous seeds in seven instances (25% of failure sites) recurrences from previously existing tumors in 10 instances (36% of failure sites) and development of new tumors in previously uninvolved retina in 11 instances (39% of failure sites). Conclusions: 1) We find that external beam radiation to a dose of 45 Gy in fractions of 1.5 to 2.0 Gy provides adequate tumor control

  2. Quantum pattern recognition with multi-neuron interactions

    Science.gov (United States)

    Fard, E. Rezaei; Aghayar, K.; Amniat-Talab, M.

    2018-03-01

    We present a quantum neural network with multi-neuron interactions for pattern recognition tasks by a combination of extended classic Hopfield network and adiabatic quantum computation. This scheme can be used as an associative memory to retrieve partial patterns with any number of unknown bits. Also, we propose a preprocessing approach to classifying the pattern space S to suppress spurious patterns. The results of pattern clustering show that for pattern association, the number of weights (η ) should equal the numbers of unknown bits in the input pattern ( d). It is also remarkable that associative memory function depends on the location of unknown bits apart from the d and load parameter α.

  3. Hand biometric recognition based on fused hand geometry and vascular patterns.

    Science.gov (United States)

    Park, GiTae; Kim, Soowon

    2013-02-28

    A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%.

  4. Finger Vein Recognition Using Local Line Binary Pattern

    Directory of Open Access Journals (Sweden)

    Bakhtiar Affendi Rosdi

    2011-11-01

    Full Text Available In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as fingerprint and palm print because the features are inside the human body. In the proposed method, a new texture descriptor called local line binary pattern (LLBP is utilized as feature extraction technique. The neighbourhood shape in LLBP is a straight line, unlike in local binary pattern (LBP which is a square shape. Experimental results show that the proposed method using LLBP has better performance than the previous methods using LBP and local derivative pattern (LDP.

  5. Finger Vein Recognition Using Local Line Binary Pattern

    Science.gov (United States)

    Rosdi, Bakhtiar Affendi; Shing, Chai Wuh; Suandi, Shahrel Azmin

    2011-01-01

    In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as fingerprint and palm print because the features are inside the human body. In the proposed method, a new texture descriptor called local line binary pattern (LLBP) is utilized as feature extraction technique. The neighbourhood shape in LLBP is a straight line, unlike in local binary pattern (LBP) which is a square shape. Experimental results show that the proposed method using LLBP has better performance than the previous methods using LBP and local derivative pattern (LDP). PMID:22247670

  6. Using excitation patterns to predict auditory masking

    NARCIS (Netherlands)

    Heijden, van der M.L.; Kohlrausch, A.G.

    1992-01-01

    We investigated how well auditory masking can be predicted from excitation patterns. For this purpose, a quantitative model proposed by Moore and Glasberg (1987) and Glasberg and Moore (1990) was used to calculate excitation patterns evoked by stationary sounds. We performed simulations of a number

  7. Zips : mining compressing sequential patterns in streams

    NARCIS (Netherlands)

    Hoang, T.L.; Calders, T.G.K.; Yang, J.; Mörchen, F.; Fradkin, D.; Chau, D.H.; Vreeken, J.; Leeuwen, van M.; Faloutsos, C.

    2013-01-01

    We propose a streaming algorithm, based on the minimal description length (MDL) principle, for extracting non-redundant sequential patterns. For static databases, the MDL-based approach that selects patterns based on their capacity to compress data rather than their frequency, was shown to be

  8. Personal continuous route pattern mining

    Institute of Scientific and Technical Information of China (English)

    Qian YE; Ling CHEN; Gen-cai CHEN

    2009-01-01

    In the daily life, people often repeat regular routes in certain periods. In this paper, a mining system is developed to find the continuous route patterns of personal past trips. In order to count the diversity of personal moving status, the mining system employs the adaptive GPS data recording and five data filters to guarantee the clean trips data. The mining system uses a client/server architecture to protect personal privacy and to reduce the computational load. The server conducts the main mining procedure but with insufficient information to recover real personal routes. In order to improve the scalability of sequential pattern mining, a novel pattern mining algorithm, continuous route pattern mining (CRPM), is proposed. This algorithm can tolerate the different disturbances in real routes and extract the frequent patterns. Experimental results based on nine persons' trips show that CRPM can extract more than two times longer route patterns than the traditional route pattern mining algorithms.

  9. Hand Biometric Recognition Based on Fused Hand Geometry and Vascular Patterns

    Science.gov (United States)

    Park, GiTae; Kim, Soowon

    2013-01-01

    A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%. PMID:23449119

  10. Learning-induced pattern classification in a chaotic neural network

    International Nuclear Information System (INIS)

    Li, Yang; Zhu, Ping; Xie, Xiaoping; He, Guoguang; Aihara, Kazuyuki

    2012-01-01

    In this Letter, we propose a Hebbian learning rule with passive forgetting (HLRPF) for use in a chaotic neural network (CNN). We then define the indices based on the Euclidean distance to investigate the evolution of the weights in a simplified way. Numerical simulations demonstrate that, under suitable external stimulations, the CNN with the proposed HLRPF acts as a fuzzy-like pattern classifier that performs much better than an ordinary CNN. The results imply relationship between learning and recognition. -- Highlights: ► Proposing a Hebbian learning rule with passive forgetting (HLRPF). ► Defining indices to investigate the evolution of the weights simply. ► The chaotic neural network with HLRPF acts as a fuzzy-like pattern classifier. ► The pattern classifier ability of the network is improved much.

  11. Image decomposition model Shearlet-Hilbert-L2 with better performance for denoising in ESPI fringe patterns.

    Science.gov (United States)

    Xu, Wenjun; Tang, Chen; Su, Yonggang; Li, Biyuan; Lei, Zhenkun

    2018-02-01

    In this paper, we propose an image decomposition model Shearlet-Hilbert-L 2 with better performance for denoising in electronic speckle pattern interferometry (ESPI) fringe patterns. In our model, the low-density fringes, high-density fringes, and noise are, respectively, described by shearlet smoothness spaces, adaptive Hilbert space, and L 2 space and processed individually. Because the shearlet transform has superior directional sensitivity, our proposed Shearlet-Hilbert-L 2 model achieves commendable filtering results for various types of ESPI fringe patterns, including uniform density fringe patterns, moderately variable density fringe patterns, and greatly variable density fringe patterns. We evaluate the performance of our proposed Shearlet-Hilbert-L 2 model via application to two computer-simulated and nine experimentally obtained ESPI fringe patterns with various densities and poor quality. Furthermore, we compare our proposed model with windowed Fourier filtering and coherence-enhancing diffusion, both of which are the state-of-the-art methods for ESPI fringe patterns denoising in transform domain and spatial domain, respectively. We also compare our proposed model with the previous image decomposition model BL-Hilbert-L 2 .

  12. Reduct Driven Pattern Extraction from Clusters

    Directory of Open Access Journals (Sweden)

    Shuchita Upadhyaya

    2009-03-01

    Full Text Available Clustering algorithms give general description of clusters, listing number of clusters and member entities in those clusters. However, these algorithms lack in generating cluster description in the form of pattern. From data mining perspective, pattern learning from clusters is as important as cluster finding. In the proposed approach, reduct derived from rough set theory is employed for pattern formulation. Further, reduct are the set of attributes which distinguishes the entities in a homogenous cluster, hence these can be clear cut removed from the same. Remaining attributes are then ranked for their contribution in the cluster. Pattern is formulated with the conjunction of most contributing attributes such that pattern distinctively describes the cluster with minimum error.

  13. [Physical activity patterns of school adolescents: Validity, reliability and percentiles proposal for their evaluation].

    Science.gov (United States)

    Cossío Bolaños, Marco; Méndez Cornejo, Jorge; Luarte Rocha, Cristian; Vargas Vitoria, Rodrigo; Canqui Flores, Bernabé; Gomez Campos, Rossana

    2017-02-01

    Regular physical activity (PA) during childhood and adolescence is important for the prevention of non-communicable diseases and their risk factors. To validate a questionnaire for measuring patterns of PA, verify the reliability, comparing the levels of PA aligned with chronological and biological age, and to develop percentile curves to assess PA levels depending on biological maturation. Descriptive cross-sectional study was performed on a sample non-probabilistic quota of 3,176 Chilean adolescents (1685 males and 1491 females), with a mean age range from 10.0 to 18.9 years. An analysis was performed on, weight, standing and sitting height. The biological age through the years of peak growth rate and chronological age in years was determined. Body Mass Index was calculated and a survey of PA was applied. The LMS method was used to develop percentiles. The values for the confirmatory analysis showed saturations between 0.517 and 0.653. The value of adequacy of Kaiser-Meyer-Olkin (KMO) was 0.879 and with 70.8% of the variance explained. The Cronbach alpha values ranged from 0.81 to 0.86. There were differences between the genders when aligned chronological age. There were no differences when aligned by biological age. Percentiles are proposed to classify the PA of adolescents of both genders according to biological age and sex. The questionnaire used was valid and reliable, plus the PA should be evaluated by biological age. These findings led to the development of percentiles to assess PA according to biological age and gender.

  14. A Pattern Language for the Evolution of Component-based Software Architectures

    DEFF Research Database (Denmark)

    Ahmad, Aakash; Jamshidi, Pooyan; Pahl, Claus

    2013-01-01

    Modern software systems are prone to a continuous evolution under frequently varying requirements. Architecture-centric software evolution enables change in system’s structure and behavior while maintaining a global view of the software to address evolution-centric tradeoffs. Lehman’s law...... evolution problems. We propose that architectural evolution process requires an explicit evolution-centric knowledge – that can be discovered, shared, and reused – to anticipate and guide change management. Therefore, we present a pattern language as a collection of interconnected change patterns......) as a complementary and integrated phase to facilitate reuse-driven architecture change execution (pattern language application). Reuse-knowledge in the proposed pattern language is expressed as a formalised collection of interconnected-patterns. Individual patterns in the language build on each other to facilitate...

  15. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

    Science.gov (United States)

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-07-07

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

  16. Fundamentals of thinking, patterns

    Science.gov (United States)

    Gafurov, O. M.; Gafurov, D. O.; Syryamkin, V. I.

    2018-05-01

    The authors analyze the fundamentals of thinking and propose to consider a model of the brain based on the presence of magnetic properties of gliacytes (Schwann cells) because of their oxygen saturation (oxygen has paramagnetic properties). The authors also propose to take into account the motion of electrical discharges through synapses causing electric and magnetic fields as well as additional effects such as paramagnetic resonance, which allows combining multisensory object-related information located in different parts of the brain. Therefore, the events of the surrounding world are reflected and remembered in the cortex columns, thus, creating isolated subnets with altered magnetic properties (patterns) and subsequently participate in recognition of objects, form a memory, and so on. The possibilities for the pattern-based thinking are based on the practical experience of applying methods and technologies of artificial neural networks in the form of a neuroemulator and neuromorphic computing devices.

  17. Quantum computing for pattern classification

    OpenAIRE

    Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco

    2014-01-01

    It is well known that for certain tasks, quantum computing outperforms classical computing. A growing number of contributions try to use this advantage in order to improve or extend classical machine learning algorithms by methods of quantum information theory. This paper gives a brief introduction into quantum machine learning using the example of pattern classification. We introduce a quantum pattern classification algorithm that draws on Trugenberger's proposal for measuring the Hamming di...

  18. Proposed actions are no actions: re-modeling an ontology design pattern with a realist top-level ontology.

    Science.gov (United States)

    Seddig-Raufie, Djamila; Jansen, Ludger; Schober, Daniel; Boeker, Martin; Grewe, Niels; Schulz, Stefan

    2012-09-21

    Ontology Design Patterns (ODPs) are representational artifacts devised to offer solutions for recurring ontology design problems. They promise to enhance the ontology building process in terms of flexibility, re-usability and expansion, and to make the result of ontology engineering more predictable. In this paper, we analyze ODP repositories and investigate their relation with upper-level ontologies. In particular, we compare the BioTop upper ontology to the Action ODP from the NeOn an ODP repository. In view of the differences in the respective approaches, we investigate whether the Action ODP can be embedded into BioTop. We demonstrate that this requires re-interpreting the meaning of classes of the NeOn Action ODP in the light of the precepts of realist ontologies. As a result, the re-design required clarifying the ontological commitment of the ODP classes by assigning them to top-level categories. Thus, ambiguous definitions are avoided. Classes of real entities are clearly distinguished from classes of information artifacts. The proposed approach avoids the commitment to the existence of unclear future entities which underlies the NeOn Action ODP. Our re-design is parsimonious in the sense that existing BioTop content proved to be largely sufficient to define the different types of actions and plans. The proposed model demonstrates that an expressive upper-level ontology provides enough resources and expressivity to represent even complex ODPs, here shown with the different flavors of Action as proposed in the NeOn ODP. The advantage of ODP inclusion into a top-level ontology is the given predetermined dependency of each class, an existing backbone structure and well-defined relations. Our comparison shows that the use of some ODPs is more likely to cause problems for ontology developers, rather than to guide them. Besides the structural properties, the explanation of classification results were particularly hard to grasp for 'self-sufficient' ODPs as

  19. Super Memory Bros.: going from mirror patterns to concordant patterns via similarity enhancements.

    Science.gov (United States)

    Ozubko, Jason D; Joordens, Steve

    2008-12-01

    When memory is contrasted for stimuli belonging to distinct stimulus classes, one of two patterns is observed: a mirror pattern, in which one stimulus gives rise to higher hits but lower false alarms (e.g., the frequency-based mirror effect) or a concordant pattern, in which one stimulus class gives rise both to higher hits and to higher false alarms (e.g., the pseudoword effect). On the basis of the dual-process account proposed by Joordens and Hockley (2000), we predict that mirror patterns occur when one stimulus class is more familiar and less distinctive than another, whereas concordant patterns occur when one stimulus class is more familiar than another. We tested these assumptions within a video game paradigm using novel stimuli that allow manipulations in terms of distinctiveness and familiarity (via similarity). When more distinctive, less familiar items are contrasted with less distinctive, more familiar items, a mirror pattern is observed. Systematically enhancing the familiarity of stimuli transforms the mirror pattern to a concordant pattern as predicted. Although our stimuli differ considerably from those used in examinations of the frequency-based mirror effect and the pseudoword effect, the implications of our findings with respect to those phenomena are also discussed.

  20. Patterns for collaborative work in health care teams.

    Science.gov (United States)

    Grando, Maria Adela; Peleg, Mor; Cuggia, Marc; Glasspool, David

    2011-11-01

    The problem of designing and managing teams of workers that can collaborate working together towards common goals is a challenging one. Incomplete or ambiguous specification of responsibilities and accountabilities, lack of continuity in teams working in shifts, inefficient organization of teams due to lack of information about workers' competences and lack of clarity to determine if the work is delegated or assigned are examples of important problems related to collaborative work in healthcare teams. Here we address these problems by specifying goal-based patterns for abstracting the delegation and assignment of services. The proposed patterns should provide generic and reusable solutions and be flexible enough to be customizable at run time to the particular context of execution. Most importantly the patterns should support a mechanism for detecting abnormal events (exceptions) and for transferring responsibility and accountability for recovering from exceptions to the appropriate actor. To provide a generic solution to the problematic issues arising from collaborative work in teams of health workers we start from definitions of standard terms relevant for team work: competence, responsibility, and accountability. We make explicit the properties satisfied by service assignment and delegation in terms of competences, responsibilities, and accountability in normal scenarios and abnormal situations that require the enactment of recovery strategies. Based on these definitions we specify (1) a basic terminology, (2) design patterns for service assignment and delegation (with and without supervision), and (3) an exception manager for detecting and recovering from exceptions. We use a formal framework to specify design patterns and exceptions. We have proved using Owicki-Gries Theory that the proposed patterns satisfy the properties that characterize service assignment and delegation in terms of competence, responsibility and accountability in normal and abnormal

  1. Nexus network journal patterns in architecture

    CERN Document Server

    2007-01-01

    This issue is dedicated to various kinds of patterns in architecture. Buthayna Eilouti and Amer Al-Jokhadar address patterns in shape grammars in the ground plans of Mamluk madrasas, religious schools. Giulio Magli goes back further in history, to the age of Greek colonies in Italy before they were conquered by the Romans, to examine patterns in urban design. In Traditional Patterns in Pyrgi of Chios: Mathematics and Community Charoula Stathopoulou examines the geometric patterns that decorate the buildings of the town of Pyrgi, on the Greek island of Chios. Curve Fitting is a study of ways to construct a function so that its graph most closely approximates the pattern given by a set of points. Dirk Huylebrouck’s paper examines how a pattern of points extracted from an arch might be associated to a precise mathematical curve. James Harris looks at the designs of Frank Lloyd Wright and Piet Mondrian to extract the rules of their pattern generation and propose possible applications.

  2. Precise shape reconstruction by active pattern in total-internal-reflection-based tactile sensor.

    Science.gov (United States)

    Saga, Satoshi; Taira, Ryosuke; Deguchi, Koichiro

    2014-03-01

    We are developing a total-internal-reflection-based tactile sensor in which the shape is reconstructed using an optical reflection. This sensor consists of silicone rubber, an image pattern, and a camera. It reconstructs the shape of the sensor surface from an image of a pattern reflected at the inner sensor surface by total internal reflection. In this study, we propose precise real-time reconstruction by employing an optimization method. Furthermore, we propose to use active patterns. Deformation of the reflection image causes reconstruction errors. By controlling the image pattern, the sensor reconstructs the surface deformation more precisely. We implement the proposed optimization and active-pattern-based reconstruction methods in a reflection-based tactile sensor, and perform reconstruction experiments using the system. A precise deformation experiment confirms the linearity and precision of the reconstruction.

  3. Random walk-based similarity measure method for patterns in complex object

    Directory of Open Access Journals (Sweden)

    Liu Shihu

    2017-04-01

    Full Text Available This paper discusses the similarity of the patterns in complex objects. The complex object is composed both of the attribute information of patterns and the relational information between patterns. Bearing in mind the specificity of complex object, a random walk-based similarity measurement method for patterns is constructed. In this method, the reachability of any two patterns with respect to the relational information is fully studied, and in the case of similarity of patterns with respect to the relational information can be calculated. On this bases, an integrated similarity measurement method is proposed, and algorithms 1 and 2 show the performed calculation procedure. One can find that this method makes full use of the attribute information and relational information. Finally, a synthetic example shows that our proposed similarity measurement method is validated.

  4. A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Cong, Rui, E-mail: congrui2684@163.com; Li, Jing, E-mail: lijing@sj-hospital.org; Guo, Song, E-mail: 21751735@qq.com

    2017-02-15

    Highlights: • Qualitative SWE classification proposed here was significantly better than quantitative SWE parameters. • Qualitative classification proposed here was better than the classification proposed before. • Qualitative classification proposed here could obtain higher specificity without a loss of sensitivity. - Abstract: Objectives: To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. Methods: From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. Results: With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all P < 0.05). When applying Qual1

  5. A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation

    International Nuclear Information System (INIS)

    Cong, Rui; Li, Jing; Guo, Song

    2017-01-01

    Highlights: • Qualitative SWE classification proposed here was significantly better than quantitative SWE parameters. • Qualitative classification proposed here was better than the classification proposed before. • Qualitative classification proposed here could obtain higher specificity without a loss of sensitivity. - Abstract: Objectives: To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. Methods: From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. Results: With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all P < 0.05). When applying Qual1

  6. Modeling urbanization patterns with generative adversarial networks

    OpenAIRE

    Albert, Adrian; Strano, Emanuele; Kaur, Jasleen; Gonzalez, Marta

    2018-01-01

    In this study we propose a new method to simulate hyper-realistic urban patterns using Generative Adversarial Networks trained with a global urban land-use inventory. We generated a synthetic urban "universe" that qualitatively reproduces the complex spatial organization observed in global urban patterns, while being able to quantitatively recover certain key high-level urban spatial metrics.

  7. Generation and Analysis of Constrained Random Sampling Patterns

    DEFF Research Database (Denmark)

    Pierzchlewski, Jacek; Arildsen, Thomas

    2016-01-01

    Random sampling is a technique for signal acquisition which is gaining popularity in practical signal processing systems. Nowadays, event-driven analog-to-digital converters make random sampling feasible in practical applications. A process of random sampling is defined by a sampling pattern, which...... indicates signal sampling points in time. Practical random sampling patterns are constrained by ADC characteristics and application requirements. In this paper, we introduce statistical methods which evaluate random sampling pattern generators with emphasis on practical applications. Furthermore, we propose...... algorithm generates random sampling patterns dedicated for event-driven-ADCs better than existed sampling pattern generators. Finally, implementation issues of random sampling patterns are discussed....

  8. 76 FR 18467 - Pattern of Violations

    Science.gov (United States)

    2011-04-04

    ... Eastern Daylight Savings Time on April 18, 2011. ADDRESSES: Submit comments by any of the following... proposed rule addressing Pattern of Violations (POV). This extension gives commenters additional time to...

  9. Quantitative analysis of breast echotexture patterns in automated breast ultrasound images

    International Nuclear Information System (INIS)

    Chang, Ruey-Feng; Hou, Yu-Ling; Lo, Chung-Ming; Huang, Chiun-Sheng; Chen, Jeon-Hor; Kim, Won Hwa; Chang, Jung Min; Bae, Min Sun; Moon, Woo Kyung

    2015-01-01

    Purpose: Breast tissue composition is considered to be associated with breast cancer risk. This study aimed to develop a computer-aided classification (CAC) system to automatically classify echotexture patterns as heterogeneous or homogeneous using automated breast ultrasound (ABUS) images. Methods: A CAC system was proposed that can recognize breast echotexture patterns in ABUS images. For each case, the echotexture pattern was assessed by two expert radiologists and classified as heterogeneous or homogeneous. After neutrosophic image transformation and fuzzy c-mean clusterings, the lower and upper boundaries of the fibroglandular tissues were defined. Then, the number of hypoechoic regions and histogram features were extracted from the fibroglandular tissues, and the support vector machine model with the leave-one-out cross-validation method was utilized as the classifier. The authors’ database included a total of 208 ABUS images of the breasts of 104 females. Results: The accuracies of the proposed system for the classification of heterogeneous and homogeneous echotexture patterns were 93.48% (43/46) and 92.59% (150/162), respectively, with an overall Az (area under the receiver operating characteristic curve) of 0.9786. The agreement between the radiologists and the proposed system was almost perfect, with a kappa value of 0.814. Conclusions: The use of ABUS and the proposed method can provide quantitative information on the echotexture patterns of the breast and can be used to evaluate whether breast echotexture patterns are associated with breast cancer risk in the future

  10. Quantitative analysis of breast echotexture patterns in automated breast ultrasound images

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Ruey-Feng [Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan and Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Hou, Yu-Ling [Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan (China); Lo, Chung-Ming [Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Huang, Chiun-Sheng [Department of Surgery, National Taiwan University Hospital, Taipei 10617, Taiwan (China); Chen, Jeon-Hor [Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung 82445, Taiwan and Tu and Yuen Center for Functional Onco-Imaging and Department of Radiological Science, University of California, Irvine, California 92697 (United States); Kim, Won Hwa; Chang, Jung Min; Bae, Min Sun; Moon, Woo Kyung, E-mail: moonwk@snu.ac.kr [Department of Radiology, Seoul National University Hospital, Seoul 110-744 (Korea, Republic of)

    2015-08-15

    Purpose: Breast tissue composition is considered to be associated with breast cancer risk. This study aimed to develop a computer-aided classification (CAC) system to automatically classify echotexture patterns as heterogeneous or homogeneous using automated breast ultrasound (ABUS) images. Methods: A CAC system was proposed that can recognize breast echotexture patterns in ABUS images. For each case, the echotexture pattern was assessed by two expert radiologists and classified as heterogeneous or homogeneous. After neutrosophic image transformation and fuzzy c-mean clusterings, the lower and upper boundaries of the fibroglandular tissues were defined. Then, the number of hypoechoic regions and histogram features were extracted from the fibroglandular tissues, and the support vector machine model with the leave-one-out cross-validation method was utilized as the classifier. The authors’ database included a total of 208 ABUS images of the breasts of 104 females. Results: The accuracies of the proposed system for the classification of heterogeneous and homogeneous echotexture patterns were 93.48% (43/46) and 92.59% (150/162), respectively, with an overall Az (area under the receiver operating characteristic curve) of 0.9786. The agreement between the radiologists and the proposed system was almost perfect, with a kappa value of 0.814. Conclusions: The use of ABUS and the proposed method can provide quantitative information on the echotexture patterns of the breast and can be used to evaluate whether breast echotexture patterns are associated with breast cancer risk in the future.

  11. Anastomosing Rivers are Disequilibrium Patterns

    NARCIS (Netherlands)

    Lavooi, E.; Haas, de T.; Kleinhans, M.G.; Makaske, B.; Smith, D.G.

    2010-01-01

    Anastomosing rivers have multiple interconnected channels that enclose floodbasins. Various theories have been proposed to explain this pattern, including an increased discharge conveyance and sediment transport capacity of multiple channels, or, alternatively, a tendency to avulse due to upstream

  12. Identification of DWI behavior patterns and methods for change

    Science.gov (United States)

    1982-09-01

    The purpose of this study was to identify patterns of behavior leading to driving while intoxicated (DWI), and to propose countermeasures for altering these patterns before they result in DWI. Two samples were studied: Los Angeles high school student...

  13. SNP interaction pattern identifier (SIPI)

    DEFF Research Database (Denmark)

    Lin, Hui Yi; Chen, Dung Tsa; Huang, Po Yu

    2017-01-01

    Motivation: Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped. Results: We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45...

  14. Fringe pattern denoising using coherence-enhancing diffusion.

    Science.gov (United States)

    Wang, Haixia; Kemao, Qian; Gao, Wenjing; Lin, Feng; Seah, Hock Soon

    2009-04-15

    Electronic speckle pattern interferometry is one of the methods measuring the displacement on object surfaces in which fringe patterns need to be evaluated. Noise is one of the key problems affecting further processing and reducing measurement quality. We propose an application of coherence-enhancing diffusion to fringe-pattern denoising. It smoothes a fringe pattern along directions both parallel and perpendicular to fringe orientation with suitable diffusion speeds to more effectively reduce noise and improve fringe-pattern quality. It is a generalized work of Tang's et al.'s [Opt. Lett.33, 2179 (2008)] model that only smoothes a fringe pattern along fringe orientation. Since our model diffuses a fringe pattern with an additional direction, it is able to denoise low-density fringes as well as improve denoising effectiveness for high-density fringes. Theoretical analysis as well as simulation and experimental verifications are addressed.

  15. Phase retrieval from reflective fringe patterns of double-sided transparent objects

    International Nuclear Information System (INIS)

    Huang, Lei; Asundi, Anand Krishna

    2012-01-01

    ‘Ghosted’ fringe patterns simultaneously reflected from both the upper and lower sides of a transparent target in the fringe reflection technique are captured for transparent surface 3D shape measurement, but the phase retrieval from the captured ‘ghosted’ fringe patterns is still not solved. A novel method is proposed to solve this issue by using two sets of phase-shifted fringe patterns with slightly different frequencies. The nonlinear least-squares method is used to estimate the fringe phase and modulation from both front and rear interfaces. Several simulations are done to show the feasibility of the proposed method. The influence of fringe noise on the algorithm is studied as well, which indicates that the proposed method is able to retrieve the phase from double-sided reflective fringe patterns with fringe noise equivalent to that in practical measurements. The merits and limitations of the method are discussed and recommendations for future studies are made. (paper)

  16. Chemically Patterned Inverse Opal Created by a Selective Photolysis Modification Process.

    Science.gov (United States)

    Tian, Tian; Gao, Ning; Gu, Chen; Li, Jian; Wang, Hui; Lan, Yue; Yin, Xianpeng; Li, Guangtao

    2015-09-02

    Anisotropic photonic crystal materials have long been pursued for their broad applications. A novel method for creating chemically patterned inverse opals is proposed here. The patterning technique is based on selective photolysis of a photolabile polymer together with postmodification on released amine groups. The patterning method allows regioselective modification within an inverse opal structure, taking advantage of selective chemical reaction. Moreover, combined with the unique signal self-reporting feature of the photonic crystal, the fabricated structure is capable of various applications, including gradient photonic bandgap and dynamic chemical patterns. The proposed method provides the ability to extend the structural and chemical complexity of the photonic crystal, as well as its potential applications.

  17. Automatic classification of thermal patterns in diabetic foot based on morphological pattern spectrum

    Science.gov (United States)

    Hernandez-Contreras, D.; Peregrina-Barreto, H.; Rangel-Magdaleno, J.; Ramirez-Cortes, J.; Renero-Carrillo, F.

    2015-11-01

    This paper presents a novel approach to characterize and identify patterns of temperature in thermographic images of the human foot plant in support of early diagnosis and follow-up of diabetic patients. Composed feature vectors based on 3D morphological pattern spectrum (pecstrum) and relative position, allow the system to quantitatively characterize and discriminate non-diabetic (control) and diabetic (DM) groups. Non-linear classification using neural networks is used for that purpose. A classification rate of 94.33% in average was obtained with the composed feature extraction process proposed in this paper. Performance evaluation and obtained results are presented.

  18. Mechanics-driven patterning of CVD graphene for roll-based manufacturing process

    Science.gov (United States)

    Kim, Sang-Min; Jang, Bongkyun; Jo, Kyungmin; Kim, Donghyuk; Lee, Jihye; Kim, Kyung-Shik; Lee, Seung-Mo; Lee, Hak-Joo; Han, Seung Min; Kim, Jae-Hyun

    2017-06-01

    Graphene is considered as a promising material for flexible and transparent electrodes due to its outstanding electrical, optical, and mechanical properties. Efforts to mass-produce graphene electrodes led to the development of roll-to-roll chemical vapor deposition (CVD) graphene growth and transfer, and the only remaining obstacle to the mass-production of CVD graphene electrodes is a cost-effective patterning technique that is compatible with the roll-to-roll manufacturing. Herein, we propose a mechanics-driven technique for patterning graphene synthesized on copper foil (commonly used in roll-to-roll manufacturing). The copper foil is exposed to high temperature for a prolonged period during the CVD growth of graphene, and thus can result in recrystallization and grain growth of the copper foil and thereby reducing to the yield strength. This softening behavior of the copper was carefully controlled to allow simple stamp patterning of the graphene. The strength of the underlying substrate was controlled for the accuracy of the residual patterns. The proposed stamp patterning technique is mask-less and photoresist-free, and can be performed at room temperature without high-energy sources such as lasers or plasma. To demonstrate the capability of this process to produce a continuous electrode, a transparent in-plane supercapacitor was fabricated using the proposed patterning technique.

  19. Robust pattern decoding in shape-coded structured light

    Science.gov (United States)

    Tang, Suming; Zhang, Xu; Song, Zhan; Song, Lifang; Zeng, Hai

    2017-09-01

    Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.

  20. Design nanocrack patterns in heterogeneous films

    International Nuclear Information System (INIS)

    Salac, David; Lu Wei

    2006-01-01

    Nanowires have significant potential in future technologies such as nanomechanical devices and electronics. Recent experiments suggest that nanowires with sub-100 nm diameters may be fabricated by filling cracks with various materials. The geometry of cracks becomes important on such a length scale, and the practical application of the approach requires an understanding of crack evolution in heterogeneous films. This paper proposes a level-set approach to model directed nanocracks on pre-patterned substrates. The approach does not require the explicit tracking of crack fronts and thus allows the simulation of complex crack patterns. Results indicate that pre-patterning a substrate can lead to various well controlled nanocrack patterns, suggesting a possibility to make designed and complex nanowires difficult to obtain with other methods

  1. Patterns of interhemispheric correlation during human communication.

    Science.gov (United States)

    Grinberg-Zylberbaum, J; Ramos, J

    1987-09-01

    Correlation patterns between the electroencephalographic activity of both hemispheres in adult subjects were obtained. The morphology of these patterns for one subject was compared with another subject's patterns during control situations without communication, and during sessions in which direct communication was stimulated. Neither verbalization nor visual or physical contact are necessary for direct communication to occur. The interhemispheric correlation patterns for each subject were observed to become similar during the communication sessions as compared to the control situations. These effects are not due to nonspecific factors such as habituation or fatigue. The results support the syntergic theory proposed by one of the authors (Grinberg-Zylberbaum).

  2. Recognition of building group patterns in topographic maps based on graph partitioning and random forest

    Science.gov (United States)

    He, Xianjin; Zhang, Xinchang; Xin, Qinchuan

    2018-02-01

    Recognition of building group patterns (i.e., the arrangement and form exhibited by a collection of buildings at a given mapping scale) is important to the understanding and modeling of geographic space and is hence essential to a wide range of downstream applications such as map generalization. Most of the existing methods develop rigid rules based on the topographic relationships between building pairs to identify building group patterns and thus their applications are often limited. This study proposes a method to identify a variety of building group patterns that allow for map generalization. The method first identifies building group patterns from potential building clusters based on a machine-learning algorithm and further partitions the building clusters with no recognized patterns based on the graph partitioning method. The proposed method is applied to the datasets of three cities that are representative of the complex urban environment in Southern China. Assessment of the results based on the reference data suggests that the proposed method is able to recognize both regular (e.g., the collinear, curvilinear, and rectangular patterns) and irregular (e.g., the L-shaped, H-shaped, and high-density patterns) building group patterns well, given that the correctness values are consistently nearly 90% and the completeness values are all above 91% for three study areas. The proposed method shows promises in automated recognition of building group patterns that allows for map generalization.

  3. Thermodynamics of complexity and pattern manipulation

    Science.gov (United States)

    Garner, Andrew J. P.; Thompson, Jayne; Vedral, Vlatko; Gu, Mile

    2017-04-01

    Many organisms capitalize on their ability to predict the environment to maximize available free energy and reinvest this energy to create new complex structures. This functionality relies on the manipulation of patterns—temporally ordered sequences of data. Here, we propose a framework to describe pattern manipulators—devices that convert thermodynamic work to patterns or vice versa—and use them to build a "pattern engine" that facilitates a thermodynamic cycle of pattern creation and consumption. We show that the least heat dissipation is achieved by the provably simplest devices, the ones that exhibit desired operational behavior while maintaining the least internal memory. We derive the ultimate limits of this heat dissipation and show that it is generally nonzero and connected with the pattern's intrinsic crypticity—a complexity theoretic quantity that captures the puzzling difference between the amount of information the pattern's past behavior reveals about its future and the amount one needs to communicate about this past to optimally predict the future.

  4. An intelligent temporal pattern classification system using fuzzy ...

    Indian Academy of Sciences (India)

    In this paper, we propose a new pattern classification system by combining Temporal features with Fuzzy Min–Max (TFMM) neural network based classifier for effective decision support in medical diagnosis. Moreover, a Particle Swarm Optimization (PSO) algorithm based rule extractor is also proposed in this work for ...

  5. Localization Using Magnetic Patterns for Autonomous Mobile Robot

    Directory of Open Access Journals (Sweden)

    Won Suk You

    2014-03-01

    Full Text Available In this paper, we present a method of localization using magnetic landmarks. With this method, it is possible to compensate the pose error (xe, ye, θe of a mobile robot correctly and localize its current position on a global coordinate system on the surface of a structured environment with magnetic landmarks. A set of four magnetic bars forms total six different patterns of landmarks and these patterns can be read by the mobile robot with magnetic hall sensors. A sequential motion strategy for a mobile robot is proposed to find the geometric center of magnetic landmarks by reading the nonlinear magnetic field. The mobile robot first moves into the center region of the landmark where it can read the magnetic pattern, after which tracking and global localization can be easily achieved by recognizing the patterns of neighboring landmarks. Experimental results show the effectiveness of the sequential motion strategy for estimating the center of the first encountered landmark as well as the performance of tracking and global localization of the proposed system.

  6. Fringe pattern denoising via image decomposition.

    Science.gov (United States)

    Fu, Shujun; Zhang, Caiming

    2012-02-01

    Filtering off noise from a fringe pattern is one of the key tasks in optical interferometry. In this Letter, using some suitable function spaces to model different components of a fringe pattern, we propose a new fringe pattern denoising method based on image decomposition. In our method, a fringe image is divided into three parts: low-frequency fringe, high-frequency fringe, and noise, which are processed in different spaces. An adaptive threshold in wavelet shrinkage involved in this algorithm improves its denoising performance. Simulation and experimental results show that our algorithm obtains smooth and clean fringes with different frequencies while preserving fringe features effectively.

  7. Classification and Target Group Selection Based Upon Frequent Patterns

    NARCIS (Netherlands)

    W.H.L.M. Pijls (Wim); R. Potharst (Rob)

    2000-01-01

    textabstractIn this technical report , two new algorithms based upon frequent patterns are proposed. One algorithm is a classification method. The other one is an algorithm for target group selection. In both algorithms, first of all, the collection of frequent patterns in the training set is

  8. Pattern activation/recognition theory of mind.

    Science.gov (United States)

    du Castel, Bertrand

    2015-01-01

    In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

  9. A novel approach for SEMG signal classification with adaptive local binary patterns.

    Science.gov (United States)

    Ertuğrul, Ömer Faruk; Kaya, Yılmaz; Tekin, Ramazan

    2016-07-01

    Feature extraction plays a major role in the pattern recognition process, and this paper presents a novel feature extraction approach, adaptive local binary pattern (aLBP). aLBP is built on the local binary pattern (LBP), which is an image processing method, and one-dimensional local binary pattern (1D-LBP). In LBP, each pixel is compared with its neighbors. Similarly, in 1D-LBP, each data in the raw is judged against its neighbors. 1D-LBP extracts feature based on local changes in the signal. Therefore, it has high a potential to be employed in medical purposes. Since, each action or abnormality, which is recorded in SEMG signals, has its own pattern, and via the 1D-LBP these (hidden) patterns may be detected. But, the positions of the neighbors in 1D-LBP are constant depending on the position of the data in the raw. Also, both LBP and 1D-LBP are very sensitive to noise. Therefore, its capacity in detecting hidden patterns is limited. To overcome these drawbacks, aLBP was proposed. In aLBP, the positions of the neighbors and their values can be assigned adaptively via the down-sampling and the smoothing coefficients. Therefore, the potential to detect (hidden) patterns, which may express an illness or an action, is really increased. To validate the proposed feature extraction approach, two different datasets were employed. Achieved accuracies by the proposed approach were higher than obtained results by employed popular feature extraction approaches and the reported results in the literature. Obtained accuracy results were brought out that the proposed method can be employed to investigate SEMG signals. In summary, this work attempts to develop an adaptive feature extraction scheme that can be utilized for extracting features from local changes in different categories of time-varying signals.

  10. Walking pattern classification and walking distance estimation algorithms using gait phase information.

    Science.gov (United States)

    Wang, Jeen-Shing; Lin, Che-Wei; Yang, Ya-Ting C; Ho, Yu-Jen

    2012-10-01

    This paper presents a walking pattern classification and a walking distance estimation algorithm using gait phase information. A gait phase information retrieval algorithm was developed to analyze the duration of the phases in a gait cycle (i.e., stance, push-off, swing, and heel-strike phases). Based on the gait phase information, a decision tree based on the relations between gait phases was constructed for classifying three different walking patterns (level walking, walking upstairs, and walking downstairs). Gait phase information was also used for developing a walking distance estimation algorithm. The walking distance estimation algorithm consists of the processes of step count and step length estimation. The proposed walking pattern classification and walking distance estimation algorithm have been validated by a series of experiments. The accuracy of the proposed walking pattern classification was 98.87%, 95.45%, and 95.00% for level walking, walking upstairs, and walking downstairs, respectively. The accuracy of the proposed walking distance estimation algorithm was 96.42% over a walking distance.

  11. Implementing gait pattern control and transition for legged locomotion

    International Nuclear Information System (INIS)

    Yang, Zhijun; Karamanoglu, Mehmet; Rocha, Marlon V; França, Felipe M G; Lima, Priscila M V

    2014-01-01

    In this work, a generalised central pattern generator (CPG) model is formulated to generate a full range of gait patterns for a hexapod insect. To this end, a recurrent neuronal network module, as the building block for rhythmic patterns, is proposed to extend the concept of oscillatory building blocks (OBB) for constructing a CPG model. The model is able to make transitions between different gait patterns by simply adjusting one model parameter. Simulation results are further presented to show the effectiveness and performance of the CPG network

  12. Categorizing Pedagogical Patterns by Teaching Activities and Pedagogical Value

    DEFF Research Database (Denmark)

    Eriksen, Ole

    2006-01-01

    The main contribution of this paper is a proposal for a universal pedagogical pattern categorization based on teaching values and activities. This categorization would be more sustainable than the arbitrary categorization implied by pedagogical pattern language themes. Pedagogical patterns from two...... central patterns languages are analyzed and categorized, and the result is a catalogue theoretically founded and practical in its application. The teaching values are derived from learning theories, implying the theoretical foundation of the catalogue. In order to increase the usability of the value...

  13. On Tree Pattern Matching by Pushdown Automata

    Directory of Open Access Journals (Sweden)

    T. Flouri

    2009-01-01

    Full Text Available Tree pattern matching is an important operation in Computer Science on which a number of tasks such as mechanical theorem proving, term-rewriting, symbolic computation and non-procedural programming languages are based on. Work has begun on a systematic approach to the construction of tree pattern matchers by deterministic pushdown automata which read subject trees in prefix notation. The method is analogous to the construction of string pattern matchers: for given patterns, a non-deterministic pushdown automaton is created and then it is determinised. In this first paper, we present the proposed non-deterministic pushdown automaton which will serve as a basis for the determinisation process, and prove its correctness. 

  14. In-vivo determination of chewing patterns using FBG and artificial neural networks

    Science.gov (United States)

    Pegorini, Vinicius; Zen Karam, Leandro; Rocha Pitta, Christiano S.; Ribeiro, Richardson; Simioni Assmann, Tangriani; Cardozo da Silva, Jean Carlos; Bertotti, Fábio L.; Kalinowski, Hypolito J.; Cardoso, Rafael

    2015-09-01

    This paper reports the process of pattern classification of the chewing process of ruminants. We propose a simplified signal processing scheme for optical fiber Bragg grating (FBG) sensors based on machine learning techniques. The FBG sensors measure the biomechanical forces during jaw movements and an artificial neural network is responsible for the classification of the associated chewing pattern. In this study, three patterns associated to dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior studies were monitored, rumination and idle period. Experimental results show that the proposed approach for pattern classification has been capable of differentiating the materials involved in the chewing process with a small classification error.

  15. Managing the Perception of Advanced Technology Risks in Mission Proposals

    Science.gov (United States)

    Bellisario, Sebastian Nickolai

    2012-01-01

    Through my work in the project proposal office I became interested in how technology advancement efforts affect competitive mission proposals. Technology development allows for new instruments and functionality. However, including technology advancement in a mission proposal often increases perceived risk. Risk mitigation has a major impact on the overall evaluation of the proposal and whether the mission is selected. In order to evaluate the different approaches proposals took I compared the proposals claims of heritage and technology advancement to the sponsor feedback provided in the NASA debriefs. I examined a set of Discovery 2010 Mission proposals to draw patterns in how they were evaluated and come up with a set of recommendations for future mission proposals in how they should approach technology advancement to reduce the perceived risk.

  16. Pattern Discovery and Change Detection of Online Music Query Streams

    Science.gov (United States)

    Li, Hua-Fu

    In this paper, an efficient stream mining algorithm, called FTP-stream (Frequent Temporal Pattern mining of streams), is proposed to find the frequent temporal patterns over melody sequence streams. In the framework of our proposed algorithm, an effective bit-sequence representation is used to reduce the time and memory needed to slide the windows. The FTP-stream algorithm can calculate the support threshold in only a single pass based on the concept of bit-sequence representation. It takes the advantage of "left" and "and" operations of the representation. Experiments show that the proposed algorithm only scans the music query stream once, and runs significant faster and consumes less memory than existing algorithms, such as SWFI-stream and Moment.

  17. Aesthetics-based classification of geological structures in outcrops for geotourism purposes: a tentative proposal

    Science.gov (United States)

    Mikhailenko, Anna V.; Nazarenko, Olesya V.; Ruban, Dmitry A.; Zayats, Pavel P.

    2017-03-01

    The current growth in geotourism requires an urgent development of classifications of geological features on the basis of criteria that are relevant to tourist perceptions. It appears that structure-related patterns are especially attractive for geotourists. Consideration of the main criteria by which tourists judge beauty and observations made in the geodiversity hotspot of the Western Caucasus allow us to propose a tentative aesthetics-based classification of geological structures in outcrops, with two classes and four subclasses. It is possible to distinguish between regular and quasi-regular patterns (i.e., striped and lined and contorted patterns) and irregular and complex patterns (paysage and sculptured patterns). Typical examples of each case are found both in the study area and on a global scale. The application of the proposed classification permits to emphasise features of interest to a broad range of tourists. Aesthetics-based (i.e., non-geological) classifications are necessary to take into account visions and attitudes of visitors.

  18. Frequency guided methods for demodulation of a single fringe pattern.

    Science.gov (United States)

    Wang, Haixia; Kemao, Qian

    2009-08-17

    Phase demodulation from a single fringe pattern is a challenging task but of interest. A frequency-guided regularized phase tracker and a frequency-guided sequential demodulation method with Levenberg-Marquardt optimization are proposed to demodulate a single fringe pattern. Demodulation path guided by the local frequency from the highest to the lowest is applied in both methods. Since critical points have low local frequency values, they are processed last so that the spurious sign problem caused by these points is avoided. These two methods can be considered as alternatives to the effective fringe follower regularized phase tracker. Demodulation results from one computer-simulated and two experimental fringe patterns using the proposed methods will be demonstrated. (c) 2009 Optical Society of America

  19. Mining Co-Location Patterns with Clustering Items from Spatial Data Sets

    Science.gov (United States)

    Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.

    2018-05-01

    The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.

  20. PABRE-Proj: applying patterns in requirements elicitation

    OpenAIRE

    Palomares Bonache, Cristina; Quer Bosor, Maria Carme; Franch Gutiérrez, Javier

    2013-01-01

    Software requirement patterns have been proposed as a type of artifact for fostering requirements reuse. In this paper, we present PABRE-Proj, a tool aimed at supporting requirements elicitation and specification. Peer Reviewed

  1. Analysis of patterns of three-phase bone scintigraphy for patients with complex regional pain syndrome diagnosed using the proposed research criteria (the 'Budapest Criteria').

    Science.gov (United States)

    Moon, J Y; Park, S Y; Kim, Y C; Lee, S C; Nahm, F S; Kim, J H; Kim, H; Oh, S W

    2012-04-01

    Three-phase bone scintigraphy (TPBS) is an established objective diagnostic method for complex regional pain syndrome (CRPS), but its validity remains controversial. The aims of this study were: (i) to re-evaluate the diagnostic performance of TPBS, and (ii) to suggest new TPBS criteria based on the proposed research criteria for CPRS in Budapest (the 2003 Budapest research criteria). The medical records of 228 consecutive patients, evaluated using the Budapest research criteria, were retrospectively analysed. Of these, 116 patients were included in the present study, and 69 of 116 were diagnosed to have CRPS based on these criteria. The diagnostic performance of TPBS was assessed by determining its sensitivity, specificity, and positive and negative likelihood ratios, and new criteria for TPBS were identified by pattern analysis using the Budapest research criteria. The sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of TPBS for the diagnosis of CRPS according to the Budapest research criteria were 40.0, 76.5, 1.73, and 0.78, respectively. Furthermore, D-D-D, D-D-S, and D-D-I patterns [i.e. according to decreased (D), symmetrical (S), or increased (I) tracer uptake during Phases I, II, and III] of TPBS were found to be positively predictive for CRPS. The diagnostic value of a positive TPBS for CRPS is low from the view point of the Budapest research criteria. Our findings suggest that a diagnosis of CRPS using the Budapest research criteria should be considered when decreased patterns of TPBS are observed during Phases I and II.

  2. Description and recognition of patterns in stochastic signals. [Electroencephalograms

    Energy Technology Data Exchange (ETDEWEB)

    Flik, T [Technische Univ. Berlin (F.R. Germany). Informatik-Forschungsgruppe Rechnerorganisation und Schaltwerke

    1975-10-01

    A method is shown for the description and recognition of patterns in stochastic signals such as electroencephalograms. For pattern extraction the signal is segmented at times of minimum amplitudes. The describing features consist of geometric values of the so defined patterns. The classification algorithm is based on the regression analysis, which is well known in the field of character recognition. For an economic classification a method is proposed which reduces the number of features. The quality of this pattern recognition method is demonstrated by the detection of spike wave complexes in electroencephalograms. The pattern description and recognition are provided for processing on a digital computer. (DE)

  3. An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences.

    Science.gov (United States)

    Ye, Kai; Kosters, Walter A; Ijzerman, Adriaan P

    2007-03-15

    Pattern discovery in protein sequences is often based on multiple sequence alignments (MSA). The procedure can be computationally intensive and often requires manual adjustment, which may be particularly difficult for a set of deviating sequences. In contrast, two algorithms, PRATT2 (http//www.ebi.ac.uk/pratt/) and TEIRESIAS (http://cbcsrv.watson.ibm.com/) are used to directly identify frequent patterns from unaligned biological sequences without an attempt to align them. Here we propose a new algorithm with more efficiency and more functionality than both PRATT2 and TEIRESIAS, and discuss some of its applications to G protein-coupled receptors, a protein family of important drug targets. In this study, we designed and implemented six algorithms to mine three different pattern types from either one or two datasets using a pattern growth approach. We compared our approach to PRATT2 and TEIRESIAS in efficiency, completeness and the diversity of pattern types. Compared to PRATT2, our approach is faster, capable of processing large datasets and able to identify the so-called type III patterns. Our approach is comparable to TEIRESIAS in the discovery of the so-called type I patterns but has additional functionality such as mining the so-called type II and type III patterns and finding discriminating patterns between two datasets. The source code for pattern growth algorithms and their pseudo-code are available at http://www.liacs.nl/home/kosters/pg/.

  4. Arthropod pattern theory and Cambrian trilobites

    NARCIS (Netherlands)

    Sundberg, Frederick A.

    1995-01-01

    An analysis of duplomere (= segment) distribution within the cephalon, thorax, and pygidium of Cambrian trilobites was undertaken to determine if the Arthropod Pattern Theory (APT) proposed by Schram & Emerson (1991) applies to Cambrian trilobites. The boundary of the cephalon/thorax occurs within

  5. Patterns of knowing: proposing a theory for nursing leadership.

    Science.gov (United States)

    Jackson, Janet R; Clements, Paul T; Averill, Jennifer B; Zimbro, Kathie

    2009-01-01

    In a time of chaotic and unpredictable health care, it is vital for nursing to employ a nursing leadership theory that is specifically applicable to nurses and will holistically, and comprehensively address and support both the science and art of this honored profession. The authors propose that Nursing Leadership Knowing can address and impact the myriad issues confronting managers and administrators within the turbulent health care industry, with the ultimate goals of quality comprehensive patient care and improved employee satisfaction. They believe that Nursing Leadership Knowing, grounded in the realties of nursing experience, is a logical theoretical extension that can be translated into nursing leadership practice particular and specific focus on empirics and evidence-based practice will not attend to the robust and multidimensional underpinnings of the lived experience that is so vital to nursing as a caring profession. The ideal of nursing leadership theory is not a single-focused shadow of its history, but a rich, inclusive, multi-faceted network of knowing. As such, Nursing Leadership Knowing provides a forum for leaders to enhance their practice, as well as their relationship with their employees, which ultimately translates into optimal care for the patients we serve.

  6. L'aile dite « des prélats » au château de Grignan (Drôme 1684-1689

    Directory of Open Access Journals (Sweden)

    Christian Trézin

    2012-04-01

    Full Text Available La construction de l'aile « des prélats » au château de Grignan de 1684 à 1689 correspond à la requalification d'un secteur composite constitué du XIIe au XVIIe siècle. Commanditée sans intervention d'architecte par l'évêque de Carcassonne et l'archevêque d'Arles, frères du comte de Grignan, elle est bâtie en deux chantiers successifs selon des partis distincts dont l'harmonisation laborieuse est restée inachevée. Si le bâtiment de Carcassonne reflète initialement le savoir traditionnel de l'entrepreneur Florent Loiseleur, celui d'Arles est imprégné des œuvres récentes de l'agence de Jules Hardouin-Mansart dont le maçon Jacque Jaquet dit Beaufleury a probablement été tenu de s'inspirer. Ce chantier est un exemple du mode d'action des architectes amateurs dans le milieu conservateur de la noblesse provençale.The "prelates" wing of the castle of Grignan was built from 1684 to 1689. It was supposed to be a requalification and a renewal of a heterogeneous area erected between 12th to 17th century. Sponsored by the bishop of Carcassonne and the archbishop of Arles, brothers of the count of Grignan, no architect was involved in its design. It was built in two successive phases reflecting distinct conceptions and accordingly its architctural harmonization was made difficult and remained unfulfilled. If the Carcassonne building reflects the traditional savoir faire of the building contractor Florent Loiseleur, Arles's was deeply close to the recent works of Jules Hardouin-Mansart's agency whom the master builder Jacque Jaquet, said Beaufleury, had most probably to be inspired of. This construction is an example of the way amateur architects used to work in the conservative circle of provençal nobility.

  7. Archetypes as action patterns.

    Science.gov (United States)

    Hogenson, George B

    2009-06-01

    The discovery of mirror neurons by researchers at the University of Parma promises to radically alter our understanding of fundamental cognitive and affective states. This paper explores the relationship of mirror neurons to Jung's theory of archetypes and proposes that archetypes may be viewed as elementary action patterns. The paper begins with a review of a proposed interpretation of the fainting spells of S. Freud in his relationship with Jung as an example of an action pattern that also defines an archetypal image. The challenge that mirror neurons present to traditional views in analytical psychology and psychoanalysis, however, is that they operate without recourse to a cognitive processing element. This is a position that is gaining increasing acceptance in other fields as well. The paper therefore reviews the most recent claims made by the Boston Process of Change Study Group as well as conclusions drawn from dynamic systems views of development and theoretical robotics to underline the conclusion that unconscious agency is not a requirement for coherent action. It concludes with the suggestion that this entire body of research may lead to the conclusion that the dynamic unconscious is an unnecessary hypothesis in psychoanalysis and analytical psychology.

  8. Classifications of Patterned Hair Loss: A Review.

    Science.gov (United States)

    Gupta, Mrinal; Mysore, Venkataram

    2016-01-01

    Patterned hair loss is the most common cause of hair loss seen in both the sexes after puberty. Numerous classification systems have been proposed by various researchers for grading purposes. These systems vary from the simpler systems based on recession of the hairline to the more advanced multifactorial systems based on the morphological and dynamic parameters that affect the scalp and the hair itself. Most of these preexisting systems have certain limitations. Currently, the Hamilton-Norwood classification system for males and the Ludwig system for females are most commonly used to describe patterns of hair loss. In this article, we review the various classification systems for patterned hair loss in both the sexes. Relevant articles were identified through searches of MEDLINE and EMBASE. Search terms included but were not limited to androgenic alopecia classification, patterned hair loss classification, male pattern baldness classification, and female pattern hair loss classification. Further publications were identified from the reference lists of the reviewed articles.

  9. Classifications of patterned hair loss: a review

    Directory of Open Access Journals (Sweden)

    Mrinal Gupta

    2016-01-01

    Full Text Available Patterned hair loss is the most common cause of hair loss seen in both the sexes after puberty. Numerous classification systems have been proposed by various researchers for grading purposes. These systems vary from the simpler systems based on recession of the hairline to the more advanced multifactorial systems based on the morphological and dynamic parameters that affect the scalp and the hair itself. Most of these preexisting systems have certain limitations. Currently, the Hamilton-Norwood classification system for males and the Ludwig system for females are most commonly used to describe patterns of hair loss. In this article, we review the various classification systems for patterned hair loss in both the sexes. Relevant articles were identified through searches of MEDLINE and EMBASE. Search terms included but were not limited to androgenic alopecia classification, patterned hair loss classification, male pattern baldness classification, and female pattern hair loss classification. Further publications were identified from the reference lists of the reviewed articles.

  10. Spectroscopic vector analysis for fast pattern quality monitoring

    Science.gov (United States)

    Sohn, Younghoon; Ryu, Sungyoon; Lee, Chihoon; Yang, Yusin

    2018-03-01

    In semiconductor industry, fast and effective measurement of pattern variation has been key challenge for assuring massproduct quality. Pattern measurement techniques such as conventional CD-SEMs or Optical CDs have been extensively used, but these techniques are increasingly limited in terms of measurement throughput and time spent in modeling. In this paper we propose time effective pattern monitoring method through the direct spectrum-based approach. In this technique, a wavelength band sensitive to a specific pattern change is selected from spectroscopic ellipsometry signal scattered by pattern to be measured, and the amplitude and phase variation in the wavelength band are analyzed as a measurement index of the pattern change. This pattern change measurement technique is applied to several process steps and verified its applicability. Due to its fast and simple analysis, the methods can be adapted to the massive process variation monitoring maximizing measurement throughput.

  11. Implementation Support of Security Design Patterns Using Test Templates

    Directory of Open Access Journals (Sweden)

    Masatoshi Yoshizawa

    2016-06-01

    Full Text Available Security patterns are intended to support software developers as the patterns encapsulate security expert knowledge. However, these patterns may be inappropriately applied because most developers are not security experts, leading to threats and vulnerabilities. Here we propose a support method for security design patterns in the implementation phase of software development. Our method creates a test template from a security design pattern, consisting of an “aspect test template” to observe the internal processing and a “test case template”. Providing design information creates a test from the test template with a tool. Because our test template is reusable, it can easily perform a test to validate a security design pattern. In an experiment involving four students majoring in information sciences, we confirm that our method can realize an effective test, verify pattern applications, and support pattern implementation.

  12. An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

    Science.gov (United States)

    Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

    2017-12-01

    Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

  13. Study on Dissemination Patterns in Location-Aware Gossiping Networks

    Science.gov (United States)

    Kami, Nobuharu; Baba, Teruyuki; Yoshikawa, Takashi; Morikawa, Hiroyuki

    We study the properties of information dissemination over location-aware gossiping networks leveraging location-based real-time communication applications. Gossiping is a promising method for quickly disseminating messages in a large-scale system, but in its application to information dissemination for location-aware applications, it is important to consider the network topology and patterns of spatial dissemination over the network in order to achieve effective delivery of messages to potentially interested users. To this end, we propose a continuous-space network model extended from Kleinberg's small-world model applicable to actual location-based applications. Analytical and simulation-based study shows that the proposed network achieves high dissemination efficiency resulting from geographically neutral dissemination patterns as well as selective dissemination to proximate users. We have designed a highly scalable location management method capable of promptly updating the network topology in response to node movement and have implemented a distributed simulator to perform dynamic target pursuit experiments as one example of applications that are the most sensitive to message forwarding delay. The experimental results show that the proposed network surpasses other types of networks in pursuit efficiency and achieves the desirable dissemination patterns.

  14. Proposed dedicated high pressure beam lines at CHESS

    International Nuclear Information System (INIS)

    Ruoff, A.L.; Vohra, Y.K.; Bassett, W.A.; Batterman, B.W.; Bilderback, D.H.

    1988-01-01

    An instrumentation proposal for dedicated high pressure beam lines at CHESS is described. It is the purpose of this proposed program to provide researchers in high pressure science with beam lines for X-ray diffraction studies in the megabar regime. This will involve radiation from a bending magnet as well as from a wiggler. Examples of the high pressure results up to 2.16 Mbar are shown. Diffraction patterns from bending magnet and wiggler beams are shown and compared. The need for this facility by the high pressure community is discussed. (orig.)

  15. Rotation-invariant neural pattern recognition system with application to coin recognition.

    Science.gov (United States)

    Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

    1992-01-01

    In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

  16. An ultra-wideband pattern reconfigurable antenna based on graphene coating

    Science.gov (United States)

    Jiang, YanNan; Yuan, Rui; Gao, Xi; Wang, Jiao; Li, SiMin; Lin, Yi-Yu

    2016-11-01

    An ultra-wideband pattern reconfigurable antenna is proposed. The antenna is a dielectric coaxial hollow monopole with a cylindrical graphene-based impedance surface coating. It consists of a graphene sheet coated onto the inner surface of a cylindrical substrate and a set of independent polysilicon DC gating pads mounted on the outside of the cylindrical substrate. By changing the DC bias voltages to the different gating pads, the surface impedance of the graphene coating can be freely controlled. Due to the tunability of graphene's surface impedance, the radiation pattern of the proposed antenna can be reconfigured. A transmission line method is used to illustrate the physical mechanism of the proposed antenna. The results show that the proposed antenna can reconfigure its radiation pattern in the omnidirectional mode with the relative bandwidth of 58.5% and the directional mode over the entire azimuth plane with the relative bandwidth of 67%. Project supported by the National Natural Science Foundation of China (Grant Nos. 61661012, 61461016, and 61361005), the Natural Science Foundation of Guangxi, China (Grant Nos. 2015GXNSFBB139003 and 2014GXNSFAA118283), Program for Innovation Research Team of Guilin University of Electromagnetic Technology, China, and the Dean Project of Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing, China.

  17. Individual Differences in Consumer Buying Patterns: A Behavioral Economic Analysis

    Science.gov (United States)

    Cavalcanti, Paulo R.; Oliveira-Castro, Jorge M.; Foxall, Gordon R.

    2013-01-01

    Although previous studies have identified several regularities in buying behavior, no integrated view of individual differences related to such patterns has been yet proposed. The present research examined individual differences in patterns of buying behavior of fast-moving consumer goods, using panel data with information concerning purchases of…

  18. DNA pattern recognition using canonical correlation algorithm.

    Science.gov (United States)

    Sarkar, B K; Chakraborty, Chiranjib

    2015-10-01

    We performed canonical correlation analysis as an unsupervised statistical tool to describe related views of the same semantic object for identifying patterns. A pattern recognition technique based on canonical correlation analysis (CCA) was proposed for finding required genetic code in the DNA sequence. Two related but different objects were considered: one was a particular pattern, and other was test DNA sequence. CCA found correlations between two observations of the same semantic pattern and test sequence. It is concluded that the relationship possesses maximum value in the position where the pattern exists. As a case study, the potential of CCA was demonstrated on the sequence found from HIV-1 preferred integration sites. The subsequences on the left and right flanking from the integration site were considered as the two views, and statistically significant relationships were established between these two views to elucidate the viral preference as an important factor for the correlation.

  19. Patterned Video Sensors For Low Vision

    Science.gov (United States)

    Juday, Richard D.

    1996-01-01

    Miniature video cameras containing photoreceptors arranged in prescribed non-Cartesian patterns to compensate partly for some visual defects proposed. Cameras, accompanied by (and possibly integrated with) miniature head-mounted video display units restore some visual function in humans whose visual fields reduced by defects like retinitis pigmentosa.

  20. Binary pattern analysis for 3D facial action unit detection

    NARCIS (Netherlands)

    Sandbach, Georgia; Zafeiriou, Stefanos; Pantic, Maja

    2012-01-01

    In this paper we propose new binary pattern features for use in the problem of 3D facial action unit (AU) detection. Two representations of 3D facial geometries are employed, the depth map and the Azimuthal Projection Distance Image (APDI). To these the traditional Local Binary Pattern is applied,

  1. A review on compressed pattern matching

    Directory of Open Access Journals (Sweden)

    Surya Prakash Mishra

    2016-09-01

    Full Text Available Compressed pattern matching (CPM refers to the task of locating all the occurrences of a pattern (or set of patterns inside the body of compressed text. In this type of matching, pattern may or may not be compressed. CPM is very useful in handling large volume of data especially over the network. It has many applications in computational biology, where it is useful in finding similar trends in DNA sequences; intrusion detection over the networks, big data analytics etc. Various solutions have been provided by researchers where pattern is matched directly over the uncompressed text. Such solution requires lot of space and consumes lot of time when handling the big data. Various researchers have proposed the efficient solutions for compression but very few exist for pattern matching over the compressed text. Considering the future trend where data size is increasing exponentially day-by-day, CPM has become a desirable task. This paper presents a critical review on the recent techniques on the compressed pattern matching. The covered techniques includes: Word based Huffman codes, Word Based Tagged Codes; Wavelet Tree Based Indexing. We have presented a comparative analysis of all the techniques mentioned above and highlighted their advantages and disadvantages.

  2. Attack Pattern Analysis Framework for a Multiagent Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Krzysztof Juszczyszyn

    2008-08-01

    Full Text Available The paper proposes the use of attack pattern ontology and formal framework for network traffic anomalies detection within a distributed multi-agent Intrusion Detection System architecture. Our framework assumes ontology-based attack definition and distributed processing scheme with exchange of communicates between agents. The role of traffic anomalies detection was presented then it has been discussed how some specific values characterizing network communication can be used to detect network anomalies caused by security incidents (worm attack, virus spreading. Finally, it has been defined how to use the proposed techniques in distributed IDS using attack pattern ontology.

  3. High-resolution patterning of silver conductive lines by adhesion contrast planography

    International Nuclear Information System (INIS)

    Kusaka, Yasuyuki; Ushijima, Hirobumi; Koutake, Masayoshi

    2015-01-01

    We developed printed electronics compatible planographic printing methods that enable single-micrometer-order patterning with high rectangularity and thickness uniformity. Instead of conventional planographic printing methods where selective wetting is used for pattern generation, an adhesive latent image produced on a silicone surface is exploited for patterning in the proposed printing methodologies. We further investigated the fundamental mechanisms of the proposed methods by focusing on adhesion contrasts between the blanket, printing area, and non-printing area of a printing plate (PP) and determined that printing is feasible when a simple magnitude relation of adhesions is satisfied for thin layers of size ranging from approximately 50 nm to 100 nm. Latent image formation can be carried out via a simple ultraviolet exposure of the silicone surface, thereby enabling the rapid prototyping of printed device fabrications. The easily preparable, single material-based flat PPs developed in this study have the advantages of flexibility in pattern designs, washing process, fabrication cost, and pattern-rewriting capability compared with the conventional printing methods in which raised surfaces such as stamps or clichés are required for patterning. (paper)

  4. SOMA: A Proposed Framework for Trend Mining in Large UK Diabetic Retinopathy Temporal Databases

    Science.gov (United States)

    Somaraki, Vassiliki; Harding, Simon; Broadbent, Deborah; Coenen, Frans

    In this paper, we present SOMA, a new trend mining framework; and Aretaeus, the associated trend mining algorithm. The proposed framework is able to detect different kinds of trends within longitudinal datasets. The prototype trends are defined mathematically so that they can be mapped onto the temporal patterns. Trends are defined and generated in terms of the frequency of occurrence of pattern changes over time. To evaluate the proposed framework the process was applied to a large collection of medical records, forming part of the diabetic retinopathy screening programme at the Royal Liverpool University Hospital.

  5. Canary tomato export prices: comparison and relationships between daily seasonal patterns

    Directory of Open Access Journals (Sweden)

    G. Martin-Rodriguez

    2013-10-01

    Full Text Available Statistical procedures are proposed to describe, compare and forecast the behaviour of seasonal variations in two daily price series of Canary tomato exported to German and British markets, respectively, over the last decade. These seasonal patterns are pseudo-periodic as the length of the seasonal period changes frequently in dependence of market conditions. Seasonal effect at a day in the harvesting period is defined as a spline function of the proportion of the length of such a period elapsed up to such a day. Then, seasonal patterns for the two series are compared in terms of the area between the corresponding spline functions. The ability of these models to capture the dynamic process of change in the seasonal pattern is useful to forecasting purpose. Furthermore, an analytical tool is also proposed to obtain forecasts of the seasonal pattern in one of these two series from the forecasts of the seasonal pattern in the other one. These procedures are useful for farmers in developing strategies related to the seasonal distribution of tomato production exported to each market.

  6. [A Screening-Tool for Three Dimensions of Work-Related Behavior and Experience Patterns in the Psychosomatic Rehabilitation - A Proposal for a Short-Form of the Occupational Stress and Coping Inventory (AVEM-3D)].

    Science.gov (United States)

    Beierlein, V; Köllner, V; Neu, R; Schulz, H

    2016-12-01

    Objectives: The assessment of work pressures is of particular importance in psychosomatic rehabilitation. An established questionnaire is the Occupational Stress and Coping Inventory (German abbr. AVEM), but it is quite long and with regard to scoring time-consuming in routine clinical care. It should therefore be tested, whether a shortened version of the AVEM can be developed, which is able to assess the formerly described three second-order factors of the AVEM, namely Working Commitment, Resilience, and Emotions, sufficiently reliable and valid, and which also may be used for screening of patients with prominent work-related behavior and experience patterns. Methods: Data were collected at admission from consecutive samples of three hospitals of psychosomatic rehabilitation ( N  = 10,635 patients). The sample was randomly divided in two subsamples (design and validation sample). Using exploratory principal component analyses in the design sample, items with the highest factor loadings for the three new scales were selected and evaluated psychometrically using the validation sample. Possible Cut-off values ought to be derived from distribution patterns of scores in the scales. Relationships with sociodemographic, occupational and diagnosis-related characteristics, as well as with patterns of work-related experiences and behaviors are examined. Results: The three performed principal component analyses explained in the design sample on the respective first factor between 31 % and 34 % of the variance. The selected 20 items were assigned to the 3-factor structure in the validation sample as expected. The three new scales are sufficiently reliable with values of Cronbach's α between 0,84 and 0,88. The naming of the three new scales is based on the names of the secondary factors. Cut-off values for the identification of distinctive patient-reported data are proposed. Conclusion: Main advantages of the proposed shortened version AVEM-3D are that with a

  7. Audit, Control and Monitoring Design Patterns (ACMDP for Autonomous Robust Systems (ARS

    Directory of Open Access Journals (Sweden)

    C. Trad

    2008-11-01

    Full Text Available This paper proposes the Audit, Control and Monitoring Design Patterns (ACMDP for building Autonomous and Robust Systems (ARS such as Mobile Robot Systems (MRS. These patterns are also applicable to other Mission Critical and Complex Systems (MCCS. This paper presents a proposal which will help ARS project managers and engineers design, build and estimate the probability that an ARS will succeed or fail. Furthermore, this proposal offers the possibility to ARS problems with the help of audit, monitoring and controlling components, adjust the project management pathways, and define the problem sources as well as their possible solutions, in order to deliver an ARS or an MRS.

  8. Formation of banded vegetation patterns resulted from interactions between sediment deposition and vegetation growth.

    Science.gov (United States)

    Huang, Tousheng; Zhang, Huayong; Dai, Liming; Cong, Xuebing; Ma, Shengnan

    2018-03-01

    This research investigates the formation of banded vegetation patterns on hillslopes affected by interactions between sediment deposition and vegetation growth. The following two perspectives in the formation of these patterns are taken into consideration: (a) increased sediment deposition from plant interception, and (b) reduced plant biomass caused by sediment accumulation. A spatial model is proposed to describe how the interactions between sediment deposition and vegetation growth promote self-organization of banded vegetation patterns. Based on theoretical and numerical analyses of the proposed spatial model, vegetation bands can result from a Turing instability mechanism. The banded vegetation patterns obtained in this research resemble patterns reported in the literature. Moreover, measured by sediment dynamics, the variation of hillslope landform can be described. The model predicts how treads on hillslopes evolve with the banded patterns. Thus, we provide a quantitative interpretation for coevolution of vegetation patterns and landforms under effects of sediment redistribution. Copyright © 2018. Published by Elsevier Masson SAS.

  9. AC-600 reactor reloading pattern optimization by using genetic algorithms

    International Nuclear Information System (INIS)

    Wu Hongchun; Xie Zhongsheng; Yao Dong; Li Dongsheng; Zhang Zongyao

    2000-01-01

    The use of genetic algorithms to optimize reloading pattern of the nuclear power plant reactor is proposed. And a new encoding and translating method is given. Optimization results of minimizing core power peak and maximizing cycle length for both low-leakage and out-in loading pattern of AC-600 reactor are obtained

  10. Spatio-Temporal Patterns in Colonies of Rod-Shaped Bacteria

    Science.gov (United States)

    Kitsunezaki, S.

    In incubation experiments of bacterial colonies of Proteus Mirabilis, macroscopic spatio-temporal patterns, such as turbulent and unidirectional spiral patterns, appear in colonies. Considering only kinetic propeties of rod-shaped bacteria, we propose a phenomenological model for the directional and positional distributions. As the average density increases, homogeneous states bifurcate sub-critically into nonuniform states exhibiting localized collective motion, and spiral patterns appear for sufficiently large density. These patterns result from interactions between the local bacteria densities and the order parameter representing collective motion. Our model can be described by reduced equations using a perturbative method for large density. The unidirectionality of sprial rotation is also discussed.

  11. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.

    Science.gov (United States)

    Lee, Sungjun; Lim, Junseok; Park, Jonghun; Kim, Kwanho

    2016-01-23

    Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user's next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user's past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user's next places than the previous approaches considered in most cases.

  12. Mining Emerging Patterns for Recognizing Activities of Multiple Users in Pervasive Computing

    DEFF Research Database (Denmark)

    Gu, Tao; Wu, Zhanqing; Wang, Liang

    2009-01-01

    Understanding and recognizing human activities from sensor readings is an important task in pervasive computing. Existing work on activity recognition mainly focuses on recognizing activities for a single user in a smart home environment. However, in real life, there are often multiple inhabitants...... activity models, and propose an Emerging Pattern based Multi-user Activity Recognizer (epMAR) to recognize both single-user and multiuser activities. We conduct our empirical studies by collecting real-world activity traces done by two volunteers over a period of two weeks in a smart home environment...... sensor readings in a home environment, and propose a novel pattern mining approach to recognize both single-user and multi-user activities in a unified solution. We exploit Emerging Pattern – a type of knowledge pattern that describes significant changes between classes of data – for constructing our...

  13. Selective memory generalization by spatial patterning of protein synthesis.

    Science.gov (United States)

    O'Donnell, Cian; Sejnowski, Terrence J

    2014-04-16

    Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings, we proposed a two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. Mobile Handset Performance Evaluation Using Radiation Pattern Measurements

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ødum; Pedersen, Gert Frølund

    2006-01-01

    The mean effective gain is an attractive performance measure of mobile handsets, since it incorporates both directional and polarization properties of the handset and environment. In this work the mean effective gain is computed from measured spherical radiation patterns of five different mobile...... pattern is reduced. Furthermore, the frequency dependence of the mean effective gain is investigated, and a method is proposed for reducing the required number of measurements on different frequencies....

  15. Face Liveness Detection Using Dynamic Local Ternary Pattern (DLTP

    Directory of Open Access Journals (Sweden)

    Sajida Parveen

    2016-05-01

    Full Text Available Face spoofing is considered to be one of the prominent threats to face recognition systems. However, in order to improve the security measures of such biometric systems against deliberate spoof attacks, liveness detection has received significant recent attention from researchers. For this purpose, analysis of facial skin texture properties becomes more popular because of its limited resource requirement and lower processing cost. The traditional method of skin analysis for liveness detection was to use Local Binary Pattern (LBP and its variants. LBP descriptors are effective, but they may exhibit certain limitations in near uniform patterns. Thus, in this paper, we demonstrate the effectiveness of Local Ternary Pattern (LTP as an alternative to LBP. In addition, we adopted Dynamic Local Ternary Pattern (DLTP, which eliminates the manual threshold setting in LTP by using Weber’s law. The proposed method was tested rigorously on four facial spoof databases: three are public domain databases and the other is the Universiti Putra Malaysia (UPM face spoof database, which was compiled through this study. The results obtained from the proposed DLTP texture descriptor attained optimum accuracy and clearly outperformed the reported LBP and LTP texture descriptors.

  16. Exploring dietary patterns by using the treelet transform

    DEFF Research Database (Denmark)

    Gorst-Rasmussen, Anders; Dahm, Christina Catherine; Dethlefsen, Claus

    2011-01-01

    Principal component analysis (PCA) has been used extensively in the field of nutritional epidemiology to derive patterns that summarize food and nutrient intake, but interpreting it can be difficult. The authors propose the use of a new statistical technique, the treelet transform (TT...... as the first 7 patterns derived with PCA, for which interpretation was less clear. When the authors used multivariate Cox regression models to estimate relative risk of myocardial infarction, the significant risk factors were comparable whether the model was based on PCA or TT factors. The present study shows......), as an alternative to PCA. TT combines the quantitative pattern extraction capabilities of PCA with the interpretational advantages of cluster analysis and produces patterns involving only naturally grouped subsets of the original variables. The authors compared patterns derived using TT with those derived using PCA...

  17. Graphene-based Yagi-Uda antenna with reconfigurable radiation patterns

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Yongle, E-mail: wuyongle138@gmail.com; Qu, Meijun; Jiao, Lingxiao; Liu, Yuanan [School of Electronic Engineering, Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, P. O. Box. 282, Beijing, 100876 (China); Ghassemlooy, Zabih [Optical Communications Research Group, NCRLab, Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne, NE1 8ST (United Kingdom)

    2016-06-15

    This paper presents a radiation pattern reconfigurable Yagi-Uda antenna based on graphene operating at terahertz frequencies. The antenna can be reconfigured to change the main beam pattern into two or four different radiation directions. The proposed antenna consists of a driven dipole radiation conductor, parasitic strips and embedded graphene. The hybrid graphene-metal implementation enables the antenna to have dynamic surface conductivity, which can be tuned by changing the chemical potentials. Therefore, the main beam direction, the resonance frequency, and the front-to-back ratio of the proposed antenna can be controlled by tuning the chemical potentials of the graphene embedded in different positions. The proposed two-beam reconfigurable Yagi-Uda antenna can achieve excellent unidirectional symmetrical radiation pattern with the front-to-back ratio of 11.9 dB and the10-dB impedance bandwidth of 15%. The different radiation directivity of the two-beam reconfigurable antenna can be achieved by controlling the chemical potentials of the graphene embedded in the parasitic stubs. The achievable peak gain of the proposed two-beam reconfigurable antenna is about 7.8 dB. Furthermore, we propose a four-beam reconfigurable Yagi-Uda antenna, which has stable reflection-coefficient performance although four main beams in reconfigurable cases point to four totally different directions. The corresponding peak gain, front-to-back ratio, and 10-dB impedance bandwidth of the four-beam reconfigurable antenna are about 6.4 dB, 12 dB, and 10%, respectively. Therefore, this novel design method of reconfigurable antennas is extremely promising for beam-scanning in terahertz and mid-infrared plasmonic devices and systems.

  18. Dynamic moire patterns for profilometry applications

    Energy Technology Data Exchange (ETDEWEB)

    De Oliveira, G N [Pos-graduacao em Engenharia Mecanica, TEM/PGMEC, Universidade Federal Fluminense, Rua Passos da Patria, 156, Niteroi, R.J., Cep.: 24.210-240 (Brazil); De Oliveira, M E; Dos Santos, P A M, E-mail: pams@if.uff.br [Instituto de Fisica, Laboratorio de Optica Nao-linear e Aplicada, Universidade Federal Fluminense, Av. Gal. Nilton Tavares de Souza, s/n, Gragoata, Niteroi, R.J., Cep.:24.210-346 (Brazil)

    2011-01-01

    In the present work is proposed that dynamic moire-like fringe patterns produced by photorefraction, with low spatial frequencies, could be used for profile determination of small objects. The Fourier transform profilometry technique is applied in the projected moire fringe pattern onto an object surface. Basically, the Fourier transform of the projected fringes is obtained. After that, a phase map is generated. Then, the optical profile of object is obtained using phase unwrapping. So, the entire process can be indicated to measure, with good accuracy degree, profile of small objects in sub-micrometer scale in optical mechanical systems.

  19. Brain response pattern identification of fMRI data using a particle swarm optimization-based approach.

    Science.gov (United States)

    Ma, Xinpei; Chou, Chun-An; Sayama, Hiroki; Chaovalitwongse, Wanpracha Art

    2016-09-01

    Many neuroscience studies have been devoted to understand brain neural responses correlating to cognition using functional magnetic resonance imaging (fMRI). In contrast to univariate analysis to identify response patterns, it is shown that multi-voxel pattern analysis (MVPA) of fMRI data becomes a relatively effective approach using machine learning techniques in the recent literature. MVPA can be considered as a multi-objective pattern classification problem with the aim to optimize response patterns, in which informative voxels interacting with each other are selected, achieving high classification accuracy associated with cognitive stimulus conditions. To solve the problem, we propose a feature interaction detection framework, integrating hierarchical heterogeneous particle swarm optimization and support vector machines, for voxel selection in MVPA. In the proposed approach, we first select the most informative voxels and then identify a response pattern based on the connectivity of the selected voxels. The effectiveness of the proposed approach was examined for the Haxby's dataset of object-level representations. The computational results demonstrated higher classification accuracy by the extracted response patterns, compared to state-of-the-art feature selection algorithms, such as forward selection and backward selection.

  20. Actors with Multi-Headed Message Receive Patterns

    DEFF Research Database (Denmark)

    Sulzmann, Martin; Lam, Edmund Soon Lee; Van Weert, Peter

    2008-01-01

    style actors with receive clauses containing multi-headed message patterns. Patterns may be non-linear and constrained by guards. We provide a number of examples to show the usefulness of the extension. We also explore the design space for multi-headed message matching semantics, for example first-match......The actor model provides high-level concurrency abstractions to coordinate simultaneous computations by message passing. Languages implementing the actor model such as Erlang commonly only support single-headed pattern matching over received messages. We propose and design an extension of Erlang...... and rule priority-match semantics. The various semantics are inspired by the multi-set constraint matching semantics found in Constraint Handling Rules. This provides us with a formal model to study actors with multi-headed message receive patterns. The system can be implemented efficiently and we have...

  1. Fabric Weave Pattern and Yarn Color Recognition and Classification Using a Deep ELM Network

    Directory of Open Access Journals (Sweden)

    Babar Khan

    2017-10-01

    Full Text Available Usually, a fabric weave pattern is recognized using methods which identify the warp floats and weft floats. Although these methods perform well for uniform or repetitive weave patterns, in the case of complex weave patterns, these methods become computationally complex and the classification error rates are comparatively higher. Furthermore, the fault-tolerance (invariance and stability (selectivity of the existing methods are still to be enhanced. We present a novel biologically-inspired method to invariantly recognize the fabric weave pattern (fabric texture and yarn color from the color image input. We proposed a model in which the fabric weave pattern descriptor is based on the HMAX model for computer vision inspired by the hierarchy in the visual cortex, the color descriptor is based on the opponent color channel inspired by the classical opponent color theory of human vision, and the classification stage is composed of a multi-layer (deep extreme learning machine. Since the weave pattern descriptor, yarn color descriptor, and the classification stage are all biologically inspired, we propose a method which is completely biologically plausible. The classification performance of the proposed algorithm indicates that the biologically-inspired computer-aided-vision models might provide accurate, fast, reliable and cost-effective solution to industrial automation.

  2. Nucleation of the Widmanstatten Pattern in Iron Meteorites

    Science.gov (United States)

    Yang, J.; Goldstein, J. I.

    2004-01-01

    The Widmanstatten pattern develops at low temperatures during the evolution of the asteroids. We have studied the origin of the Widmanstatten pattern in order to obtain metallographic cooling rates in the temperature range (approx. 700 to 300 deg C). This paper summarizes our recent evaluation of the various mechanisms for the formation of the Widmanstatten pattern. All chemical groups of the iron meteorites are considered. We also propose a new mechanism for the formation of the Widmanstatten pattern in the low P metal phase of iron, stony-iron and stony meteorites. The results of this evaluation enables us to more accurately determine metallographic cooling rates particularly when incorporated with other recent advances in Fe-Ni and Fe-Ni (P saturated) phase diagrams and interdiffusion coefficients.

  3. The impact of fracking on freight distribution patterns.

    Science.gov (United States)

    2016-11-01

    The increasing production of domestic energy through the use of fracking will likely alter local/regional/national economies and corresponding freight distribution patterns (highway, rail, marine, pipeline) in the United States. The proposed project ...

  4. Optimization of patterns of control bars using neural networks; Optimizacion de patrones de barras de control usando redes neuronales

    Energy Technology Data Exchange (ETDEWEB)

    Mejia S, D.M. [IPN, ESFM, Depto. de Ingenieria Nuclear, 07738 Mexico D.F. (Mexico); Ortiz S, J.J. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)]. e-mail: dulcema6715@hotmail.com

    2005-07-01

    In this work the RENOPBC system that is based on a recurrent multi state neural network, for the optimization of patterns of control bars in a cycle of balance of a boiling water reactor (BWR for their initials in English) is presented. The design of patterns of bars is based on the execution of operation thermal limits, to maintain criticizes the reactor and that the axial profile of power is adjusted to one predetermined along several steps of burnt. The patterns of control bars proposed by the system are comparable to those proposed by human experts with many hour-man of experience. These results are compared with those proposed by other techniques as genetic algorithms, colonies of ants and tabu search for the same operation cycle. As consequence it is appreciated that the proposed patterns of control bars, have bigger operation easiness that those proposed by the other techniques. (Author)

  5. A new method for discovering behavior patterns among animal movements

    Science.gov (United States)

    Wang, Y.; Luo, Ze; Takekawa, John Y.; Prosser, Diann J.; Xiong, Y.; Newman, S.; Xiao, X.; Batbayar, N.; Spragens, Kyle A.; Balachandran, S.; Yan, B.

    2016-01-01

    Advanced satellite tracking technologies enable biologists to track animal movements at fine spatial and temporal scales. The resultant data present opportunities and challenges for understanding animal behavioral mechanisms. In this paper, we develop a new method to elucidate animal movement patterns from tracking data. Here, we propose the notion of continuous behavior patterns as a concise representation of popular migration routes and underlying sequential behaviors during migration. Each stage in the pattern is characterized in terms of space (i.e., the places traversed during movements) and time (i.e. the time spent in those places); that is, the behavioral state corresponding to a stage is inferred according to the spatiotemporal and sequential context. Hence, the pattern may be interpreted predictably. We develop a candidate generation and refinement framework to derive all continuous behavior patterns from raw trajectories. In the framework, we first define the representative spots to denote the underlying potential behavioral states that are extracted from individual trajectories according to the similarity of relaxed continuous locations in certain distinct time intervals. We determine the common behaviors of multiple individuals according to the spatiotemporal proximity of representative spots and apply a projection-based extension approach to generate candidate sequential behavior sequences as candidate patterns. Finally, the candidate generation procedure is combined with a refinement procedure to derive continuous behavior patterns. We apply an ordered processing strategy to accelerate candidate refinement. The proposed patterns and discovery framework are evaluated through conceptual experiments on both real GPS-tracking and large synthetic datasets.

  6. Automated CBED processing: Sample thickness estimation based on analysis of zone-axis CBED pattern

    Energy Technology Data Exchange (ETDEWEB)

    Klinger, M., E-mail: klinger@post.cz; Němec, M.; Polívka, L.; Gärtnerová, V.; Jäger, A.

    2015-03-15

    An automated processing of convergent beam electron diffraction (CBED) patterns is presented. The proposed methods are used in an automated tool for estimating the thickness of transmission electron microscopy (TEM) samples by matching an experimental zone-axis CBED pattern with a series of patterns simulated for known thicknesses. The proposed tool detects CBED disks, localizes a pattern in detected disks and unifies the coordinate system of the experimental pattern with the simulated one. The experimental pattern is then compared disk-by-disk with a series of simulated patterns each corresponding to different known thicknesses. The thickness of the most similar simulated pattern is then taken as the thickness estimate. The tool was tested on [0 1 1] Si, [0 1 0] α-Ti and [0 1 1] α-Ti samples prepared using different techniques. Results of the presented approach were compared with thickness estimates based on analysis of CBED patterns in two beam conditions. The mean difference between these two methods was 4.1% for the FIB-prepared silicon samples, 5.2% for the electro-chemically polished titanium and 7.9% for Ar{sup +} ion-polished titanium. The proposed techniques can also be employed in other established CBED analyses. Apart from the thickness estimation, it can potentially be used to quantify lattice deformation, structure factors, symmetry, defects or extinction distance. - Highlights: • Automated TEM sample thickness estimation using zone-axis CBED is presented. • Computer vision and artificial intelligence are employed in CBED processing. • This approach reduces operator effort, analysis time and increases repeatability. • Individual parts can be employed in other analyses of CBED/diffraction pattern.

  7. Wavelet-based moment invariants for pattern recognition

    Science.gov (United States)

    Chen, Guangyi; Xie, Wenfang

    2011-07-01

    Moment invariants have received a lot of attention as features for identification and inspection of two-dimensional shapes. In this paper, two sets of novel moments are proposed by using the auto-correlation of wavelet functions and the dual-tree complex wavelet functions. It is well known that the wavelet transform lacks the property of shift invariance. A little shift in the input signal will cause very different output wavelet coefficients. The autocorrelation of wavelet functions and the dual-tree complex wavelet functions, on the other hand, are shift-invariant, which is very important in pattern recognition. Rotation invariance is the major concern in this paper, while translation invariance and scale invariance can be achieved by standard normalization techniques. The Gaussian white noise is added to the noise-free images and the noise levels vary with different signal-to-noise ratios. Experimental results conducted in this paper show that the proposed wavelet-based moments outperform Zernike's moments and the Fourier-wavelet descriptor for pattern recognition under different rotation angles and different noise levels. It can be seen that the proposed wavelet-based moments can do an excellent job even when the noise levels are very high.

  8. A system for learning statistical motion patterns.

    Science.gov (United States)

    Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

    2006-09-01

    Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

  9. Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization.

    Science.gov (United States)

    Peng, Huan-Kai; Lee, Hao-Chih; Pan, Jia-Yu; Marculescu, Radu

    2016-01-01

    In this paper, we define a new problem related to social media, namely, the data-driven engineering of social dynamics. More precisely, given a set of observations from the past, we aim at finding the best short-term intervention that can lead to predefined long-term outcomes. Toward this end, we propose a general formulation that covers two useful engineering tasks as special cases, namely, pattern matching and profit maximization. By incorporating a deep learning model, we derive a solution using convex relaxation and quadratic-programming transformation. Moreover, we propose a data-driven evaluation method in place of the expensive field experiments. Using a Twitter dataset, we demonstrate the effectiveness of our dynamics engineering approach for both pattern matching and profit maximization, and study the multifaceted interplay among several important factors of dynamics engineering, such as solution validity, pattern-matching accuracy, and intervention cost. Finally, the method we propose is general enough to work with multi-dimensional time series, so it can potentially be used in many other applications.

  10. Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization.

    Directory of Open Access Journals (Sweden)

    Huan-Kai Peng

    Full Text Available In this paper, we define a new problem related to social media, namely, the data-driven engineering of social dynamics. More precisely, given a set of observations from the past, we aim at finding the best short-term intervention that can lead to predefined long-term outcomes. Toward this end, we propose a general formulation that covers two useful engineering tasks as special cases, namely, pattern matching and profit maximization. By incorporating a deep learning model, we derive a solution using convex relaxation and quadratic-programming transformation. Moreover, we propose a data-driven evaluation method in place of the expensive field experiments. Using a Twitter dataset, we demonstrate the effectiveness of our dynamics engineering approach for both pattern matching and profit maximization, and study the multifaceted interplay among several important factors of dynamics engineering, such as solution validity, pattern-matching accuracy, and intervention cost. Finally, the method we propose is general enough to work with multi-dimensional time series, so it can potentially be used in many other applications.

  11. Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization

    Science.gov (United States)

    Peng, Huan-Kai; Lee, Hao-Chih; Pan, Jia-Yu; Marculescu, Radu

    2016-01-01

    In this paper, we define a new problem related to social media, namely, the data-driven engineering of social dynamics. More precisely, given a set of observations from the past, we aim at finding the best short-term intervention that can lead to predefined long-term outcomes. Toward this end, we propose a general formulation that covers two useful engineering tasks as special cases, namely, pattern matching and profit maximization. By incorporating a deep learning model, we derive a solution using convex relaxation and quadratic-programming transformation. Moreover, we propose a data-driven evaluation method in place of the expensive field experiments. Using a Twitter dataset, we demonstrate the effectiveness of our dynamics engineering approach for both pattern matching and profit maximization, and study the multifaceted interplay among several important factors of dynamics engineering, such as solution validity, pattern-matching accuracy, and intervention cost. Finally, the method we propose is general enough to work with multi-dimensional time series, so it can potentially be used in many other applications. PMID:26771830

  12. In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning

    Directory of Open Access Journals (Sweden)

    Vinicius Pegorini

    2015-11-01

    Full Text Available Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%.

  13. In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning.

    Science.gov (United States)

    Pegorini, Vinicius; Karam, Leandro Zen; Pitta, Christiano Santos Rocha; Cardoso, Rafael; da Silva, Jean Carlos Cardozo; Kalinowski, Hypolito José; Ribeiro, Richardson; Bertotti, Fábio Luiz; Assmann, Tangriani Simioni

    2015-11-11

    Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%.

  14. Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies

    Science.gov (United States)

    Fournier-Viger, Philippe; Nkambou, Roger; Faghihi, Usef; Nguifo, Engelbert Mephu

    We propose two mechanisms for agent learning based on the idea of mining temporal patterns from agent behavior. The first one consists of extracting temporal patterns from the perceived behavior of other agents accomplishing a task, to learn the task. The second learning mechanism consists in extracting temporal patterns from an agent's own behavior. In this case, the agent then reuses patterns that brought self-satisfaction. In both cases, no assumption is made on how the observed agents' behavior is internally generated. A case study with a real application is presented to illustrate each learning mechanism.

  15. Latent Feature Models for Uncovering Human Mobility Patterns from Anonymized User Location Traces with Metadata

    KAUST Repository

    Alharbi, Basma Mohammed

    2017-04-10

    In the mobile era, data capturing individuals’ locations have become unprecedentedly available. Data from Location-Based Social Networks is one example of large-scale user-location data. Such data provide a valuable source for understanding patterns governing human mobility, and thus enable a wide range of research. However, mining and utilizing raw user-location data is a challenging task. This is mainly due to the sparsity of data (at the user level), the imbalance of data with power-law users and locations check-ins degree (at the global level), and more importantly the lack of a uniform low-dimensional feature space describing users. Three latent feature models are proposed in this dissertation. Each proposed model takes as an input a collection of user-location check-ins, and outputs a new representation space for users and locations respectively. To avoid invading users privacy, the proposed models are designed to learn from anonymized location data where only IDs - not geophysical positioning or category - of locations are utilized. To enrich the inferred mobility patterns, the proposed models incorporate metadata, often associated with user-location data, into the inference process. In this dissertation, two types of metadata are utilized to enrich the inferred patterns, timestamps and social ties. Time adds context to the inferred patterns, while social ties amplifies incomplete user-location check-ins. The first proposed model incorporates timestamps by learning from collections of users’ locations sharing the same discretized time. The second proposed model also incorporates time into the learning model, yet takes a further step by considering time at different scales (hour of a day, day of a week, month, and so on). This change in modeling time allows for capturing meaningful patterns over different times scales. The last proposed model incorporates social ties into the learning process to compensate for inactive users who contribute a large volume

  16. Ultrafast layer based computer-generated hologram calculation with sparse template holographic fringe pattern for 3-D object.

    Science.gov (United States)

    Kim, Hak Gu; Man Ro, Yong

    2017-11-27

    In this paper, we propose a new ultrafast layer based CGH calculation that exploits the sparsity of hologram fringe pattern in 3-D object layer. Specifically, we devise a sparse template holographic fringe pattern. The holographic fringe pattern on a depth layer can be rapidly calculated by adding the sparse template holographic fringe patterns at each object point position. Since the size of sparse template holographic fringe pattern is much smaller than that of the CGH plane, the computational load can be significantly reduced. Experimental results show that the proposed method achieves 10-20 msec for 1024x1024 pixels providing visually plausible results.

  17. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs

    Directory of Open Access Journals (Sweden)

    Sungjun Lee

    2016-01-01

    Full Text Available Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user’s next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user’s past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user’s next places than the previous approaches considered in most cases.

  18. OBJECT TRACKING WITH ROTATION-INVARIANT LARGEST DIFFERENCE INDEXED LOCAL TERNARY PATTERN

    Directory of Open Access Journals (Sweden)

    J Shajeena

    2017-02-01

    Full Text Available This paper presents an ideal method for object tracking directly in the compressed domain in video sequences. An enhanced rotation-invariant image operator called Largest Difference Indexed Local Ternary Pattern (LDILTP has been proposed. The Local Ternary Pattern which worked very well in texture classification and face recognition is now extended for rotation invariant object tracking. Histogramming the LTP code makes the descriptor resistant to translation. The histogram intersection is used to find the similarity measure. This method is robust to noise and retain contrast details. The proposed scheme has been verified on various datasets and shows a commendable performance.

  19. Endothelial cell motility, coordination and pattern formation during vasculogenesis.

    Science.gov (United States)

    Czirok, Andras

    2013-01-01

    How vascular networks assemble is a fundamental problem of developmental biology that also has medical importance. To explain the organizational principles behind vascular patterning, we must understand how can tissue level structures be controlled through cell behavior patterns like motility and adhesion that, in turn, are determined by biochemical signal transduction processes? We discuss the various ideas that have been proposed as mechanisms for vascular network assembly: cell motility guided by extracellular matrix alignment (contact guidance), chemotaxis guided by paracrine and autocrine morphogens, and multicellular sprouting guided by cell-cell contacts. All of these processes yield emergent patterns, thus endothelial cells can form an interconnected structure autonomously, without guidance from an external pre-pattern. © 2013 Wiley Periodicals, Inc.

  20. Image Watermarking Scheme for Specifying False Positive Probability and Bit-pattern Embedding

    Science.gov (United States)

    Sayama, Kohei; Nakamoto, Masayoshi; Muneyasu, Mitsuji; Ohno, Shuichi

    This paper treats a discrete wavelet transform(DWT)-based image watermarking with considering the false positive probability and bit-pattern embedding. We propose an iterative embedding algorithm of watermarking signals which are K sets pseudo-random numbers generated by a secret key. In the detection, K correlations between the watermarked DWT coefficients and watermark signals are computed by using the secret key. L correlations are made available for the judgment of the watermark presence with specified false positive probability, and the other K-L correlations are corresponding to the bit-pattern signal. In the experiment, we show the detection results with specified false positive probability and the bit-pattern recovery, and the comparison of the proposed method against JPEG compression, scaling down and cropping.

  1. Landscape metrics for three-dimension urban pattern recognition

    Science.gov (United States)

    Liu, M.; Hu, Y.; Zhang, W.; Li, C.

    2017-12-01

    Understanding how landscape pattern determines population or ecosystem dynamics is crucial for managing our landscapes. Urban areas are becoming increasingly dominant social-ecological systems, so it is important to understand patterns of urbanization. Most studies of urban landscape pattern examine land-use maps in two dimensions because the acquisition of 3-dimensional information is difficult. We used Brista software based on Quickbird images and aerial photos to interpret the height of buildings, thus incorporating a 3-dimensional approach. We estimated the feasibility and accuracy of this approach. A total of 164,345 buildings in the Liaoning central urban agglomeration of China, which included seven cities, were measured. Twelve landscape metrics were proposed or chosen to describe the urban landscape patterns in 2- and 3-dimensional scales. The ecological and social meaning of landscape metrics were analyzed with multiple correlation analysis. The results showed that classification accuracy compared with field surveys was 87.6%, which means this method for interpreting building height was acceptable. The metrics effectively reflected the urban architecture in relation to number of buildings, area, height, 3-D shape and diversity aspects. We were able to describe the urban characteristics of each city with these metrics. The metrics also captured ecological and social meanings. The proposed landscape metrics provided a new method for urban landscape analysis in three dimensions.

  2. Towards Tamper-Evident Storage on Patterned Media

    NARCIS (Netherlands)

    Hartel, Pieter H.; Abelmann, Leon; Khatib, Mohammed G.; Baker, M.; Riedel, E.

    We propose a tamper-evident storage system based on probe storage with a patterned magnetic medium. This medium supports normal read/write operations by out-of-plane magnetisation of individual magnetic dots. We report on measurements showing that in principle the medium also supports a separate

  3. American Crystallographic Association Project: numerical ratings of powder diffraction patterns

    International Nuclear Information System (INIS)

    Smith, G.S.; Snyder, R.L.

    1977-01-01

    At present, nearly 30,000 powder diffraction patterns are available as references. It is proposed that the patterns in this file as well as new patterns submitted for publication be given quantitative quality factors. A simple-to-use figure of merit, F/sub N/, covering both accuracy of d-values and completeness of a pattern was derived. This figure of merit provides the user with a means of rapid evaluation of powder patterns in much the same way that the R-factor does for single-crystal structure determinations. The present F/sub N/ ranking scheme is shown to be superior to de Wolff's M 20 ranking scheme. It is recommended that the latter be discontinued. Guidelines are given on the use and implementation of F/sub N/ rating of powder diffraction patterns

  4. Patterning crystalline indium tin oxide by high repetition rate femtosecond laser-induced crystallization

    International Nuclear Information System (INIS)

    Cheng, Chung-Wei; Lin, Cen-Ying; Shen, Wei-Chih; Lee, Yi-Ju; Chen, Jenq-Shyong

    2010-01-01

    A method is proposed for patterning crystalline indium tin oxide (c-ITO) patterns on amorphous ITO (a-ITO) thin films by femtosecond laser irradiation at 80 MHz repetition rate followed by chemical etching. In the proposed approach, the a-ITO film is transformed into a c-ITO film over a predetermined area via the heat accumulation energy supplied by the high repetition rate laser beam, and the unirradiated a-ITO film is then removed using an acidic etchant solution. The fabricated c-ITO patterns are observed using scanning electron microscopy and cross-sectional transmission electron microscopy. The crystalline, optical, electrical properties were measured by X-ray diffraction, spectrophotometer, and four point probe station, respectively. The experimental results show that a high repetition rate reduces thermal shock and yields a corresponding improvement in the surface properties of the c-ITO patterns.

  5. A feasibility study of low-order harmonics expansion applied to loading pattern search

    Energy Technology Data Exchange (ETDEWEB)

    Shaohong, Z.; Dong, L.; Tao, W. [Shanghai Jiao Tong Univ., 1954 Hua Shan Road, Shanghai, 200030 (China); Chao, Y. A. [Westinghouse Electric Company, P. O. Box 355, Pittsburgh, PA 15230-0355 (United States)

    2006-07-01

    Despite significant progress in core loading pattern search methods over years, there still remains the issue of large computing workload and the need for improving the speed of evaluating loading pattern candidates during the search process. This paper focuses on improving the computing speed for loading pattern evaluation, rather than the method of searching for the patterns. A low order harmonics expansion method for flux distribution representation is proposed for fast LP evaluation application. The novel feature of the method is the separation of the short range local perturbation effect from the long range global tilt effect. The latter effect can be captured by low order harmonics expansion. Demonstration examples are presented to show that even for extremely large perturbations induced by fuel shuffling the proposed method can accurately calculate the flux distribution for the LP with very minimal computation. (authors)

  6. Simple micro-patterning of high conductive polymer with UV-nano-imprinted patterned substrate and ethylene glycol-based second doping

    International Nuclear Information System (INIS)

    Takamatsu, Seiichi; Kurihara, Kazuma; Yamashita, Takahiro; Itoh, Toshihiro

    2014-01-01

    We have developed a simple micro-patterning process for high conductive polymer (i.e., poly (3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)) with a patterned substrate by using an ultraviolet (UV) nano-imprint and an ethylene glycol-based second doping technique. In the patterning process, the PEDOT:PSS water dispersion is first coated only on the hydrophilic area, which is fabricated by UV nano-imprinting, forming patterned PEDOT:PSS on the substrate. The patterned PEDOT:PSS film is then immersed in the ethylene glycol as a second doping technique for increasing its conductivity. The proposed process provides simplicity in terms of shorter process steps of the UV nano-imprinting and PEDOT:PSS coating and higher conductivity of patterned PEDOT:PSS film than existing complicated micro-fabrication processes for organic materials. The 200 nm wide nano-imprinted pillar structures change the wettability of the substrate where the contact angle of the substrate is decreased from 66.8° to 33.3°. The patterning resolution with the nano-imprinted pattern substrate is down to 100 µm, which is useful for sensor applications. The conductivity increase delivers a low sheet resistance (120 Ω sq −1 ) of patterned PEDOT:PSS film. Then, the patterning of PEDOT:PSS sensor shapes with its 300 µm wide feature line and high conductivity are demonstrated. Therefore, our process leads to applications to a variety of PEDOT:PSS-based sensors. (paper)

  7. A SOM clustering pattern sequence-based next symbol prediction method for day-ahead direct electricity load and price forecasting

    International Nuclear Information System (INIS)

    Jin, Cheng Hao; Pok, Gouchol; Lee, Yongmi; Park, Hyun-Woo; Kim, Kwang Deuk; Yun, Unil; Ryu, Keun Ho

    2015-01-01

    Highlights: • A novel pattern sequence-based direct time series forecasting method was proposed. • Due to the use of SOM’s topology preserving property, only SOM can be applied. • SCPSNSP only deals with the cluster patterns not each specific time series value. • SCPSNSP performs better than recently developed forecasting algorithms. - Abstract: In this paper, we propose a new day-ahead direct time series forecasting method for competitive electricity markets based on clustering and next symbol prediction. In the clustering step, pattern sequence and their topology relations are obtained from self organizing map time series clustering. In the next symbol prediction step, with each cluster label in the pattern sequence represented as a pair of its topologically identical coordinates, artificial neural network is used to predict the topological coordinates of next day by training the relationship between previous daily pattern sequence and its next day pattern. According to the obtained topology relations, the nearest nonzero hits pattern is assigned to next day so that the whole time series values can be directly forecasted from the assigned cluster pattern. The proposed method was evaluated on Spanish, Australian and New York electricity markets and compared with PSF and some of the most recently published forecasting methods. Experimental results show that the proposed method outperforms the best forecasting methods at least 3.64%

  8. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System.

    Science.gov (United States)

    Epstein, Jonathan I; Egevad, Lars; Amin, Mahul B; Delahunt, Brett; Srigley, John R; Humphrey, Peter A

    2016-02-01

    of 10, it implies that their prognosis is intermediate and contributes to their fear of having a more aggressive cancer. Also, in the literature and for therapeutic purposes, various scores have been incorrectly grouped together with the assumption that they have a similar prognosis. For example, many classification systems consider Gleason score 7 as a single score without distinguishing 3+4 versus 4+3, despite studies showing significantly worse prognosis for the latter. The basis for a new grading system was proposed in 2013 by one of the authors (J.I.E.) based on data from Johns Hopkins Hospital resulting in 5 prognostically distinct Grade Groups. This new system was validated in a multi-institutional study of over 20,000 radical prostatectomy specimens, over 16,000 needle biopsy specimens, and over 5,000 biopsies followed by radiation therapy. There was broad (90%) consensus for the adoption of this new prostate cancer Grading system in the 2014 consensus conference based on: (1) the new classification provided more accurate stratification of tumors than the current system; (2) the classification simplified the number of grading categories from Gleason scores 2 to 10, with even more permutations based on different pattern combinations, to Grade Groups 1 to 5; (3) the lowest grade is 1 not 6 as in Gleason, with the potential to reduce overtreatment of indolent cancer; and (4) the current modified Gleason grading, which forms the basis for the new grade groups, bears little resemblance to the original Gleason system. The new grades would, for the foreseeable future, be used in conjunction with the Gleason system [ie. Gleason score 3+3=6 (Grade Group 1)]. The new grading system and the terminology Grade Groups 1-5 have also been accepted by the World Health Organization for the 2016 edition of Pathology and Genetics: Tumours of the Urinary System and Male Genital Organs.

  9. Selective metal pattern formation and its EMI shielding efficiency

    International Nuclear Information System (INIS)

    Lee, Ho-Chul; Kim, Jin-Young; Noh, Chang-Ho; Song, Ki Yong; Cho, Sung-Heon

    2006-01-01

    A novel method for selective metal pattern formation by using an enhanced life-time of photoexcited electron-hole pairs in bilayer thin film of amorphous titanium dioxide and hole-scavenger-containing poly(vinyl alcohol) was proposed. By UV-irradiation through photomask on the bilayer film, the photodefined image of photoelectrons could be easily and simply produced, consequently resulting in selective palladium (Pd) catalyst deposition by reduction. The successive electrolessplating on Pd catalysts and electroplating on electrolessplated pattern were possible. Furthermore, the electromagnetic interference shielding efficiencies of the metal mesh patterns with various characteristic length scales of line width and thickness were investigated

  10. Definition of new 3D invariants. Applications to pattern recognition problems with neural networks

    International Nuclear Information System (INIS)

    Proriol, J.

    1996-01-01

    We propose a definition of new 3D invariants. Usual pattern recognition methods use 2D descriptions of 3D objects, we propose a 2D approximation of the defined 3D invariants which can be used with neural networks to solve pattern recognition problems. We describe some methods to use the 2 D approximants. This work is an extension of previous 3D invariants used to solve some high energy physics problems. (author)

  11. Auto warranty and driving patterns

    International Nuclear Information System (INIS)

    Anastasiadis, Simon; Anderson, Boyd; Chukova, Stefanka

    2013-01-01

    Automobile warranty coverage is typically limited by age as well as mileage. However, the age is known for all sold vehicles at all times, but mileage is only observed for a vehicle with a claim and only at the time of the claim. We study the relationship between the expected number/cost of warranty claims and the driving patterns. Within a nonparametric framework, we account for the rate of mileage accumulation and propose a measure for the variability of this rate over a vehicle's observable life. We illustrate the ideas with real warranty data and comment on the relationship between the expected number/cost of warranty claims and the driving patterns using results adjusted/unadjusted for withdrawals from the warranty coverage due to mileage accumulation

  12. What drives the formation of global oil trade patterns?

    International Nuclear Information System (INIS)

    Zhang, Hai-Ying; Ji, Qiang; Fan, Ying

    2015-01-01

    In this paper, the spatial characteristics of current global oil trade patterns are investigated by proposing a new indicator Moran-F. Meanwhile, the factors that influence the formation of oil trade patterns are identified by constructing four different kinds of spatial econometric models. The findings indicate that most oil exporters have an obvious export focus in North America and a relatively balanced export in Europe and the Asia-Pacific region. Besides supply and demand factors, technological progress and energy efficiency have also significantly influenced the oil trade. Moreover, there is a spillover effect of trade flow among different regions, but its impact is weak. In addition, oil importers in the same region have the potential to cooperate due to their similar import sources. Finally, promotion of oil importers' R&D investments can effectively reduce the demand for global oil trade. - Highlights: • A new spatial association Moran-F indicator that applies to trade flows is proposed. • Driving factors affecting the formation of oil trade patterns are identified. • Oil-exporting countries implement various export strategies in different regions. • Supply, demand and technological factors contribute to the oil trade patterns. • Spillover effect of each factor affecting oil trade flows does exist but is limited

  13. Three-dimensional shape profiling by out-of-focus projection of colored pulse width modulation fringe patterns.

    Science.gov (United States)

    Silva, Adriana; Flores, Jorge L; Muñoz, Antonio; Ayubi, Gastón A; Ferrari, José A

    2017-06-20

    Three-dimensional (3D) shape profiling by sinusoidal phase-shifting methods is affected by the non-linearity of the projector. To overcome this problem, the defocusing technique has become an important alternative to generate sinusoidal fringe patterns. The precision of this method depends on the binary pattern used and on the defocusing applied. To improve the defocusing technique, we propose the implementation of a color-based binary fringe patterns. The proposed technique involves the generation of colored pulse width modulation (PWM) fringe patterns, which are generated with different frequencies at the carrier signal. From an adequate selection of these frequencies, the colored PWM fringe patterns will lead to amplitude harmonics lower than the conventional PWM fringe patterns. Hence, the defocusing can decrease, and the 3D shape profiling can be more accurate. Numerical simulations and experimental results are presented as validation.

  14. Mobile assemblies of Bennett linkages from four-crease origami patterns

    Science.gov (United States)

    Zhang, Xiao; Chen, Yan

    2018-02-01

    This paper deals with constructing mobile assemblies of Bennett linkages inspired by four-crease origami patterns. A transition technique has been proposed by taking the thick-panel form of an origami pattern as an intermediate bridge. A zero-thickness rigid origami pattern and its thick-panel form share the same sector angles and folding behaviours, while the thick-panel origami and the mobile assembly of linkages are kinematically equivalent with differences only in link profiles. Applying this transition technique to typical four-crease origami patterns, we have found that the Miura-ori and graded Miura-ori patterns lead to assemblies of Bennett linkages with identical link lengths. The supplementary-type origami patterns with different mountain-valley crease assignments correspond to different types of Bennett linkage assemblies with negative link lengths. And the identical linkage-type origami pattern generates a new mobile assembly. Hence, the transition technique offers a novel approach to constructing mobile assemblies of spatial linkages from origami patterns.

  15. Comparing sets of patterns with the Jaccard index

    Directory of Open Access Journals (Sweden)

    Sam Fletcher

    2018-03-01

    Full Text Available The ability to extract knowledge from data has been the driving force of Data Mining since its inception, and of statistical modeling long before even that. Actionable knowledge often takes the form of patterns, where a set of antecedents can be used to infer a consequent. In this paper we offer a solution to the problem of comparing different sets of patterns. Our solution allows comparisons between sets of patterns that were derived from different techniques (such as different classification algorithms, or made from different samples of data (such as temporal data or data perturbed for privacy reasons. We propose using the Jaccard index to measure the similarity between sets of patterns by converting each pattern into a single element within the set. Our measure focuses on providing conceptual simplicity, computational simplicity, interpretability, and wide applicability. The results of this measure are compared to prediction accuracy in the context of a real-world data mining scenario.

  16. A node linkage approach for sequential pattern mining.

    Directory of Open Access Journals (Sweden)

    Osvaldo Navarro

    Full Text Available Sequential Pattern Mining is a widely addressed problem in data mining, with applications such as analyzing Web usage, examining purchase behavior, and text mining, among others. Nevertheless, with the dramatic increase in data volume, the current approaches prove inefficient when dealing with large input datasets, a large number of different symbols and low minimum supports. In this paper, we propose a new sequential pattern mining algorithm, which follows a pattern-growth scheme to discover sequential patterns. Unlike most pattern growth algorithms, our approach does not build a data structure to represent the input dataset, but instead accesses the required sequences through pseudo-projection databases, achieving better runtime and reducing memory requirements. Our algorithm traverses the search space in a depth-first fashion and only preserves in memory a pattern node linkage and the pseudo-projections required for the branch being explored at the time. Experimental results show that our new approach, the Node Linkage Depth-First Traversal algorithm (NLDFT, has better performance and scalability in comparison with state of the art algorithms.

  17. Sound recovery via intensity variations of speckle pattern pixels selected with variance-based method

    Science.gov (United States)

    Zhu, Ge; Yao, Xu-Ri; Qiu, Peng; Mahmood, Waqas; Yu, Wen-Kai; Sun, Zhi-Bin; Zhai, Guang-Jie; Zhao, Qing

    2018-02-01

    In general, the sound waves can cause the vibration of the objects that are encountered in the traveling path. If we make a laser beam illuminate the rough surface of an object, it will be scattered into a speckle pattern that vibrates with these sound waves. Here, an efficient variance-based method is proposed to recover the sound information from speckle patterns captured by a high-speed camera. This method allows us to select the proper pixels that have large variances of the gray-value variations over time, from a small region of the speckle patterns. The gray-value variations of these pixels are summed together according to a simple model to recover the sound with a high signal-to-noise ratio. Meanwhile, our method will significantly simplify the computation compared with the traditional digital-image-correlation technique. The effectiveness of the proposed method has been verified by applying a variety of objects. The experimental results illustrate that the proposed method is robust to the quality of the speckle patterns and costs more than one-order less time to perform the same number of the speckle patterns. In our experiment, a sound signal of time duration 1.876 s is recovered from various objects with time consumption of 5.38 s only.

  18. Methodology for evaluating pattern transfer completeness in inkjet printing with irregular edges

    Science.gov (United States)

    Huang, Bo-Cin; Chan, Hui-Ju; Hong, Jian-Wei; Lo, Cheng-Yao

    2016-06-01

    A methodology for quantifying and qualifying pattern transfer completeness in inkjet printing through examining both pattern dimensions and pattern contour deviations from reference design is proposed, which enables scientifically identifying and evaluating inkjet-printed lines, corners, circles, ellipses, and spirals with irregular edges of bulging, necking, and unpredictable distortions resulting from different process conditions. This methodology not only avoids differences in individual perceptions of ambiguous pattern distortions but also indicates the systematic effects of mechanical stresses applied in different directions to a polymer substrate, and is effective for both optical and electrical microscopy in direct and indirect lithography or lithography-free patterning.

  19. Methodology for evaluating pattern transfer completeness in inkjet printing with irregular edges

    International Nuclear Information System (INIS)

    Huang, Bo-Cin; Chan, Hui-Ju; Lo, Cheng-Yao; Hong, Jian-Wei

    2016-01-01

    A methodology for quantifying and qualifying pattern transfer completeness in inkjet printing through examining both pattern dimensions and pattern contour deviations from reference design is proposed, which enables scientifically identifying and evaluating inkjet-printed lines, corners, circles, ellipses, and spirals with irregular edges of bulging, necking, and unpredictable distortions resulting from different process conditions. This methodology not only avoids differences in individual perceptions of ambiguous pattern distortions but also indicates the systematic effects of mechanical stresses applied in different directions to a polymer substrate, and is effective for both optical and electrical microscopy in direct and indirect lithography or lithography-free patterning. (paper)

  20. From lag synchronization to pattern formation in one-dimensional open flow models

    International Nuclear Information System (INIS)

    Liu Zengrong; Luo Jigui

    2006-01-01

    In this paper, the relation between synchronization and pattern formation in one-dimensional discrete and continuous open flow models is investigated in detail. Firstly a sufficient condition for globally asymptotical stability of lag/anticipating synchronization among lattices of these models is proved by analytic method. Then, by analyzing and simulating lag/anticipating synchronization in discrete case, three kinds of pattern of wave (it is called wave pattern) travelling in the lattices are discovered. Finally, a proper definition for these kinds of pattern is proposed

  1. Estimation of color modification in digital images by CFA pattern change.

    Science.gov (United States)

    Choi, Chang-Hee; Lee, Hae-Yeoun; Lee, Heung-Kyu

    2013-03-10

    Extensive studies have been carried out for detecting image forgery such as copy-move, re-sampling, blurring, and contrast enhancement. Although color modification is a common forgery technique, there is no reported forensic method for detecting this type of manipulation. In this paper, we propose a novel algorithm for estimating color modification in images acquired from digital cameras when the images are modified. Most commercial digital cameras are equipped with a color filter array (CFA) for acquiring the color information of each pixel. As a result, the images acquired from such digital cameras include a trace from the CFA pattern. This pattern is composed of the basic red green blue (RGB) colors, and it is changed when color modification is carried out on the image. We designed an advanced intermediate value counting method for measuring the change in the CFA pattern and estimating the extent of color modification. The proposed method is verified experimentally by using 10,366 test images. The results confirmed the ability of the proposed method to estimate color modification with high accuracy. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  2. 78 FR 62814 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule...

    Science.gov (United States)

    2013-10-22

    ...-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule Change To Assume... Authority and Supervision September 30, 2013. On July 31, 2013, The NASDAQ Stock Market LLC (``NASDAQ'' or...) Manipulation patterns that monitor solely NASDAQ activity, including patterns that monitor the Exchange's...

  3. Control of the Radiation Patterns Using Homogeneous and Isotropic Impedance Metasurface

    Directory of Open Access Journals (Sweden)

    Fan Yang

    2015-01-01

    Full Text Available We propose to control the radiation patterns of a two-dimensional (2D point source by using impedance metasurfaces. We show that the radiation patterns can be manipulated by altering the surface impedance of the metasurface. Full-wave simulation results are provided to validate the theoretical derivations. The proposed design enjoys novel properties of isotropy, homogeneity, low profile, and high selectivity of frequency, making it potentially applicable in many applications. We also point out that this design can be implemented with active metasurfaces and the surface impedance can be tuned by modulating the value of loaded elements, like resistors, inductors, and capacitors.

  4. Optimal defocus selection based on normed Fourier transform for digital fringe pattern profilometry.

    Science.gov (United States)

    Kamagara, Abel; Wang, Xiangzhao; Li, Sikun

    2017-10-01

    Owing to gamma-effect robustness and high-speed imaging capabilities, projector defocusing of binary-coded fringe patterns is by far the most widely used and effective technique in generating sinusoidal fringe patterns for three-dimensional optical topography measurement with digital fringe projection techniques. However, this technique is not trouble-free. It is borne with uncertainty and challenges mainly because it remains somewhat difficult to quantify and ascertain the level of defocus required for desired fidelity in sinuousness of the projected fringe pattern. Too much or too little defocusing will affect the sinuosity accuracy of fringe patterns and consequently jeopardize the quality of the measurement results. In this paper, by combining intrinsic phase spectral sensitivities and normed Fourier transform, a method to quantify the amount of defocus and subsequently select the optimal degree of sinuosity for generating digital sinusoidal fringe patterns with projector defocusing for fringe pattern optical three-dimensional profilometry is proposed. Numerical simulations plus experiments give evidence of the feasibility and validity of the proposed method in enabling an improved digital binary defocusing technique for optical phase-shift profilometry using the digital fringe projection technique.

  5. Formation of periodic and localized patterns in an oscillating granular layer.

    Energy Technology Data Exchange (ETDEWEB)

    Aranson, I.; Tsimring, L. S.; Materials Science Division; Bar Ilan Univ.; Univ. of California at San Diego

    1998-02-01

    A simple phenomenological model for pattern formation in a vertically vibrated layer of granular particles is proposed. This model exhibits a variety of stable cellular patterns including standing rolls and squares as well as localized excitations (oscillons and worms), similar to recent experimental observations (Umbanhowar et al., 1996). The model is an order parameter equation for the parametrically excited waves coupled to the mass conservation law. The structure and dynamics of the solutions resemble closely the properties of patterns observed in the experiments.

  6. Pre-conceptual-schema-based patterns for deriving key performance indicators from strategic objectives

    Directory of Open Access Journals (Sweden)

    Carlos Mario Zapata Jaramillo

    2017-05-01

    Full Text Available Performance measurement is crucial for achieving business success. Moreover, such success is also related to the fulfillment of the organizational strategic objectives. Hence, an adequate determination of relevant performance indicators—or key performance indicators (KPIs—and their relationships to organizational objectives is needed. Even though several approaches for treating KPIs and objective-KPI relationships have been proposed, they exhibit some drawbacks associated with the lack of reusability and traceability. We attempt to fill this gap by proposing a set of patterns based on pre-conceptual schemas for supporting the systematic derivation of KPIs and their relationships to organizational objectives. In this way, the proposed patterns guarantee a reusable and traceable derivation process of a set of candidate KPIs from organizational strategic objectives. Lastly, we provide a lab study in order to illustrate the usefulness of this proposal.

  7. Hidden pattern discovery on epileptic EEG with 1-D local binary patterns and epileptic seizures detection by grey relational analysis.

    Science.gov (United States)

    Kaya, Yılmaz

    2015-09-01

    This paper proposes a novel approach to detect epilepsy seizures by using Electroencephalography (EEG), which is one of the most common methods for the diagnosis of epilepsy, based on 1-Dimension Local Binary Pattern (1D-LBP) and grey relational analysis (GRA) methods. The main aim of this paper is to evaluate and validate a novel approach, which is a computer-based quantitative EEG analyzing method and based on grey systems, aimed to help decision-maker. In this study, 1D-LBP, which utilizes all data points, was employed for extracting features in raw EEG signals, Fisher score (FS) was employed to select the representative features, which can also be determined as hidden patterns. Additionally, GRA is performed to classify EEG signals through these Fisher scored features. The experimental results of the proposed approach, which was employed in a public dataset for validation, showed that it has a high accuracy in identifying epileptic EEG signals. For various combinations of epileptic EEG, such as A-E, B-E, C-E, D-E, and A-D clusters, 100, 96, 100, 99.00 and 100% were achieved, respectively. Also, this work presents an attempt to develop a new general-purpose hidden pattern determination scheme, which can be utilized for different categories of time-varying signals.

  8. Computationally Secure Pattern Matching in the Presence of Malicious Adversaries

    DEFF Research Database (Denmark)

    Hazay, Carmit; Toft, Tomas

    2014-01-01

    for important variations of the secure pattern matching problem that are significantly more efficient than the current state of art solutions: First, we deal with secure pattern matching with wildcards. In this variant the pattern may contain wildcards that match both 0 and 1. Our protocol requires O......We propose a protocol for the problem of secure two-party pattern matching, where Alice holds a text t∈{0,1}∗ of length n, while Bob has a pattern p∈{0,1}∗ of length m. The goal is for Bob to (only) learn where his pattern occurs in Alice’s text, while Alice learns nothing. Private pattern matching...... is an important problem that has many applications in the area of DNA search, computational biology and more. Our construction guarantees full simulation in the presence of malicious, polynomial-time adversaries (assuming the hardness of DDH assumption) and exhibits computation and communication costs of O...

  9. Cellular-automata-based learning network for pattern recognition

    Science.gov (United States)

    Tzionas, Panagiotis G.; Tsalides, Phillippos G.; Thanailakis, Adonios

    1991-11-01

    Most classification techniques either adopt an approach based directly on the statistical characteristics of the pattern classes involved, or they transform the patterns in a feature space and try to separate the point clusters in this space. An alternative approach based on memory networks has been presented, its novelty being that it can be implemented in parallel and it utilizes direct features of the patterns rather than statistical characteristics. This study presents a new approach for pattern classification using pseudo 2-D binary cellular automata (CA). This approach resembles the memory network classifier in the sense that it is based on an adaptive knowledge based formed during a training phase, and also in the fact that both methods utilize pattern features that are directly available. The main advantage of this approach is that the sensitivity of the pattern classifier can be controlled. The proposed pattern classifier has been designed using 1.5 micrometers design rules for an N-well CMOS process. Layout has been achieved using SOLO 1400. Binary pseudo 2-D hybrid additive CA (HACA) is described in the second section of this paper. The third section describes the operation of the pattern classifier and the fourth section presents some possible applications. The VLSI implementation of the pattern classifier is presented in the fifth section and, finally, the sixth section draws conclusions from the results obtained.

  10. A Global Online Handwriting Recognition Approach Based on Frequent Patterns

    Directory of Open Access Journals (Sweden)

    C. Gmati

    2018-06-01

    Full Text Available In this article, the handwriting signals are represented based on geometric and spatio-temporal characteristics to increase the feature vectors relevance of each object. The main goal was to extract features in the form of a numeric vector based on the extraction of frequent patterns. We used two types of frequent motifs (closed frequent patterns and maximal frequent patterns that can represent handwritten characters pertinently. These common features patterns are generated from a raw data transformation method to achieve high relevance. A database of words consisting of two different letters was created. The proposed application gives promising results and highlights the advantages that frequent pattern extraction algorithms can achieve, as well as the central role played by the “minimum threshold” parameter in the overall description of the characters.

  11. Performance improvement of ERP-based brain-computer interface via varied geometric patterns.

    Science.gov (United States)

    Ma, Zheng; Qiu, Tianshuang

    2017-12-01

    Recently, many studies have been focusing on optimizing the stimulus of an event-related potential (ERP)-based brain-computer interface (BCI). However, little is known about the effectiveness when increasing the stimulus unpredictability. We investigated a new stimulus type of varied geometric pattern where both complexity and unpredictability of the stimulus are increased. The proposed and classical paradigms were compared in within-subject experiments with 16 healthy participants. Results showed that the BCI performance was significantly improved for the proposed paradigm, with an average online written symbol rate increasing by 138% comparing with that of the classical paradigm. Amplitudes of primary ERP components, such as N1, P2a, P2b, N2, were also found to be significantly enhanced with the proposed paradigm. In this paper, a novel ERP BCI paradigm with a new stimulus type of varied geometric pattern is proposed. By jointly increasing the complexity and unpredictability of the stimulus, the performance of an ERP BCI could be considerably improved.

  12. Sub-pattern based multi-manifold discriminant analysis for face recognition

    Science.gov (United States)

    Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

    2018-04-01

    In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

  13. Stress: a naturalistic proposal

    Directory of Open Access Journals (Sweden)

    María de Lourdes Rodríguez Campuzano

    2013-08-01

    Full Text Available Some of the stress related topics, especially from the conceptual framework of Lazarus and Folkman are reviewed on this work. It is sustained that this approach is dualistic and that the research made from this view is made on the basis of morphological criteria that don’t allow studying important elements of this kind of behavior. From an interbehavioral approach three functional criteria are proposed to study this phenomenon: the functional nature of situations, aptitude levels of behavior, and its three dimensions. Emphasis is made on the singular and individual nature of stress reactions. Finally it is suggested to take into account these functional criteria to develop a generic situational taxonomy to study these reactions as parts of complex behavioral patterns.

  14. Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface.

    Science.gov (United States)

    Zhang, Yu; Zhou, Guoxu; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

    2015-11-30

    Common spatial pattern (CSP) has been most popularly applied to motor-imagery (MI) feature extraction for classification in brain-computer interface (BCI) application. Successful application of CSP depends on the filter band selection to a large degree. However, the most proper band is typically subject-specific and can hardly be determined manually. This study proposes a sparse filter band common spatial pattern (SFBCSP) for optimizing the spatial patterns. SFBCSP estimates CSP features on multiple signals that are filtered from raw EEG data at a set of overlapping bands. The filter bands that result in significant CSP features are then selected in a supervised way by exploiting sparse regression. A support vector machine (SVM) is implemented on the selected features for MI classification. Two public EEG datasets (BCI Competition III dataset IVa and BCI Competition IV IIb) are used to validate the proposed SFBCSP method. Experimental results demonstrate that SFBCSP help improve the classification performance of MI. The optimized spatial patterns by SFBCSP give overall better MI classification accuracy in comparison with several competing methods. The proposed SFBCSP is a potential method for improving the performance of MI-based BCI. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. Factors influencing the seasonal patterns of infectious diseases

    Directory of Open Access Journals (Sweden)

    Auda Fares

    2013-01-01

    Full Text Available The recognition of seasonal patterns in infectious disease occurrence dates back at least as far as the hippocratic era, but the mechanisms underlying these fluctuations remain poorly understood. Many classes of mechanistic hypotheses have been proposed to explain seasonality of various directly transmitted diseases, including at least the following; human activity, seasonal variability in human immune system function, seasonal variations in vitamin D levels, seasonality of melatonin, and pathogen infectivity. In this short paper will briefly discuss the role of these factors in the seasonal patterns of infectious diseases.

  16. Adaptive oriented PDEs filtering methods based on new controlling speed function for discontinuous optical fringe patterns

    Science.gov (United States)

    Zhou, Qiuling; Tang, Chen; Li, Biyuan; Wang, Linlin; Lei, Zhenkun; Tang, Shuwei

    2018-01-01

    The filtering of discontinuous optical fringe patterns is a challenging problem faced in this area. This paper is concerned with oriented partial differential equations (OPDEs)-based image filtering methods for discontinuous optical fringe patterns. We redefine a new controlling speed function to depend on the orientation coherence. The orientation coherence can be used to distinguish the continuous regions and the discontinuous regions, and can be calculated by utilizing fringe orientation. We introduce the new controlling speed function to the previous OPDEs and propose adaptive OPDEs filtering models. According to our proposed adaptive OPDEs filtering models, the filtering in the continuous and discontinuous regions can be selectively carried out. We demonstrate the performance of the proposed adaptive OPDEs via application to the simulated and experimental fringe patterns, and compare our methods with the previous OPDEs.

  17. Application of the robust design concept for fuel loading pattern

    International Nuclear Information System (INIS)

    Endo, Tomohiro; Ohori, Kazuma; Yamamoto, Akio

    2011-01-01

    Application of the robust design concept for fuel loading pattern design is proposed as a new approach to improve the prediction accuracy of core characteristics. The robust design is a design concept that establishes a resistant (robust) system for perturbations or noises, by properly setting design variables. In order to apply the concept of robust design to fuel loading pattern design, we focus on a theoretical approach based on the higher order perturbation method. This approach indicates that the eigenvalue separation is one of the effective indices to measure the robustness of a designed fuel loading pattern. In order to verify the effectiveness of the eigenvalue separation as an index of robustness, numerical analysis is carried out for typical 3-loop PWR cores, and we evaluated the correlation between the eigenvalue separation and the variation of relative assembly power due to the perturbation of the cross section. The numerical results show that the variation of relative power decreases as the eigenvalue separation increases; thus, it is confirmed that the eigenvalue separation is an effective index of robustness. Based on the eigenvalue separation of a fuel loading pattern, we discuss design guidelines of a fuel loading pattern to improve the robustness. For example, if each fuel assembly has independent uncertainty on its cross section, the robustness of the core can be enhanced by increasing the relative power at the center of the core. The proposed guidelines will be useful to design a loading pattern that has robustness for uncertainties due to cross section, calculation method, and so on. (author)

  18. An Innovative Cellular Automata Technique for Mapping Cracking Pattern of Airport Pavement

    Directory of Open Access Journals (Sweden)

    Yin Fucheng

    2017-01-01

    Full Text Available In this study, an innovative cellular automata (CA technique was proposed for mapping cracking pattern of the airport pavement. The CA technique was developed to establish a numerical model describing the effect of boundary condition of pavement on zones (CA cells within the pavement. A state function was used to describe the state values in the cells within the CA lattice. The correction coefficient principle is used as the criterion of zone similarity and the corresponding technique is proposed to find similar zones within and between pavements. Three pavement models, HRS, MRS and LRS, tested in FAA, USA, are set as the base pavements to map the cracking patterns of pavements with different sizes from the base pavements. The mapped cracking patterns of unseen pavements are empirically verified by referring to the relative experimental models.

  19. Internet Connection Control based on Idle Time Using User Behavior Pattern Analysis

    Directory of Open Access Journals (Sweden)

    Fadilah Fahrul Hardiansyah

    2014-12-01

    Full Text Available The increase of smartphone ability is rapidly increasing the power consumption. Many methods have been proposed to reduce smartphone power consumption. Most of these methods use the internet connection control based on the availability of the battery power level regardless of when and where a waste of energy occurs. This paper proposes a new approach to control the internet connection based on idle time using user behavior pattern analysis. User behavior patterns are used to predict idle time duration. Internet connection control performed during idle time. During idle time internet connection periodically switched on and off by a certain time interval. This method effectively reduces a waste of energy. Control of the internet connection does not interfere the user because it is implemented on idle time. Keywords: Smartphone, User Behavior, Pattern Recognition, Idle Time, Internet Connection Control

  20. Automatic Generation of English-Japanese Translation Pattern Utilizing Genetic Programming Technique

    Science.gov (United States)

    Matsumura, Koki; Tamekuni, Yuji; Kimura, Shuhei

    There are a lot of constructional differences in an English-Japanese phrase template, and that often makes the act of translation difficult. Moreover, there exist various and tremendous phrase templates and sentence to be refered to. It is not easy to prepare the corpus that covers the all. Therefore, it is very significant to generate the translation pattern of the sentence pattern automatically from a viewpoint of the translation success rate and the capacity of the pattern dictionary. Then, for the purpose of realizing the automatic generation of the translation pattern, this paper proposed the new method for the generation of the translation pattern by using the genetic programming technique (GP). The technique tries to generate the translation pattern of various sentences which are not registered in the phrase template dictionary automatically by giving the genetic operation to the parsing tree of a basic pattern. The tree consists of the pair of the English-Japanese sentence generated as the first stage population. The analysis tree data base with 50,100,150,200 pairs was prepared as the first stage population. And this system was applied and executed for an English input of 1,555 sentences. As a result, the analysis tree increases from 200 to 517, and the accuracy rate of the translation pattern has improved from 42.57% to 70.10%. And, 86.71% of the generated translations was successfully done, whose meanings are enough acceptable and understandable. It seemed that this proposal technique became a clue to raise the translation success rate, and to find the possibility of the reduction of the analysis tree data base.

  1. Combining Biometric Fractal Pattern and Particle Swarm Optimization-Based Classifier for Fingerprint Recognition

    Directory of Open Access Journals (Sweden)

    Chia-Hung Lin

    2010-01-01

    Full Text Available This paper proposes combining the biometric fractal pattern and particle swarm optimization (PSO-based classifier for fingerprint recognition. Fingerprints have arch, loop, whorl, and accidental morphologies, and embed singular points, resulting in the establishment of fingerprint individuality. An automatic fingerprint identification system consists of two stages: digital image processing (DIP and pattern recognition. DIP is used to convert to binary images, refine out noise, and locate the reference point. For binary images, Katz's algorithm is employed to estimate the fractal dimension (FD from a two-dimensional (2D image. Biometric features are extracted as fractal patterns using different FDs. Probabilistic neural network (PNN as a classifier performs to compare the fractal patterns among the small-scale database. A PSO algorithm is used to tune the optimal parameters and heighten the accuracy. For 30 subjects in the laboratory, the proposed classifier demonstrates greater efficiency and higher accuracy in fingerprint recognition.

  2. Single shot fringe pattern phase demodulation using Hilbert-Huang transform aided by the principal component analysis.

    Science.gov (United States)

    Trusiak, Maciej; Służewski, Łukasz; Patorski, Krzysztof

    2016-02-22

    Hybrid single shot algorithm for accurate phase demodulation of complex fringe patterns is proposed. It employs empirical mode decomposition based adaptive fringe pattern enhancement (i.e., denoising, background removal and amplitude normalization) and subsequent boosted phase demodulation using 2D Hilbert spiral transform aided by the Principal Component Analysis method for novel, correct and accurate local fringe direction map calculation. Robustness to fringe pattern significant noise, uneven background and amplitude modulation as well as local fringe period and shape variations is corroborated by numerical simulations and experiments. Proposed automatic, adaptive, fast and comprehensive fringe analysis solution compares favorably with other previously reported techniques.

  3. Critical dimension and pattern size enhancement using pre-strained lithography

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Jian-Wei [Department of Power Mechanical Engineering, National Tsing Hua University, 101, Section 2, Kuang Fu Road, Hsin Chu 30013, Taiwan (China); Yang, Chung-Yuan [Institute of NanoEngineering and MicroSystems, National Tsing Hua University, 101, Section 2, Kuang Fu Road, Hsin Chu 30013, Taiwan (China); Lo, Cheng-Yao, E-mail: chengyao@mx.nthu.edu.tw [Department of Power Mechanical Engineering, National Tsing Hua University, 101, Section 2, Kuang Fu Road, Hsin Chu 30013, Taiwan (China); Institute of NanoEngineering and MicroSystems, National Tsing Hua University, 101, Section 2, Kuang Fu Road, Hsin Chu 30013, Taiwan (China)

    2014-10-13

    This paper proposes a non-wavelength-shortening-related critical dimension and pattern size reduction solution for the integrated circuit industry that entails generating strain on the substrate prior to lithography. Pattern size reduction of up to 49% was achieved regardless of shape, location, and size on the xy plane, and complete theoretical calculations and process steps are described in this paper. This technique can be applied to enhance pattern resolution by employing materials and process parameters already in use and, thus, to enhance the capability of outdated lithography facilities, enabling them to particularly support the manufacturing of flexible electronic devices with polymer substrates.

  4. Patterning of PMMA microfluidic parts using screen printing process

    Science.gov (United States)

    Ahari Kaleibar, Aminreza; Rahbar, Mona; Haiducu, Marius; Parameswaran, Ash M.

    2010-02-01

    An inexpensive and rapid micro-fabrication process for producing PMMA microfluidic components has been presented. Our proposed technique takes advantages of commercially available economical technologies such as the silk screen printing and UV patterning of PMMA substrates to produce the microfluidic components. As a demonstration of our proposed technique, we had utilized a homemade deep-UV source, λ=254nm, a silk screen mask made using a local screen-printing shop and Isopropyl alcohol - water mixture (IPA-water) as developer to quickly define the microfluidic patterns. The prototyped devices were successfully bonded, sealed, and the device functionality tested and demonstrated. The screen printing based technique can produce microfluidic channels as small as 50 micrometers quite easily, making this technique the most cost-effective, fairly high precision and at the same time an ultra economical plastic microfluidic components fabrication process reported to date.

  5. Identification of linearised RMS-voltage dip patterns based on clustering in renewable plants

    Energy Technology Data Exchange (ETDEWEB)

    García-Sánchez, Tania; Gómez-Lázaro, Emilio; Muljadi, Edward; Kessler, Mathieu; Muñoz-Benavente, Irene; Molina-García, Angel

    2018-03-27

    Generation units connected to the grid are currently required to meet low-voltage ride-through (LVRT) requirements. In most developed countries, these requirements also apply to renewable sources, mainly wind power plants and photovoltaic installations connected to the grid. This study proposes an alternative characterisation solution to classify and visualise a large number of collected events in light of current limits and requirements. The authors' approach is based on linearised root-mean-square-(RMS)-voltage trajectories, taking into account LRVT requirements, and a clustering process to identify the most likely pattern trajectories. The proposed solution gives extensive information on an event's severity by providing a simple but complete visualisation of the linearised RMS-voltage patterns. In addition, these patterns are compared to current LVRT requirements to determine similarities or discrepancies. A large number of collected events can then be automatically classified and visualised for comparative purposes. Real disturbances collected from renewable sources in Spain are used to assess the proposed solution. Extensive results and discussions are also included in this study.

  6. Movement Pattern Analysis Based on Sequence Signatures

    Directory of Open Access Journals (Sweden)

    Seyed Hossein Chavoshi

    2015-09-01

    Full Text Available Increased affordability and deployment of advanced tracking technologies have led researchers from various domains to analyze the resulting spatio-temporal movement data sets for the purpose of knowledge discovery. Two different approaches can be considered in the analysis of moving objects: quantitative analysis and qualitative analysis. This research focuses on the latter and uses the qualitative trajectory calculus (QTC, a type of calculus that represents qualitative data on moving point objects (MPOs, and establishes a framework to analyze the relative movement of multiple MPOs. A visualization technique called sequence signature (SESI is used, which enables to map QTC patterns in a 2D indexed rasterized space in order to evaluate the similarity of relative movement patterns of multiple MPOs. The applicability of the proposed methodology is illustrated by means of two practical examples of interacting MPOs: cars on a highway and body parts of a samba dancer. The results show that the proposed method can be effectively used to analyze interactions of multiple MPOs in different domains.

  7. Leveraging workflow control patterns in the domain of clinical practice guidelines.

    Science.gov (United States)

    Kaiser, Katharina; Marcos, Mar

    2016-02-10

    Clinical practice guidelines (CPGs) include recommendations describing appropriate care for the management of patients with a specific clinical condition. A number of representation languages have been developed to support executable CPGs, with associated authoring/editing tools. Even with tool assistance, authoring of CPG models is a labor-intensive task. We aim at facilitating the early stages of CPG modeling task. In this context, we propose to support the authoring of CPG models based on a set of suitable procedural patterns described in an implementation-independent notation that can be then semi-automatically transformed into one of the alternative executable CPG languages. We have started with the workflow control patterns which have been identified in the fields of workflow systems and business process management. We have analyzed the suitability of these patterns by means of a qualitative analysis of CPG texts. Following our analysis we have implemented a selection of workflow patterns in the Asbru and PROforma CPG languages. As implementation-independent notation for the description of patterns we have chosen BPMN 2.0. Finally, we have developed XSLT transformations to convert the BPMN 2.0 version of the patterns into the Asbru and PROforma languages. We showed that although a significant number of workflow control patterns are suitable to describe CPG procedural knowledge, not all of them are applicable in the context of CPGs due to their focus on single-patient care. Moreover, CPGs may require additional patterns not included in the set of workflow control patterns. We also showed that nearly all the CPG-suitable patterns can be conveniently implemented in the Asbru and PROforma languages. Finally, we demonstrated that individual patterns can be semi-automatically transformed from a process specification in BPMN 2.0 to executable implementations in these languages. We propose a pattern and transformation-based approach for the development of CPG models

  8. Spatio-temporal flow maps for visualizing movement and contact patterns

    Directory of Open Access Journals (Sweden)

    Bing Ni

    2017-03-01

    Full Text Available The advanced telecom technologies and massive volumes of intelligent mobile phone users have yielded a huge amount of real-time data of people’s all-in-one telecommunication records, which we call telco big data. With telco data and the domain knowledge of an urban city, we are now able to analyze the movement and contact patterns of humans in an unprecedented scale. Flow map is widely used to display the movements of humans from one single source to multiple destinations by representing locations as nodes and movements as edges. However, it fails the task of visualizing both movement and contact data. In addition, analysts often need to compare and examine the patterns side by side, and do various quantitative analysis. In this work, we propose a novel spatio-temporal flow map layout to visualize when and where people from different locations move into the same places and make contact. We also propose integrating the spatiotemporal flow maps into existing spatiotemporal visualization techniques to form a suite of techniques for visualizing the movement and contact patterns. We report a potential application the proposed techniques can be applied to. The results show that our design and techniques properly unveil hidden information, while analysis can be achieved efficiently. Keywords: Spatio-temporal data, Flow map, Urban mobility

  9. Heterogeneous patterns enhancing static and dynamic texture classification

    International Nuclear Information System (INIS)

    Silva, Núbia Rosa da; Martinez Bruno, Odemir

    2013-01-01

    Some mixtures, such as colloids like milk, blood, and gelatin, have homogeneous appearance when viewed with the naked eye, however, to observe them at the nanoscale is possible to understand the heterogeneity of its components. The same phenomenon can occur in pattern recognition in which it is possible to see heterogeneous patterns in texture images. However, current methods of texture analysis can not adequately describe such heterogeneous patterns. Common methods used by researchers analyse the image information in a global way, taking all its features in an integrated manner. Furthermore, multi-scale analysis verifies the patterns at different scales, but still preserving the homogeneous analysis. On the other hand various methods use textons to represent the texture, breaking texture down into its smallest unit. To tackle this problem, we propose a method to identify texture patterns not small as textons at distinct scales enhancing the separability among different types of texture. We find sub patterns of texture according to the scale and then group similar patterns for a more refined analysis. Tests were performed in four static texture databases and one dynamical one. Results show that our method provide better classification rate compared with conventional approaches both in static and in dynamic texture.

  10. Design and realization of a novel multitask TT&C operation pattern

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    With the sharp increase of China's in-orbit spacecraft and the constraint TT&C resources, a mathematical model for optimal TT&C resource allocation is proposed, and the TT&C facility remote monitoring function is designed to achieve the multitask operation pattern under the unified management of the network management center. With this pattern, the TT&C network management and the spacecraft management are separated, which is quite different from the previous pattern. Further, a novel spacecraft TT&C technique based on spacecraft control language is developed, and the telecommanding pattern is designed to address the spacecraft operation problems. The engineering application shows that this pattern fundamentally improves the TT&C network capability, increases the resource efficiency, and satisfies the efficient, accurate, and flexible operation of spacecraft.

  11. Growth Patterns and E-Moderating Supports in Asynchronous Online Discussions in an Undergraduate Blended Course

    Science.gov (United States)

    Ghadirian, Hajar; Ayub, Ahmad Fauzi Mohd; Bakar, Kamariah Binti Abu; Hassanzadeh, Maryam

    2016-01-01

    This study presents a case study of asynchronous online discussions' (AOD) growth patterns in an undergraduate blended course to address the gap in our current understanding of how threads are developed in peer-moderated AODs. Building on a taxonomy of thread pattern proposed by Chan, Hew and Cheung (2009), growth patterns of thirty-six forums…

  12. Nondestructive analysis of lithographic patterns with natural line edge roughness from Mueller matrix ellipsometric data

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xiuguo; Shi, Yating; Jiang, Hao [State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Zhang, Chuanwei [State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Wuhan Eoptics Technology Co. Ltd., Wuhan, Hubei 430075 (China); Liu, Shiyuan, E-mail: shyliu@hust.edu.cn [State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Wuhan Eoptics Technology Co. Ltd., Wuhan, Hubei 430075 (China)

    2016-12-01

    Highlights: • MME is applied to characterize lithographic patterns with natural LER. • A computationally efficient approach based on EMA is proposed to model LER. • Both theoretical and experimental results verify the effective modeling approach. • The comparison between MME and SEM results reveals the potential of this technique. - Abstract: Mueller matrix ellipsometry (MME) is applied to characterize lithographic patterns with natural line edge roughness (LER). A computationally efficient approach based on effective medium approximation is proposed to model the effects of LER in MME measurements. We present both the theoretical and experimental results on lithographic patterns with realistic LER which demonstrate that MME in combination with the proposed effective modeling method is capable of quantifying LER amplitudes. Quantitative comparisons between the MME and scanning electron microscopy measured results also reveal the strong potential of this technique for in-line nondestructive line roughness monitoring.

  13. Automatic Test Pattern Generator for Fuzzing Based on Finite State Machine

    Directory of Open Access Journals (Sweden)

    Ming-Hung Wang

    2017-01-01

    Full Text Available With the rapid development of the Internet, several emerging technologies are adopted to construct fancy, interactive, and user-friendly websites. Among these technologies, HTML5 is a popular one and is widely used in establishing modern sites. However, the security issues in the new web technologies are also raised and are worthy of investigation. For vulnerability investigation, many previous studies used fuzzing and focused on generation-based approaches to produce test cases for fuzzing; however, these methods require a significant amount of knowledge and mental efforts to develop test patterns for generating test cases. To decrease the entry barrier of conducting fuzzing, in this study, we propose a test pattern generation algorithm based on the concept of finite state machines. We apply graph analysis techniques to extract paths from finite state machines and use these paths to construct test patterns automatically. According to the proposal, fuzzing can be completed through inputting a regular expression corresponding to the test target. To evaluate the performance of our proposal, we conduct an experiment in identifying vulnerabilities of the input attributes in HTML5. According to the results, our approach is not only efficient but also effective for identifying weak validators in HTML5.

  14. Dysfunctional breathing: a review of the literature and proposal for classification

    Directory of Open Access Journals (Sweden)

    Richard Boulding

    2016-09-01

    Full Text Available Dysfunctional breathing is a term describing breathing disorders where chronic changes in breathing pattern result in dyspnoea and other symptoms in the absence or in excess of the magnitude of physiological respiratory or cardiac disease. We reviewed the literature and propose a classification system for the common dysfunctional breathing patterns described. The literature was searched using the terms: dysfunctional breathing, hyperventilation, Nijmegen questionnaire and thoraco-abdominal asynchrony. We have summarised the presentation, assessment and treatment of dysfunctional breathing, and propose that the following system be used for classification. 1 Hyperventilation syndrome: associated with symptoms both related to respiratory alkalosis and independent of hypocapnia. 2 Periodic deep sighing: frequent sighing with an irregular breathing pattern. 3 Thoracic dominant breathing: can often manifest in somatic disease, if occurring without disease it may be considered dysfunctional and results in dyspnoea. 4 Forced abdominal expiration: these patients utilise inappropriate and excessive abdominal muscle contraction to aid expiration. 5 Thoraco-abdominal asynchrony: where there is delay between rib cage and abdominal contraction resulting in ineffective breathing mechanics. This review highlights the common abnormalities, current diagnostic methods and therapeutic implications in dysfunctional breathing. Future work should aim to further investigate the prevalence, clinical associations and treatment of these presentations.

  15. An Efficient Approach to Mining Maximal Contiguous Frequent Patterns from Large DNA Sequence Databases

    Directory of Open Access Journals (Sweden)

    Md. Rezaul Karim

    2012-03-01

    Full Text Available Mining interesting patterns from DNA sequences is one of the most challenging tasks in bioinformatics and computational biology. Maximal contiguous frequent patterns are preferable for expressing the function and structure of DNA sequences and hence can capture the common data characteristics among related sequences. Biologists are interested in finding frequent orderly arrangements of motifs that are responsible for similar expression of a group of genes. In order to reduce mining time and complexity, however, most existing sequence mining algorithms either focus on finding short DNA sequences or require explicit specification of sequence lengths in advance. The challenge is to find longer sequences without specifying sequence lengths in advance. In this paper, we propose an efficient approach to mining maximal contiguous frequent patterns from large DNA sequence datasets. The experimental results show that our proposed approach is memory-efficient and mines maximal contiguous frequent patterns within a reasonable time.

  16. A Studentized Permutation Test for the Comparison of Spatial Point Patterns

    DEFF Research Database (Denmark)

    Hahn, Ute

    of empirical K-functions are compared by a permutation test using a studentized test statistic. The proposed test performs convincingly in terms of empirical level and power in a simulation study, even for point patterns where the K-function estimates on neighboring subsamples are not strictly exchangeable....... It also shows improved behavior compared to a test suggested by Diggle et al. (1991, 2000) for the comparison of groups of independently replicated point patterns. In an application to two point patterns from pathology that represent capillary positions in sections of healthy and tumorous tissue, our...

  17. Irradiation Pattern Analysis for Designing Light Sources-Based on Light Emitting Diodes

    International Nuclear Information System (INIS)

    Rojas, E.; Stolik, S.; La Rosa, J. de; Valor, A.

    2016-01-01

    Nowadays it is possible to design light sources with a specific irradiation pattern for many applications. Light Emitting Diodes present features like high luminous efficiency, durability, reliability, flexibility, among others as the result of its rapid development. In this paper the analysis of the irradiation pattern of the light emitting diodes is presented. The approximation of these irradiation patterns to both, a Lambertian, as well as a Gaussian functions for the design of light sources is proposed. Finally, the obtained results and the functionality of bringing the irradiation pattern of the light emitting diodes to these functions are discussed. (Author)

  18. A comprehensive data mining study shows that most nuclear receptors act as newly proposed homeostasis-associated molecular pattern receptors.

    Science.gov (United States)

    Wang, Luqiao; Nanayakkara, Gayani; Yang, Qian; Tan, Hongmei; Drummer, Charles; Sun, Yu; Shao, Ying; Fu, Hangfei; Cueto, Ramon; Shan, Huimin; Bottiglieri, Teodoro; Li, Ya-Feng; Johnson, Candice; Yang, William Y; Yang, Fan; Xu, Yanjie; Xi, Hang; Liu, Weiqing; Yu, Jun; Choi, Eric T; Cheng, Xiaoshu; Wang, Hong; Yang, Xiaofeng

    2017-10-24

    Nuclear receptors (NRs) can regulate gene expression; therefore, they are classified as transcription factors. Despite the extensive research carried out on NRs, still several issues including (1) the expression profile of NRs in human tissues, (2) how the NR expression is modulated during atherosclerosis and metabolic diseases, and (3) the overview of the role of NRs in inflammatory conditions are not fully understood. To determine whether and how the expression of NRs are regulated in physiological/pathological conditions, we took an experimental database analysis to determine expression of all 48 known NRs in 21 human and 17 murine tissues as well as in pathological conditions. We made the following significant findings: (1) NRs are differentially expressed in tissues, which may be under regulation by oxygen sensors, angiogenesis pathway, stem cell master regulators, inflammasomes, and tissue hypo-/hypermethylation indexes; (2) NR sequence mutations are associated with increased risks for development of cancers and metabolic, cardiovascular, and autoimmune diseases; (3) NRs have less tendency to be upregulated than downregulated in cancers, and autoimmune and metabolic diseases, which may be regulated by inflammation pathways and mitochondrial energy enzymes; and (4) the innate immune sensor inflammasome/caspase-1 pathway regulates the expression of most NRs. Based on our findings, we propose a new paradigm that most nuclear receptors are anti-inflammatory homeostasis-associated molecular pattern receptors (HAMPRs). Our results have provided a novel insight on NRs as therapeutic targets in metabolic diseases, inflammations, and malignancies.

  19. Simple and effective graphene laser processing for neuron patterning application

    Science.gov (United States)

    Lorenzoni, Matteo; Brandi, Fernando; Dante, Silvia; Giugni, Andrea; Torre, Bruno

    2013-06-01

    A straightforward fabrication technique to obtain patterned substrates promoting ordered neuron growth is presented. Chemical vapor deposition (CVD) single layer graphene (SLG) was machined by means of single pulse UV laser ablation technique at the lowest effective laser fluence in order to minimize laser damage effects. Patterned substrates were then coated with poly-D-lysine by means of a simple immersion in solution. Primary embryonic hippocampal neurons were cultured on our substrate, demonstrating an ordered interconnected neuron pattern mimicking the pattern design. Surprisingly, the functionalization is more effective on the SLG, resulting in notably higher alignment for neuron adhesion and growth. Therefore the proposed technique should be considered a valuable candidate to realize a new generation of highly specialized biosensors.

  20. R&D Proposal RD51 Extension Beyond 2018

    CERN Document Server

    Dalla Torre, S; Ropelewski, L; Titov, M

    2018-01-01

    The RD51 Collaboration, in charge of the development and dissemination of MicroPattern Gaseous Detectors (MPGD) since 2008, proposes to extend its ac-tivity, after 2018, for a further five-year term. Since the RD51 initial years, the community of MPGD developers and users has grown considerably. It is reflected by the many MPGD-based applications in high energy and nuclear physics experi-ments as well as in other basic and applied-research fields. They rely on the parallel progress of detector concepts and associated technologies. The cultural, infrastruc-ture and networking support offered by RD51 has been essential in this process. The rich portfolio of MPGD projects, under constant expansion, is accompanied by novel ideas on further developments and applications. The proposed next term of RD51 activities aims at bringing a number of de-tector concepts to maturity, initiating new projects and continuing the support to the community. Among leading proposed projects are ultrafast, high-rate MPGDs; discharg...

  1. Noise power spectrum of the fixed pattern noise in digital radiography detectors

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dong Sik, E-mail: dskim@hufs.ac.kr [Department of Electronics Engineering, Hankuk University of Foreign Studies, Gyeonggi-do 449-791 (Korea, Republic of); Kim, Eun [R& D Center, DRTECH Co., Gyeonggi-do 13558 (Korea, Republic of)

    2016-06-15

    Purpose: The fixed pattern noise in radiography image detectors is caused by various sources. Multiple readout circuits with gate drivers and charge amplifiers are used to efficiently acquire the pixel voltage signals. However, the multiple circuits are not identical and thus yield nonuniform system gains. Nonuniform sensitivities are also produced from local variations in the charge collection elements. Furthermore, in phosphor-based detectors, the optical scattering at the top surface of the columnar CsI growth, the grain boundaries, and the disorder structure causes spatial sensitivity variations. These nonuniform gains or sensitivities cause fixed pattern noise and degrade the detector performance, even though the noise problem can be partially alleviated by using gain correction techniques. Hence, in order to develop good detectors, comparative analysis of the energy spectrum of the fixed pattern noise is important. Methods: In order to observe the energy spectrum of the fixed pattern noise, a normalized noise power spectrum (NNPS) of the fixed pattern noise is considered in this paper. Since the fixed pattern noise is mainly caused by the nonuniform gains, we call the spectrum the gain NNPS. We first asymptotically observe the gain NNPS and then formulate two relationships to calculate the gain NNPS based on a nonuniform-gain model. Since the gain NNPS values are quite low compared to the usual NNPS, measuring such a low NNPS value is difficult. By using the average of the uniform exposure images, a robust measuring method for the gain NNPS is proposed in this paper. Results: By using the proposed measuring method, the gain NNPS curves of several prototypes of general radiography and mammography detectors were measured to analyze their fixed pattern noise properties. We notice that a direct detector, which is based on the a-Se photoconductor, showed lower gain NNPS than the indirect-detector case, which is based on the CsI scintillator. By comparing the gain

  2. Quantifying gait patterns in Parkinson's disease

    Science.gov (United States)

    Romero, Mónica; Atehortúa, Angélica; Romero, Eduardo

    2017-11-01

    Parkinson's disease (PD) is constituted by a set of motor symptoms, namely tremor, rigidity, and bradykinesia, which are usually described but not quantified. This work proposes an objective characterization of PD gait patterns by approximating the single stance phase a single grounded pendulum. This model estimates the force generated by the gait during the single support from gait data. This force describes the motion pattern for different stages of the disease. The model was validated using recorded videos of 8 young control subjects, 10 old control subjects and 10 subjects with Parkinson's disease in different stages. The estimated force showed differences among stages of Parkinson disease, observing a decrease of the estimated force for the advanced stages of this illness.

  3. Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

    Science.gov (United States)

    Huo, Guanying

    2017-01-01

    As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CNN models employ the softmax function for classification. However, owing to the limited capacity of the softmax function, there are some shortcomings of traditional CNN models in image classification. To deal with this problem, a new method combining Biomimetic Pattern Recognition (BPR) with CNNs is proposed for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. The proposed method is evaluated on three famous image classification benchmarks, that is, MNIST, AR, and CIFAR-10. The classification accuracies of the proposed method for the three datasets are 99.01%, 98.40%, and 87.11%, respectively, which are much higher in comparison with the other four methods in most cases. PMID:28316614

  4. Design, Analysis, and Verification of Ka-Band Pattern Reconfigurable Patch Antenna Using RF MEMS Switches

    Directory of Open Access Journals (Sweden)

    Zhongliang Deng

    2016-08-01

    Full Text Available This paper proposes a radiating pattern reconfigurable antenna by employing RF Micro-electromechanical Systems (RF MEMS switches. The antenna has a low profile and small size of 4 mm × 5 mm × 0.4 mm, and mainly consists of one main patch, two assistant patches, and two RF MEMS switches. By changing the RF MEMS switches operating modes, the proposed antenna can switch among three radiating patterns (with main lobe directions of approximately −17.0°, 0° and +17.0° at 35 GHz. The far-field vector addition model is applied to analyse the pattern. Comparing the measured results with analytical and simulated results, good agreements are obtained.

  5. Simplified absolute phase retrieval of dual-frequency fringe patterns in fringe projection profilometry

    Science.gov (United States)

    Lu, Jin; Mo, Rong; Sun, Huibin; Chang, Zhiyong; Zhao, Xiaxia

    2016-04-01

    In fringe projection profilometry, a simplified method is proposed to recover absolute phase maps of two-frequency fringe patterns by using a unique mapping rule. The mapping rule is designed from the rounded phase values to the fringe order of each pixel. Absolute phase can be recovered by the fringe order maps. Unlike the existing techniques, where the lowest frequency of dual- or multiple-frequency fringe patterns must be single, the presented method breaks the limitation and simplifies the procedure of phase unwrapping. Additionally, due to many issues including ambient light, shadow, sharp edges, step height boundaries and surface reflectivity variations, a novel framework of automatically identifying and removing invalid phase values is also proposed. Simulations and experiments have been carried out to validate the performances of the proposed method.

  6. A nonlinear dynamics approach for incorporating wind-speed patterns into wind-power project evaluation.

    Science.gov (United States)

    Huffaker, Ray; Bittelli, Marco

    2015-01-01

    Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind-the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns.

  7. Patterns-Based IS Change Management in SMEs

    Science.gov (United States)

    Makna, Janis; Kirikova, Marite

    The majority of information systems change management guidelines and standards are either too abstract or too bureaucratic to be easily applicable in small enterprises. This chapter proposes the approach, the method, and the prototype that are designed especially for information systems change management in small and medium enterprises. The approach is based on proven patterns of changes in the set of information systems elements. The set of elements was obtained by theoretical analysis of information systems and business process definitions and enterprise architectures. The patterns were evolved from a number of information systems theories and tested in 48 information systems change management projects. The prototype presents and helps to handle three basic change patterns, which help to anticipate the overall scope of changes related to particular elementary changes in an enterprise information system. The use of prototype requires just basic knowledge in organizational business process and information management.

  8. Morphogenesis and Complexity of the Tumor Patterns

    Science.gov (United States)

    Izquierdo-Kulich, E.; Nieto-Villar, J. M.

    A mechanism to describe the apoptosis process at mesoscopic level through p53 is proposed in this paper. A deterministic model given by three differential equations is deduced from the mesoscopic approach, which exhibits sustained oscillations caused by a supercritical Andronov-Hopf bifurcation. Taking as hypothesis that the p53 sustained oscillation is the fundamental mechanism for apoptosis regulation; the model predicts that it is necessary a strict control of p53 to stimulated it, which is an important consideration to established new therapy strategy to fight cancer. The mathematical modeling of tumor growth allows us to describe the most important regularities of these systems. A stochastic model, based on the most important processes that take place at the level of individual cells, is proposed to predict the dynamical behavior of the expected radius of the tumor and its fractal dimension. It was found that the tumor has a characteristic fractal dimension, which contains the necessary information to predict the tumor growth until it reaches a stationary state. The mathematical modeling of tumor growth is an approach to explain the complex nature of these systems. A model that describes tumor growth was obtained by using a mesoscopic formalism and fractal dimension. This model theoretically predicts the relation between the morphology of the cell pattern and the mitosis/apoptosis quotient that helps to predict tumor growth from tumoral cells fractal dimension. The relation between the tumor macroscopic morphology and the cell pattern morphology is also determined. This could explain why the interface fractal dimension decreases with the increase of the cell pattern fractal dimension and consequently with the increase of the mitosis/apoptosis relation. Indexes to characterize tumoral cell proliferation and invasion capacities are proposed and used to predict the growth of different types of tumors. These indexes also show that the proliferation capacity is

  9. User Identification Using Gait Patterns on UbiFloorII

    Science.gov (United States)

    Yun, Jaeseok

    2011-01-01

    This paper presents a system of identifying individuals by their gait patterns. We take into account various distinguishable features that can be extracted from a user’s gait and then divide them into two classes: walking pattern and stepping pattern. The conditions we assume are that our target environments are domestic areas, the number of users is smaller than 10, and all users ambulate with bare feet considering the everyday lifestyle of the Korean home. Under these conditions, we have developed a system that identifies individuals’ gait patterns using our biometric sensor, UbiFloorII. We have created UbiFloorII to collect walking samples and created software modules to extract the user’s gait pattern. To identify the users based on the gait patterns extracted from walking samples over UbiFloorII, we have deployed multilayer perceptron network, a feedforward artificial neural network model. The results show that both walking pattern and stepping pattern extracted from users’ gait over the UbiFloorII are distinguishable enough to identify the users and that fusing two classifiers at the matching score level improves the recognition accuracy. Therefore, our proposed system may provide unobtrusive and automatic user identification methods in ubiquitous computing environments, particularly in domestic areas. PMID:22163758

  10. The dynamics of visual experience, an EEG study of subjective pattern formation.

    Directory of Open Access Journals (Sweden)

    Mark A Elliott

    Full Text Available BACKGROUND: Since the origin of psychological science a number of studies have reported visual pattern formation in the absence of either physiological stimulation or direct visual-spatial references. Subjective patterns range from simple phosphenes to complex patterns but are highly specific and reported reliably across studies. METHODOLOGY/PRINCIPAL FINDINGS: Using independent-component analysis (ICA we report a reduction in amplitude variance consistent with subjective-pattern formation in ventral posterior areas of the electroencephalogram (EEG. The EEG exhibits significantly increased power at delta/theta and gamma-frequencies (point and circle patterns or a series of high-frequency harmonics of a delta oscillation (spiral patterns. CONCLUSIONS/SIGNIFICANCE: Subjective-pattern formation may be described in a way entirely consistent with identical pattern formation in fluids or granular flows. In this manner, we propose subjective-pattern structure to be represented within a spatio-temporal lattice of harmonic oscillations which bind topographically organized visual-neuronal assemblies by virtue of low frequency modulation.

  11. Pattern formation during electropolishing

    International Nuclear Information System (INIS)

    Yuzhakov, V.V.; Chang, H.; Miller, A.E.

    1997-01-01

    Using atomic force microscopy, we find that the surface morphology of a dissolving aluminum anode in a commercial electropolishing electrolyte can exhibit both highly regular and randomly packed stripe and hexagonal patterns with amplitudes of about 5 nm and wavelengths of 100 nm. The driving instability of this pattern formation phenomenon is proposed to be the preferential adsorption of polar or polarizable organic molecules on surface ridges where the contorted double layer produces a higher electric potential gradient. The enhanced relative coverage shields the anode and induces a smaller dissolution rate at the ridges. The instability is balanced by surface diffusion of the adsorbate to yield a length scale of 4π(D s /k d ) 1/2 , where D s is the surface diffusivity and k d is the desorption coefficient of the adsorbate, which correlates well with the measured wavelength. A long-wavelength expansion of the double-layer field yields an interface evolution equation that reproduces all of the observed patterns. In particular, bifurcation analysis and numerical simulation yield a single voltage-dependent dimensionless parameter ξ that measures a balance between smoothing of adsorbate concentration by electric-field-dependent surface diffusion and fluctuation due to interfacial curvature and stretching. Randomly oriented stripes are favored at large ξ (low voltage), while random hills dominate at small ξ (high voltage) with perfectly periodic stripes and hexagonal hill patterns within a small window near ξ=1. These predictions are in qualitative and quantitative agreement with our measurements. copyright 1997 The American Physical Society

  12. Oscillator Neural Network Retrieving Sparsely Coded Phase Patterns

    Science.gov (United States)

    Aoyagi, Toshio; Nomura, Masaki

    1999-08-01

    Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case of sparsely coded patterns, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of a nonfiring state. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.

  13. 76 FR 48799 - Agency Information Collection Activities: Proposed Collection; Comment Request-Characteristics...

    Science.gov (United States)

    2011-08-09

    ...: Proposed Collection; Comment Request--Characteristics and Circumstances of Zero-Income SNAP Households... examine the characteristics, circumstances, program dynamics, and benefit redemption patterns of... Service during regular business hours (8:30 a.m. to 5 p.m., Monday through Friday) at 3101 Park Center...

  14. 3D-shape of objects with straight line-motion by simultaneous projection of color coded patterns

    Science.gov (United States)

    Flores, Jorge L.; Ayubi, Gaston A.; Di Martino, J. Matías; Castillo, Oscar E.; Ferrari, Jose A.

    2018-05-01

    In this work, we propose a novel technique to retrieve the 3D shape of dynamic objects by the simultaneous projection of a fringe pattern and a homogeneous light pattern which are both coded in two of the color channels of a RGB image. The fringe pattern, red channel, is used to retrieve the phase by phase-shift algorithms with arbitrary phase-step, while the homogeneous pattern, blue channel, is used to match pixels from the test object in consecutive images, which are acquired at different positions, and thus, to determine the speed of the object. The proposed method successfully overcomes the standard requirement of projecting fringes of two different frequencies; one frequency to extract object information and the other one to retrieve the phase. Validation experiments are presented.

  15. Exploiting Sequential Patterns Found in Users' Solutions and Virtual Tutor Behavior to Improve Assistance in ITS

    Science.gov (United States)

    Fournier-Viger, Philippe; Faghihi, Usef; Nkambou, Roger; Nguifo, Engelbert Mephu

    2010-01-01

    We propose to mine temporal patterns in Intelligent Tutoring Systems (ITSs) to uncover useful knowledge that can enhance their ability to provide assistance. To discover patterns, we suggest using a custom, sequential pattern-mining algorithm. Two ways of applying the algorithm to enhance an ITS's capabilities are addressed. The first is to…

  16. Cascading walks model for human mobility patterns.

    Science.gov (United States)

    Han, Xiao-Pu; Wang, Xiang-Wen; Yan, Xiao-Yong; Wang, Bing-Hong

    2015-01-01

    Uncovering the mechanism behind the scaling laws and series of anomalies in human trajectories is of fundamental significance in understanding many spatio-temporal phenomena. Recently, several models, e.g. the explorations-returns model (Song et al., 2010) and the radiation model for intercity travels (Simini et al., 2012), have been proposed to study the origin of these anomalies and the prediction of human movements. However, an agent-based model that could reproduce most of empirical observations without priori is still lacking. In this paper, considering the empirical findings on the correlations of move-lengths and staying time in human trips, we propose a simple model which is mainly based on the cascading processes to capture the human mobility patterns. In this model, each long-range movement activates series of shorter movements that are organized by the law of localized explorations and preferential returns in prescribed region. Based on the numerical simulations and analytical studies, we show more than five statistical characters that are well consistent with the empirical observations, including several types of scaling anomalies and the ultraslow diffusion properties, implying the cascading processes associated with the localized exploration and preferential returns are indeed a key in the understanding of human mobility activities. Moreover, the model shows both of the diverse individual mobility and aggregated scaling displacements, bridging the micro and macro patterns in human mobility. In summary, our model successfully explains most of empirical findings and provides deeper understandings on the emergence of human mobility patterns.

  17. The numerical model of multi-layer insulation with a defined wrapping pattern immersed in superfluid helium

    Science.gov (United States)

    Malecha, Ziemowit; Lubryka, Eliza

    2017-11-01

    The numerical model of thin layers, characterized by a defined wrapping pattern can be a crucial element of many computational problems related to engineering and science. A motivating example is found in multilayer electrical insulation, which is an important component of superconducting magnets and other cryogenic installations. The wrapping pattern of the insulation can significantly affect heat transport and the performance of the considered instruments. The major objective of this study is to develop the numerical boundary conditions (BC) needed to model the wrapping pattern of thin insulation. An example of the practical application of the proposed BC includes the heat transfer of Rutherford NbTi cables immersed in super-fluid helium (He II) across thin layers of electrical insulation. The proposed BC and a mathematical model of heat transfer in He II are implemented in the open source CFD toolbox OpenFOAM. The implemented mathematical model and the BC are compared in the experiments. The study confirms that the thermal resistance of electrical insulation can be lowered by implementing the proper wrapping pattern. The proposed BC can be useful in the study of new patterns for wrapping schemes. The work has been supported by statutory funds from Polish Ministry for Science and Higher Education for the year of 2017.

  18. Understanding Activation Patterns in Shared Circuits: Toward a Value Driven Model

    Directory of Open Access Journals (Sweden)

    Lisa Aziz-Zadeh

    2018-05-01

    Full Text Available Over the past decade many studies indicate that we utilize our own motor system to understand the actions of other people. This mirror neuron system (MNS has been proposed to be involved in social cognition and motor learning. However, conflicting findings regarding the underlying mechanisms that drive these shared circuits make it difficult to decipher a common model of their function. Here we propose adapting a “value-driven” model to explain discrepancies in the human mirror system literature and to incorporate this model with existing models. We will use this model to explain discrepant activation patterns in multiple shared circuits in the human data, such that a unified model may explain reported activation patterns from previous studies as a function of value.

  19. Discovering significant evolution patterns from satellite image time series.

    Science.gov (United States)

    Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain

    2011-12-01

    Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.

  20. Foundations for a syntatic pattern recognition system for genomic DNA sequences

    Energy Technology Data Exchange (ETDEWEB)

    Searles, D.B.

    1993-03-01

    The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

  1. Optimization of Gad Pattern with Geometrical Weight

    International Nuclear Information System (INIS)

    Chang, Do Ik; Woo, Hae Seuk; Choi, Seong Min

    2009-01-01

    The prevailing burnable absorber for domestic nuclear power plants is a gad fuel rod which is used for the partial control of excess reactivity and power peaking. The radial peaking factor, which is one of the critical constraints for the plant safety depends largely on the number of gad bearing rods and the location of gad rods within fuel assembly. Also the concentration of gad, UO 2 enrichment in the gad fuel rod, and fuel lattice type play important roles for the resultant radial power peaking. Since fuel is upgraded periodically and longer fuel cycle management requires more burnable absorbers or higher gad weight percent, it is required frequently to search for the optimized gad patterns, i.e., the distribution of gad fuel rods within assembly, for the various fuel environment and fuel management changes. In this study, the gad pattern optimization algorithm with respect to radial power peaking factor using geometrical weight is proposed for a single gad weight percent, in which the candidates of the optimized gad pattern are determined based on the weighting of the gad rod location and the guide tube. Also the pattern evaluation is performed systematically to determine the optimal gad pattern for the various situation

  2. Synchronized femtosecond laser pulse switching system based nano-patterning technology

    Science.gov (United States)

    Sohn, Ik-Bu; Choi, Hun-Kook; Yoo, Dongyoon; Noh, Young-Chul; Sung, Jae-Hee; Lee, Seong-Ku; Ahsan, Md. Shamim; Lee, Ho

    2017-07-01

    This paper demonstrates the design and development of a synchronized femtosecond laser pulse switching system and its applications in nano-patterning of transparent materials. Due to synchronization, we are able to control the location of each irradiated laser pulse in any kind of substrate. The control over the scanning speed and scanning step of the laser beam enables us to pattern periodic micro/nano-metric holes, voids, and/or lines in various materials. Using the synchronized laser system, we pattern synchronized nano-holes on the surface of and inside various transparent materials including fused silica glass and polymethyl methacrylate to replicate any image or pattern on the surface of or inside (transparent) materials. We also investigate the application areas of the proposed synchronized femtosecond laser pulse switching system in a diverse field of science and technology, especially in optical memory, color marking, and synchronized micro/nano-scale patterning of materials.

  3. 78 FR 50123 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule...

    Science.gov (United States)

    2013-08-16

    ...-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule Change to Assume... NASDAQ Stock Market LLC (``NASDAQ'' or the ``Exchange'') filed with the Securities and Exchange...: Manipulation patterns that monitor solely NASDAQ activity, including patterns that monitor the Exchange's...

  4. Short local descriptors from 2D connected pattern spectra

    NARCIS (Netherlands)

    Bosilj, Petra; Kijak, Ewa; Wilkinson, Michael H. F.; Lefèvre, Sebastien

    2015-01-01

    We propose a local region descriptor based on connected pattern spectra, and combined with normalized central moments. The descriptors are calculated for MSER regions of the image, and their performance compared against SIFT. The MSER regions were chosen because they can be efficiently selected by

  5. Personal sleep pattern visualization using sequence-based kernel self-organizing map on sound data.

    Science.gov (United States)

    Wu, Hongle; Kato, Takafumi; Yamada, Tomomi; Numao, Masayuki; Fukui, Ken-Ichi

    2017-07-01

    We propose a method to discover sleep patterns via clustering of sound events recorded during sleep. The proposed method extends the conventional self-organizing map algorithm by kernelization and sequence-based technologies to obtain a fine-grained map that visualizes the distribution and changes of sleep-related events. We introduced features widely applied in sound processing and popular kernel functions to the proposed method to evaluate and compare performance. The proposed method provides a new aspect of sleep monitoring because the results demonstrate that sound events can be directly correlated to an individual's sleep patterns. In addition, by visualizing the transition of cluster dynamics, sleep-related sound events were found to relate to the various stages of sleep. Therefore, these results empirically warrant future study into the assessment of personal sleep quality using sound data. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Prioritising lexical patterns to increase axiomatisation in biomedical ontologies. The role of localisation and modularity.

    Science.gov (United States)

    Quesada-Martínez, M; Fernández-Breis, J T; Stevens, R; Mikroyannidi, E

    2015-01-01

    This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". In previous work, we have defined methods for the extraction of lexical patterns from labels as an initial step towards semi-automatic ontology enrichment methods. Our previous findings revealed that many biomedical ontologies could benefit from enrichment methods using lexical patterns as a starting point.Here, we aim to identify which lexical patterns are appropriate for ontology enrichment, driving its analysis by metrics to prioritised the patterns. We propose metrics for suggesting which lexical regularities should be the starting point to enrich complex ontologies. Our method determines the relevance of a lexical pattern by measuring its locality in the ontology, that is, the distance between the classes associated with the pattern, and the distribution of the pattern in a certain module of the ontology. The methods have been applied to four significant biomedical ontologies including the Gene Ontology and SNOMED CT. The metrics provide information about the engineering of the ontologies and the relevance of the patterns. Our method enables the suggestion of links between classes that are not made explicit in the ontology. We propose a prioritisation of the lexical patterns found in the analysed ontologies. The locality and distribution of lexical patterns offer insights into the further engineering of the ontology. Developers can use this information to improve the axiomatisation of their ontologies.

  7. Acoustic beam steering by light refraction: illustration with directivity patterns of a tilted volume photoacoustic source.

    Science.gov (United States)

    Raetz, Samuel; Dehoux, Thomas; Perton, Mathieu; Audoin, Bertrand

    2013-12-01

    The symmetry of a thermoelastic source resulting from laser absorption can be broken when the direction of light propagation in an elastic half-space is inclined relatively to the surface. This leads to an asymmetry of the directivity patterns of both compressional and shear acoustic waves. In contrast to classical surface acoustic sources, the tunable volume source allows one to take advantage of the mode conversion at the surface to control the directivity of specific modes. Physical interpretations of the evolution of the directivity patterns with the increasing light angle of incidence and of the relations between the preferential directions of compressional- and shear-wave emission are proposed. In order to compare calculated directivity patterns with measurements of normal displacement amplitudes performed on plates, a procedure is proposed to transform the directivity patterns into pseudo-directivity patterns representative of the experimental conditions. The comparison of the theoretical with measured pseudo-directivity patterns demonstrates the ability to enhance bulk-wave amplitudes and to steer specific bulk acoustic modes by adequately tuning light refraction.

  8. On tests of randomness for spatial point patterns

    International Nuclear Information System (INIS)

    Doguwa, S.I.

    1990-11-01

    New tests of randomness for spatial point patterns are introduced. These test statistics are then compared in a power study with the existing alternatives. These results of the power study suggest that one of the tests proposed is extremely powerful against both aggregated and regular alternatives. (author). 9 refs, 7 figs, 3 tabs

  9. PGG: An Online Pattern Based Approach for Stream Variation Management

    Institute of Scientific and Technical Information of China (English)

    Lu-An Tang; Bin Cui; Hong-Yan Li; Gao-Shan Miao; Dong-Qing Yang; Xin-Biao Zhou

    2008-01-01

    Many database applications require efficient processing of data streams with value variations and fiuctuant sampling frequency. The variations typically imply fundamental features of the stream and important domain knowledge of underlying objects. In some data streams, successive events seem to recur in a certain time interval, but the data indeed evolves with tiny differences as time elapses. This feature, so called pseudo periodicity, poses a new challenge to stream variation management. This study focuses on the online management for variations over such streams. The idea can be applied to many scenarios such as patient vital signal monitoring in medical applications. This paper proposes a new method named Pattern Growth Graph (PGG) to detect and manage variations over evolving streams with following features: 1) adopts the wave-pattern to capture the major information of data evolution and represent them compactly;2) detects the variations in a single pass over the stream with the help of wave-pattern matching algorithm; 3) only stores different segments of the pattern for incoming stream, and hence substantially compresses the data without losing important information; 4) distinguishes meaningful data changes from noise and reconstructs the stream with acceptable accuracy.Extensive experiments on real datasets containing millions of data items, as well as a prototype system, are carried out to demonstrate the feasibility and effectiveness of the proposed scheme.

  10. Optimal pattern synthesis for speech recognition based on principal component analysis

    Science.gov (United States)

    Korsun, O. N.; Poliyev, A. V.

    2018-02-01

    The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

  11. Design Pattern Retrieval and Style Analysis for Content Creation of Comic Figures

    Directory of Open Access Journals (Sweden)

    Bor-Shen Lin

    2014-01-01

    Full Text Available Placement of objects within a constrained space is a common challenge for designers; it is associated with decisions regarding the furnishing of a space with furniture, collocation of dressings, flower arrangement, and design of comic figures. Though many design elements can be shared on the Internet in the current age of technology, it is still not easy to compare or search for design patterns based on these elements. Thus, it is difficult for designers to efficiently retrieve similar patterns designed by others, to compare them, or to learn from them. This paper proposes the architecture of representing, comparing, retrieving, and analyzing the design patterns of digital contents for design support. This scheme can help the designers to explore the huge space of design patterns efficiently, to analyze and summarize the design styles quickly, and to improve design skills and stimulate imaginations effectively during the process of learning or creating. The proposed scheme has been verified with a design support system for the content creation of comic figures. It is generally applicable to the creation of digital contents and shows potential for applications in the fields of design and education.

  12. Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities

    Directory of Open Access Journals (Sweden)

    Rubén Pérez-Chacón

    2018-03-01

    Full Text Available New technologies such as sensor networks have been incorporated into the management of buildings for organizations and cities. Sensor networks have led to an exponential increase in the volume of data available in recent years, which can be used to extract consumption patterns for the purposes of energy and monetary savings. For this reason, new approaches and strategies are needed to analyze information in big data environments. This paper proposes a methodology to extract electric energy consumption patterns in big data time series, so that very valuable conclusions can be made for managers and governments. The methodology is based on the study of four clustering validity indices in their parallelized versions along with the application of a clustering technique. In particular, this work uses a voting system to choose an optimal number of clusters from the results of the indices, as well as the application of the distributed version of the k-means algorithm included in Apache Spark’s Machine Learning Library. The results, using electricity consumption for the years 2011–2017 for eight buildings of a public university, are presented and discussed. In addition, the performance of the proposed methodology is evaluated using synthetic big data, which cab represent thousands of buildings in a smart city. Finally, policies derived from the patterns discovered are proposed to optimize energy usage across the university campus.

  13. Gardosian Patterns in Tribology

    Science.gov (United States)

    DellaCorte, Christopher

    2004-01-01

    The following paper is a memorial retrospective on selected research of Dr. Michael N. Gardos. Dr. Gardos spent his professional career engaged in tribological research which often extended the scientific boundaries of the field. Several of the concepts he put forth into the tribology community were initially met with grave skepticism but over time his views have been largely embraced but not widely acknowledged. His approach to new research topics was often characterized by these qualities: 1) pioneering points of view, 2) the use of the model experiment, and 3) the presence of multiple research agendas for each single experiment. I have chosen to name his research approach as "Gardosian Patterns" in honor of his contributions to Tribology. Three specific examples of these patterns will be reviewed. One is the concept of atomic level tailoring of materials to control macroscopic properties. A second is the use of a model ball polishing experiment to identify high fracture toughness ceramics for use in rolling element bearings. A third Gardosian Pattern example is his pioneering work with the tribology of diamond and diamond films in which he proposed controlling friction via surface bond tailoring. In these examples, Gardos utilized conventional research tools in unconventional ways and, at times, even developed new tools which have become part of the mainstream. His remarkable career has left a positive and lasting mark on Tribology.

  14. Application of Classification Methods for Forecasting Mid-Term Power Load Patterns

    Science.gov (United States)

    Piao, Minghao; Lee, Heon Gyu; Park, Jin Hyoung; Ryu, Keun Ho

    Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in long duration load profiles. The proposed approach in this paper consists of three stages: (i) data preprocessing: noise or outlier is removed and the continuous attribute-valued features are transformed to discrete values, (ii) cluster analysis: k-means clustering is used to create load pattern classes and the representative load profiles for each class and (iii) classification: we evaluated several supervised learning methods in order to select a suitable prediction method. According to the proposed methodology, power load measured from AMR (automatic meter reading) system, as well as customer indexes, were used as inputs for clustering. The output of clustering was the classification of representative load profiles (or classes). In order to evaluate the result of forecasting load patterns, the several classification methods were applied on a set of high voltage customers of the Korea power system and derived class labels from clustering and other features are used as input to produce classifiers. Lastly, the result of our experiments was presented.

  15. A dual-band reconfigurable Yagi-Uda antenna with diverse radiation patterns

    Science.gov (United States)

    Saurav, Kushmanda; Sarkar, Debdeep; Srivastava, Kumar Vaibhav

    2017-07-01

    In this paper, a dual-band pattern reconfigurable antenna is proposed. The antenna comprises of a dual-band complementary split ring resonators (CSRRs) loaded dipole as the driven element and two copper strips with varying lengths as parasitic segments on both sides of the driven dipole. PIN diodes are used with the parasitic elements to control their electrical length. The CSRRs loading provide a lower order mode in addition to the reference dipole mode, while the parasitic elements along with the PIN diodes are capable of switching the omni-directional radiation of the dual-band driven element to nine different configurations of radiation patterns which include bi-directional end-fire, broadside, and uni-directional end-fire in both the operating bands. A prototype of the designed antenna together with the PIN diodes and DC bias lines is fabricated to validate the concept of dual-band radiation pattern diversity. The simulation and measurement results are in good agreement. The proposed antenna can be used in wireless access points for PCS and WLAN applications.

  16. Texture Classification in Lung CT Using Local Binary Patterns

    DEFF Research Database (Denmark)

    Sørensen, Lauge Emil Borch Laurs; Shaker, Saher B.; de Bruijne, Marleen

    2008-01-01

    the k nearest neighbor classifier with histogram similarity as distance measure. The proposed method is evaluated on a set of 168 regions of interest comprising normal tissue and different emphysema patterns, and compared to a filter bank based on Gaussian derivatives. The joint LBP and intensity...

  17. Vector space representation of array antenna pattern synthesis problems

    DEFF Research Database (Denmark)

    Wu, Jian; Roederer, A.G

    1991-01-01

    and to visualize the optimization process. The vector space approach described provides a very powerful representation of the array pattern synthesis problems. It is not only general, since many parameters are represented under one model, but also helps to visualize the problem. The proposed approach provides...

  18. Two-shot fringe pattern phase-amplitude demodulation using Gram-Schmidt orthonormalization with Hilbert-Huang pre-filtering.

    Science.gov (United States)

    Trusiak, Maciej; Patorski, Krzysztof

    2015-02-23

    Gram-Schmidt orthonormalization is a very fast and efficient method for the fringe pattern phase demodulation. It requires only two arbitrarily phase-shifted frames. Images are treated as vectors and upon orthogonal projection of one fringe vector onto another the quadrature fringe pattern pair is obtained. Orthonormalization process is very susceptible, however, to noise, uneven background and amplitude modulation fluctuations. The Hilbert-Huang transform based preprocessing is proposed to enhance fringe pattern phase demodulation by filtering out the spurious noise and background illumination and performing fringe normalization. The Gram-Schmidt orthonormalization process error analysis is provided and its filtering-expanded capabilities are corroborated analyzing DSPI fringes and performing amplitude demodulation of Bessel fringes. Synthetic and experimental fringe pattern analyses presented to validate the proposed technique show that it compares favorably with other pre-filtering schemes, i.e., Gaussian filtering and continuous wavelet transform.

  19. A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series

    Directory of Open Access Journals (Sweden)

    Madeira Sara C

    2009-06-01

    Full Text Available Abstract Background The ability to monitor the change in expression patterns over time, and to observe the emergence of coherent temporal responses using gene expression time series, obtained from microarray experiments, is critical to advance our understanding of complex biological processes. In this context, biclustering algorithms have been recognized as an important tool for the discovery of local expression patterns, which are crucial to unravel potential regulatory mechanisms. Although most formulations of the biclustering problem are NP-hard, when working with time series expression data the interesting biclusters can be restricted to those with contiguous columns. This restriction leads to a tractable problem and enables the design of efficient biclustering algorithms able to identify all maximal contiguous column coherent biclusters. Methods In this work, we propose e-CCC-Biclustering, a biclustering algorithm that finds and reports all maximal contiguous column coherent biclusters with approximate expression patterns in time polynomial in the size of the time series gene expression matrix. This polynomial time complexity is achieved by manipulating a discretized version of the original matrix using efficient string processing techniques. We also propose extensions to deal with missing values, discover anticorrelated and scaled expression patterns, and different ways to compute the errors allowed in the expression patterns. We propose a scoring criterion combining the statistical significance of expression patterns with a similarity measure between overlapping biclusters. Results We present results in real data showing the effectiveness of e-CCC-Biclustering and its relevance in the discovery of regulatory modules describing the transcriptomic expression patterns occurring in Saccharomyces cerevisiae in response to heat stress. In particular, the results show the advantage of considering approximate patterns when compared to state of

  20. Parallel patterns determination in solving cyclic flow shop problem with setups

    Directory of Open Access Journals (Sweden)

    Bożejko Wojciech

    2017-06-01

    Full Text Available The subject of this work is the new idea of blocks for the cyclic flow shop problem with setup times, using multiple patterns with different sizes determined for each machine constituting optimal schedule of cities for the traveling salesman problem (TSP. We propose to take advantage of the Intel Xeon Phi parallel computing environment during so-called ’blocks’ determination basing on patterns, in effect significantly improving the quality of obtained results.

  1. FAST: A fully asynchronous and status-tracking pattern for geoprocessing services orchestration

    Science.gov (United States)

    Wu, Huayi; You, Lan; Gui, Zhipeng; Gao, Shuang; Li, Zhenqiang; Yu, Jingmin

    2014-09-01

    Geoprocessing service orchestration (GSO) provides a unified and flexible way to implement cross-application, long-lived, and multi-step geoprocessing service workflows by coordinating geoprocessing services collaboratively. Usually, geoprocessing services and geoprocessing service workflows are data and/or computing intensive. The intensity feature may make the execution process of a workflow time-consuming. Since it initials an execution request without blocking other interactions on the client side, an asynchronous mechanism is especially appropriate for GSO workflows. Many critical problems remain to be solved in existing asynchronous patterns for GSO including difficulties in improving performance, status tracking, and clarifying the workflow structure. These problems are a challenge when orchestrating performance efficiency, making statuses instantly available, and constructing clearly structured GSO workflows. A Fully Asynchronous and Status-Tracking (FAST) pattern that adopts asynchronous interactions throughout the whole communication tier of a workflow is proposed for GSO. The proposed FAST pattern includes a mechanism that actively pushes the latest status to clients instantly and economically. An independent proxy was designed to isolate the status tracking logic from the geoprocessing business logic, which assists the formation of a clear GSO workflow structure. A workflow was implemented in the FAST pattern to simulate the flooding process in the Poyang Lake region. Experimental results show that the proposed FAST pattern can efficiently tackle data/computing intensive geoprocessing tasks. The performance of all collaborative partners was improved due to the asynchronous mechanism throughout communication tier. A status-tracking mechanism helps users retrieve the latest running status of a GSO workflow in an efficient and instant way. The clear structure of the GSO workflow lowers the barriers for geospatial domain experts and model designers to

  2. Design And Implementation Of Tool For Detecting Anti-Patterns In Relational Database

    Directory of Open Access Journals (Sweden)

    Gaurav Kumar

    2017-07-01

    Full Text Available Anti-patterns are poor solution to design and im-plementation problems. Developers may introduce anti-patterns in their software systems because of time pressure lack of understanding communication and or-skills. Anti-patterns create problems in software maintenance and development. Database anti-patterns lead to complex and time consuming query process-ing and loss of integrity constraints. Detecting anti-patterns could reduce costs efforts and resources. Researchers have proposed approaches to detect anti-patterns in software development. But not much research has been done about database anti-patterns. This report presents two approaches to detect schema design anti-patterns in relational database. Our first approach is based on pattern matchingwe look into potential candidates based on schema patterns. Second approach is a machine learning based approach we generate features of possible anti-patterns and build SVMbased classifier to detect them. Here we look into these four anti-patterns a Multi-valued attribute b Nave tree based c Entity Attribute Value and dPolymorphic Association . We measure precision and recall of each approach and compare the results. SVM-based approach provides more precision and recall with more training dataset.

  3. Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment

    DEFF Research Database (Denmark)

    Christensen, Kim; Hounyo, Ulrich; Podolskij, Mark

    In this paper, we propose a nonparametric way to test the hypothesis that time-variation in intraday volatility is caused solely by a deterministic and recurrent diurnal pattern. We assume that noisy high-frequency data from a discretely sampled jump-diffusion process are available. The test...... inference, we propose a new bootstrap approach, which leads to almost correctly sized tests of the null hypothesis. We apply the developed framework to a large cross-section of equity high-frequency data and find that the diurnal pattern accounts for a rather significant fraction of intraday variation...

  4. Proposal of a congestion control technique in LAN networks using an econometric model ARIMA

    Directory of Open Access Journals (Sweden)

    Joaquín F Sánchez

    2017-01-01

    Full Text Available Hasty software development can produce immediate implementations with source code unnecessarily complex and hardly readable. These small kinds of software decay generate a technical debt that could be big enough to seriously affect future maintenance activities. This work presents an analysis technique for identifying architectural technical debt related to non-uniformity of naming patterns; the technique is based on term frequency over package hierarchies. The proposal has been evaluated on projects of two popular organizations, Apache and Eclipse. The results have shown that most of the projects have frequent occurrences of the proposed naming patterns, and using a graph model and aggregated data could enable the elaboration of simple queries for debt identification. The technique has features that favor its applicability on emergent architectures and agile software development.

  5. Test Pattern Generator for Mixed Mode BIST

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hong Sik; Lee, Hang Kyu; Kang, Sung Ho [Yonsei University (Korea, Republic of)

    1998-07-01

    As the increasing integrity of VLSI, the BIST (Built-In Self Test) is used as an effective method to test chips. Generally the pseudo-random test pattern generation is used for BIST. But it requires lots of test patterns when there exist random resistant faults. Therefore deterministic testing is an interesting BIST technique due to the minimal number of test patterns and to its high fault coverage. However this is not applicable since the existing deterministic test pattern generators require too much area overhead despite their efficiency. Therefore we propose a mixed test scheme which applies to the circuit under test, a deterministic test sequence followed by a pseudo-random one. This scheme allows the maximum fault coverage detection to be achieved, furthermore the silicon area overhead of the mixed hardware generator can be reduced. The deterministic test generator is made with a finite state machine and a pseudo-random test generator is made with LFSR(linear feedback shift register). The results of ISCAS circuits show that the maximum fault coverage is guaranteed with small number of test set and little hardware overhead. (author). 15 refs., 10 figs., 4 tabs.

  6. Screening for pain-persistence and pain-avoidance patterns in fibromyalgia.

    NARCIS (Netherlands)

    Koulil, S. van; Kraaimaat, F.W.; Lankveld, W.G.J.M. van; Helmond, T. van; Vedder, A.; Hoorn, H. van; Cats, H.; Riel, P.L.C.M. van; Evers, A.W.M.

    2008-01-01

    BACKGROUND: The heterogeneity of patients regarding pain-related cognitive-behavioral mechanisms, such as pain-avoidance and pain-persistence patterns, has been proposed to underlie varying treatment outcomes in patients with fibromyalgia (FM). PURPOSE: To investigate the validity of a screening

  7. Group of Hexagonal Search Patterns for Motion Estimation and Object Tracking

    International Nuclear Information System (INIS)

    Elazm, A.A.; Mahmoud, I.I; Hashima, S.M.

    2010-01-01

    This paper presents a group of fast block matching algorithms based on the hexagon pattern search .A new predicted one point hexagon (POPHEX) algorithm is proposed and compared with other well known algorithms. The comparison of these algorithms and our proposed one is performed for both motion estimation and object tracking. Test video sequences are used to demonstrate the behavior of studied algorithms. All algorithms are implemented in MATLAB environment .Experimental results showed that the proposed algorithm posses less number of search points however its computational overhead is little increased due to prediction procedure.

  8. A Study of Pattern Prediction in the Monitoring Data of Earthen Ruins with the Internet of Things.

    Science.gov (United States)

    Xiao, Yun; Wang, Xin; Eshragh, Faezeh; Wang, Xuanhong; Chen, Xiaojiang; Fang, Dingyi

    2017-05-11

    An understanding of the changes of the rammed earth temperature of earthen ruins is important for protection of such ruins. To predict the rammed earth temperature pattern using the air temperature pattern of the monitoring data of earthen ruins, a pattern prediction method based on interesting pattern mining and correlation, called PPER, is proposed in this paper. PPER first finds the interesting patterns in the air temperature sequence and the rammed earth temperature sequence. To reduce the processing time, two pruning rules and a new data structure based on an R-tree are also proposed. Correlation rules between the air temperature patterns and the rammed earth temperature patterns are then mined. The correlation rules are merged into predictive rules for the rammed earth temperature pattern. Experiments were conducted to show the accuracy of the presented method and the power of the pruning rules. Moreover, the Ming Dynasty Great Wall dataset was used to examine the algorithm, and six predictive rules from the air temperature to rammed earth temperature based on the interesting patterns were obtained, with the average hit rate reaching 89.8%. The PPER and predictive rules will be useful for rammed earth temperature prediction in protection of earthen ruins.

  9. Polypharmacy patterns: unravelling systematic associations between prescribed medications.

    Directory of Open Access Journals (Sweden)

    Amaia Calderón-Larrañaga

    Full Text Available OBJECTIVES: The aim of this study was to demonstrate the existence of systematic associations in drug prescription that lead to the establishment of patterns of polypharmacy, and the clinical interpretation of the associations found in each pattern. METHODS: A cross-sectional study was conducted based on information obtained from electronic medical records and the primary care pharmacy database in 2008. An exploratory factor analysis of drug dispensing information regarding 79,089 adult patients was performed to identify the patterns of polypharmacy. The analysis was stratified by age and sex. RESULTS: Seven patterns of polypharmacy were identified, which may be classified depending on the type of disease they are intended to treat: cardiovascular, depression-anxiety, acute respiratory infection (ARI, chronic obstructive pulmonary disease (COPD, rhinitis-asthma, pain, and menopause. Some of these patterns revealed a clear clinical consistency and included drugs that are prescribed together for the same clinical indication (i.e., ARI and COPD patterns. Other patterns were more complex but also clinically consistent: in the cardiovascular pattern, drugs for the treatment of known risk factors-such as hypertension or dyslipidemia-were combined with other medications for the treatment of diabetes or established cardiovascular pathology (e.g., antiplatelet agents. Almost all of the patterns included drugs for preventing or treating potential side effects of other drugs in the same pattern. CONCLUSIONS: The present study demonstrated the existence of non-random associations in drug prescription, resulting in patterns of polypharmacy that are sound from the pharmacological and clinical viewpoints and that exist in a significant proportion of the population. This finding necessitates future longitudinal studies to confirm some of the proposed causal associations. The information discovered would further the development and/or adaptation of clinical

  10. The Smallest Valid Extension-Based Efficient, Rare Graph Pattern Mining, Considering Length-Decreasing Support Constraints and Symmetry Characteristics of Graphs

    Directory of Open Access Journals (Sweden)

    Unil Yun

    2016-05-01

    Full Text Available Frequent graph mining has been proposed to find interesting patterns (i.e., frequent sub-graphs from databases composed of graph transaction data, which can effectively express complex and large data in the real world. In addition, various applications for graph mining have been suggested. Traditional graph pattern mining methods use a single minimum support threshold factor in order to check whether or not mined patterns are interesting. However, it is not a sufficient factor that can consider valuable characteristics of graphs such as graph sizes and features of graph elements. That is, previous methods cannot consider such important characteristics in their mining operations since they only use a fixed minimum support threshold in the mining process. For this reason, in this paper, we propose a novel graph mining algorithm that can consider various multiple, minimum support constraints according to the types of graph elements and changeable minimum support conditions, depending on lengths of graph patterns. In addition, the proposed algorithm performs in mining operations more efficiently because it can minimize duplicated operations and computational overheads by considering symmetry features of graphs. Experimental results provided in this paper demonstrate that the proposed algorithm outperforms previous mining approaches in terms of pattern generation, runtime and memory usage.

  11. SVM-based Partial Discharge Pattern Classification for GIS

    Science.gov (United States)

    Ling, Yin; Bai, Demeng; Wang, Menglin; Gong, Xiaojin; Gu, Chao

    2018-01-01

    Partial discharges (PD) occur when there are localized dielectric breakdowns in small regions of gas insulated substations (GIS). It is of high importance to recognize the PD patterns, through which we can diagnose the defects caused by different sources so that predictive maintenance can be conducted to prevent from unplanned power outage. In this paper, we propose an approach to perform partial discharge pattern classification. It first recovers the PRPD matrices from the PRPD2D images; then statistical features are extracted from the recovered PRPD matrix and fed into SVM for classification. Experiments conducted on a dataset containing thousands of images demonstrates the high effectiveness of the method.

  12. Blind Channel Equalization Using Constrained Generalized Pattern Search Optimization and Reinitialization Strategy

    Directory of Open Access Journals (Sweden)

    Charles Tatkeu

    2008-12-01

    Full Text Available We propose a global convergence baud-spaced blind equalization method in this paper. This method is based on the application of both generalized pattern optimization and channel surfing reinitialization. The potentially used unimodal cost function relies on higher- order statistics, and its optimization is achieved using a pattern search algorithm. Since the convergence to the global minimum is not unconditionally warranted, we make use of channel surfing reinitialization (CSR strategy to find the right global minimum. The proposed algorithm is analyzed, and simulation results using a severe frequency selective propagation channel are given. Detailed comparisons with constant modulus algorithm (CMA are highlighted. The proposed algorithm performances are evaluated in terms of intersymbol interference, normalized received signal constellations, and root mean square error vector magnitude. In case of nonconstant modulus input signals, our algorithm outperforms significantly CMA algorithm with full channel surfing reinitialization strategy. However, comparable performances are obtained for constant modulus signals.

  13. Blind Channel Equalization Using Constrained Generalized Pattern Search Optimization and Reinitialization Strategy

    Science.gov (United States)

    Zaouche, Abdelouahib; Dayoub, Iyad; Rouvaen, Jean Michel; Tatkeu, Charles

    2008-12-01

    We propose a global convergence baud-spaced blind equalization method in this paper. This method is based on the application of both generalized pattern optimization and channel surfing reinitialization. The potentially used unimodal cost function relies on higher- order statistics, and its optimization is achieved using a pattern search algorithm. Since the convergence to the global minimum is not unconditionally warranted, we make use of channel surfing reinitialization (CSR) strategy to find the right global minimum. The proposed algorithm is analyzed, and simulation results using a severe frequency selective propagation channel are given. Detailed comparisons with constant modulus algorithm (CMA) are highlighted. The proposed algorithm performances are evaluated in terms of intersymbol interference, normalized received signal constellations, and root mean square error vector magnitude. In case of nonconstant modulus input signals, our algorithm outperforms significantly CMA algorithm with full channel surfing reinitialization strategy. However, comparable performances are obtained for constant modulus signals.

  14. Transiently expressed pattern during myogenesis and candidate ...

    Indian Academy of Sciences (India)

    Navya

    pattern of Tmem8C in goose, it appears that infusion occurred in the E15 and E19 periods in LM and E19 in BM, which is a few days later than in chicken and duck. Li et al. proposed that the development of BM lags behind that of LM in embryonic phases in duck, and suggested this might be related to the environmental ...

  15. Developement of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    International Nuclear Information System (INIS)

    Deputch, G.; Hoff, J.; Lipton, R.; Liu, T.; Olsen, J.; Ramberg, E.; Wu, Jin-Yuan; Yarema, R.; Shochet, M.; Tang, F.; Demarteau, M.

    2011-01-01

    Many next-generation physics experiments will be characterized by the collection of large quantities of data, taken in rapid succession, from which scientists will have to unravel the underlying physical processes. In most cases, large backgrounds will overwhelm the physics signal. Since the quantity of data that can be stored for later analysis is limited, real-time event selection is imperative to retain the interesting events while rejecting the background. Scaling of current technologies is unlikely to satisfy the scientific needs of future projects, so investments in transformational new technologies need to be made. For example, future particle physics experiments looking for rare processes will have to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare processes. In this proposal, we intend to develop hardware-based technology that significantly advances the state-of-the-art for fast pattern recognition within and outside HEP using the 3D vertical integration technology that has emerged recently in industry. The ultimate physics reach of the LHC experiments will crucially depend on the tracking trigger's ability to help discriminate between interesting rare events and the background. Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing pattern recognition

  16. Generating spatiotemporal joint torque patterns from dynamical synchronization of distributed pattern generators

    Directory of Open Access Journals (Sweden)

    Alex Pitti

    2009-10-01

    Full Text Available Pattern generators found in the spinal cords are no more seen as simple rhythmic oscillators for motion control. Indeed, they achieve flexible and dynamical coordination in interaction with the body and the environment dynamics to rise motor synergies. Discovering the mechanisms underlying the control of motor synergies constitute an important research question not only for neuroscience but also for robotics: the motors coordination of high dimensional robotic systems is still a drawback and new control methods based on biological solutions may reduce their overall complexity. We propose to model the flexible combination of motor synergies in embodied systems via partial phase synchronization of distributed chaotic systems; for specific coupling strength, chaotic systems are able to phase synchronize their dynamics to the resonant frequencies of one external force. We take advantage of this property to explore and exploit the intrinsic dynamics of one specified embodied system. In two experiments with bipedal walkers, we show how motor synergies emerge when the controllers phase synchronize to the body’s dynamics, entraining it to its intrinsic behavioral patterns. This stage is characterized by directed information flow from the sensors to the motors exhibiting the optimal situation when the body dynamics drive the controllers (mutual entrainment. Based on our results, we discuss the relevance of our findings for modeling the modular control of distributed pattern generators exhibited in the spinal cords, and for exploring the motor synergies in robots.

  17. Characteristics of the transmission of autoregressive sub-patterns in financial time series

    Science.gov (United States)

    Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong

    2014-09-01

    There are many types of autoregressive patterns in financial time series, and they form a transmission process. Here, we define autoregressive patterns quantitatively through an econometrical regression model. We present a computational algorithm that sets the autoregressive patterns as nodes and transmissions between patterns as edges, and then converts the transmission process of autoregressive patterns in a time series into a network. We utilised daily Shanghai (securities) composite index time series to study the transmission characteristics of autoregressive patterns. We found statistically significant evidence that the financial market is not random and that there are similar characteristics between parts and whole time series. A few types of autoregressive sub-patterns and transmission patterns drive the oscillations of the financial market. A clustering effect on fluctuations appears in the transmission process, and certain non-major autoregressive sub-patterns have high media capabilities in the financial time series. Different stock indexes exhibit similar characteristics in the transmission of fluctuation information. This work not only proposes a distinctive perspective for analysing financial time series but also provides important information for investors.

  18. Reloading pattern optimization of VVER-1000 reactors in transient cycles using genetic algorithm

    International Nuclear Information System (INIS)

    Rahmani, Yashar

    2017-01-01

    Highlights: • The genetic algorithm (GA) and the innovative weighting factors method were used. • The coupling of WIMSD5-B and CITATION-LDI2 neutronic codes with the thermohydraulic WERL code was employed. • Optimization of reloading patterns was carried out in two states. • First an arrangement with satisfactory excess reactivity and the flattest power distribution was searched. • Second, it is tried to obtain an arrangement with satisfactory safety threshold and the maximum K_e_f_f. - Abstract: The present paper proposes application of the genetic algorithm (GA) and the innovative weighting factor method to optimize the reloading pattern of Bushehr VVER-1000 reactor in the second cycle. To estimate the composition of fuel assemblies remaining from the first cycle and precisely calculate the objective parameters of each reloading pattern in the second cycle, coupling of WIMSD5-B and CITATION-LDI2 codes in the neutronic section and the WERL code in the thermo-hydraulic section was employed. Optimization of the reloading patterns was carried out in two states. To meet the mentioned objective, with application of the weighting factor method in the first state, the type and quantity of the loadable fresh assemblies were determined to enable the reactor core to maintain the core criticality over the entire cycle length. Afterwards, the genetic algorithm was used to optimize the reloading pattern of the reactor to obtain an arrangement with flat radial power distribution. In the second state, the optimization algorithm was free to select the type and number of fresh fuel assemblies to be able to search for an arrangement with the maximum effective multiplication factor and the safe power peaking factor. In addition, in order to ensure the safety and desirability of the proposed patterns in both states, a time-dependent examination of the thermo-neutronic behavior of the reactor core was carried out during the second cycle. With consideration of the new

  19. On the physical basis of pattern formation in nonlinear systems

    International Nuclear Information System (INIS)

    Sanduloviciu, M.; Lozneanu, E.; Popescu, S.

    2003-01-01

    Spatial, respectively spatiotemporal patterns appear in a gaseous conductor (plasma) when an external constraint produces a local gradient of electron kinetic energy. Under such conditions, collective quantum effects related to the spatial separation of the excitation and ionization cross-sections determine the appearance of adjacent opposite space charges. The state of the resulting space charge configuration depends on the self-enhancement process of positive ions production, which destabilizes the system. Thus, a spatial pattern in the form of a stable double layer appears after self-organization when the above gradient is smaller than that for which the double layer transits into a moving phase (spatiotemporal pattern). The proposed explanation, based on investigations performed on self-organization phenomena observed in gaseous conductors, suggests a new possibility to clarify the challenging problems concerning the actual physical basis of pattern formation in semiconductors

  20. Investigation of patterning effects in ultrafast SOA-based optical switches

    DEFF Research Database (Denmark)

    Xu, Jing; Zhang, Xinliang; Mørk, Jesper

    2010-01-01

    , has been proposed based on the idea of driving the SOA at two saturation extremes by two periodic pulse trains. The predictive power of the periodic method is verified by comparing its results with those obtained by using ordinary PRBS patterns. Finally, the effectiveness of the periodic method...... is exploited by analyzing in detail the performance properties of a specific type of switch over large parameter regions. Besides allowing an investigation of patterning effects, the periodic method also simultaneously provides such figures of merit as output power and pulsewidth....... that limits the ultimate speed at which SOA-based switches can be operated. In this paper, we investigate the patterning effects of SOA-based switches using a systematic approach. A simple condition for the lower bound limit of the bit pattern length that should be adopted in the performance evaluations...

  1. Handling Dynamic Weights in Weighted Frequent Pattern Mining

    Science.gov (United States)

    Ahmed, Chowdhury Farhan; Tanbeer, Syed Khairuzzaman; Jeong, Byeong-Soo; Lee, Young-Koo

    Even though weighted frequent pattern (WFP) mining is more effective than traditional frequent pattern mining because it can consider different semantic significances (weights) of items, existing WFP algorithms assume that each item has a fixed weight. But in real world scenarios, the weight (price or significance) of an item can vary with time. Reflecting these changes in item weight is necessary in several mining applications, such as retail market data analysis and web click stream analysis. In this paper, we introduce the concept of a dynamic weight for each item, and propose an algorithm, DWFPM (dynamic weighted frequent pattern mining), that makes use of this concept. Our algorithm can address situations where the weight (price or significance) of an item varies dynamically. It exploits a pattern growth mining technique to avoid the level-wise candidate set generation-and-test methodology. Furthermore, it requires only one database scan, so it is eligible for use in stream data mining. An extensive performance analysis shows that our algorithm is efficient and scalable for WFP mining using dynamic weights.

  2. MRI Patterns of Isolated Lesions in the Medulla Oblongata.

    Science.gov (United States)

    Prakkamakul, Supada; Schaefer, Pamela; Gonzalez, Gilberto; Rapalino, Otto

    2017-01-01

    Isolated lesions of the medulla oblongata are difficult to diagnose due to their rarity and high biopsy risk. Several individual case reports have been published, but a systematic descriptive study is lacking. Our study has three objectives that 1) provide a differential diagnosis, 2) describe magnetic resonance imaging (MRI) findings, and 3) propose a stepwise MRI-based approach to the isolated lesions of the medulla oblongata in nonstroke patients. We performed an institutional Review Board-approved retrospective analysis of 34 consecutive cases of isolated medullary lesions from nonstroke causes identified from our imaging database between January 2000 and May 2015. Eleven were excluded due to lack of pretreatment or follow-up MRI. MR studies were reviewed by two blinded neuroradiologists. The diagnosis, demographic data, and MR findings were reported using frequencies and proportions. An MRI-based diagnostic algorithm was proposed. Most lesions were neoplasms (47%), followed by vascular malformations (15%), demyelinating/inflammatory lesions (15%), others (12%), unknown (8%), and infection (3%). Five MRI patterns were identified: 1) cystic lesion, 2) exophytic noncystic lesion, 3) intrinsic lesion with T2 hypointensity, 4) enhancing intrinsic lesion, and 5) nonenhancing intrinsic lesion. All showing patterns 1 and 2 were neoplasms or cysts. All showing pattern 3 were vascular malformations. Patterns 4 and 5 comprised of multiple etiologies. Neoplasms are the most common cause of isolated medullary lesions in nonstroke patients. Other differential diagnoses include vascular malformations, demyelinating/inflammatory lesions, and infections. A stepwise MRI-based approach can help differentiate between various etiologies. Copyright © 2016 by the American Society of Neuroimaging.

  3. Finger crease pattern recognition using Legendre moments and principal component analysis

    Science.gov (United States)

    Luo, Rongfang; Lin, Tusheng

    2007-03-01

    The finger joint lines defined as finger creases and its distribution can identify a person. In this paper, we propose a new finger crease pattern recognition method based on Legendre moments and principal component analysis (PCA). After obtaining the region of interest (ROI) for each finger image in the pre-processing stage, Legendre moments under Radon transform are applied to construct a moment feature matrix from the ROI, which greatly decreases the dimensionality of ROI and can represent principal components of the finger creases quite well. Then, an approach to finger crease pattern recognition is designed based on Karhunen-Loeve (K-L) transform. The method applies PCA to a moment feature matrix rather than the original image matrix to achieve the feature vector. The proposed method has been tested on a database of 824 images from 103 individuals using the nearest neighbor classifier. The accuracy up to 98.584% has been obtained when using 4 samples per class for training. The experimental results demonstrate that our proposed approach is feasible and effective in biometrics.

  4. Proposal of Non-Contact Type Interface of Command Input Using Lip Motion Features

    Science.gov (United States)

    Sato, Yoshiyuki; Kageyama, Yoichi; Nishida, Makoto

    Lip motion features are of practical use in identifying individuals. It is therefore important to develop non-contact type interface. For the interface using lip motion features, individual differences such as accents and dialects in commands should be accepted. In this paper, we propose a method to identify commands by analyzing three kinds of lip motion features. They are lip width, lip length, and ratio of width and length. The analysis is made on the basis of these features' relative values obtained from the primary and object frame. The proposed method has three steps. First, we extracted the lip motion features on the basis of both positions and shapes of lip in each frame of facial images. Second, standard patterns were created from features of six utterances per command. The standard pattern is able to reduce the relative difference in the lip motion features. Third, similarities among commands were computed by Dynamic-Programming (DP) matching. And then, the command with the largest similarity was selected as the target one. Our experimental results suggest that proposed method is useful to construct the non-contact type interface of command input using lip motion features.

  5. Identification of strong earthquake ground motion by using pattern recognition

    International Nuclear Information System (INIS)

    Suzuki, Kohei; Tozawa, Shoji; Temmyo, Yoshiharu.

    1983-01-01

    The method of grasping adequately the technological features of complex waveform of earthquake ground motion and utilizing them as the input to structural systems has been proposed by many researchers, and the method of making artificial earthquake waves to be used for the aseismatic design of nuclear facilities has not been established in the unified form. In this research, earthquake ground motion was treated as an irregular process with unsteady amplitude and frequency, and the running power spectral density was expressed as a dark and light image on a plane of the orthogonal coordinate system with both time and frequency axes. The method of classifying this image into a number of technologically important categories by pattern recognition was proposed. This method is based on the concept called compound similarity method in the image technology, entirely different from voice diagnosis, and it has the feature that the result of identification can be quantitatively evaluated by the analysis of correlation of spatial images. Next, the standard pattern model of the simulated running power spectral density corresponding to the representative classification categories was proposed. Finally, the method of making unsteady simulated earthquake motion was shown. (Kako, I.)

  6. Temperature dependence of ordered GeSi island growth on patterned Si (001) substrates

    International Nuclear Information System (INIS)

    ZhongZhenyang; Chen Peixuan; Jiang Zuimin; Bauer, Guenther

    2008-01-01

    Statistical information on GeSi islands grown on two-dimensionally pit-patterned Si substrates at different temperatures is presented. Three growth regimes on patterned substrates are identified: (i) kinetically limited growth at low growth temperatures, (ii) ordered island growth in an intermediate temperature range, and (iii) stochastic island growth within pits at high temperatures. A qualitative model based on growth kinetics is proposed to explain these phenomena. It can serve as a guidance to realize optimum growth conditions for ordered islands on patterned substrates

  7. Classifying Human Activity Patterns from Smartphone Collected GPS data: a Fuzzy Classification and Aggregation Approach.

    Science.gov (United States)

    Wan, Neng; Lin, Ge

    2016-12-01

    Smartphones have emerged as a promising type of equipment for monitoring human activities in environmental health studies. However, degraded location accuracy and inconsistency of smartphone-measured GPS data have limited its effectiveness for classifying human activity patterns. This study proposes a fuzzy classification scheme for differentiating human activity patterns from smartphone-collected GPS data. Specifically, a fuzzy logic reasoning was adopted to overcome the influence of location uncertainty by estimating the probability of different activity types for single GPS points. Based on that approach, a segment aggregation method was developed to infer activity patterns, while adjusting for uncertainties of point attributes. Validations of the proposed methods were carried out based on a convenient sample of three subjects with different types of smartphones. The results indicate desirable accuracy (e.g., up to 96% in activity identification) with use of this method. Two examples were provided in the appendix to illustrate how the proposed methods could be applied in environmental health studies. Researchers could tailor this scheme to fit a variety of research topics.

  8. A Multiscale Survival Process for Modeling Human Activity Patterns.

    Science.gov (United States)

    Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

    2016-01-01

    Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

  9. Degraded character recognition based on gradient pattern

    Science.gov (United States)

    Babu, D. R. Ramesh; Ravishankar, M.; Kumar, Manish; Wadera, Kevin; Raj, Aakash

    2010-02-01

    Degraded character recognition is a challenging problem in the field of Optical Character Recognition (OCR). The performance of an optical character recognition depends upon printed quality of the input documents. Many OCRs have been designed which correctly identifies the fine printed documents. But, very few reported work has been found on the recognition of the degraded documents. The efficiency of the OCRs system decreases if the input image is degraded. In this paper, a novel approach based on gradient pattern for recognizing degraded printed character is proposed. The approach makes use of gradient pattern of an individual character for recognition. Experiments were conducted on character image that is either digitally written or a degraded character extracted from historical documents and the results are found to be satisfactory.

  10. Global control of colored moiré pattern in layered optical structures

    Science.gov (United States)

    Li, Kunyang; Zhou, Yangui; Pan, Di; Ma, Xueyan; Ma, Hongqin; Liang, Haowen; Zhou, Jianying

    2018-05-01

    Accurate description of visual effect of colored moiré pattern caused by layered optical structures consisting of gratings and Fresnel lens is proposed in this work. The colored moiré arising from the periodic and quasi-periodic structures is numerically simulated and experimentally verified. It is found that the visibility of moiré pattern generated by refractive optical elements is related to not only the spatial structures of gratings but also the viewing angles. To effectively control the moiré visibility, two constituting gratings are slightly separated. Such scheme is proved to be effective to globally eliminate moiré pattern for displays containing refractive optical films with quasi-periodic structures.

  11. Automated classification of immunostaining patterns in breast tissue from the human protein atlas.

    Science.gov (United States)

    Swamidoss, Issac Niwas; Kårsnäs, Andreas; Uhlmann, Virginie; Ponnusamy, Palanisamy; Kampf, Caroline; Simonsson, Martin; Wählby, Carolina; Strand, Robin

    2013-01-01

    The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many

  12. Automated classification of immunostaining patterns in breast tissue from the human protein Atlas

    Directory of Open Access Journals (Sweden)

    Issac Niwas Swamidoss

    2013-01-01

    Full Text Available Background: The Human Protein Atlas (HPA is an effort to map the location of all human proteins (http://www.proteinatlas.org/. It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. Materials and Methods: The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM features, complex wavelet co-occurrence matrix (CWCM features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM and linear discriminant analysis (LDA classifier. Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. Results: We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Conclusions: Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for

  13. On the lexical stress patterns of Ilami Kurdish

    Directory of Open Access Journals (Sweden)

    Amir Karimipour

    2017-06-01

    Full Text Available This paper aims to investigate the stress patterns of Ilami Kurdish, a southern variety of Kurdish language, based on the criteria proposed by Kager (1995 and also Hayes (1995 regarding the stress patterns of human languages, including ‘boundedness’, ‘quantity sensitivity’, ‘word headedness’, ‘foot headedness’ and ‘directionality’. After analyzing Ilami Kurdish data and specifying the stress patterns of this dialect of Kurdish, we adopt Optimality Theory framework, which is a modern perspective towards phonology, to show how the optimal candidates are in conformity with the universal phonological constraints in Ilami dialect. All in all, it can be said that Ilami is a right-bounded quantity-sensitive variety as far as monomorphemic words are considered.The next part of the research is devoted to the study of the stress pattern of compound words in Ilami Kurdish. In order to evaluate the stress pattern of these constructions, we use PRAAT software program to analyze the data collected from native speakers of Ilami. Concerning the stress pattern of compounds, it was observed that this is always the rightmost syllable of the final morpheme that bears the strong stress, regardless of the length of word and the number of morphemes. Actually, this tendency always violates the main-left (C universal constraint according to which a clitic group (c is left- headed.

  14. Recognizing lexical and semantic change patterns in evolving life science ontologies to inform mapping adaptation.

    Science.gov (United States)

    Dos Reis, Julio Cesar; Dinh, Duy; Da Silveira, Marcos; Pruski, Cédric; Reynaud-Delaître, Chantal

    2015-03-01

    Mappings established between life science ontologies require significant efforts to maintain them up to date due to the size and frequent evolution of these ontologies. In consequence, automatic methods for applying modifications on mappings are highly demanded. The accuracy of such methods relies on the available description about the evolution of ontologies, especially regarding concepts involved in mappings. However, from one ontology version to another, a further understanding of ontology changes relevant for supporting mapping adaptation is typically lacking. This research work defines a set of change patterns at the level of concept attributes, and proposes original methods to automatically recognize instances of these patterns based on the similarity between attributes denoting the evolving concepts. This investigation evaluates the benefits of the proposed methods and the influence of the recognized change patterns to select the strategies for mapping adaptation. The summary of the findings is as follows: (1) the Precision (>60%) and Recall (>35%) achieved by comparing manually identified change patterns with the automatic ones; (2) a set of potential impact of recognized change patterns on the way mappings is adapted. We found that the detected correlations cover ∼66% of the mapping adaptation actions with a positive impact; and (3) the influence of the similarity coefficient calculated between concept attributes on the performance of the recognition algorithms. The experimental evaluations conducted with real life science ontologies showed the effectiveness of our approach to accurately characterize ontology evolution at the level of concept attributes. This investigation confirmed the relevance of the proposed change patterns to support decisions on mapping adaptation. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. All-fiber maskless lithographic technology to form microcircular interference pattern on Azo polymer film

    Science.gov (United States)

    Kim, Junki; Jung, Yongmin; Oh, Kyunghwan; Chun, Chaemin; Hong, Jeachul; Kim, Dongyu

    2005-03-01

    We report a novel all-fiber, maskless lithograpic technology to form various concentric grating patterns for micro zone plate on azo polymer film. The proposed technology is based on the interference pattern out of the cleaved end of a coreless silica fiber (CSF)-single mode fiber (SMF) composite. The light guided along SMF expands into the CSF segment to generate various circular interference patterns depending on the length of CSF. Interference patterns are experimentally observed when the CSF length is over a certain length and the finer spacing between the concentric rings are obtained for a longer CSF. By using beam propagation method (BPM) package, we could further investigated the concentric interference patterns in terms of intensity distribution and fringe spacing as a function of CSF length. These intereference patterns are directly projected over azo polymer film and their intensity distrubution formed surface relief grating (SRG) patterns. Compared to photoresist films azo polymer layers produce surface relief grating (SRG), where the actual mass of layer is modulated rather than refractive index. The geometric parameters of the CSF length as well as diameter and the spacing between the cleaved end of a CSF and azo polymer film, were found to play a major role to generate various concentric structures. With the demonstration of the circular SRG patterns, we confirmed that the proposed technique do have an ample potential to fabricate micro fresnel zone plate, that could find applications in lens arrays for optical beam formings as well as compact photonic devices.

  16. Evaluating the role of reentrant output-to-input feedback in simultaneous pattern processing

    Energy Technology Data Exchange (ETDEWEB)

    Achler, Tsvi [Los Alamos National Laboratory

    2010-01-01

    Simultaneous Pattern Processing (SPP) is defined as the ability to identify simultaneous-intermixed patterns without isolating them individually (e.g. without separating each pattern in space and processing it individually). Enhanced SPP ability is beneficial for many real-life applications such as scene understanding, separating simultaneous voices, and identifying odorant or taste mixes. The first part of this work identifies how SPP scenarios are problematic to models which train synaptic connections or implement lateral inhibition and quantifies how subtle difficulties lead to complex combinatorial issues. The second part of this work proposes and tests an algorithm motivated by Ubiquitous re-entrant 'output to input' connections found throughout sensory processing regions of the brain. Through these connections the model proposes a dynamic gain mechanism that can provide functionality normally achieved through variable synaptic connections. The re-entrant structure combined with enhanced perfonnance suggests the brain may utilize this configuration for SPP flexibility.

  17. Fast-switching initially-transparent liquid crystal light shutter with crossed patterned electrodes

    Directory of Open Access Journals (Sweden)

    Joon Heo

    2015-04-01

    Full Text Available We propose an initially transparent light shutter using polymer-networked liquid crystals with crossed patterned electrodes. The proposed light shutter is switchable between the transparent and opaque states, and it exhibits a fast response time and a low operating voltage. In the transparent state, the light shutter has high transmittance; in the opaque state, it can block the background image and provides black color. We expect that the proposed light shutter can be applied to see-through displays and smart windows.

  18. A Framework for Mining Actionable Navigation Patterns from In-Store RFID Datasets via Indoor Mapping

    Science.gov (United States)

    Shen, Bin; Zheng, Qiuhua; Li, Xingsen; Xu, Libo

    2015-01-01

    With the quick development of RFID technology and the decreasing prices of RFID devices, RFID is becoming widely used in various intelligent services. Especially in the retail application domain, RFID is increasingly adopted to capture the shopping tracks and behavior of in-store customers. To further enhance the potential of this promising application, in this paper, we propose a unified framework for RFID-based path analytics, which uses both in-store shopping paths and RFID-based purchasing data to mine actionable navigation patterns. Four modules of this framework are discussed, which are: (1) mapping from the physical space to the cyber space, (2) data preprocessing, (3) pattern mining and (4) knowledge understanding and utilization. In the data preprocessing module, the critical problem of how to capture the mainstream shopping path sequences while wiping out unnecessary redundant and repeated details is addressed in detail. To solve this problem, two types of redundant patterns, i.e., loop repeat pattern and palindrome-contained pattern are recognized and the corresponding processing algorithms are proposed. The experimental results show that the redundant pattern filtering functions are effective and scalable. Overall, this work builds a bridge between indoor positioning and advanced data mining technologies, and provides a feasible way to study customers’ shopping behaviors via multi-source RFID data. PMID:25751076

  19. SPEAKING IN TEAMS: MOTIVATING A PATTERN LANGUAGE FOR COLLABORATION

    Directory of Open Access Journals (Sweden)

    Darrin Hicks

    2004-12-01

    Full Text Available Collaborative work is increasing in frequency and importance in business, academia, and communities. The knowledge behind what makes for a successful collaboration is also increasing but is normally focused on only one aspect of collaboration theory. The understanding of how successful collaborations are built is greatly improved by the creation of a unified framework that organises and transfers knowledge and practices. The framework proposed in this paper is the concept of a pattern language for collaboration. The notion of a pattern language was first detailed in 1979 by Christopher Alexander in his book, A Timeless Way of Building [1]. A pattern language consists of a hierarchy of individual patterns that are used to solve problems associated with the parts in the pattern. When developed, researchers can use a pattern language for collaboration as a tool set to evaluate existing collaborations, repair unhealthy collaborations, and build future collaborations. The core concept is that the structure of an environment guides the pattern of events that occurs. A healthy collaboration is more likely to be responsive to the needs of its community and robust enough to overcome unanticipated challenges. The development and evolution of the pattern language is similar to a genetic process in that quality of the overall language emerges from the interaction of individual and complex patterns. The article applies the pattern language to the real world example of twenty eight different collaborations that are part of the Colorado Healthy Communities Initiative to illustrate the application of the pattern language in context. The article closes with recommendations for future development of the language.

  20. Reducing variability in the output of pattern classifiers using histogram shaping

    International Nuclear Information System (INIS)

    Gupta, Shalini; Kan, Chih-Wen; Markey, Mia K.

    2010-01-01

    Purpose: The authors present a novel technique based on histogram shaping to reduce the variability in the output and (sensitivity, specificity) pairs of pattern classifiers with identical ROC curves, but differently distributed outputs. Methods: The authors identify different sources of variability in the output of linear pattern classifiers with identical ROC curves, which also result in classifiers with differently distributed outputs. They theoretically develop a novel technique based on the matching of the histograms of these differently distributed pattern classifier outputs to reduce the variability in their (sensitivity, specificity) pairs at fixed decision thresholds, and to reduce the variability in their actual output values. They empirically demonstrate the efficacy of the proposed technique by means of analyses on the simulated data and real world mammography data. Results: For the simulated data, with three different known sources of variability, and for the real world mammography data with unknown sources of variability, the proposed classifier output calibration technique significantly reduced the variability in the classifiers' (sensitivity, specificity) pairs at fixed decision thresholds. Furthermore, for classifiers with monotonically or approximately monotonically related output variables, the histogram shaping technique also significantly reduced the variability in their actual output values. Conclusions: Classifier output calibration based on histogram shaping can be successfully employed to reduce the variability in the output values and (sensitivity, specificity) pairs of pattern classifiers with identical ROC curves, but differently distributed outputs.

  1. Similarity-dissimilarity plot for visualization of high dimensional data in biomedical pattern classification.

    Science.gov (United States)

    Arif, Muhammad

    2012-06-01

    In pattern classification problems, feature extraction is an important step. Quality of features in discriminating different classes plays an important role in pattern classification problems. In real life, pattern classification may require high dimensional feature space and it is impossible to visualize the feature space if the dimension of feature space is greater than four. In this paper, we have proposed a Similarity-Dissimilarity plot which can project high dimensional space to a two dimensional space while retaining important characteristics required to assess the discrimination quality of the features. Similarity-dissimilarity plot can reveal information about the amount of overlap of features of different classes. Separable data points of different classes will also be visible on the plot which can be classified correctly using appropriate classifier. Hence, approximate classification accuracy can be predicted. Moreover, it is possible to know about whom class the misclassified data points will be confused by the classifier. Outlier data points can also be located on the similarity-dissimilarity plot. Various examples of synthetic data are used to highlight important characteristics of the proposed plot. Some real life examples from biomedical data are also used for the analysis. The proposed plot is independent of number of dimensions of the feature space.

  2. Fluid pipeline system leak detection based on neural network and pattern recognition

    International Nuclear Information System (INIS)

    Tang Xiujia

    1998-01-01

    The mechanism of the stress wave propagation along the pipeline system of NPP, caused by turbulent ejection from pipeline leakage, is researched. A series of characteristic index are described in time domain or frequency domain, and compress numerical algorithm is developed for original data compression. A back propagation neural networks (BPNN) with the input matrix composed by stress wave characteristics in time domain or frequency domain is first proposed to classify various situations of the pipeline, in order to detect the leakage in the fluid flow pipelines. The capability of the new method had been demonstrated by experiments and finally used to design a handy instrument for the pipeline leakage detection. Usually a pipeline system has many inner branches and often in adjusting dynamic condition, it is difficult for traditional pipeline diagnosis facilities to identify the difference between inner pipeline operation and pipeline fault. The author first proposed pipeline wave propagation identification by pattern recognition to diagnose pipeline leak. A series of pattern primitives such as peaks, valleys, horizon lines, capstan peaks, dominant relations, slave relations, etc., are used to extract features of the negative pressure wave form. The context-free grammar of symbolic representation of the negative wave form is used, and a negative wave form parsing system with application to structural pattern recognition based on the representation is first proposed to detect and localize leaks of the fluid pipelines

  3. Environmental impact assessment of the proposed Information Technology Park at Perungudi.

    Science.gov (United States)

    Sharmilaa, G

    2007-10-01

    Environmental impact assessment studies of the proposed Information Technology Park at Perungudi have been carried out. The study involved assessing the existing environmental quality of the proposed site, and predicting impacts and preparing an environmental management plan. Data on the existing quality of water, soil, land use pattern, air, noise and socio-economic details of the proposed project were assessed. The impacts due to the proposed activity were identified and evaluated using the Network Impact Methodology. The water requirement was found to be 3,63,400 L/day. The total wastewater likely to be generated was found to be 2,90,720 L/day. The wastewater will be treated in a sewage treatment plant. The generation of solid waste was assessed to about 500 kg/day. Increase in traffic level was found out by traffic survey. The socio-economic environment will have a positive impact from the proposed project. An Environmental Management Plan was prepared which includes the mitigation measures for improving the eco-profile of the study area.

  4. Technical Reviews on Pattern Recognition in Process Analytical Technology

    International Nuclear Information System (INIS)

    Kim, Jong Yun; Choi, Yong Suk; Ji, Sun Kyung; Park, Yong Joon; Song, Kyu Seok; Jung, Sung Hee

    2008-12-01

    Pattern recognition is one of the first and the most widely adopted chemometric tools among many active research area in chemometrics such as design of experiment(DoE), pattern recognition, multivariate calibration, signal processing. Pattern recognition has been used to identify the origin of a wine and the time of year that the vine was grown by using chromatography, cause of fire by using GC/MS chromatography, detection of explosives and land mines, cargo and luggage inspection in seaports and airports by using a prompt gamma-ray activation analysis, and source apportionment of environmental pollutant by using a stable isotope ratio mass spectrometry. Recently, pattern recognition has been taken into account as a major chemometric tool in the so-called 'process analytical technology (PAT)', which is a newly-developed concept in the area of process analytics proposed by US Food and Drug Administration (US FDA). For instance, identification of raw material by using a pattern recognition analysis plays an important role for the effective quality control of the production process. Recently, pattern recognition technique has been used to identify the spatial distribution and uniformity of the active ingredients present in the product such as tablet by transforming the chemical data into the visual information

  5. Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

    Science.gov (United States)

    Khoshahval, S.; Farnaghi, M.; Taleai, M.

    2017-09-01

    Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user's visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users' behaviour in a system and can be utilized in various location-based applications.

  6. Crossover patterning by the beam-film model: analysis and implications.

    Directory of Open Access Journals (Sweden)

    Liangran Zhang

    2014-01-01

    Full Text Available Crossing-over is a central feature of meiosis. Meiotic crossover (CO sites are spatially patterned along chromosomes. CO-designation at one position disfavors subsequent CO-designation(s nearby, as described by the classical phenomenon of CO interference. If multiple designations occur, COs tend to be evenly spaced. We have previously proposed a mechanical model by which CO patterning could occur. The central feature of a mechanical mechanism is that communication along the chromosomes, as required for CO interference, can occur by redistribution of mechanical stress. Here we further explore the nature of the beam-film model, its ability to quantitatively explain CO patterns in detail in several organisms, and its implications for three important patterning-related phenomena: CO homeostasis, the fact that the level of zero-CO bivalents can be low (the "obligatory CO", and the occurrence of non-interfering COs. Relationships to other models are discussed.

  7. Machine Learning of the Reactor Core Loading Pattern Critical Parameters

    Directory of Open Access Journals (Sweden)

    Krešimir Trontl

    2008-01-01

    Full Text Available The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR, which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy.

  8. Machine Learning of the Reactor Core Loading Pattern Critical Parameters

    International Nuclear Information System (INIS)

    Trontl, K.; Pevec, D.; Smuc, T.

    2008-01-01

    The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR), which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy

  9. Ontogenetic patterns in the dreams of women across the lifespan.

    Science.gov (United States)

    Dale, Allyson; Lortie-Lussier, Monique; De Koninck, Joseph

    2015-12-01

    The present study supports and extends previous research on the developmental differences in women's dreams across the lifespan. The participants included 75 Canadian women in each of 5 age groups from adolescence to old age including 12-17, 18-24, 25-39, 40-64, and 65-85, totaling 375 women. One dream per participant was scored by two independent judges using the method of content analysis. Trend analysis was used to determine the ontogenetic pattern of the dream content categories. Results demonstrated significant ontogenetic decreases (linear trends) for female and familiar characters, activities, aggression, and friendliness. These patterns of dream imagery reflect the waking developmental patterns as proposed by social theories and recognized features of aging as postulated by the continuity hypothesis. Limitations and suggestions for future research including the examining of developmental patterns in the dreams of males are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. High efficient OLED displays prepared with the air-gapped bridges on quantum dot patterns for optical recycling

    Science.gov (United States)

    Kim, Hyo-Jun; Shin, Min-Ho; Kim, Joo-Suc; Kim, Se-Eun; Kim, Young-Joo

    2017-02-01

    An optically efficient structure was proposed and fabricated to realize high brightness organic light emitting diode (OLED) displays based on a white OLED prepared with the air-gapped bridges on the quantum dot (QD) patterns. Compared with a conventional white OLED display, in our experiments, the optical intensity of the proposed OLED display shows the enhancement of 58.2% in the red color and 16.8% in the green color after applying the air-gapped bridge structure on QD patterns of 20 wt% concentration. This enhancement comes from the two facts that the QD patterns downconvert unnecessary blue or blue/green light to the required green or red light and the air-gapped bridges increase the color conversion efficiency of QDs by optical recycling using total internal reflection (TIR) at the interface. In addition, the color gamut of the proposed OLED display increases from 65.5 to 75.9% (NTSC x, y ratio) due to the narrow emission spectra of QDs.

  11. Horses help to maintain CERN's forests

    CERN Multimedia

    François Briard

    2016-01-01

    On the initiative of the Office National des Forêts, France’s forestry commission, horses are helping to remove trees cut down in CERN’s forests.   The CERN site covers 625 hectares, of which around 200 are fenced sites used for CERN’s research activities. The rest of the land consists of fields rented out to farmers and about 90 hectares of forests, mainly in France and managed by the French forestry commission, the Office National des Forêts (ONF), under an agreement with CERN signed in 2010. The upkeep of CERN’s forests requires regular maintenance work, which includes thinning out seedlings, selecting the strongest saplings and harvesting mature trees. This June, the ONF has decided to involve horses in the removal of felled trees from CERN’s woods in Prévessin.  As Florent Daloz, the logger entrusted with this activity by the ONF, explains, the use of horses to haul timber completely died out i...

  12. Coherent patterning of matter waves with subwavelength localization

    International Nuclear Information System (INIS)

    Mompart, J.; Ahufinger, V.; Birkl, G.

    2009-01-01

    We propose the subwavelength localization via adiabatic passage (SLAP) technique to coherently achieve state-selective patterning of matter waves well beyond the diffraction limit. The SLAP technique consists in coupling two partially overlapping and spatially structured laser fields to three internal levels of the matter wave yielding state-selective localization at those positions where the adiabatic passage process does not occur. We show that by means of this technique matter wave localization down to the single nanometer scale can be achieved. We analyze in detail the potential implementation of the SLAP technique for nanolithography with an atomic beam of metastable Ne* and for coherent patterning of a two-component 87 Rb Bose-Einstein condensate.

  13. Reconstruction of Eroded and Visually Complicated Archaeological Geometric Patterns: Minaret Choli, Iraq

    Directory of Open Access Journals (Sweden)

    Rima Al Ajlouni

    2011-12-01

    Full Text Available Visually complicated patterns can be found in many cultural heritages of the world. Islamic geometric patterns present us with one example of such visually complicated archaeological ornaments. As long-lived artifacts, these patterns have gone through many phases of construction, damage, and repair and are constantly subject to erosion and vandalism. The task of reconstructing these visually complicated ornaments faces many practical challenges. The main challenge is posed by the fact that archaeological reality often deals with ornaments that are broken, incomplete or hidden. Recognizing faint traces of eroded or missing parts proved to be an extremely difficult task. This is also combined with the need for specialized knowledge about the mathematical rules of patterns’ structure, in order to regenerate the missing data. This paper presents a methodology for reconstructing deteriorated Islamic geometric patterns; to predict the features that are not observed and output a complete reconstructed two-dimension accurate measurable model. The simulation process depends primarily on finding the parameters necessary to predict information, at other locations, based on the relationships embedded in the existing data and in the prior -knowledge of these relations. The aim is to build up from the fragmented data and from the historic and general knowledge, a model of the reconstructed object. The proposed methodology was proven to be successful in capturing the accurate structural geometry of many of the deteriorated ornaments on the Minaret Choli, Iraq. However, in the case of extremely deteriorated samples, the proposed methodology failed to recognize the correct geometry. The conceptual framework proposed by this paper can serve as a platform for developing professional tools for fast and efficient results.

  14. Experimental study on flow pattern and heat transfer of inverted annular flow

    International Nuclear Information System (INIS)

    Takenaka, Nobuyuki; Akagawa, Koji; Fujii, Terushige; Nishida, Koji

    1990-01-01

    Experimental results are presented on flow pattern and heat transfer in the regions from inverted annular flow to dispersed flow in a vertical tube using freon R-113 as a working fluid at atmospheric pressure to discuss the correspondence between them. Axial distributions of heat transfer coefficient are measured and flow patterns are observed. The heat transfer characteristics are divided into three regions and a heat transfer characteristics map is proposed. The flow pattern changes from inverted annular flow (IAF) to dispersed flow (DF) through inverted slug flow (ISF) for lower inlet velocities and through agitated inverted annular flow (AIAF) for higher inlet velocities. A flow pattern map is obtained which corresponds well with the heat transfer characteristic map. (orig.)

  15. Selective deposition contact patterning using atomic layer deposition for the fabrication of crystalline silicon solar cells

    International Nuclear Information System (INIS)

    Cho, Young Joon; Shin, Woong-Chul; Chang, Hyo Sik

    2014-01-01

    Selective deposition contact (SDC) patterning was applied to fabricate the rear side passivation of crystalline silicon (Si) solar cells. By this method, using screen printing for contact patterning and atomic layer deposition for the passivation of Si solar cells with Al 2 O 3 , we produced local contacts without photolithography or any laser-based processes. Passivated emitter and rear-contact solar cells passivated with ozone-based Al 2 O 3 showed, for the SDC process, an up-to-0.7% absolute conversion-efficiency improvement. The results of this experiment indicate that the proposed method is feasible for conversion-efficiency improvement of industrial crystalline Si solar cells. - Highlights: • We propose a local contact formation process. • Local contact forms a screen print and an atomic layer deposited-Al 2 O 3 film. • Ozone-based Al 2 O 3 thin film was selectively deposited onto patterned silicon. • Selective deposition contact patterning method can increase cell-efficiency by 0.7%

  16. Ground level air convection produces frost damage patterns in turfgrass.

    Science.gov (United States)

    Ackerson, Bruce J; Beier, Richard A; Martin, Dennis L

    2015-11-01

    Frost injury patterns are commonly observed on the warm-season turfgrass species bermudagrass (Cynodon species Rich.), zoysiagrass (Zoysia species Willd.), and buffalograss [Bouteloua dactyloides (Nutt.) J.T. Columbus] in cool-temperate and subtropical zones. Qualitative observations of these injury patterns are presented and discussed. A model for the formation of such patterns based on thermal instability and convection of air is presented. The characteristic length scale of the observed frost pattern injury requires a temperature profile that decreases with height from the soil to the turfgrass canopy surface followed by an increase in temperature with height above the turfgrass canopy. This is justified by extending the earth temperature theory to include a turf layer with atmosphere above it. Then the theory for a thermally unstable layer beneath a stable region by Ogura and Kondo is adapted to a turf layer to include different parameter values for pure air, as well as for turf, which is treated as a porous medium. The earlier porous medium model of Thompson and Daniels proposed to explain frost injury patterns is modified to give reasonable agreement with observed patterns.

  17. Ground level air convection produces frost damage patterns in turfgrass

    Science.gov (United States)

    Ackerson, Bruce J.; Beier, Richard A.; Martin, Dennis L.

    2015-11-01

    Frost injury patterns are commonly observed on the warm-season turfgrass species bermudagrass ( Cynodon species Rich.), zoysiagrass ( Zoysia species Willd.), and buffalograss [ Bouteloua dactyloides (Nutt.) J.T. Columbus] in cool-temperate and subtropical zones. Qualitative observations of these injury patterns are presented and discussed. A model for the formation of such patterns based on thermal instability and convection of air is presented. The characteristic length scale of the observed frost pattern injury requires a temperature profile that decreases with height from the soil to the turfgrass canopy surface followed by an increase in temperature with height above the turfgrass canopy. This is justified by extending the earth temperature theory to include a turf layer with atmosphere above it. Then the theory for a thermally unstable layer beneath a stable region by Ogura and Kondo is adapted to a turf layer to include different parameter values for pure air, as well as for turf, which is treated as a porous medium. The earlier porous medium model of Thompson and Daniels proposed to explain frost injury patterns is modified to give reasonable agreement with observed patterns.

  18. A Design Pattern for Decentralised Decision Making

    Science.gov (United States)

    Valentini, Gabriele; Fernández-Oto, Cristian; Dorigo, Marco

    2015-01-01

    The engineering of large-scale decentralised systems requires sound methodologies to guarantee the attainment of the desired macroscopic system-level behaviour given the microscopic individual-level implementation. While a general-purpose methodology is currently out of reach, specific solutions can be given to broad classes of problems by means of well-conceived design patterns. We propose a design pattern for collective decision making grounded on experimental/theoretical studies of the nest-site selection behaviour observed in honeybee swarms (Apis mellifera). The way in which honeybee swarms arrive at consensus is fairly well-understood at the macroscopic level. We provide formal guidelines for the microscopic implementation of collective decisions to quantitatively match the macroscopic predictions. We discuss implementation strategies based on both homogeneous and heterogeneous multiagent systems, and we provide means to deal with spatial and topological factors that have a bearing on the micro-macro link. Finally, we exploit the design pattern in two case studies that showcase the viability of the approach. Besides engineering, such a design pattern can prove useful for a deeper understanding of decision making in natural systems thanks to the inclusion of individual heterogeneities and spatial factors, which are often disregarded in theoretical modelling. PMID:26496359

  19. Spatial patterns of correlated scale size and scale color in relation to color pattern elements in butterfly wings.

    Science.gov (United States)

    Iwata, Masaki; Otaki, Joji M

    2016-02-01

    Complex butterfly wing color patterns are coordinated throughout a wing by unknown mechanisms that provide undifferentiated immature scale cells with positional information for scale color. Because there is a reasonable level of correspondence between the color pattern element and scale size at least in Junonia orithya and Junonia oenone, a single morphogenic signal may contain positional information for both color and size. However, this color-size relationship has not been demonstrated in other species of the family Nymphalidae. Here, we investigated the distribution patterns of scale size in relation to color pattern elements on the hindwings of the peacock pansy butterfly Junonia almana, together with other nymphalid butterflies, Vanessa indica and Danaus chrysippus. In these species, we observed a general decrease in scale size from the basal to the distal areas, although the size gradient was small in D. chrysippus. Scales of dark color in color pattern elements, including eyespot black rings, parafocal elements, and submarginal bands, were larger than those of their surroundings. Within an eyespot, the largest scales were found at the focal white area, although there were exceptional cases. Similarly, ectopic eyespots that were induced by physical damage on the J. almana background area had larger scales than in the surrounding area. These results are consistent with the previous finding that scale color and size coordinate to form color pattern elements. We propose a ploidy hypothesis to explain the color-size relationship in which the putative morphogenic signal induces the polyploidization (genome amplification) of immature scale cells and that the degrees of ploidy (gene dosage) determine scale color and scale size simultaneously in butterfly wings. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. A Partial Join Approach for Mining Co-Location Patterns: A Summary of Results

    National Research Council Canada - National Science Library

    Yoo, Jin S; Shekhar, Shashi

    2005-01-01

    .... They propose a novel partial-join approach for mining co-location patterns efficiently. It transactionizes continuous spatial data while keeping track of the spatial information not modeled by transactions...

  1. Spurious Seasonality Detection: A Non-Parametric Test Proposal

    Directory of Open Access Journals (Sweden)

    Aurelio F. Bariviera

    2018-01-01

    Full Text Available This paper offers a general and comprehensive definition of the day-of-the-week effect. Using symbolic dynamics, we develop a unique test based on ordinal patterns in order to detect it. This test uncovers the fact that the so-called “day-of-the-week” effect is partly an artifact of the hidden correlation structure of the data. We present simulations based on artificial time series as well. While time series generated with long memory are prone to exhibit daily seasonality, pure white noise signals exhibit no pattern preference. Since ours is a non-parametric test, it requires no assumptions about the distribution of returns, so that it could be a practical alternative to conventional econometric tests. We also made an exhaustive application of the here-proposed technique to 83 stock indexes around the world. Finally, the paper highlights the relevance of symbolic analysis in economic time series studies.

  2. Modifications of center-surround, spot detection and dot-pattern selective operators

    NARCIS (Netherlands)

    Petkov, Nicolai; Visser, Wicher T.

    2005-01-01

    This paper describes modifications of the models of center-surround and dot-pattern selective cells proposed previously. These modifications concern mainly the normalization of the difference of Gaussians (DoG) function used to model center-surround receptive fields, the normalization of

  3. High efficient OLED displays prepared with the air-gapped bridges on quantum dot patterns for optical recycling

    OpenAIRE

    Hyo-Jun Kim; Min-Ho Shin; Joo-Suc Kim; Se-Eun Kim; Young-Joo Kim

    2017-01-01

    An optically efficient structure was proposed and fabricated to realize high brightness organic light emitting diode (OLED) displays based on a white OLED prepared with the air-gapped bridges on the quantum dot (QD) patterns. Compared with a conventional white OLED display, in our experiments, the optical intensity of the proposed OLED display shows the enhancement of 58.2% in the red color and 16.8% in the green color after applying the air-gapped bridge structure on QD patterns of 20?wt% co...

  4. Mining association patterns of drug-interactions using post marketing FDA's spontaneous reporting data.

    Science.gov (United States)

    Ibrahim, Heba; Saad, Amr; Abdo, Amany; Sharaf Eldin, A

    2016-04-01

    Pharmacovigilance (PhV) is an important clinical activity with strong implications for population health and clinical research. The main goal of PhV is the timely detection of adverse drug events (ADEs) that are novel in their clinical nature, severity and/or frequency. Drug interactions (DI) pose an important problem in the development of new drugs and post marketing PhV that contribute to 6-30% of all unexpected ADEs. Therefore, the early detection of DI is vital. Spontaneous reporting systems (SRS) have served as the core data collection system for post marketing PhV since the 1960s. The main objective of our study was to particularly identify signals of DI from SRS. In addition, we are presenting an optimized tailored mining algorithm called "hybrid Apriori". The proposed algorithm is based on an optimized and modified association rule mining (ARM) approach. A hybrid Apriori algorithm has been applied to the SRS of the United States Food and Drug Administration's (U.S. FDA) adverse events reporting system (FAERS) in order to extract significant association patterns of drug interaction-adverse event (DIAE). We have assessed the resulting DIAEs qualitatively and quantitatively using two different triage features: a three-element taxonomy and three performance metrics. These features were applied on two random samples of 100 interacting and 100 non-interacting DIAE patterns. Additionally, we have employed logistic regression (LR) statistic method to quantify the magnitude and direction of interactions in order to test for confounding by co-medication in unknown interacting DIAE patterns. Hybrid Apriori extracted 2933 interacting DIAE patterns (including 1256 serious ones) and 530 non-interacting DIAE patterns. Referring to the current knowledge using four different reliable resources of DI, the results showed that the proposed method can extract signals of serious interacting DIAEs. Various association patterns could be identified based on the relationships among

  5. Assessment of human respiration patterns via noncontact sensing using Doppler multi-radar system.

    Science.gov (United States)

    Gu, Changzhan; Li, Changzhi

    2015-03-16

    Human respiratory patterns at chest and abdomen are associated with both physical and emotional states. Accurate measurement of the respiratory patterns provides an approach to assess and analyze the physical and emotional states of the subject persons. Not many research efforts have been made to wirelessly assess different respiration patterns, largely due to the inaccuracy of the conventional continuous-wave radar sensor to track the original signal pattern of slow respiratory movements. This paper presents the accurate assessment of different respiratory patterns based on noncontact Doppler radar sensing. This paper evaluates the feasibility of accurately monitoring different human respiration patterns via noncontact radar sensing. A 2.4 GHz DC coupled multi-radar system was used for accurate measurement of the complete respiration patterns without any signal distortion. Experiments were carried out in the lab environment to measure the different respiration patterns when the subject person performed natural breathing, chest breathing and diaphragmatic breathing. The experimental results showed that accurate assessment of different respiration patterns is feasible using the proposed noncontact radar sensing technique.

  6. Diagnosis of Tempromandibular Disorders Using Local Binary Patterns.

    Science.gov (United States)

    Haghnegahdar, A A; Kolahi, S; Khojastepour, L; Tajeripour, F

    2018-03-01

    Temporomandibular joint disorder (TMD) might be manifested as structural changes in bone through modification, adaptation or direct destruction. We propose to use Local Binary Pattern (LBP) characteristics and histogram-oriented gradients on the recorded images as a diagnostic tool in TMD assessment. CBCT images of 66 patients (132 joints) with TMD and 66 normal cases (132 joints) were collected and 2 coronal cut prepared from each condyle, although images were limited to head of mandibular condyle. In order to extract features of images, first we use LBP and then histogram of oriented gradients. To reduce dimensionality, the linear algebra Singular Value Decomposition (SVD) is applied to the feature vectors matrix of all images. For evaluation, we used K nearest neighbor (K-NN), Support Vector Machine, Naïve Bayesian and Random Forest classifiers. We used Receiver Operating Characteristic (ROC) to evaluate the hypothesis. K nearest neighbor classifier achieves a very good accuracy (0.9242), moreover, it has desirable sensitivity (0.9470) and specificity (0.9015) results, when other classifiers have lower accuracy, sensitivity and specificity. We proposed a fully automatic approach to detect TMD using image processing techniques based on local binary patterns and feature extraction. K-NN has been the best classifier for our experiments in detecting patients from healthy individuals, by 92.42% accuracy, 94.70% sensitivity and 90.15% specificity. The proposed method can help automatically diagnose TMD at its initial stages.

  7. Stochastic Turing Patterns: Analysis of Compartment-Based Approaches

    KAUST Repository

    Cao, Yang; Erban, Radek

    2014-01-01

    © 2014, Society for Mathematical Biology. Turing patterns can be observed in reaction-diffusion systems where chemical species have different diffusion constants. In recent years, several studies investigated the effects of noise on Turing patterns and showed that the parameter regimes, for which stochastic Turing patterns are observed, can be larger than the parameter regimes predicted by deterministic models, which are written in terms of partial differential equations (PDEs) for species concentrations. A common stochastic reaction-diffusion approach is written in terms of compartment-based (lattice-based) models, where the domain of interest is divided into artificial compartments and the number of molecules in each compartment is simulated. In this paper, the dependence of stochastic Turing patterns on the compartment size is investigated. It has previously been shown (for relatively simpler systems) that a modeler should not choose compartment sizes which are too small or too large, and that the optimal compartment size depends on the diffusion constant. Taking these results into account, we propose and study a compartment-based model of Turing patterns where each chemical species is described using a different set of compartments. It is shown that the parameter regions where spatial patterns form are different from the regions obtained by classical deterministic PDE-based models, but they are also different from the results obtained for the stochastic reaction-diffusion models which use a single set of compartments for all chemical species. In particular, it is argued that some previously reported results on the effect of noise on Turing patterns in biological systems need to be reinterpreted.

  8. Stochastic Turing Patterns: Analysis of Compartment-Based Approaches

    KAUST Repository

    Cao, Yang

    2014-11-25

    © 2014, Society for Mathematical Biology. Turing patterns can be observed in reaction-diffusion systems where chemical species have different diffusion constants. In recent years, several studies investigated the effects of noise on Turing patterns and showed that the parameter regimes, for which stochastic Turing patterns are observed, can be larger than the parameter regimes predicted by deterministic models, which are written in terms of partial differential equations (PDEs) for species concentrations. A common stochastic reaction-diffusion approach is written in terms of compartment-based (lattice-based) models, where the domain of interest is divided into artificial compartments and the number of molecules in each compartment is simulated. In this paper, the dependence of stochastic Turing patterns on the compartment size is investigated. It has previously been shown (for relatively simpler systems) that a modeler should not choose compartment sizes which are too small or too large, and that the optimal compartment size depends on the diffusion constant. Taking these results into account, we propose and study a compartment-based model of Turing patterns where each chemical species is described using a different set of compartments. It is shown that the parameter regions where spatial patterns form are different from the regions obtained by classical deterministic PDE-based models, but they are also different from the results obtained for the stochastic reaction-diffusion models which use a single set of compartments for all chemical species. In particular, it is argued that some previously reported results on the effect of noise on Turing patterns in biological systems need to be reinterpreted.

  9. Change detection for synthetic aperture radar images based on pattern and intensity distinctiveness analysis

    Science.gov (United States)

    Wang, Xiao; Gao, Feng; Dong, Junyu; Qi, Qiang

    2018-04-01

    Synthetic aperture radar (SAR) image is independent on atmospheric conditions, and it is the ideal image source for change detection. Existing methods directly analysis all the regions in the speckle noise contaminated difference image. The performance of these methods is easily affected by small noisy regions. In this paper, we proposed a novel change detection framework for saliency-guided change detection based on pattern and intensity distinctiveness analysis. The saliency analysis step can remove small noisy regions, and therefore makes the proposed method more robust to the speckle noise. In the proposed method, the log-ratio operator is first utilized to obtain a difference image (DI). Then, the saliency detection method based on pattern and intensity distinctiveness analysis is utilized to obtain the changed region candidates. Finally, principal component analysis and k-means clustering are employed to analysis pixels in the changed region candidates. Thus, the final change map can be obtained by classifying these pixels into changed or unchanged class. The experiment results on two real SAR images datasets have demonstrated the effectiveness of the proposed method.

  10. Design Support System for Coloring Illustrations by Using the Colors Preferred by a User as Determined from the Hue Patterns of Illustrations Prepared by that User

    Science.gov (United States)

    Fukai, Hironobu; Mitsukura, Yasue

    We propose a new design support system that can color illustrations according to a person's color preferences that are determined on the basis of the color patterns of illustrations prepared by that person. Recently, many design tools for promoting free design have been developed. However, preferences for various colors differ depending on individual personality. Therefore, a system that can automatically color various designs on the basis of human preference is required. In this study, we propose an automatic modeling system that can be used to model illustrations. To verify the effectiveness of the proposed system, we simulate a coloring design experiment to determine the color patterns preferred by some subjects by using various design data. By using the design data, we determine each subjects preferred color pattern, and send feedback on these individual color patterns to the proposed system.

  11. Laban Movement Analysis towards Behavior Patterns

    Science.gov (United States)

    Santos, Luís; Dias, Jorge

    This work presents a study about the use of Laban Movement Analysis (LMA) as a robust tool to describe human basic behavior patterns, to be applied in human-machine interaction. LMA is a language used to describe and annotate dancing movements and is divided in components [1]: Body, Space, Shape and Effort. Despite its general framework is widely used in physical and mental therapy [2], it has found little application in the engineering domain. Rett J. [3] proposed to implement LMA using Bayesian Networks. However LMA component models have not yet been fully implemented. A study on how to approach behavior using LMA is presented. Behavior is a complex feature and movement chain, but we believe that most basic behavior primitives can be discretized in simple features. Correctly identifying Laban parameters and the movements the authors feel that good patterns can be found within a specific set of basic behavior semantics.

  12. EFFECT OF COST INCREMENT DISTRIBUTION PATTERNS ON THE PERFORMANCE OF JIT SUPPLY CHAIN

    Directory of Open Access Journals (Sweden)

    Ayu Bidiawati J.R

    2008-01-01

    Full Text Available Cost is an important consideration in supply chain (SC optimisation. This is due to emphasis placed on cost reduction in order to optimise profit. Some researchers use cost as one of their performance measures and others propose ways of accurately calculating cost. As product moves across SC, the product cost also increases. This paper studied the effect of cost increment distribution patterns on the performance of a JIT Supply Chain. In particular, it is necessary to know if inventory allocation across SC needs to be modified to accommodate different cost increment distribution patterns. It was found that funnel is still the best card distribution pattern for JIT-SC regardless the cost increment distribution patterns used.

  13. Pattern Of Skin Prick Allergy Test Results In Enugu | Mgbor ...

    African Journals Online (AJOL)

    In this study we report on pattern of allergy prick skin test results found among atopic patients attending the department of otorhinolargngology of the University of Nigeria Teaching Hospital Enugu and Hansa Clinics, Enugu and propose ways of minimizing the exposure of the population to allergens. Material and method

  14. The Effect of Family Communication Patterns on Adopted Adolescent Adjustment

    Science.gov (United States)

    Rueter, Martha A.; Koerner, Ascan F.

    2008-01-01

    Adoption and family communication both affect adolescent adjustment. We proposed that adoption status and family communication interact such that adopted adolescents in families with certain communication patterns are at greater risk for adjustment problems. We tested this hypothesis using a community-based sample of 384 adoptive and 208…

  15. Constructing and predicting solitary pattern solutions for nonlinear time-fractional dispersive partial differential equations

    Science.gov (United States)

    Arqub, Omar Abu; El-Ajou, Ahmad; Momani, Shaher

    2015-07-01

    Building fractional mathematical models for specific phenomena and developing numerical or analytical solutions for these fractional mathematical models are crucial issues in mathematics, physics, and engineering. In this work, a new analytical technique for constructing and predicting solitary pattern solutions of time-fractional dispersive partial differential equations is proposed based on the generalized Taylor series formula and residual error function. The new approach provides solutions in the form of a rapidly convergent series with easily computable components using symbolic computation software. For method evaluation and validation, the proposed technique was applied to three different models and compared with some of the well-known methods. The resultant simulations clearly demonstrate the superiority and potentiality of the proposed technique in terms of the quality performance and accuracy of substructure preservation in the construct, as well as the prediction of solitary pattern solutions for time-fractional dispersive partial differential equations.

  16. Data mining and Pattern Recognizing Models for Identifying Inherited Diseases: Challenges and Implications

    OpenAIRE

    Lahiru Iddamalgoda; Partha Sarathi Das; Partha Sarathi Das; Achala Aponso; Vijayaraghava Seshadri Sundararajan; Prashanth Suravajhala; Prashanth Suravajhala; Prashanth Suravajhala; Jayaraman K Valadi

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately determining the responsible genetic factors for prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern r...

  17. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications

    OpenAIRE

    Iddamalgoda, Lahiru; Das, Partha S.; Aponso, Achala; Sundararajan, Vijayaraghava S.; Suravajhala, Prashanth; Valadi, Jayaraman K.

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited ...

  18. Hyperspectral image classification based on local binary patterns and PCANet

    Science.gov (United States)

    Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang

    2018-04-01

    Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

  19. Subtyping of Toddlers with ASD Based on Patterns of Social Attention Deficits

    Science.gov (United States)

    2015-10-30

    1 AWARD NUMBER: W81XWH-13-1-0179 TITLE: “Subtyping of Toddlers with ASD Based on Patterns of Social Attention Deficits” PRINCIPAL INVESTIGATOR...SUBTITLE “Subtyping of Toddlers with ASD Based on Patterns of Social Attention Deficits” 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-13-1-0179 5c...proposed project is to elucidate the factors that affect spontaneous dyadic orienting at the earliest stages when ASD can be reliably diagnosed in order

  20. Synchronization stability and pattern selection in a memristive neuronal network

    Science.gov (United States)

    Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

    2017-11-01

    Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

  1. Synchronization stability and pattern selection in a memristive neuronal network.

    Science.gov (United States)

    Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

    2017-11-01

    Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

  2. Applications of evolutionary computation in image processing and pattern recognition

    CERN Document Server

    Cuevas, Erik; Perez-Cisneros, Marco

    2016-01-01

    This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an...

  3. Numerical approaches to model perturbation fire in turing pattern formations

    Science.gov (United States)

    Campagna, R.; Brancaccio, M.; Cuomo, S.; Mazzoleni, S.; Russo, L.; Siettos, K.; Giannino, F.

    2017-11-01

    Turing patterns were observed in chemical, physical and biological systems described by coupled reaction-diffusion equations. Several models have been formulated proposing the water as the causal mechanism of vegetation pattern formation, but this isn't an exhaustive hypothesis in some natural environments. An alternative explanation has been related to the plant-soil negative feedback. In Marasco et al. [1] the authors explored the hypothesis that both mechanisms contribute in the formation of regular and irregular vegetation patterns. The mathematical model consists in three partial differential equations (PDEs) that take into account for a dynamic balance between biomass, water and toxic compounds. A numerical approach is mandatory also to investigate on the predictions of this kind of models. In this paper we start from the mathematical model described in [1], set the model parameters such that the biomass reaches a stable spatial pattern (spots) and present preliminary studies about the occurrence of perturbing events, such as wildfire, that can affect the regularity of the biomass configuration.

  4. A genetic programming approach for Burkholderia Pseudomallei diagnostic pattern discovery

    Science.gov (United States)

    Yang, Zheng Rong; Lertmemongkolchai, Ganjana; Tan, Gladys; Felgner, Philip L.; Titball, Richard

    2009-01-01

    Motivation: Finding diagnostic patterns for fighting diseases like Burkholderia pseudomallei using biomarkers involves two key issues. First, exhausting all subsets of testable biomarkers (antigens in this context) to find a best one is computationally infeasible. Therefore, a proper optimization approach like evolutionary computation should be investigated. Second, a properly selected function of the antigens as the diagnostic pattern which is commonly unknown is a key to the diagnostic accuracy and the diagnostic effectiveness in clinical use. Results: A conversion function is proposed to convert serum tests of antigens on patients to binary values based on which Boolean functions as the diagnostic patterns are developed. A genetic programming approach is designed for optimizing the diagnostic patterns in terms of their accuracy and effectiveness. During optimization, it is aimed to maximize the coverage (the rate of positive response to antigens) in the infected patients and minimize the coverage in the non-infected patients while maintaining the fewest number of testable antigens used in the Boolean functions as possible. The final coverage in the infected patients is 96.55% using 17 of 215 (7.4%) antigens with zero coverage in the non-infected patients. Among these 17 antigens, BPSL2697 is the most frequently selected one for the diagnosis of Burkholderia Pseudomallei. The approach has been evaluated using both the cross-validation and the Jack–knife simulation methods with the prediction accuracy as 93% and 92%, respectively. A novel approach is also proposed in this study to evaluate a model with binary data using ROC analysis. Contact: z.r.yang@ex.ac.uk PMID:19561021

  5. LOCAL LINE BINARY PATTERN FOR FEATURE EXTRACTION ON PALM VEIN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Jayanti Yusmah Sari

    2015-08-01

    Full Text Available In recent years, palm vein recognition has been studied to overcome problems in conventional systems in biometrics technology (finger print, face, and iris. Those problems in biometrics includes convenience and performance. However, due to the clarity of the palm vein image, the veins could not be segmented properly. To overcome this problem, we propose a palm vein recognition system using Local Line Binary Pattern (LLBP method that can extract robust features from the palm vein images that has unclear veins. LLBP is an advanced method of Local Binary Pattern (LBP, a texture descriptor based on the gray level comparison of a neighborhood of pixels. There are four major steps in this paper, Region of Interest (ROI detection, image preprocessing, features extraction using LLBP method, and matching using Fuzzy k-NN classifier. The proposed method was applied on the CASIA Multi-Spectral Image Database. Experimental results showed that the proposed method using LLBP has a good performance with recognition accuracy of 97.3%. In the future, experiments will be conducted to observe which parameter that could affect processing time and recognition accuracy of LLBP is needed

  6. Plasma-Sprayed Titanium Patterns for Enhancing Early Cell Responses

    Science.gov (United States)

    Shi, Yunqi; Xie, Youtao; Pan, Houhua; Zheng, Xuebin; Huang, Liping; Ji, Fang; Li, Kai

    2016-06-01

    Titanium coating has been widely used as a biocompatible metal in biomedical applications. However, the early cell responses and long-term fixation of titanium implants are not satisfied. To obviate these defects, in this paper, micro-post arrays with various widths (150-1000 μm) and intervals (100-300 μm) were fabricated on the titanium substrate by template-assisted plasma spraying technology. In vitro cell culture experiments showed that MC3T3-E1 cells exhibited significantly higher osteogenic differentiation as well as slightly improved adhesion and proliferation on the micro-patterned coatings compared with the traditional one. The cell number on the pattern with 1000 µm width reached 130% after 6 days of incubation, and the expressions of osteopontin (OPN) as well as osteocalcin (OC) were doubled. No obvious difference was found in cell adhesion on various size patterns. The present micro-patterned coatings proposed a new modification method for the traditional plasma spraying technology to enhance the early cell responses and convenience for the bone in-growth.

  7. Differential and Cooperative Cell Adhesion Regulates Cellular Pattern in Sensory Epithelia.

    Science.gov (United States)

    Togashi, Hideru

    2016-01-01

    Animal tissues are composed of multiple cell types arranged in complex and elaborate patterns. In sensory epithelia, including the auditory epithelium and olfactory epithelium, different types of cells are arranged in unique mosaic patterns. These mosaic patterns are evolutionarily conserved, and are thought to be important for hearing and olfaction. Recent progress has provided accumulating evidence that the cellular pattern formation in epithelia involves cell rearrangements, movements, and shape changes. These morphogenetic processes are largely mediated by intercellular adhesion systems. Differential adhesion and cortical tension have been proposed to promote cell rearrangements. Many different types of cells in tissues express various types of cell adhesion molecules. Although cooperative mechanisms between multiple adhesive systems are likely to contribute to the production of complex cell patterns, our current understanding of the cooperative roles between multiple adhesion systems is insufficient to entirely explain the complex mechanisms underlying cellular patterning. Recent studies have revealed that nectins, in cooperation with cadherins, are crucial for the mosaic cellular patterning in sensory organs. The nectin and cadherin systems are interacted with one another, and these interactions provide cells with differential adhesive affinities for complex cellular pattern formations in sensory epithelia, which cannot be achieved by a single mechanism.

  8. Automated effect-specific mammographic pattern measures

    DEFF Research Database (Denmark)

    Raundahl, Jakob; Loog, Marco; Pettersen, Paola

    2008-01-01

    We investigate the possibility to develop methodologies for assessing effect specific structural changes of the breast tissue using a general statistical machine learning framework. We present an approach of obtaining objective mammographic pattern measures quantifying a specific biological effect......, such as hormone replacement therapy (HRT). We compare results using this approach to using standard density measures. We show that the proposed method can quantify both age related effects and effects caused by HRT. Age effects are significantly detected by our method where standard methodologies fail...

  9. Pattern formation in optical resonators

    International Nuclear Information System (INIS)

    Weiss, C O; Larionova, Ye

    2007-01-01

    We review pattern formation in optical resonators. The emphasis is on 'particle-like' structures such as vortices or spatial solitons. On the one hand, similarities impose themselves with other fields of physics (condensed matter, phase transitions, particle physics, fluds/super fluids). On the other hand the feedback is led by the resonator mirrors to bi- and multi-stability of the spatial field structure, which is the basic ingredient for optical information processing. The spatial dimension or the 'parallelism' is the strength of optics compared to electronics (and will have to be employed to fully use the advantages optics offers in information processing). But even in the 'serial' processing tasks of telecoms (e.g. information buffering) spatial resonator solitons can do better than the schemes proposed so far-including 'slow light'. Pattern formation in optical resonators will likely be the key to brain-like information processing like cognition, learning and association; to complement the precise but limited algorithmic capabilities of electronic processing. But even in the short term it will be useful for solving serial optical processing problems. The prospects for technical uses of pattern formation in resonators are one motivation for this research. The fundamental similarities with other fields of physics, on the other hand, inspire transfer of concepts between fields; something that has always proven fruitful for gaining deeper insights or for solving technical problems

  10. The use of load patterns to identify residential customers in a chosen area

    Energy Technology Data Exchange (ETDEWEB)

    Michalik, G.; Lech, M.; Mielczarski, W. [Monash Univ., Clayton, VIC (Australia). Centre for Electrical Power Engineering

    1995-12-31

    Information on customers` categories and energy use patterns is a basis for the development of any Demand Side Management program. This paper presents an application of energy consumption patterns to identification of customers in a chosen area. Customers have been segmented into four main categories with six subgroups in each category. A total pattern of energy use can be achieved by the combination of characteristic patterns for each subgroup with multiplication by the number of customers in each subgroup. The paper proposes to apply characteristic patterns developed and nonlinear programming techniques to identify customers in a chosen area from patterns measured at distribution feeders. The procedure can be applied as an alternative to surveys and measurements at the mains of particular customers but may also be implemented as an accompanying system to verify results from other procedures of customer identification. (author). 1 tab., 6 figs., 4 refs.

  11. Two-dimensional wavelet transform for reliability-guided phase unwrapping in optical fringe pattern analysis.

    Science.gov (United States)

    Li, Sikun; Wang, Xiangzhao; Su, Xianyu; Tang, Feng

    2012-04-20

    This paper theoretically discusses modulus of two-dimensional (2D) wavelet transform (WT) coefficients, calculated by using two frequently used 2D daughter wavelet definitions, in an optical fringe pattern analysis. The discussion shows that neither is good enough to represent the reliability of the phase data. The differences between the two frequently used 2D daughter wavelet definitions in the performance of 2D WT also are discussed. We propose a new 2D daughter wavelet definition for reliability-guided phase unwrapping of optical fringe pattern. The modulus of the advanced 2D WT coefficients, obtained by using a daughter wavelet under this new daughter wavelet definition, includes not only modulation information but also local frequency information of the deformed fringe pattern. Therefore, it can be treated as a good parameter that represents the reliability of the retrieved phase data. Computer simulation and experimentation show the validity of the proposed method.

  12. Proposed FPGA based tracking for a Level-1 track trigger at CMS for the HL-LHC

    CERN Document Server

    Pozzobon, Nicola

    2014-01-01

    The High Luminosity LHC (HL-LHC) is expected to deliver a luminosity in excess of $5\\times10^{34}$ cm$^{-2}$/s. The high event rate places stringent requirements on the trigger system. A key component of the CMS upgrade for the HL-LHC is a track trigger system which will identify tracks with transverse momenta above 2 GeV already at the first-level trigger within 5 $\\mu$s. This presentation will discuss a proposed track finding and fitting based on the tracklet based approach implemented on FPGAs. Tracklets are formed from pairs of hits in nearby layers in the detector and used in a road search. Summary Fast pattern recognition in Silicon trackers for triggering has often made use of Associative Memories for the pattern recognition step. We propose an alternative approach to solving the pattern recognition and track fitting problem for the upgraded CMS tracker for the HL-LHC operation. We make use of the trigger primitives,stubs, from the tracker. The stubs are formed from pairs of hits in sensors separated r...

  13. A Framework for Mining Actionable Navigation Patterns from In-Store RFID Datasets via Indoor Mapping

    Directory of Open Access Journals (Sweden)

    Bin Shen

    2015-03-01

    Full Text Available With the quick development of RFID technology and the decreasing prices of RFID devices, RFID is becoming widely used in various intelligent services. Especially in the retail application domain, RFID is increasingly adopted to capture the shopping tracks and behavior of in-store customers. To further enhance the potential of this promising application, in this paper, we propose a unified framework for RFID-based path analytics, which uses both in-store shopping paths and RFID-based purchasing data to mine actionable navigation patterns. Four modules of this framework are discussed, which are: (1 mapping from the physical space to the cyber space, (2 data preprocessing, (3 pattern mining and (4 knowledge understanding and utilization. In the data preprocessing module, the critical problem of how to capture the mainstream shopping path sequences while wiping out unnecessary redundant and repeated details is addressed in detail. To solve this problem, two types of redundant patterns, i.e., loop repeat pattern and palindrome-contained pattern are recognized and the corresponding processing algorithms are proposed. The experimental results show that the redundant pattern filtering functions are effective and scalable. Overall, this work builds a bridge between indoor positioning and advanced data mining technologies, and provides a feasible way to study customers’ shopping behaviors via multi-source RFID data.

  14. Mutual Coupling Effects on Pattern Diversity Antennas for MIMO Femtocells

    Directory of Open Access Journals (Sweden)

    Yue Gao

    2010-01-01

    Full Text Available Diversity antennas play an important role in wireless communications. However, mutual coupling between multiple ports of a diversity antenna has significant effects on wireless radio links and channel capacity. In this paper, dual-port pattern diversity antennas for femtocell applications are proposed to cover GSM1800, UMTS, and WLAN frequency bands. The channel capacities of the proposed antennas and two ideal dipoles with different mutual coupling levels are investigated in an indoor environment. The relation between mutual coupling and channel capacity is observed through investigations of these antennas.

  15. Transfer of Direct and Moiré Patterns by Reactive Ion Etching Through Ex Situ Fabricated Nanoporous Polymer Masks

    DEFF Research Database (Denmark)

    Shvets, Violetta; Hentschel, Thomas; Schulte, Lars

    2015-01-01

    modification, which are essential prerequisites for the conventional procedure of block copolymer directed self-assembly. The demonstrated elliptic and moire pattern transfers prove that the proposed ex situ procedure allows us to realize nanolithographic patterns that are difficult to realize...

  16. Patterns recognition of electric brain activity using artificial neural networks

    Science.gov (United States)

    Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

    2017-04-01

    An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

  17. Microtransfer printing of metal ink patterns onto plastic substrates utilizing an adhesion-controlled polymeric donor layer

    International Nuclear Information System (INIS)

    Park, Ji-Sub; Choi, Jun-Chan; Park, Min-Kyu; Bae, Jeong Min; Bae, Jin-Hyuk; Kim, Hak-Rin

    2016-01-01

    We propose a method for transfer-printed electrode patterns onto flexible/plastic substrates, specifically intended for metal ink that requires a high sintering temperature. Typically, metal-ink-based electrodes cannot be picked up for microtransfer printing because the adhesion between the electrodes and the donor substrate greatly increases after the sintering process due to the binding materials. We introduced a polymeric donor layer between the printed electrodes and the donor substrate and effectively reduced the adhesion between the Ag pattern and the polymeric donor layer by controlling the interfacial contact area. After completing a wet-etching process for the polymeric donor layer, we obtained Ag patterns supported on the fine polymeric anchor structures; the Ag patterns could be picked up onto the stamp surface even after the sintering process by utilizing the viscoelastic properties of the elastomeric stamp with a pick-up velocity control. The proposed method enables highly conductive metal-ink-based electrode patterns to be applied on thermally weak plastic substrates via an all-solution process. Metal electrodes transferred onto a film showed superior electrical and mechanical stability under the bending stress test required for use in printed flexible electronics. (paper)

  18. A Model of Bus Bunching under Reliability-based Passenger Arrival Patterns

    OpenAIRE

    Fonzone, Achille; Schmöcker, Jan-Dirk; Liu, Ronghui

    2015-01-01

    If bus service departure times are not completely unknown to the passengers, non-uniform passenger arrival patterns can be expected. We propose that passengers decide their arrival time at stops based on a continuous logit model that considers the risk of missing services. Expected passenger waiting times are derived in a bus system that allows also for overtaking between bus services. We then propose an algorithm to derive the dwell time of subsequent buses serving a stop in order to illustr...

  19. Color Mixing Correction for Post-printed Patterns on Colored Background Using Modified Particle Density Model

    OpenAIRE

    Suwa , Misako; Fujimoto , Katsuhito

    2006-01-01

    http://www.suvisoft.com; Color mixing occurs between background and foreground colors when a pattern is post-printed on a colored area because ink is not completely opaque. This paper proposes a new method for the correction of color mixing in line pattern such as characters and stamps, by using a modified particle density model. Parameters of the color correction can be calculated from two sets of foreground and background colors. By employing this method, the colors of foreground patterns o...

  20. SPATIO-TEMPORAL PATTERN MINING ON TRAJECTORY DATA USING ARM

    Directory of Open Access Journals (Sweden)

    S. Khoshahval

    2017-09-01

    Full Text Available Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user’s visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users’ behaviour in a system and can be utilized in various location-based applications.

  1. Biodiversity patterns along ecological gradients: unifying β-diversity indices.

    Science.gov (United States)

    Szava-Kovats, Robert C; Pärtel, Meelis

    2014-01-01

    Ecologists have developed an abundance of conceptions and mathematical expressions to define β-diversity, the link between local (α) and regional-scale (γ) richness, in order to characterize patterns of biodiversity along ecological (i.e., spatial and environmental) gradients. These patterns are often realized by regression of β-diversity indices against one or more ecological gradients. This practice, however, is subject to two shortcomings that can undermine the validity of the biodiversity patterns. First, many β-diversity indices are constrained to range between fixed lower and upper limits. As such, regression analysis of β-diversity indices against ecological gradients can result in regression curves that extend beyond these mathematical constraints, thus creating an interpretational dilemma. Second, despite being a function of the same measured α- and γ-diversity, the resultant biodiversity pattern depends on the choice of β-diversity index. We propose a simple logistic transformation that rids beta-diversity indices of their mathematical constraints, thus eliminating the possibility of an uninterpretable regression curve. Moreover, this transformation results in identical biodiversity patterns for three commonly used classical beta-diversity indices. As a result, this transformation eliminates the difficulties of both shortcomings, while allowing the researcher to use whichever beta-diversity index deemed most appropriate. We believe this method can help unify the study of biodiversity patterns along ecological gradients.

  2. Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

    Science.gov (United States)

    Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

    2017-09-01

    With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

  3. Patterns of intergenerational mobility of the old and new middle classes

    NARCIS (Netherlands)

    Güveli, Ayse; Luijkx, Ruud; Ganzeboom, Harry B.G.

    2013-01-01

    It has often been proposed that new cleavages have emerged within the middle class. In this paper, we examine the distinction between social and cultural specialists and technocrats, and investigate whether these new and old middle class fractions are differentiated by their patterns of

  4. Understanding the critical challenges of self-aligned octuple patterning

    Science.gov (United States)

    Yu, Ji; Xiao, Wei; Kang, Weiling; Chen, Yijian

    2014-03-01

    In this paper, we present a thorough investigation of self-aligned octuple patterning (SAOP) process characteristics, cost structure, integration challenges, and layout decomposition. The statistical characteristics of SAOP CD variations such as multi-modality are analyzed and contributions from various features to CDU and MTT (mean-to-target) budgets are estimated. The gap space is found to have the worst CDU+MTT performance and is used to determine the required overlay accuracy to ensure a satisfactory edge-placement yield of a cut process. Moreover, we propose a 5-mask positive-tone SAOP (pSAOP) process for memory FEOL patterning and a 3-mask negative-tone SAOP (nSAOP) process for logic BEOL patterning. The potential challenges of 2-D SAOP layout decomposition for BEOL applications are identified. Possible decomposition approaches are explored and the functionality of several developed algorithm is verified using 2-D layout examples from Open Cell Library.

  5. Training spiking neural networks to associate spatio-temporal input-output spike patterns

    OpenAIRE

    Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

    2013-01-01

    In a previous work (Mohemmed et al., Method for training a spiking neuron to associate input–output spike trains) [1] we have proposed a supervised learning algorithm based on temporal coding to train a spiking neuron to associate input spatiotemporal spike patterns to desired output spike patterns. The algorithm is based on the conversion of spike trains into analogue signals and the application of the Widrow–Hoff learning rule. In this paper we present a mathematical formulation of the prop...

  6. EEG analysis of seizure patterns using visibility graphs for detection of generalized seizures.

    Science.gov (United States)

    Wang, Lei; Long, Xi; Arends, Johan B A M; Aarts, Ronald M

    2017-10-01

    The traditional EEG features in the time and frequency domain show limited seizure detection performance in the epileptic population with intellectual disability (ID). In addition, the influence of EEG seizure patterns on detection performance was less studied. A single-channel EEG signal can be mapped into visibility graphs (VGS), including basic visibility graph (VG), horizontal VG (HVG), and difference VG (DVG). These graphs were used to characterize different EEG seizure patterns. To demonstrate its effectiveness in identifying EEG seizure patterns and detecting generalized seizures, EEG recordings of 615h on one EEG channel from 29 epileptic patients with ID were analyzed. A novel feature set with discriminative power for seizure detection was obtained by using the VGS method. The degree distributions (DDs) of DVG can clearly distinguish EEG of each seizure pattern. The degree entropy and power-law degree power in DVG were proposed here for the first time, and they show significant difference between seizure and non-seizure EEG. The connecting structure measured by HVG can better distinguish seizure EEG from background than those by VG and DVG. A traditional EEG feature set based on frequency analysis was used here as a benchmark feature set. With a support vector machine (SVM) classifier, the seizure detection performance of the benchmark feature set (sensitivity of 24%, FD t /h of 1.8s) can be improved by combining our proposed VGS features extracted from one EEG channel (sensitivity of 38%, FD t /h of 1.4s). The proposed VGS-based features can help improve seizure detection for ID patients. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Assessment of printability for printed electronics patterns by measuring geometric dimensions and defining assessment parameters

    Energy Technology Data Exchange (ETDEWEB)

    Jeon, Sung Woong [Dept. of Robotics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu (Korea, Republic of); Kim, Cheol; Kim, Chung Hwan [Chungnam National University, Daejeon (Korea, Republic of)

    2016-12-15

    The printability of patterns for printed electronic devices determines the performance, yield rate, and reliability of the devices; therefore, it should be assessed quantitatively. In this paper, parameters for printability assessment of printed patterns for width, pinholes, and edge waviness are suggested. For quantitative printability assessment, printability grades for each parameter are proposed according to the parameter values. As examples of printability assessment, printed line patterns and mesh patterns obtained using roll-to-roll gravure printing are used. Both single-line patterns and mesh patterns show different levels of printability, even in samples obtained using the same printing equipment and conditions. Therefore, for reliable assessment, it is necessary to assess the printability of the patterns by enlarging the sampling area and increasing the number of samples. We can predict the performance of printed electronic devices by assessing the printability of the patterns that constitute them.

  8. Assessment of printability for printed electronics patterns by measuring geometric dimensions and defining assessment parameters

    International Nuclear Information System (INIS)

    Jeon, Sung Woong; Kim, Cheol; Kim, Chung Hwan

    2016-01-01

    The printability of patterns for printed electronic devices determines the performance, yield rate, and reliability of the devices; therefore, it should be assessed quantitatively. In this paper, parameters for printability assessment of printed patterns for width, pinholes, and edge waviness are suggested. For quantitative printability assessment, printability grades for each parameter are proposed according to the parameter values. As examples of printability assessment, printed line patterns and mesh patterns obtained using roll-to-roll gravure printing are used. Both single-line patterns and mesh patterns show different levels of printability, even in samples obtained using the same printing equipment and conditions. Therefore, for reliable assessment, it is necessary to assess the printability of the patterns by enlarging the sampling area and increasing the number of samples. We can predict the performance of printed electronic devices by assessing the printability of the patterns that constitute them

  9. Different protein-protein interface patterns predicted by different machine learning methods.

    Science.gov (United States)

    Wang, Wei; Yang, Yongxiao; Yin, Jianxin; Gong, Xinqi

    2017-11-22

    Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns are preferred for prediction by different machine learning methods? Here, four different machine learning methods were employed to predict protein-protein interface residue pairs on different interface patterns. The performances of the methods for different types of proteins are different, which suggest that different machine learning methods tend to predict different protein-protein interface patterns. We made use of ANOVA and variable selection to prove our result. Our proposed methods taking advantages of different single methods also got a good prediction result compared to single methods. In addition to the prediction of protein-protein interactions, this idea can be extended to other research areas such as protein structure prediction and design.

  10. Convective heat transfer enhancement by diamond shaped micro-protruded patterns for heat sinks: Thermal fluid dynamic investigation and novel optimization methodology

    International Nuclear Information System (INIS)

    Ventola, Luigi; Dialameh, Masoud; Fasano, Matteo; Chiavazzo, Eliodoro; Asinari, Pietro

    2016-01-01

    Highlights: • A novel methodology for optimal design of patterned heat sink surfaces is proposed. • Heat transfer enhancement by patterned surfaces is measured experimentally. • Role of fluid dynamics and geometrical scales on heat transfer is clarified. - Abstract: In the present work, micro-protruded patterns on flush mounted heat sinks for convective heat transfer enhancement are investigated and a novel methodology for thermal optimization is proposed. Patterned heat sinks are experimentally characterized in fully turbulent regime, and the role played by geometrical parameters and fluid dynamic scales is discussed. A methodology specifically suited for micro-protruded pattern optimization is designed, leading to 73% enhancement in thermal performance respect to commercially available heat sinks, at fixed costs. This work is expected to introduce a new methodological approach for a more systematic and efficient development of solutions for electronics cooling.

  11. Children's participation in family food consumption patterns

    DEFF Research Database (Denmark)

    Brunsø, Karen; Christensen, Pia Haudrup

    2006-01-01

    This paper presents a theoretical framework for researching children and food consumption in the family. The proposed framework draws on contemporary social science approaches to the study of family decision making, food consumption patterns and routines, and consumer competence and food......-related lifestyle in order to understand children and families through their everyday practices. It suggest a new emphasis on children as active agents in the formation of family food consumption patterns and looks at children's food choices as embedded in everyday family life. We focus especially on the construct...... of the "Consumer Competence" of the child as one important aspect determining the way a child is involved in and gains influence over family food consumption. The paper also demonstrates how a mixed methods design, employing ethnographic and survey techniques, involves advances in methodological and analytical...

  12. Adaptive pixel-to-pixel projection intensity adjustment for measuring a shiny surface using orthogonal color fringe pattern projection

    Science.gov (United States)

    Chen, Chao; Gao, Nan; Wang, Xiangjun; Zhang, Zonghua

    2018-05-01

    Three-dimensional (3D) shape measurement based on fringe pattern projection techniques has been commonly used in various fields. One of the remaining challenges in fringe pattern projection is that camera sensor saturation may occur if there is a large range of reflectivity variation across the surface that causes measurement errors. To overcome this problem, a novel fringe pattern projection method is proposed to avoid image saturation and maintain high-intensity modulation for measuring shiny surfaces by adaptively adjusting the pixel-to-pixel projection intensity according to the surface reflectivity. First, three sets of orthogonal color fringe patterns and a sequence of uniform gray-level patterns with different gray levels are projected onto a measured surface by a projector. The patterns are deformed with respect to the object surface and captured by a camera from a different viewpoint. Subsequently, the optimal projection intensity at each pixel is determined by fusing different gray levels and transforming the camera pixel coordinate system into the projector pixel coordinate system. Finally, the adapted fringe patterns are created and used for 3D shape measurement. Experimental results on a flat checkerboard and shiny objects demonstrate that the proposed method can measure shiny surfaces with high accuracy.

  13. Weighted Local Active Pixel Pattern (WLAPP for Face Recognition in Parallel Computation Environment

    Directory of Open Access Journals (Sweden)

    Gundavarapu Mallikarjuna Rao

    2013-10-01

    Full Text Available Abstract  - The availability of multi-core technology resulted totally new computational era. Researchers are keen to explore available potential in state of art-machines for breaking the bearer imposed by serial computation. Face Recognition is one of the challenging applications on so ever computational environment. The main difficulty of traditional Face Recognition algorithms is lack of the scalability. In this paper Weighted Local Active Pixel Pattern (WLAPP, a new scalable Face Recognition Algorithm suitable for parallel environment is proposed.  Local Active Pixel Pattern (LAPP is found to be simple and computational inexpensive compare to Local Binary Patterns (LBP. WLAPP is developed based on concept of LAPP. The experimentation is performed on FG-Net Aging Database with deliberately introduced 20% distortion and the results are encouraging. Keywords — Active pixels, Face Recognition, Local Binary Pattern (LBP, Local Active Pixel Pattern (LAPP, Pattern computing, parallel workers, template, weight computation.  

  14. Pattern of secure bilateral transactions ensuring power economic dispatch in hybrid electricity markets

    International Nuclear Information System (INIS)

    Kumar, Ashwani; Gao, Wenzhong

    2009-01-01

    This paper proposes a new method for secure bilateral transactions determination ensuring economic power dispatch of the generators using new AC distribution factors for pool and bilateral coordinated markets. The new optimization problem considers simultaneous minimization of deviations from scheduled transactions and fuel cost of the generators in the network. The fuel cost has been obtained for hybrid market model and impact of different percentage of bilateral demand on fuel cost, generation share, and pattern of transactions has also been determined. The impact of optimally located unified power flow controller (UPFC) on the bilateral transactions, fuel cost and generation pattern has also been studied. The results have also been obtained for pool market model. The proposed technique has been applied on IEEE 24-bus reliability test system (RTS). (author)

  15. Federated Access Control in Heterogeneous Intercloud Environment: Basic Models and Architecture Patterns

    NARCIS (Netherlands)

    Demchenko, Y.; Ngo, C.; de Laat, C.; Lee, C.

    2014-01-01

    This paper presents on-going research to define the basic models and architecture patterns for federated access control in heterogeneous (multi-provider) multi-cloud and inter-cloud environment. The proposed research contributes to the further definition of Intercloud Federation Framework (ICFF)

  16. Physical optics modeling of modal patterns in a crossed porro prism resonator

    CSIR Research Space (South Africa)

    Litvin, IA

    2006-07-01

    Full Text Available A physical optics model is proposed to describe the transverse modal patterns in crossed Porro prism resonators. The model departs from earlier attempts in that the prisms are modeled as non-classical rotating elements with amplitude and phase...

  17. Pattern optimizing verification of self-align quadruple patterning

    Science.gov (United States)

    Yamato, Masatoshi; Yamada, Kazuki; Oyama, Kenichi; Hara, Arisa; Natori, Sakurako; Yamauchi, Shouhei; Koike, Kyohei; Yaegashi, Hidetami

    2017-03-01

    Lithographic scaling continues to advance by extending the life of 193nm immersion technology, and spacer-type multi-patterning is undeniably the driving force behind this trend. Multi-patterning techniques such as self-aligned double patterning (SADP) and self-aligned quadruple patterning (SAQP) have come to be used in memory devices, and they have also been adopted in logic devices to create constituent patterns in the formation of 1D layout designs. Multi-patterning has consequently become an indispensible technology in the fabrication of all advanced devices. In general, items that must be managed when using multi-patterning include critical dimension uniformity (CDU), line edge roughness (LER), and line width roughness (LWR). Recently, moreover, there has been increasing focus on judging and managing pattern resolution performance from a more detailed perspective and on making a right/wrong judgment from the perspective of edge placement error (EPE). To begin with, pattern resolution performance in spacer-type multi-patterning is affected by the process accuracy of the core (mandrel) pattern. Improving the controllability of CD and LER of the mandrel is most important, and to reduce LER, an appropriate smoothing technique should be carefully selected. In addition, the atomic layer deposition (ALD) technique is generally used to meet the need for high accuracy in forming the spacer film. Advances in scaling are accompanied by stricter requirements in the controllability of fine processing. In this paper, we first describe our efforts in improving controllability by selecting the most appropriate materials for the mandrel pattern and spacer film. Then, based on the materials selected, we present experimental results on a technique for improving etching selectivity.

  18. Mining Experiential Patterns from Game-Logs of Board Game

    Directory of Open Access Journals (Sweden)

    Liang Wang

    2015-01-01

    Full Text Available In board games, game-logs record past game processes, which can be regarded as an accumulation of experience. Similar to a real person, a computer player can gradually increase its skill by learning from game-logs. Therefore, the game becomes more interesting. This paper proposes an extensible approach to mine experiential patterns from increasing game-logs. The computer player improves its strategies by utilizing these growing patterns, just as it acquires experience. To evaluate the effect and performance of the approach, we designed a sample board game as a test platform and elaborated an experiment consisting of a series of tests. Experimental results show that our approach is effective and efficient.

  19. The Michelson interferometer-how to detect invisible interference patterns

    International Nuclear Information System (INIS)

    Verovnik, Ivo; Likar, Andrej

    2004-01-01

    In a Michelson interferometer, the contrast of the interference pattern fades away due to incoherence of light when the mirrors are not in equidistant positions. We propose an experiment where the distance between the interference fringes can be determined, even when the difference in length of the interferometer arms is far beyond the coherence length of the light, i.e. when the interference pattern disappears completely for the naked eye. We used a semiconductor laser with two photodiodes as sensors, which enabled us to follow the fluctuations of the light intensity on the screen. The distance between invisible interference fringes was determined from periodic changes of the summed fluctuating signal, obtained by changing the distance between the two sensors

  20. Phase retrieval from a single fringe pattern by using empirical wavelet transform

    International Nuclear Information System (INIS)

    Guo, Xiaopeng; Zhao, Hong; Wang, Xin

    2015-01-01

    Phase retrieval from a single fringe pattern is one of the key tasks in optical metrology. In this paper, we present a new method for phase retrieval from a single fringe pattern based on empirical wavelet transform. In the proposed method, a fringe pattern can be effectively divided into three components: nonuniform background, fringes and random noise, which are described in different sub-pass. So the phase distribution information can be robustly extracted from fringes representing a fundamental frequency component. In simulation and a practical projection fringes test, the performance of the present method is successfully verified by comparing with the conventional wavelet transform method in terms of both image quality and phase estimation errors. (paper)

  1. A High Optical Transmittance and Low Cost Touch Screen without Patterning

    Directory of Open Access Journals (Sweden)

    SAMADZAMINI, K.

    2017-02-01

    Full Text Available Transparent Conducting Oxide (TCO materials such as Fluorine Tin Oxide (FTO and Indium Tin Oxide (ITO due to their optical and electrical properties are used in touch screens as electrodes and wires. This paper proposes a novel technique of using Electrical Resistivity Tomography (ERT method in order to produce touch screens without pattering. Unlike existing techniques, the proposed methodology employs a uniform TCO coated screen with a maximum optical transmittance to convert the touch point coordinates into side electrodes voltages. The performance of the proposed method is tested experimentally on a FTO coated glass with a sheet resistance of 20 ohms/sq. The proposed methodology is found to be less complicated and low cost, since no pattern or electrodes are implemented in the display area.

  2. Detection of dependence patterns with delay.

    Science.gov (United States)

    Chevallier, Julien; Laloë, Thomas

    2015-11-01

    The Unitary Events (UE) method is a popular and efficient method used this last decade to detect dependence patterns of joint spike activity among simultaneously recorded neurons. The first introduced method is based on binned coincidence count (Grün, 1996) and can be applied on two or more simultaneously recorded neurons. Among the improvements of the methods, a transposition to the continuous framework has recently been proposed by Muiño and Borgelt (2014) and fully investigated by Tuleau-Malot et al. (2014) for two neurons. The goal of the present paper is to extend this study to more than two neurons. The main result is the determination of the limit distribution of the coincidence count. This leads to the construction of an independence test between L≥2 neurons. Finally, we propose a multiple test procedure via a Benjamini and Hochberg approach (Benjamini and Hochberg, 1995). All the theoretical results are illustrated by a simulation study, and compared to the UE method proposed by Grün et al. (2002). Furthermore our method is applied on real data. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Onset patterns in a simple model of localized parametric forcing.

    Science.gov (United States)

    Porter, J; Tinao, I; Laverón-Simavilla, A; Rodríguez, J

    2013-10-01

    We investigate pattern selection at onset in a parametrically and inhomogeneously forced partial differential equation obtained by generalizing Mathieu's equation to include spatial interactions. No separation of scales is assumed. The proposed model is directly relevant to the case of parametrically forced surface waves, such as cross-waves, excited by the horizontal vibration of a fluid, where the forcing is localized to a finite region near the endwall or wavemaker. The availability of analytical solutions in the limit of piecewise constant forcing allows us investigate in detail the dependence of selected eigenfunctions on spatial detuning, forcing width, damping, boundary conditions, and container size. A wide range of onset patterns are located and described, many of which are rotated, modulated, or both, and deviate far from simple crosswise oriented standing waves. The linear selection mechanisms governing this multiplicity of potential onset patterns are discussed.

  4. Analysis of pattern formation in systems with competing range interactions

    International Nuclear Information System (INIS)

    Zhao, H J; Misko, V R; Peeters, F M

    2012-01-01

    We analyzed pattern formation and identified various morphologies in a system of particles interacting through a non-monotonic potential with a competing range interaction characterized by a repulsive core (r c ) and an attractive tail (r > r c ), using molecular-dynamics simulations. Depending on parameters, the interaction potential models the inter-particle interaction in various physical systems ranging from atoms, molecules and colloids to vortices in low κ type-II superconductors and in recently discovered ‘type-1.5’ superconductors. We constructed a ‘morphology diagram’ in the plane ‘critical radius r c -density n’ and proposed a new approach to characterizing the different types of patterns. Namely, we elaborated a set of quantitative criteria in order to identify the different pattern types, using the radial distribution function (RDF), the local density function and the occupation factor. (paper)

  5. CHF Enhancement by Surface Patterning based on Hydrodynamic Instability Model

    Energy Technology Data Exchange (ETDEWEB)

    Seo, Han; Bang, In Cheol [UNIST, Ulsan (Korea, Republic of)

    2015-05-15

    If the power density of a device exceeds the CHF point, bubbles and vapor films will be covered on the whole heater surface. Because vapor films have much lower heat transfer capabilities compared to the liquid layer, the temperature of the heater surface will increase rapidly, and the device could be damaged due to the heater burnout. Therefore, the prediction and the enhancement of the CHF are essential to maximizing the efficient heat removal region. Numerous studies have been conducted to describe the CHF phenomenon, such as hydrodynamic instability theory, macrolayer dryout theory, hot/dry spot theory, and bubble interaction theory. The hydrodynamic instability model, proposed by Zuber, is the predominant CHF model that Helmholtz instability attributed to the CHF. Zuber assumed that the Rayleigh-Taylor (RT) instability wavelength is related to the Helmholtz wavelength. Lienhard and Dhir proposed a CHF model that Helmholtz instability wavelength is equal to the most dangerous RT wavelength. In addition, they showed the heater size effect using various heater surfaces. Lu et al. proposed a modified hydrodynamic theory that the Helmholtz instability was assumed to be the heater size and the area of the vapor column was used as a fitting factor. The modified hydrodynamic theories were based on the change of Helmholtz wavelength related to the RT instability wavelength. In the present study, the change of the RT instability wavelength, based on the heater surface modification, was conducted to show the CHF enhancement based on the heater surface patterning in a plate pool boiling. Sapphire glass was used as a base heater substrate, and the Pt film was used as a heating source. The patterning surface was based on the change of RT instability wavelength. In the present work the study of the CHF was conducted using bare Pt and patterned heating surfaces.

  6. Transformations of visual memory induced by implied motions of pattern elements.

    Science.gov (United States)

    Finke, R A; Freyd, J J

    1985-10-01

    Four experiments measured distortions in short-term visual memory induced by displays depicting independent translations of the elements of a pattern. In each experiment, observers saw a sequence of 4 dot patterns and were instructed to remember the third pattern and to compare it with the fourth. The first three patterns depicted translations of the dots in consistent, but separate directions. Error rates and reaction times for rejecting the fourth pattern as different from the third were substantially higher when the dots in that pattern were displaced slightly forward, in the same directions as the implied motions, compared with when the dots were displaced in the opposite, backward directions. These effects showed little variation across interstimulus intervals ranging from 250 to 2,000 ms, and did not depend on whether the displays gave rise to visual apparent motion. However, they were eliminated when the dots in the fourth pattern were displaced by larger amounts in each direction, corresponding to the dot positions in the next and previous patterns in the same inducing sequence. These findings extend our initial report of the phenomenon of "representational momentum" (Freyd & Finke, 1984a), and help to rule out alternatives to the proposal that visual memories tend to undergo, at least to some extent, the transformations implied by a prior sequence of observed events.

  7. High performance embedded system for real-time pattern matching

    Energy Technology Data Exchange (ETDEWEB)

    Sotiropoulou, C.-L., E-mail: c.sotiropoulou@cern.ch [University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Luciano, P. [University of Cassino and Southern Lazio, Gaetano di Biasio 43, Cassino 03043 (Italy); INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Gkaitatzis, S. [Aristotle University of Thessaloniki, 54124 Thessaloniki (Greece); Citraro, S. [University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Giannetti, P. [INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Dell' Orso, M. [University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy)

    2017-02-11

    In this paper we present an innovative and high performance embedded system for real-time pattern matching. This system is based on the evolution of hardware and algorithms developed for the field of High Energy Physics and more specifically for the execution of extremely fast pattern matching for tracking of particles produced by proton–proton collisions in hadron collider experiments. A miniaturized version of this complex system is being developed for pattern matching in generic image processing applications. The system works as a contour identifier able to extract the salient features of an image. It is based on the principles of cognitive image processing, which means that it executes fast pattern matching and data reduction mimicking the operation of the human brain. The pattern matching can be executed by a custom designed Associative Memory chip. The reference patterns are chosen by a complex training algorithm implemented on an FPGA device. Post processing algorithms (e.g. pixel clustering) are also implemented on the FPGA. The pattern matching can be executed on a 2D or 3D space, on black and white or grayscale images, depending on the application and thus increasing exponentially the processing requirements of the system. We present the firmware implementation of the training and pattern matching algorithm, performance and results on a latest generation Xilinx Kintex Ultrascale FPGA device. - Highlights: • A high performance embedded system for real-time pattern matching is proposed. • It is based on a system developed for High Energy Physics experiment triggers. • It mimics the operation of the human brain (cognitive image processing). • The process can be executed on 2D and 3D, black and white or grayscale images. • The implementation uses FPGAs and custom designed associative memory (AM) chips.

  8. High performance embedded system for real-time pattern matching

    International Nuclear Information System (INIS)

    Sotiropoulou, C.-L.; Luciano, P.; Gkaitatzis, S.; Citraro, S.; Giannetti, P.; Dell'Orso, M.

    2017-01-01

    In this paper we present an innovative and high performance embedded system for real-time pattern matching. This system is based on the evolution of hardware and algorithms developed for the field of High Energy Physics and more specifically for the execution of extremely fast pattern matching for tracking of particles produced by proton–proton collisions in hadron collider experiments. A miniaturized version of this complex system is being developed for pattern matching in generic image processing applications. The system works as a contour identifier able to extract the salient features of an image. It is based on the principles of cognitive image processing, which means that it executes fast pattern matching and data reduction mimicking the operation of the human brain. The pattern matching can be executed by a custom designed Associative Memory chip. The reference patterns are chosen by a complex training algorithm implemented on an FPGA device. Post processing algorithms (e.g. pixel clustering) are also implemented on the FPGA. The pattern matching can be executed on a 2D or 3D space, on black and white or grayscale images, depending on the application and thus increasing exponentially the processing requirements of the system. We present the firmware implementation of the training and pattern matching algorithm, performance and results on a latest generation Xilinx Kintex Ultrascale FPGA device. - Highlights: • A high performance embedded system for real-time pattern matching is proposed. • It is based on a system developed for High Energy Physics experiment triggers. • It mimics the operation of the human brain (cognitive image processing). • The process can be executed on 2D and 3D, black and white or grayscale images. • The implementation uses FPGAs and custom designed associative memory (AM) chips.

  9. SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

    DEFF Research Database (Denmark)

    Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran

    2017-01-01

    We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400...... to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient....

  10. Wafer-Level Packaging Method for RF MEMS Applications Using Pre-Patterned BCB Polymer

    OpenAIRE

    Zhuhao Gong; Yulong Zhang; Xin Guo; Zewen Liu

    2018-01-01

    A radio-frequency micro-electro-mechanical system (RF MEMS) wafer-level packaging (WLP) method using pre-patterned benzo-cyclo-butene (BCB) polymers with a high-resistivity silicon cap is proposed to achieve high bonding quality and excellent RF performance. In this process, the BCB polymer was pre-defined to form the sealing ring and bonding layer by the spin-coating and patterning of photosensitive BCB before the cavity formation. During anisotropic wet etching of the silicon wafer to gener...

  11. Patterns of inclusion

    DEFF Research Database (Denmark)

    Pedersen, Alex Young; Nørgård, Rikke Toft; Köppe, Christian

    2018-01-01

    Reconsidering the concept of digital citizenship and the essential component of education the authors propose that the concept of Hybrid Education may serve both as a guideline for the utilization of digital technologies in education and as a methodology for fostering new forms of participation......, inclusion and engagement in society. Following T.H. Marshall’s conception of citizenship the authors suggest that becoming, belonging and the capabilities to do so is essential to digital citizenship in a culturally diverse and digitally mediated world. The paper presents a theory-based, value driven...... for Hybrid Education that are directly applicable in relation to the concept of digital citizenship. The process introduces a value-based and vision-driven design pattern approach to innovation in education by framing and aligning values and visions of the participants. This work resulted in approximately 85...

  12. Characterizing the Spatio-Temporal Pattern of Land Surface Temperature through Time Series Clustering: Based on the Latent Pattern and Morphology

    Directory of Open Access Journals (Sweden)

    Huimin Liu

    2018-04-01

    patterns. The homogeneous geographical clusters correspond to the zoning custom of urban planning and design, and thus, may efficiently bridge the urban and environmental systems in terms of research scope and scale. The proposed workflow can be utilized for other cities and potentially used for comparison among different cities.

  13. Pattern Recognition of Signals for the Fault-Slip Type of Rock Burst in Coal Mines

    Directory of Open Access Journals (Sweden)

    X. S. Liu

    2015-01-01

    Full Text Available The fault-slip type of rock burst is a major threat to the safety of coal mining, and effectively recognizing its signals patterns is the foundation for the early warning and prevention. At first, a mechanical model of the fault-slip was established and the mechanism of the rock burst induced by the fault-slip was revealed. Then, the patterns of the electromagnetic radiation, acoustic emission (AE, and microseismic signals in the fault-slip type of rock burst were proposed, in that before the rock burst occurs, the electromagnetic radiation intensity near the sliding surface increases rapidly, the AE energy rises exponentially, and the energy released by microseismic events experiences at least one peak and is close to the next peak. At last, in situ investigations were performed at number 1412 coal face in the Huafeng Mine, China. Results showed that the signals patterns proposed are in good agreement with the process of the fault-slip type of rock burst. The pattern recognition can provide a basis for the early warning and the implementation of relief measures of the fault-slip type of rock burst.

  14. Laser patterning of transparent polymers assisted by plasmon excitation.

    Science.gov (United States)

    Elashnikov, R; Trelin, A; Otta, J; Fitl, P; Mares, D; Jerabek, V; Svorcik, V; Lyutakov, O

    2018-06-13

    Plasmon-assisted lithography of thin transparent polymer films, based on polymer mass-redistribution under plasmon excitation, is presented. The plasmon-supported structures were prepared by thermal annealing of thin Ag films sputtered on glass or glass/graphene substrates. Thin films of polymethylmethacrylate, polystyrene and polylactic acid were then spin-coated on the created plasmon-supported structures. Subsequent laser beam writing, at the wavelength corresponding to the position of plasmon absorption, leads to mass redistribution and patterning of the thin polymer films. The prepared structures were characterized using UV-Vis spectroscopy and confocal and AFM microscopy. The shape of the prepared structures was found to be strongly dependent on the substrate type. The mechanism leading to polymer patterning was examined and attributed to the plasmon-heating. The proposed method makes it possible to create different patterns in polymer films without the need for wet technological stages, powerful light sources or a change in the polymer optical properties.

  15. High precision patterning of ITO using femtosecond laser annealing process

    International Nuclear Information System (INIS)

    Cheng, Chung-Wei; Lin, Cen-Ying

    2014-01-01

    Highlights: • We have reported a process of fabrication of crystalline indium tin oxide (c-ITO) patterns using femtosecond laser-induced crystallization with a Gaussian beam profile followed by chemical etching. • The experimental results have demonstrated that the ablation and crystallization threshold fluences of a-ITO thin film are well-defined, the line width of the c-ITO patterns is controllable. • Fast fabrication of the two parallel sub-micro (∼0.5 μm) c-ITO line patterns using a single femtosecond laser beam and a single scanning path can be achieved. • A long-length sub-micro c-ITO line pattern is fabricated, and the feasibility of fabricating c-ITO patterns is confirmed, which are expected to be used in micro-electronics devices. - Abstract: High precision patterning of crystalline indium tin oxide (c-ITO) patterns on amorphous ITO (a-ITO) thin films by femtosecond laser-induced crystallization with a Gaussian beam profile followed by chemical etching is demonstrated. In the proposed approach, the a-ITO thin film is selectively transformed into a c-ITO structure via a low heat affect zone and the well-defined thresholds (ablation and crystallization) supplied by the femtosecond laser pulse. The experimental results show that by careful control of the laser fluence above the crystallization threshold, c-ITO patterns with controllable line widths and ridge-free characteristics can be accomplished. By careful control of the laser fluence above the ablation threshold, fast fabrication of the two parallel sub-micro c-ITO line patterns using a single femtosecond laser beam and single scanning path can be achieved. Along-length sub-micro c-ITO line pattern is fabricated, and the feasibility of fabricating c-ITO patterns is confirmed, which are expected to be used in micro-electronics devices

  16. Research for superconducting energy storage patterns and its practical countermeasures

    Energy Technology Data Exchange (ETDEWEB)

    Lin, D.H., E-mail: lindehua_cn@yahoo.com.cn [College of Physics, Chongqing University, JD Duz (USA)-CQU Institute for Superconductivity, Chongqing 400030 (China); Cui, D.J.; Li, B.; Teng, Y.; Zheng, G.L. [College of Physics, Chongqing University, JD Duz (USA)-CQU Institute for Superconductivity, Chongqing 400030 (China); Wang, X.Q. [College of Physics, Chongqing University, JD Duz (USA)-CQU Institute for Superconductivity, Chongqing 400030 (China); State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400030 (China)

    2013-10-15

    Highlights: • Proposed some new ideas and strategies about how to improve the energy storage density for SMES system. • Increasing the effective current density in the superconducting coils or optimizing the configuration of the SMES coil could improve the energy storage density. • A new conceive of energy compression is also proposed. -- Abstract: In this paper, we attempt to introduce briefly the significance, the present status, as well as the working principle of the primary patterns of the superconducting energy storage system, first of all. According to the defect on the lower energy storage density of existed superconducting energy storage device, we proposed some new ideas and strategies about how to improve the energy storage density, in which, a brand-new but a tentative proposal regarding the concept of energy compression was emphasized. This investigation has a certain reference value towards the practical application of the superconducting energy storage.

  17. Research for superconducting energy storage patterns and its practical countermeasures

    International Nuclear Information System (INIS)

    Lin, D.H.; Cui, D.J.; Li, B.; Teng, Y.; Zheng, G.L.; Wang, X.Q.

    2013-01-01

    Highlights: • Proposed some new ideas and strategies about how to improve the energy storage density for SMES system. • Increasing the effective current density in the superconducting coils or optimizing the configuration of the SMES coil could improve the energy storage density. • A new conceive of energy compression is also proposed. -- Abstract: In this paper, we attempt to introduce briefly the significance, the present status, as well as the working principle of the primary patterns of the superconducting energy storage system, first of all. According to the defect on the lower energy storage density of existed superconducting energy storage device, we proposed some new ideas and strategies about how to improve the energy storage density, in which, a brand-new but a tentative proposal regarding the concept of energy compression was emphasized. This investigation has a certain reference value towards the practical application of the superconducting energy storage

  18. An Optimization Framework for Travel Pattern Interpretation of Cellular Data

    Directory of Open Access Journals (Sweden)

    Sarit Freund

    2013-09-01

    This paper explores methods for identifying travel patterns from cellular data. A primary challenge in this research is to provide an interpretation of the raw data that distinguishes between activity durations and travel durations. A novel framework is proposed for this purpose, based on a grading scheme for candidate interpretations of the raw data. A genetic algorithm is used to find interpretations with high grades, which are considered as the most reasonable ones. The proposed method is tested on a dataset of records covering 9454 cell-phone users over a period of one week. Preliminary evaluation of the resulting interpretations is presented.

  19. Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition

    Directory of Open Access Journals (Sweden)

    Bineng Zhong

    2008-06-01

    Full Text Available This paper proposes a new face recognition method, named kernel learning of histogram of local Gabor phase pattern (K-HLGPP, which is based on Daugman’s method for iris recognition and the local XOR pattern (LXP operator. Unlike traditional Gabor usage exploiting the magnitude part in face recognition, we encode the Gabor phase information for face classification by the quadrant bit coding (QBC method. Two schemes are proposed for face recognition. One is based on the nearest-neighbor classifier with chi-square as the similarity measurement, and the other makes kernel discriminant analysis for HLGPP (K-HLGPP using histogram intersection and Gaussian-weighted chi-square kernels. The comparative experiments show that K-HLGPP achieves a higher recognition rate than other well-known face recognition systems on the large-scale standard FERET, FERET200, and CAS-PEAL-R1 databases.

  20. Cliché fabrication method using precise roll printing process with 5 um pattern width

    Science.gov (United States)

    Shin, Yejin; Kim, Inyoung; Oh, Dong-Ho; Lee, Taik-Min

    2016-09-01

    Among the printing processes for printed electronic devices, gravure offset and reverse offset method have drawn attention for its fine pattern printing possibility. These printing methods use cliché, which has critical effect on the final product precision and quality. In this research, a novel precise cliché replica method is proposed. It consists of copper sputtering, precise mask pattern printing with 5 um width using reverse offset printing, Ni electroplating, lift-off, etching, and DLC coating. We finally compare the fabricated replica cliché with the original one and print out precise patterns using the replica cliché.

  1. Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition

    CERN Document Server

    Melin, Patricia

    2012-01-01

    This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural ne...

  2. Testing for coevolutionary diversification: linking pattern with process.

    Science.gov (United States)

    Althoff, David M; Segraves, Kari A; Johnson, Marc T J

    2014-02-01

    Coevolutionary diversification is cited as a major mechanism driving the evolution of diversity, particularly in plants and insects. However, tests of coevolutionary diversification have focused on elucidating macroevolutionary patterns rather than the processes giving rise to such patterns. Hence, there is weak evidence that coevolution promotes diversification. This is in part due to a lack of understanding about the mechanisms by which coevolution can cause speciation and the difficulty of integrating results across micro- and macroevolutionary scales. In this review, we highlight potential mechanisms of coevolutionary diversification, outline approaches to examine this process across temporal scales, and propose a set of minimal requirements for demonstrating coevolutionary diversification. Our aim is to stimulate research that tests more rigorously for coevolutionary diversification. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Pulse patterning effect in optical pulse division multiplexing for flexible single wavelength multiple access optical network

    Science.gov (United States)

    Jung, Sun-Young; Kim, Chang-Hun; Han, Sang-Kook

    2018-05-01

    A demand for high spectral efficiency requires multiple access within a single wavelength, but the uplink signals are significantly degraded because of optical beat interference (OBI) in intensity modulation/direct detection system. An optical pulse division multiplexing (OPDM) technique was proposed that could effectively reduce the OBI via a simple method as long as near-orthogonality is satisfied, but the condition was strict, and thus, the number of multiplexing units was very limited. We propose pulse pattern enhanced OPDM (e-OPDM) to reduce the OBI and improve the flexibility in multiple access within a single wavelength. The performance of the e-OPDM and patterning effect are experimentally verified after 23-km single mode fiber transmission. By employing pulse patterning in OPDM, the tight requirement was relaxed by extending the optical delay dynamic range. This could support more number of access with reduced OBI, which could eventually enhance a multiple access function.

  4. Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond

    International Nuclear Information System (INIS)

    Gasparotto, Piero; Ceriotti, Michele

    2014-01-01

    The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how they transform into one another. Here, we discuss how to use a computer to identify atomic patterns automatically, so as to provide an algorithmic definition of a bond based solely on structural information. We concentrate in particular on hydrogen bonding – a central concept to our understanding of the physical chemistry of water, biological systems, and many technologically important materials. Since the hydrogen bond is a somewhat fuzzy entity that covers a broad range of energies and distances, many different criteria have been proposed and used over the years, based either on sophisticate electronic structure calculations followed by an energy decomposition analysis, or on somewhat arbitrary choices of a range of structural parameters that is deemed to correspond to a hydrogen-bonded configuration. We introduce here a definition that is univocal, unbiased, and adaptive, based on our machine-learning analysis of an atomistic simulation. The strategy we propose could be easily adapted to similar scenarios, where one has to recognize or classify structural patterns in a material or chemical compound

  5. Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond

    Energy Technology Data Exchange (ETDEWEB)

    Gasparotto, Piero; Ceriotti, Michele, E-mail: michele.ceriotti@epfl.ch [Laboratory of Computational Science and Modeling, and National Center for Computational Design and Discovery of Novel Materials MARVEL, IMX, École Polytechnique Fédérale de Lausanne, 1015 Lausanne (Switzerland)

    2014-11-07

    The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how they transform into one another. Here, we discuss how to use a computer to identify atomic patterns automatically, so as to provide an algorithmic definition of a bond based solely on structural information. We concentrate in particular on hydrogen bonding – a central concept to our understanding of the physical chemistry of water, biological systems, and many technologically important materials. Since the hydrogen bond is a somewhat fuzzy entity that covers a broad range of energies and distances, many different criteria have been proposed and used over the years, based either on sophisticate electronic structure calculations followed by an energy decomposition analysis, or on somewhat arbitrary choices of a range of structural parameters that is deemed to correspond to a hydrogen-bonded configuration. We introduce here a definition that is univocal, unbiased, and adaptive, based on our machine-learning analysis of an atomistic simulation. The strategy we propose could be easily adapted to similar scenarios, where one has to recognize or classify structural patterns in a material or chemical compound.

  6. Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond

    Science.gov (United States)

    Gasparotto, Piero; Ceriotti, Michele

    2014-11-01

    The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how they transform into one another. Here, we discuss how to use a computer to identify atomic patterns automatically, so as to provide an algorithmic definition of a bond based solely on structural information. We concentrate in particular on hydrogen bonding - a central concept to our understanding of the physical chemistry of water, biological systems, and many technologically important materials. Since the hydrogen bond is a somewhat fuzzy entity that covers a broad range of energies and distances, many different criteria have been proposed and used over the years, based either on sophisticate electronic structure calculations followed by an energy decomposition analysis, or on somewhat arbitrary choices of a range of structural parameters that is deemed to correspond to a hydrogen-bonded configuration. We introduce here a definition that is univocal, unbiased, and adaptive, based on our machine-learning analysis of an atomistic simulation. The strategy we propose could be easily adapted to similar scenarios, where one has to recognize or classify structural patterns in a material or chemical compound.

  7. SENSING URBAN LAND-USE PATTERNS BY INTEGRATING GOOGLE TENSORFLOW AND SCENE-CLASSIFICATION MODELS

    Directory of Open Access Journals (Sweden)

    Y. Yao

    2017-09-01

    Full Text Available With the rapid progress of China’s urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model’s ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI. Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs. To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737 for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

  8. Relevance feature selection of modal frequency-ambient condition pattern recognition in structural health assessment for reinforced concrete buildings

    Directory of Open Access Journals (Sweden)

    He-Qing Mu

    2016-08-01

    Full Text Available Modal frequency is an important indicator for structural health assessment. Previous studies have shown that this indicator is substantially affected by the fluctuation of ambient conditions, such as temperature and humidity. Therefore, recognizing the pattern between modal frequency and ambient conditions is necessary for reliable long-term structural health assessment. In this article, a novel machine-learning algorithm is proposed to automatically select relevance features in modal frequency-ambient condition pattern recognition based on structural dynamic response and ambient condition measurement. In contrast to the traditional feature selection approaches by examining a large number of combinations of extracted features, the proposed algorithm conducts continuous relevance feature selection by introducing a sophisticated hyperparameterization on the weight parameter vector controlling the relevancy of different features in the prediction model. The proposed algorithm is then utilized for structural health assessment for a reinforced concrete building based on 1-year daily measurements. It turns out that the optimal model class including the relevance features for each vibrational mode is capable to capture the pattern between the corresponding modal frequency and the ambient conditions.

  9. The use of arc-erosion as a patterning technique for transparent conductive materials

    Energy Technology Data Exchange (ETDEWEB)

    Jimenez-Trillo, J. [Dpt. Ingenieria de Circuitos y Sistemas, EUIT Telecomunicacion, U. P. M, 28031 Madrid (Spain); Alvarez, A.L., E-mail: angelluis.alvarez@urjc.es [Dpt. Tecnologia Electronica, Univ. Rey Juan Carlos, Mostoles, 28933 Madrid (Spain); Coya, C. [Dpt. Tecnologia Electronica, Univ. Rey Juan Carlos, Mostoles, 28933 Madrid (Spain); Cespedes, E.; Espinosa, A. [Instituto de Ciencia de los Materiales (CSIC), Cantoblanco, 28049 Madrid (Spain)

    2011-12-01

    Within the framework of cost-effective patterning processes a novel technique that saves photolithographic processing steps, easily scalable to wide area production, is proposed. It consists of a tip-probe, which is biased with respect to a conductive substrate and slides on it, keeping contact with the material. The sliding tip leaves an insulating path (which currently is as narrow as 30 {mu}m) across the material, which enables the drawing of tracks and pads electrically insulated from the surroundings. This ablation method, called arc-erosion, requires an experimental set up that had to be customized for this purpose and is described. Upon instrumental monitoring, a brief proposal of the physics below this process is also presented. As a result an optimal control of the patterning process has been acquired. The system has been used on different substrates, including indium tin oxide either on glass or on polyethylene terephtalate, as well as alloys like Au/Cr, and Al. The influence of conditions such as tip speed and applied voltage is discussed. - Research highlights: Black-Right-Pointing-Pointer An experimental set up has been arranged to use arc erosion as a cost-effective patterning technique of conductive materials (ITO, and thin film metals). Black-Right-Pointing-Pointer Monitoring of the process has revealed that patterning is performed by a sequence of electrical discharges, assisted by the bypass capacitor at the source output. Black-Right-Pointing-Pointer This process has been controlled optimizing the patterning conditions and quality over different materials.

  10. Personal authentication through dorsal hand vein patterns

    Science.gov (United States)

    Hsu, Chih-Bin; Hao, Shu-Sheng; Lee, Jen-Chun

    2011-08-01

    Biometric identification is an emerging technology that can solve security problems in our networked society. A reliable and robust personal verification approach using dorsal hand vein patterns is proposed in this paper. The characteristic of the approach needs less computational and memory requirements and has a higher recognition accuracy. In our work, the near-infrared charge-coupled device (CCD) camera is adopted as an input device for capturing dorsal hand vein images, it has the advantages of the low-cost and noncontact imaging. In the proposed approach, two finger-peaks are automatically selected as the datum points to define the region of interest (ROI) in the dorsal hand vein images. The modified two-directional two-dimensional principal component analysis, which performs an alternate two-dimensional PCA (2DPCA) in the column direction of images in the 2DPCA subspace, is proposed to exploit the correlation of vein features inside the ROI between images. The major advantage of the proposed method is that it requires fewer coefficients for efficient dorsal hand vein image representation and recognition. The experimental results on our large dorsal hand vein database show that the presented schema achieves promising performance (false reject rate: 0.97% and false acceptance rate: 0.05%) and is feasible for dorsal hand vein recognition.

  11. Visual analytics of geo-social interaction patterns for epidemic control.

    Science.gov (United States)

    Luo, Wei

    2016-08-10

    Human interaction and population mobility determine the spatio-temporal course of the spread of an airborne disease. This research views such spreads as geo-social interaction problems, because population mobility connects different groups of people over geographical locations via which the viruses transmit. Previous research argued that geo-social interaction patterns identified from population movement data can provide great potential in designing effective pandemic mitigation. However, little work has been done to examine the effectiveness of designing control strategies taking into account geo-social interaction patterns. To address this gap, this research proposes a new framework for effective disease control; specifically this framework proposes that disease control strategies should start from identifying geo-social interaction patterns, designing effective control measures accordingly, and evaluating the efficacy of different control measures. This framework is used to structure design of a new visual analytic tool that consists of three components: a reorderable matrix for geo-social mixing patterns, agent-based epidemic models, and combined visualization methods. With real world human interaction data in a French primary school as a proof of concept, this research compares the efficacy of vaccination strategies between the spatial-social interaction patterns and the whole areas. The simulation results show that locally targeted vaccination has the potential to keep infection to a small number and prevent spread to other regions. At some small probability, the local control strategies will fail; in these cases other control strategies will be needed. This research further explores the impact of varying spatial-social scales on the success of local vaccination strategies. The results show that a proper spatial-social scale can help achieve the best control efficacy with a limited number of vaccines. The case study shows how GS-EpiViz does support the design

  12. Fan fault diagnosis based on symmetrized dot pattern analysis and image matching

    Science.gov (United States)

    Xu, Xiaogang; Liu, Haixiao; Zhu, Hao; Wang, Songling

    2016-07-01

    To detect the mechanical failure of fans, a new diagnostic method based on the symmetrized dot pattern (SDP) analysis and image matching is proposed. Vibration signals of 13 kinds of running states are acquired on a centrifugal fan test bed and reconstructed by the SDP technique. The SDP pattern templates of each running state are established. An image matching method is performed to diagnose the fault. In order to improve the diagnostic accuracy, the single template, multiple templates and clustering fault templates are used to perform the image matching.

  13. Cross-View Neuroimage Pattern Analysis for Alzheimer's Disease Staging

    Directory of Open Access Journals (Sweden)

    Sidong eLiu

    2016-02-01

    Full Text Available The research on staging of pre-symptomatic and prodromal phase of neurological disorders, e.g., Alzheimer's disease (AD, is essential for prevention of dementia. New strategies for AD staging with a focus on early detection, are demanded to optimize potential efficacy of disease-modifying therapies that can halt or slow the disease progression. Recently, neuroimaging are increasingly used as additional research-based markers to detect AD onset and predict conversion of MCI and normal control (NC to AD. Researchers have proposed a variety of neuroimaging biomarkers to characterize the patterns of the pathology of AD and MCI, and suggested that multi-view neuroimaging biomarkers could lead to better performance than single-view biomarkers in AD staging. However, it is still unclear what leads to such synergy and how to preserve or maximize. In an attempt to answer these questions, we proposed a cross-view pattern analysis framework for investigating the synergy between different neuroimaging biomarkers. We quantitatively analyzed 9 types of biomarkers derived from FDG-PET and T1-MRI, and evaluated their performance in a task of classifying AD, MCI and NC subjects obtained from the ADNI baseline cohort. The experiment results showed that these biomarkers could depict the pathology of AD from different perspectives, and output distinct patterns that are significantly associated with the disease progression. Most importantly, we found that these features could be separated into clusters, each depicting a particular aspect; and the inter-cluster features could always achieve better performance than the intra-cluster features in AD staging.

  14. Improving image-quality of interference fringes of out-of-plane vibration using temporal speckle pattern interferometry and standard deviation for piezoelectric plates.

    Science.gov (United States)

    Chien-Ching Ma; Ching-Yuan Chang

    2013-07-01

    Interferometry provides a high degree of accuracy in the measurement of sub-micrometer deformations; however, the noise associated with experimental measurement undermines the integrity of interference fringes. This study proposes the use of standard deviation in the temporal domain to improve the image quality of patterns obtained from temporal speckle pattern interferometry. The proposed method combines the advantages of both mean and subtractive methods to remove background noise and ambient disturbance simultaneously, resulting in high-resolution images of excellent quality. The out-of-plane vibration of a thin piezoelectric plate is the main focus of this study, providing information useful to the development of energy harvesters. First, ten resonant states were measured using the proposed method, and both mode shape and resonant frequency were investigated. We then rebuilt the phase distribution of the first resonant mode based on the clear interference patterns obtained using the proposed method. This revealed instantaneous deformations in the dynamic characteristics of the resonant state. The proposed method also provides a frequency-sweeping function, facilitating its practical application in the precise measurement of resonant frequency. In addition, the mode shapes and resonant frequencies obtained using the proposed method were recorded and compared with results obtained using finite element method and laser Doppler vibrometery, which demonstrated close agreement.

  15. Energy prediction using spatiotemporal pattern networks

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun; Henze, Gregor P.; Sarkar, Soumik

    2017-11-01

    This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated by the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.

  16. Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

    Science.gov (United States)

    Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

    2017-01-01

    There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

  17. PWM pulse pattern optimization method using carrier frequency modulation. Carrier shuhasu hencho ni yoru PWM pulse pattern saitekikaho

    Energy Technology Data Exchange (ETDEWEB)

    Iwaji, Y.; Fukuda, S. (Hokkaido University, Sapporo (Japan))

    1991-07-15

    Sinusoidal inverters are getting more widely used keeping pace with the development of semiconductor switching elements. This paper discusses optimizing a PWM pulse pattern at an inverter output to drive an induction motor, proposes methods for improving distortion and torque ripples using a carrier frequency modulation (CFM), and describes a method for realizing the improvement through use of a single-chip microcomputer. The method defines evaluation parameters corresponding to the distortion and torque ripples, and optimizes the CFM depth to the parameters. The PWM pulse pattern has its voltage vector and time width so selected that the time integrated space vector of a three-phase voltage approaches a circular locus. Furthermore, the carrier frequency, that is the sampling frequency of the inverter, is also adjusted so that the above evaluation parameters are minimized. The addition of a new variable called the frequency modulation provides freedom in selecting an output characteristic as called for by the purpose. 12 refs., 18 figs.

  18. Compressed multi-block local binary pattern for object tracking

    Science.gov (United States)

    Li, Tianwen; Gao, Yun; Zhao, Lei; Zhou, Hao

    2018-04-01

    Both robustness and real-time are very important for the application of object tracking under a real environment. The focused trackers based on deep learning are difficult to satisfy with the real-time of tracking. Compressive sensing provided a technical support for real-time tracking. In this paper, an object can be tracked via a multi-block local binary pattern feature. The feature vector was extracted based on the multi-block local binary pattern feature, which was compressed via a sparse random Gaussian matrix as the measurement matrix. The experiments showed that the proposed tracker ran in real-time and outperformed the existed compressive trackers based on Haar-like feature on many challenging video sequences in terms of accuracy and robustness.

  19. Complex networks from experimental horizontal oil–water flows: Community structure detection versus flow pattern discrimination

    International Nuclear Information System (INIS)

    Gao, Zhong-Ke; Fang, Peng-Cheng; Ding, Mei-Shuang; Yang, Dan; Jin, Ning-De

    2015-01-01

    We propose a complex network-based method to distinguish complex patterns arising from experimental horizontal oil–water two-phase flow. We first use the adaptive optimal kernel time–frequency representation (AOK TFR) to characterize flow pattern behaviors from the energy and frequency point of view. Then, we infer two-phase flow complex networks from experimental measurements and detect the community structures associated with flow patterns. The results suggest that the community detection in two-phase flow complex network allows objectively discriminating complex horizontal oil–water flow patterns, especially for the segregated and dispersed flow patterns, a task that existing method based on AOK TFR fails to work. - Highlights: • We combine time–frequency analysis and complex network to identify flow patterns. • We explore the transitional flow behaviors in terms of betweenness centrality. • Our analysis provides a novel way for recognizing complex flow patterns. • Broader applicability of our method is demonstrated and articulated

  20. Pattern recognition for cache management in distributed medical imaging environments.

    Science.gov (United States)

    Viana-Ferreira, Carlos; Ribeiro, Luís; Matos, Sérgio; Costa, Carlos

    2016-02-01

    Traditionally, medical imaging repositories have been supported by indoor infrastructures with huge operational costs. This paradigm is changing thanks to cloud outsourcing which not only brings technological advantages but also facilitates inter-institutional workflows. However, communication latency is one main problem in this kind of approaches, since we are dealing with tremendous volumes of data. To minimize the impact of this issue, cache and prefetching are commonly used. The effectiveness of these mechanisms is highly dependent on their capability of accurately selecting the objects that will be needed soon. This paper describes a pattern recognition system based on artificial neural networks with incremental learning to evaluate, from a set of usage pattern, which one fits the user behavior at a given time. The accuracy of the pattern recognition model in distinct training conditions was also evaluated. The solution was tested with a real-world dataset and a synthesized dataset, showing that incremental learning is advantageous. Even with very immature initial models, trained with just 1 week of data samples, the overall accuracy was very similar to the value obtained when using 75% of the long-term data for training the models. Preliminary results demonstrate an effective reduction in communication latency when using the proposed solution to feed a prefetching mechanism. The proposed approach is very interesting for cache replacement and prefetching policies due to the good results obtained since the first deployment moments.

  1. Illumination normalization based on simplified local binary patterns for a face verification system

    NARCIS (Netherlands)

    Tao, Q.; Veldhuis, Raymond N.J.

    2007-01-01

    Illumination normalization is a very important step in face recognition. In this paper we propose a simple implementation of Local Binary Patterns, which effectively reduces the variability caused by illumination changes. In combination with a likelihood ratio classifier, this illumination

  2. Using visual information analysis to explore complex patterns in the activity of designers

    DEFF Research Database (Denmark)

    Cash, Philip; Stanković, Tino; Štorga, Mario

    2014-01-01

    The analysis of complex interlinked datasets poses a significant problem for design researchers. This is addressed by proposing an information visualisation method for analysing patterns of design activity, qualitatively and quantitatively, with respect to time. This method visualises the tempora...

  3. Direct self-assembling and patterning of semiconductor quantum dots on transferable elastomer layer

    Energy Technology Data Exchange (ETDEWEB)

    Coppola, Sara [Institute of Applied Sciences and Intelligent System- CNR, Via Campi Flegrei 34, Pozzuoli, 80078 (Italy); Vespini, Veronica, E-mail: v.vespini@isasi.cnr.it [Institute of Applied Sciences and Intelligent System- CNR, Via Campi Flegrei 34, Pozzuoli, 80078 (Italy); Olivieri, Federico [Institute of Applied Sciences and Intelligent System- CNR, Via Campi Flegrei 34, Pozzuoli, 80078 (Italy); University of Naples Federico II, Department of Chemical Materials and Production Engineering, Piazzale Tecchio 80, Naples 80125 (Italy); Nasti, Giuseppe; Todino, Michele; Mandracchia, Biagio; Pagliarulo, Vito; Ferraro, Pietro [Institute of Applied Sciences and Intelligent System- CNR, Via Campi Flegrei 34, Pozzuoli, 80078 (Italy)

    2017-03-31

    Highlights: • A quantum dots self-patterning on micrometrical polymeric array is proposed. • The effect of a quantum dots mix on the array is evaluated. • A PDMS membrane is exploited to transfer the pattern on it. - Abstract: Functionalization of thin and stretchable polymer layers by nano- and micro-patterning of nanoparticles is a very promising field of research that can lead to many different applications in biology and nanotechnology. In this work, we present a new procedure to self-assemble semiconductor quantum dots (QDs) nanoparticles by a simple fabrication process on a freestanding flexible PolyDiMethylSiloxane (PDMS) membrane. We used a Periodically Poled Lithium Niobate (PPLN) crystal to imprint a micrometrical pattern on the PDMS membrane that drives the QDs self-structuring on its surface. This process allows patterning QDs with different wavelength emissions in a single step in order to tune the overall emission spectrum of the composite, tuning the QDs mixing ratio.

  4. Compare local pocket and global protein structure models by small structure patterns

    KAUST Repository

    Cui, Xuefeng

    2015-09-09

    Researchers proposed several criteria to assess the quality of predicted protein structures because it is one of the essential tasks in the Critical Assessment of Techniques for Protein Structure Prediction (CASP) competitions. Popular criteria include root mean squared deviation (RMSD), MaxSub score, TM-score, GDT-TS and GDT-HA scores. All these criteria require calculation of rigid transformations to superimpose the the predicted protein structure to the native protein structure. Yet, how to obtain the rigid transformations is unknown or with high time complexity, and, hence, heuristic algorithms were proposed. In this work, we carefully design various small structure patterns, including the ones specifically tuned for local pockets. Such structure patterns are biologically meaningful, and address the issue of relying on a sufficient number of backbone residue fragments for existing methods. We sample the rigid transformations from these small structure patterns; and the optimal superpositions yield by these small structures are refined and reported. As a result, among 11; 669 pairs of predicted and native local protein pocket models from the CASP10 dataset, the GDT-TS scores calculated by our method are significantly higher than those calculated by LGA. Moreover, our program is computationally much more efficient. Source codes and executables are publicly available at http://www.cbrc.kaust.edu.sa/prosta/

  5. Intermodal transport and distribution patterns in ports relationship to hinterland

    Science.gov (United States)

    Dinu, O.; Dragu, V.; Ruscă, F.; Ilie, A.; Oprea, C.

    2017-08-01

    It is of great importance to examine all interactions between ports, terminals, intermodal transport and logistic actors of distribution channels, as their optimization can lead to operational improvement. Proposed paper starts with a brief overview of different goods types and allocation of their logistic costs, with emphasis on storage component. Present trend is to optimize storage costs by means of port storage area buffer function, by making the best use of free storage time available, most of the ports offer. As a research methodology, starting point is to consider the cost structure of a generic intermodal transport (storage, handling and transport costs) and to link this to intermodal distribution patterns most frequently cast-off in port relationship to hinterland. The next step is to evaluate storage costs impact on distribution pattern selection. For a given value of port free storage time, a corresponding value of total storage time in the distribution channel can be identified, in order to substantiate a distribution pattern shift. Different scenarios for transport and handling costs variation, recorded when distribution pattern shift, are integrated in order to establish the reaction of the actors involved in port related logistic and intermodal transport costs evolution is analysed in order to optimize distribution pattern selection.

  6. Optimal Point-to-Point Trajectory Tracking of Redundant Manipulators using Generalized Pattern Search

    Directory of Open Access Journals (Sweden)

    Thi Rein Myo

    2008-11-01

    Full Text Available Optimal point-to-point trajectory planning for planar redundant manipulator is considered in this study. The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Search GPS is introduced to design the optimal trajectory. To verify the proposed algorithm, simulations for a 3-D-O-F planar manipulator with different end-effector trajectories have been carried out. A comparison between the Genetic Algorithm and the Generalized Pattern Search shows that The GPS gives excellent tracking performance.

  7. Practical 3-D Beam Pattern Based Channel Modeling for Multi-Polarized Massive MIMO Systems.

    Science.gov (United States)

    Aghaeinezhadfirouzja, Saeid; Liu, Hui; Balador, Ali

    2018-04-12

    In this paper, a practical non-stationary three-dimensional (3-D) channel models for massive multiple-input multiple-output (MIMO) systems, considering beam patterns for different antenna elements, is proposed. The beam patterns using dipole antenna elements with different phase excitation toward the different direction of travels (DoTs) contributes various correlation weights for rays related towards/from the cluster, thus providing different elevation angle of arrivals (EAoAs) and elevation angle of departures (EAoDs) for each antenna element. These include the movements of the user that makes our channel to be a non-stationary model of clusters at the receiver (RX) on both the time and array axes. In addition, their impacts on 3-D massive MIMO channels are investigated via statistical properties including received spatial correlation. Additionally, the impact of elevation/azimuth angles of arrival on received spatial correlation is discussed. Furthermore, experimental validation of the proposed 3-D channel models on azimuth and elevation angles of the polarized antenna are specifically evaluated and compared through simulations. The proposed 3-D generic models are verified using relevant measurement data.

  8. Visibility Network Patterns and Methods for Studying Visual Relational Phenomena in Archeology

    Directory of Open Access Journals (Sweden)

    Tom Brughmans

    2017-08-01

    Full Text Available A review of the archeological and non-archeological use of visibility networks reveals the use of a limited range of formal techniques, in particular for representing visibility theories. This paper aims to contribute to the study of complex visual relational phenomena in landscape archeology by proposing a range of visibility network patterns and methods. We propose first- and second-order visibility graph representations of total and cumulative viewsheds, and two-mode representations of cumulative viewsheds. We present network patterns that can be used to represent aspects of visibility theories and that can be used in statistical simulation models to compare theorized networks with observed networks. We argue for the need to incorporate observed visibility network density in these simulation models, by illustrating strong differences in visibility network density in three example landscapes. The approach is illustrated through a brief case study of visibility networks of long barrows in Cranborne Chase.

  9. A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns.

    Directory of Open Access Journals (Sweden)

    Mohammad Manir Hossain Mollah

    Full Text Available Identifying genes that are differentially expressed (DE between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA, are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0 to outlying expressions and larger weights (≤ 1 to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA.Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large

  10. A fingertip force prediction model for grasp patterns characterised from the chaotic behaviour of EEG.

    Science.gov (United States)

    Roy, Rinku; Sikdar, Debdeep; Mahadevappa, Manjunatha; Kumar, C S

    2018-05-19

    A stable grasp is attained through appropriate hand preshaping and precise fingertip forces. Here, we have proposed a method to decode grasp patterns from motor imagery and subsequent fingertip force estimation model with a slippage avoidance strategy. We have developed a feature-based classification of electroencephalography (EEG) associated with imagination of the grasping postures. Chaotic behaviour of EEG for different grasping patterns has been utilised to capture the dynamics of associated motor activities. We have computed correlation dimension (CD) as the feature and classified with "one against one" multiclass support vector machine (SVM) to discriminate between different grasping patterns. The result of the analysis showed varying classification accuracies at different subband levels. Broad categories of grasping patterns, namely, power grasp and precision grasp, were classified at a 96.0% accuracy rate in the alpha subband. Furthermore, power grasp subtypes were classified with an accuracy of 97.2% in the upper beta subband, whereas precision grasp subtypes showed relatively lower 75.0% accuracy in the alpha subband. Following assessment of fingertip force distributions while grasping, a nonlinear autoregressive (NAR) model with proper prediction of fingertip forces was proposed for each grasp pattern. A slippage detection strategy has been incorporated with automatic recalibration of the regripping force. Intention of each grasp pattern associated with corresponding fingertip force model was virtualised in this work. This integrated system can be utilised as the control strategy for prosthetic hand in the future. The model to virtualise motor imagery based fingertip force prediction with inherent slippage correction for different grasp types ᅟ.

  11. Research on the Eco-tourism and Environment-friendly Land Use Patterns in Shangri-La

    OpenAIRE

    Yan, Fei; Li, Wei; Liu, Yun

    2014-01-01

    Through the analysis of the geographical features of the Shangri-La, the eco-tourism and environment-friendly land use patterns were proposed. And the significances of the mode of economic development in Shangri-La were analyzed.

  12. Pattern Recognition-Based Analysis of COPD in CT

    DEFF Research Database (Denmark)

    Sørensen, Lauge Emil Borch Laurs

    recognition part is used to turn the texture measures, measured in a CT image of the lungs, into a quantitative measure of disease. This is done by applying a classifier that is trained on a training set of data examples with known lung tissue patterns. Different classification systems are considered, and we...... will in particular use the pattern recognition concepts of supervised learning, multiple instance learning, and dissimilarity representation-based classification. The proposed texture-based measures are applied to CT data from two different sources, one comprising low dose CT slices from subjects with manually...... annotated regions of emphysema and healthy tissue, and one comprising volumetric low dose CT images from subjects that are either healthy or suffer from COPD. Several experiments demonstrate that it is clearly beneficial to take the lung tissue texture into account when classifying or quantifying emphysema...

  13. Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

    Science.gov (United States)

    Inoue, Kentaro; Shimozono, Shinichi; Yoshida, Hideaki; Kurata, Hiroyuki

    2012-01-01

    For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

  14. Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

    Directory of Open Access Journals (Sweden)

    Kentaro Inoue

    Full Text Available BACKGROUND: For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. RESULTS: We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. CONCLUSIONS: Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

  15. Rapid selective metal patterning on polydimethylsiloxane (PDMS) fabricated by capillarity-assisted laser direct write

    KAUST Repository

    Lee, Ming-Tsang

    2011-08-12

    In this study we demonstrate a novel approach for the rapid fabricating micro scale metal (silver) patterning directly on a polydimethylsiloxane (PDMS) substrate. Silver nanoparticles were sintered on PDMS to form conductive metal films using laser direct write (LDW) technology. To achieve good metal film quality, a capillarity-assisted laser direct writing (CALDW) of nanoparticle suspensions on a low surface energy material (PDMS) was utilized. Experimental results showed controllable electrical conductivities and good film properties of the sintered silver patterns. This study reveals an advanced method of metal patterning on PDMS, and proposes a new research application of LDW in a nanoparticle colloidal environment. © 2011 IOP Publishing Ltd.

  16. Peculiarities of Pattern Information Transmission

    Directory of Open Access Journals (Sweden)

    Evgeniy V. Yurkevich

    2017-01-01

    Full Text Available The rates of modern technologies development is such that educational programs are constantly required to be enlarged with new material. However, the introduced supplements often do not take into account the limited possibilities of perceiving amounts of information offered in class. As a result, a significant number of graduates get diplomas of educational institutions with a number of pathologies. Despite heavy load during training, the knowledge of a graduate is often not enough to recognize him ready to participate in modern production. The problem of providing quality education by creating a technology making it possible to maximize students’ knowledge while reducing the number of messages transmitted in the classroom. Consideration of the educational process in the form of an information system with messages transmitted in the form of images is proposed as one of the ways of solving it. The work assumed that each message is reflected in the consciousness of the source and receiver of information in the form of mental images. Mental images of the teacher and student are considered as a convolution of information. The analysis of peculiarities of mental images formation and development is given, a model of the mechanism of pattern information transmission is proposed. The model of transmitting sign, pattern, and symbol information is described. The communication bandwidth between the participants  of the educational process is considered as depending on their goal setting, training, physiological and emotional features, as well as a number of other non-formalized factors. Graduates of educational institutions are considered as means of producing intellectual products, and the purpose of obtaining knowledge is proposed to be formed based on the definition of the attractor of developing the “teacher-student” system. A principle of organizing educational processes is proposed: the education technology should not violate the consistency

  17. Applying a Machine Learning Technique to Classification of Japanese Pressure Patterns

    Directory of Open Access Journals (Sweden)

    H Kimura

    2009-04-01

    Full Text Available In climate research, pressure patterns are often very important. When a climatologists need to know the days of a specific pressure pattern, for example "low pressure in Western areas of Japan and high pressure in Eastern areas of Japan (Japanese winter-type weather," they have to visually check a huge number of surface weather charts. To overcome this problem, we propose an automatic classification system using a support vector machine (SVM, which is a machine-learning method. We attempted to classify pressure patterns into two classes: "winter type" and "non-winter type". For both training datasets and test datasets, we used the JRA-25 dataset from 1981 to 2000. An experimental evaluation showed that our method obtained a greater than 0.8 F-measure. We noted that variations in results were based on differences in training datasets.

  18. Mining Spatiotemporal Patterns of the Elder's Daily Movement

    Science.gov (United States)

    Chen, C. R.; Chen, C. F.; Liu, M. E.; Tsai, S. J.; Son, N. T.; Kinh, L. V.

    2016-06-01

    With rapid developments in wearable device technology, a vast amount of spatiotemporal data, such as people's movement and physical activities, are generated. Information derived from the data reveals important knowledge that can contribute a long-term care and psychological assessment of the elders' living condition especially in long-term care institutions. This study aims to develop a method to investigate the spatial-temporal movement patterns of the elders with their outdoor trajectory information. To achieve the goal, GPS based location data of the elderly subjects from long-term care institutions are collected and analysed with geographic information system (GIS). A GIS statistical model is developed to mine the elderly subjects' spatiotemporal patterns with the location data and represent their daily movement pattern at particular time. The proposed method first finds the meaningful trajectory and extracts the frequent patterns from the time-stamp location data. Then, a density-based clustering method is used to identify the major moving range and the gather/stay hotspot in both spatial and temporal dimensions. The preliminary results indicate that the major moving area of the elderly people encompasses their dorm and has a short moving distance who often stay in the same site. Subjects' outdoor appearance are corresponded to their life routine. The results can be useful for understanding elders' social network construction, risky area identification and medical care monitoring.

  19. A subject-independent pattern-based Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    Andreas Markus Ray

    2015-10-01

    Full Text Available While earlier Brain-Computer Interface (BCI studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e. happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to match their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders.

  20. A Pilot-Pattern Based Algorithm for MIMO-OFDM Channel Estimation

    Directory of Open Access Journals (Sweden)

    Guomin Li

    2016-12-01

    Full Text Available An improved pilot pattern algorithm for facilitating the channel estimation in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM systems is proposed in this paper. The presented algorithm reconfigures the parameter in the least square (LS algorithm, which belongs to the space-time block-coded (STBC category for channel estimation in pilot-based MIMO-OFDM system. Simulation results show that the algorithm has better performance in contrast to the classical single symbol scheme. In contrast to the double symbols scheme, the proposed algorithm can achieve nearly the same performance with only half of the complexity of the double symbols scheme.

  1. Detecting causality from online psychiatric texts using inter-sentential language patterns

    Directory of Open Access Journals (Sweden)

    Wu Jheng-Long

    2012-07-01

    Full Text Available Abstract Background Online psychiatric texts are natural language texts expressing depressive problems, published by Internet users via community-based web services such as web forums, message boards and blogs. Understanding the cause-effect relations embedded in these psychiatric texts can provide insight into the authors’ problems, thus increasing the effectiveness of online psychiatric services. Methods Previous studies have proposed the use of word pairs extracted from a set of sentence pairs to identify cause-effect relations between sentences. A word pair is made up of two words, with one coming from the cause text span and the other from the effect text span. Analysis of the relationship between these words can be used to capture individual word associations between cause and effect sentences. For instance, (broke up, life and (boyfriend, meaningless are two word pairs extracted from the sentence pair: “I broke up with my boyfriend. Life is now meaningless to me”. The major limitation of word pairs is that individual words in sentences usually cannot reflect the exact meaning of the cause and effect events, and thus may produce semantically incomplete word pairs, as the previous examples show. Therefore, this study proposes the use of inter-sentential language patterns such as ≪broke up, boyfriend>, Results Performance was evaluated on a corpus of texts collected from PsychPark (http://www.psychpark.org, a virtual psychiatric clinic maintained by a group of volunteer professionals from the Taiwan Association of Mental Health Informatics. Experimental results show that the use of inter-sentential language patterns outperformed the use of word pairs proposed in previous studies. Conclusions This study demonstrates the acquisition of inter-sentential language patterns for causality detection from online psychiatric texts. Such semantically more complete and precise features can improve causality detection performance.

  2. Pattern specification in the insect embryo. [uv radiation, Smittia

    Energy Technology Data Exchange (ETDEWEB)

    Sander, K

    1975-01-01

    Specification of developmental pathways by specific determining substances prelocalized in the egg cytoplasm is discussed using the so-called germ cell determinants as an example. Some theoretical considerations speak against the assumption that in insects the various elements of the basic body plan are specified by a prelocalized mosaic of specific determinants. Experimental evidence also points towards a largely epigenetic mode of pattern specification. The process of axial pattern specification can be altered drastically by experiment: in some insects, tail ends may be formed in place of head parts and identical sequences of body segments may be specified two or even three times along the longitudinal egg axis. The experimental results indicate that polarity and regional character of pattern elements formed are specified by one and the same influence, and that this influence can be shifted to or simulated in various other egg regions by transposition or elimination of egg components, or by uv irradiation. Evidence obtained from several types of experiment in the chironomid midge Smittia points towards a key role for local metabolism or energy charge in determination of cell polarity and in pattern spcification. A model for embryonic pattern specification involving differential reaction of cells to a system of longitudinal gradients, which was proposed in 1960, can in principle formally account for all results described. Some striking coincidences of model and experimental results with Wolpert's concept of positional information are noted. Finally it is pointed out that universality of mechanisms for pattern specification is much more likely with respect to formal principles than at the level of their physiological realization.

  3. An approach to evaluate the topological significance of motifs and other patterns in regulatory networks

    Directory of Open Access Journals (Sweden)

    Wingender Edgar

    2009-05-01

    Full Text Available Abstract Background The identification of network motifs as statistically over-represented topological patterns has become one of the most promising topics in the analysis of complex networks. The main focus is commonly made on how they operate by means of their internal organization. Yet, their contribution to a network's global architecture is poorly understood. However, this requires switching from the abstract view of a topological pattern to the level of its instances. Here, we show how a recently proposed metric, the pairwise disconnectivity index, can be adapted to survey if and which kind of topological patterns and their instances are most important for sustaining the connectivity within a network. Results The pairwise disconnectivity index of a pattern instance quantifies the dependency of the pairwise connections between vertices in a network on the presence of this pattern instance. Thereby, it particularly considers how the coherence between the unique constituents of a pattern instance relates to the rest of a network. We have applied the method exemplarily to the analysis of 3-vertex topological pattern instances in the transcription networks of a bacteria (E. coli, a unicellular eukaryote (S. cerevisiae and higher eukaryotes (human, mouse, rat. We found that in these networks only very few pattern instances break lots of the pairwise connections between vertices upon the removal of an instance. Among them network motifs do not prevail. Rather, those patterns that are shared by the three networks exhibit a conspicuously enhanced pairwise disconnectivity index. Additionally, these are often located in close vicinity to each other or are even overlapping, since only a small number of genes are repeatedly present in most of them. Moreover, evidence has gathered that the importance of these pattern instances is due to synergistic rather than merely additive effects between their constituents. Conclusion A new method has been proposed

  4. Pattern recognition in cyclic and discrete skills performance from inertial measurement units

    NARCIS (Netherlands)

    Seifert, Ludovic; L'Hermette, Maxime; Komar, John; Orth, Dominic; Mell, Florian; Merriaux, Pierre; Grenet, Pierre; Caritu, Yanis; Hérault, Romain; Dovgalecs, Vladislavs; Davids, Keith

    2014-01-01

    The aim of this study is to compare and validate an Inertial Measurement Unit (IMU) relative to an optic system, and to propose methods for pattern recognition to capture behavioural dynamics during sport performance. IMU validation was conducted by comparing the motions of the two arms of a

  5. Pattern-mixture models for analyzing normal outcome data with proxy respondents.

    Science.gov (United States)

    Shardell, Michelle; Hicks, Gregory E; Miller, Ram R; Langenberg, Patricia; Magaziner, Jay

    2010-06-30

    Studies of older adults often involve interview questions regarding subjective constructs such as perceived disability. In some studies, when subjects are unable (e.g. due to cognitive impairment) or unwilling to respond to these questions, proxies (e.g. relatives or other care givers) are recruited to provide responses in place of the subject. Proxies are usually not approached to respond on behalf of subjects who respond for themselves; thus, for each subject, data from only one of the subject or proxy are available. Typically, proxy responses are simply substituted for missing subject responses, and standard complete-data analyses are performed. However, this approach may introduce measurement error and produce biased parameter estimates. In this paper, we propose using pattern-mixture models that relate non-identifiable parameters to identifiable parameters to analyze data with proxy respondents. We posit three interpretable pattern-mixture restrictions to be used with proxy data, and we propose estimation procedures using maximum likelihood and multiple imputation. The methods are applied to a cohort of elderly hip-fracture patients. (c) 2010 John Wiley & Sons, Ltd.

  6. Enterprise Pattern: integrating the business process into a unified enterprise model of modern service company

    Science.gov (United States)

    Li, Ying; Luo, Zhiling; Yin, Jianwei; Xu, Lida; Yin, Yuyu; Wu, Zhaohui

    2017-01-01

    Modern service company (MSC), the enterprise involving special domains, such as the financial industry, information service industry and technology development industry, depends heavily on information technology. Modelling of such enterprise has attracted much research attention because it promises to help enterprise managers to analyse basic business strategies (e.g. the pricing strategy) and even optimise the business process (BP) to gain benefits. While the existing models proposed by economists cover the economic elements, they fail to address the basic BP and its relationship with the economic characteristics. Those proposed in computer science regardless of achieving great success in BP modelling perform poorly in supporting the economic analysis. Therefore, the existing approaches fail to satisfy the requirement of enterprise modelling for MSC, which demands simultaneous consideration of both economic analysing and business processing. In this article, we provide a unified enterprise modelling approach named Enterprise Pattern (EP) which bridges the gap between the BP model and the enterprise economic model of MSC. Proposing a language named Enterprise Pattern Description Language (EPDL) covering all the basic language elements of EP, we formulate the language syntaxes and two basic extraction rules assisting economic analysis. Furthermore, we extend Business Process Model and Notation (BPMN) to support EPDL, named BPMN for Enterprise Pattern (BPMN4EP). The example of mobile application platform is studied in detail for a better understanding of EPDL.

  7. fMRI activation patterns in an analytic reasoning task: consistency with EEG source localization

    Science.gov (United States)

    Li, Bian; Vasanta, Kalyana C.; O'Boyle, Michael; Baker, Mary C.; Nutter, Brian; Mitra, Sunanda

    2010-03-01

    Functional magnetic resonance imaging (fMRI) is used to model brain activation patterns associated with various perceptual and cognitive processes as reflected by the hemodynamic (BOLD) response. While many sensory and motor tasks are associated with relatively simple activation patterns in localized regions, higher-order cognitive tasks may produce activity in many different brain areas involving complex neural circuitry. We applied a recently proposed probabilistic independent component analysis technique (PICA) to determine the true dimensionality of the fMRI data and used EEG localization to identify the common activated patterns (mapped as Brodmann areas) associated with a complex cognitive task like analytic reasoning. Our preliminary study suggests that a hybrid GLM/PICA analysis may reveal additional regions of activation (beyond simple GLM) that are consistent with electroencephalography (EEG) source localization patterns.

  8. Polyhedral patterns

    KAUST Repository

    Jiang, Caigui; Tang, Chengcheng; Vaxman, Amir; Wonka, Peter; Pottmann, Helmut

    2015-01-01

    We study the design and optimization of polyhedral patterns, which are patterns of planar polygonal faces on freeform surfaces. Working with polyhedral patterns is desirable in architectural geometry and industrial design. However, the classical

  9. Modeling and clustering water demand patterns from real-world smart meter data

    Directory of Open Access Journals (Sweden)

    N. Cheifetz

    2017-08-01

    Full Text Available Nowadays, drinking water utilities need an acute comprehension of the water demand on their distribution network, in order to efficiently operate the optimization of resources, manage billing and propose new customer services. With the emergence of smart grids, based on automated meter reading (AMR, a better understanding of the consumption modes is now accessible for smart cities with more granularities. In this context, this paper evaluates a novel methodology for identifying relevant usage profiles from the water consumption data produced by smart meters. The methodology is fully data-driven using the consumption time series which are seen as functions or curves observed with an hourly time step. First, a Fourier-based additive time series decomposition model is introduced to extract seasonal patterns from time series. These patterns are intended to represent the customer habits in terms of water consumption. Two functional clustering approaches are then used to classify the extracted seasonal patterns: the functional version of K-means, and the Fourier REgression Mixture (FReMix model. The K-means approach produces a hard segmentation and K representative prototypes. On the other hand, the FReMix is a generative model and also produces K profiles as well as a soft segmentation based on the posterior probabilities. The proposed approach is applied to a smart grid deployed on the largest water distribution network (WDN in France. The two clustering strategies are evaluated and compared. Finally, a realistic interpretation of the consumption habits is given for each cluster. The extensive experiments and the qualitative interpretation of the resulting clusters allow one to highlight the effectiveness of the proposed methodology.

  10. Modeling and clustering water demand patterns from real-world smart meter data

    Science.gov (United States)

    Cheifetz, Nicolas; Noumir, Zineb; Samé, Allou; Sandraz, Anne-Claire; Féliers, Cédric; Heim, Véronique

    2017-08-01

    Nowadays, drinking water utilities need an acute comprehension of the water demand on their distribution network, in order to efficiently operate the optimization of resources, manage billing and propose new customer services. With the emergence of smart grids, based on automated meter reading (AMR), a better understanding of the consumption modes is now accessible for smart cities with more granularities. In this context, this paper evaluates a novel methodology for identifying relevant usage profiles from the water consumption data produced by smart meters. The methodology is fully data-driven using the consumption time series which are seen as functions or curves observed with an hourly time step. First, a Fourier-based additive time series decomposition model is introduced to extract seasonal patterns from time series. These patterns are intended to represent the customer habits in terms of water consumption. Two functional clustering approaches are then used to classify the extracted seasonal patterns: the functional version of K-means, and the Fourier REgression Mixture (FReMix) model. The K-means approach produces a hard segmentation and K representative prototypes. On the other hand, the FReMix is a generative model and also produces K profiles as well as a soft segmentation based on the posterior probabilities. The proposed approach is applied to a smart grid deployed on the largest water distribution network (WDN) in France. The two clustering strategies are evaluated and compared. Finally, a realistic interpretation of the consumption habits is given for each cluster. The extensive experiments and the qualitative interpretation of the resulting clusters allow one to highlight the effectiveness of the proposed methodology.

  11. PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

    Science.gov (United States)

    Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

    2004-11-01

    Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

  12. Separation of complex fringe patterns using two-dimensional continuous wavelet transform.

    Science.gov (United States)

    Pokorski, Krzysztof; Patorski, Krzysztof

    2012-12-10

    A method for processing fringe patterns containing additively superimposed multiple fringe sets is presented. It enables to analyze different fringe families present in a single image separately. The proposed method is based on a two-dimensional continuous wavelet transform. A robust ridge extraction algorithm for a single fringe set extraction is presented. The method is fully automatic and requires no user interference. Spectral separation of fringe families is not required. Simulations are presented to verify performance and advantage of the proposed method over the Fourier transform based technique. Method validity has been confirmed using experimental images.

  13. Reload pattern optimization by application of multiple cyclic interchange algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Geemert, R. van; Quist, A.J.; Hoogenboom, J.E. [Technische Univ. Delft (Netherlands)

    1996-09-01

    Reload pattern optimization procedures are proposed which are based on the multiple cyclic interchange approach, according to which the search for the reload pattern associated with the highest objective function value can be thought of as divided in multiple stages. The transition from the initial to the final stage is characterized by an increase in the degree of locality of the search procedure. The general idea is that, during the first stages, the `elite` cluster containing the group of best patterns must be located, after which the solution space is sampled in a more and more local sense to find the local optimum in this cluster. The transition(s) from global search behaviour to local search behaviour can be either prompt, by defining strictly separate search regimes, or gradual by introducing stochastic tests for the number of fuel bundles involved in a cyclic interchange. Equilibrium cycle optimization results are reported for a test PWR reactor core of modest size. (author)

  14. Reload pattern optimization by application of multiple cyclic interchange algorithms

    International Nuclear Information System (INIS)

    Geemert, R. van; Quist, A.J.; Hoogenboom, J.E.

    1996-01-01

    Reload pattern optimization procedures are proposed which are based on the multiple cyclic interchange approach, according to which the search for the reload pattern associated with the highest objective function value can be thought of as divided in multiple stages. The transition from the initial to the final stage is characterized by an increase in the degree of locality of the search procedure. The general idea is that, during the first stages, the 'elite' cluster containing the group of best patterns must be located, after which the solution space is sampled in a more and more local sense to find the local optimum in this cluster. The transition(s) from global search behaviour to local search behaviour can be either prompt, by defining strictly separate search regimes, or gradual by introducing stochastic tests for the number of fuel bundles involved in a cyclic interchange. Equilibrium cycle optimization results are reported for a test PWR reactor core of modest size. (author)

  15. Spongiosa Primary Development: A Biochemical Hypothesis by Turing Patterns Formations

    Directory of Open Access Journals (Sweden)

    Oscar Rodrigo López-Vaca

    2012-01-01

    Full Text Available We propose a biochemical model describing the formation of primary spongiosa architecture through a bioregulatory model by metalloproteinase 13 (MMP13 and vascular endothelial growth factor (VEGF. It is assumed that MMP13 regulates cartilage degradation and the VEGF allows vascularization and advances in the ossification front through the presence of osteoblasts. The coupling of this set of molecules is represented by reaction-diffusion equations with parameters in the Turing space, creating a stable spatiotemporal pattern that leads to the formation of the trabeculae present in the spongy tissue. Experimental evidence has shown that the MMP13 regulates VEGF formation, and it is assumed that VEGF negatively regulates MMP13 formation. Thus, the patterns obtained by ossification may represent the primary spongiosa formation during endochondral ossification. Moreover, for the numerical solution, we used the finite element method with the Newton-Raphson method to approximate partial differential nonlinear equations. Ossification patterns obtained may represent the primary spongiosa formation during endochondral ossification.

  16. Master stability functions reveal diffusion-driven pattern formation in networks

    Science.gov (United States)

    Brechtel, Andreas; Gramlich, Philipp; Ritterskamp, Daniel; Drossel, Barbara; Gross, Thilo

    2018-03-01

    We study diffusion-driven pattern formation in networks of networks, a class of multilayer systems, where different layers have the same topology, but different internal dynamics. Agents are assumed to disperse within a layer by undergoing random walks, while they can be created or destroyed by reactions between or within a layer. We show that the stability of homogeneous steady states can be analyzed with a master stability function approach that reveals a deep analogy between pattern formation in networks and pattern formation in continuous space. For illustration, we consider a generalized model of ecological meta-food webs. This fairly complex model describes the dispersal of many different species across a region consisting of a network of individual habitats while subject to realistic, nonlinear predator-prey interactions. In this example, the method reveals the intricate dependence of the dynamics on the spatial structure. The ability of the proposed approach to deal with this fairly complex system highlights it as a promising tool for ecology and other applications.

  17. Diversity Patterns of Benthic Macrofauna Caused by Marine Fish Farming

    Directory of Open Access Journals (Sweden)

    Arnaldo Marín

    2011-04-01

    Full Text Available This paper reviews the patterns observed in the diversity and structure of the macrofauna benthic community under the influence of fish farming. First, we explain the effects of organic enrichment on the sediment and the consequences for the inhabiting communities. We describe the diversity trends in spatial and temporal gradients affected by fish farming and compare them with those described by the Pearson and Rosenberg model. We found that in general terms, the trends of diversity and other community parameters followed the Pearson and Rosenberg model but they can vary to some extent due to sediment local characteristics or to secondary disturbances. We also show the different mechanisms by which wild fish can affect macrofauna diversity patterns under fish farming influence. In addition, we comment the importance of the macrofauna diversity in the ecosystem functions and propose some guidelines to measure functional diversity related to relevant processes at ecosystem level. We propose more research efforts in the main topics commented in this review to improve management strategies to guarantee a good status of the diversity and ecosystem functioning of sediments influenced by fish farming.

  18. Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape

    Science.gov (United States)

    Ramírez-Forero, Sandra Carolina; López-Caloca, Alejandra; Silván-Cárdenas, José Luis

    2011-11-01

    The tropical coastal landscape of Tulum in Quintana Roo, Mexico has a high ecological, economical, social and cultural value, it provides environmental and tourism services at global, national, regional and local levels. The landscape of the area is heterogeneous and presents random fragmentation patterns. In recent years, tourist services of the region has been increased promoting an accelerate expansion of hotels, transportation and recreation infrastructure altering the complex landscape. It is important to understand the environmental dynamics through temporal changes on the spatial patterns and to propose a better management of this ecological area to the authorities. This paper addresses a multi-temporal analysis of land cover changes from 1993 to 2000 in Tulum using Thematic Mapper data acquired by Landsat-5. Two independent methodologies were applied for the analysis of changes in the landscape and for the definition of fragmentation patterns. First, an Iteratively Multivariate Alteration Detection (IR-MAD) algorithm was used to detect and localize land cover change/no-change areas. Second, the post-classification change detection evaluated using the Support Vector Machine (SVM) algorithm. Landscape metrics were calculated from the results of IR-MAD and SVM. The analysis of the metrics indicated, among other things, a higher fragmentation pattern along roadways.

  19. Stress Prediction for Distributed Structural Health Monitoring Using Existing Measurements and Pattern Recognition.

    Science.gov (United States)

    Lu, Wei; Teng, Jun; Zhou, Qiushi; Peng, Qiexin

    2018-02-01

    The stress in structural steel members is the most useful and directly measurable physical quantity to evaluate the structural safety in structural health monitoring, which is also an important index to evaluate the stress distribution and force condition of structures during structural construction and service phases. Thus, it is common to set stress as a measure in steel structural monitoring. Considering the economy and the importance of the structural members, there are only a limited number of sensors that can be placed, which means that it is impossible to obtain the stresses of all members directly using sensors. This study aims to develop a stress response prediction method for locations where there are insufficent sensors, using measurements from a limited number of sensors and pattern recognition. The detailed improved aspects are: (1) a distributed computing process is proposed, where the same pattern is recognized by several subsets of measurements; and (2) the pattern recognition using the subset of measurements is carried out by considering the optimal number of sensors and number of fusion patterns. The validity and feasibility of the proposed method are verified using two examples: the finite-element simulation of a single-layer shell-like steel structure, and the structural health monitoring of the space steel roof of Shenzhen Bay Stadium; for the latter, the anti-noise performance of this method is verified by the stress measurements from a real-world project.

  20. Prediction of Human Activity by Discovering Temporal Sequence Patterns.

    Science.gov (United States)

    Li, Kang; Fu, Yun

    2014-08-01

    Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

  1. Topics in Complexity: Dynamical Patterns in the Cyberworld

    Science.gov (United States)

    Qi, Hong

    Quantitative understanding of mechanism in complex systems is a common "difficult" problem across many fields such as physical, biological, social and economic sciences. Investigation on underlying dynamics of complex systems and building individual-based models have recently been fueled by big data resulted from advancing information technology. This thesis investigates complex systems in social science, focusing on civil unrests on streets and relevant activities online. Investigation consists of collecting data of unrests from open digital source, featuring dynamical patterns underlying, making predictions and constructing models. A simple law governing the progress of two-sided confrontations is proposed with data of activities at micro-level. Unraveling the connections between activity of organizing online and outburst of unrests on streets gives rise to a further meso-level pattern of human behavior, through which adversarial groups evolve online and hyper-escalate ahead of real-world uprisings. Based on the patterns found, noticeable improvement of prediction of civil unrests is achieved. Meanwhile, novel model created from combination of mobility dynamics in the cyberworld and a traditional contagion model can better capture the characteristics of modern civil unrests and other contagion-like phenomena than the original one.

  2. On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction.

    Directory of Open Access Journals (Sweden)

    Julien Becker

    Full Text Available Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix together with the CSP (cysteine separation profile are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of [Formula: see text] on the benchmark dataset SPX[Formula: see text], which corresponds to

  3. Adaptive evolution of facial colour patterns in Neotropical primates.

    Science.gov (United States)

    Santana, Sharlene E; Lynch Alfaro, Jessica; Alfaro, Michael E

    2012-06-07

    The rich diversity of primate faces has interested naturalists for over a century. Researchers have long proposed that social behaviours have shaped the evolution of primate facial diversity. However, the primate face constitutes a unique structure where the diverse and potentially competing functions of communication, ecology and physiology intersect, and the major determinants of facial diversity remain poorly understood. Here, we provide the first evidence for an adaptive role of facial colour patterns and pigmentation within Neotropical primates. Consistent with the hypothesis that facial patterns function in communication and species recognition, we find that species living in smaller groups and in sympatry with a higher number of congener species have evolved more complex patterns of facial colour. The evolution of facial pigmentation and hair length is linked to ecological factors, and ecogeographical rules related to UV radiation and thermoregulation are met by some facial regions. Our results demonstrate the interaction of behavioural and ecological factors in shaping one of the most outstanding facial diversities of any mammalian lineage.

  4. Image Correlation Pattern Optimization for Micro-Scale In-Situ Strain Measurements

    Science.gov (United States)

    Bomarito, G. F.; Hochhalter, J. D.; Cannon, A. H.

    2016-01-01

    -matched shape functions. An important implication, as discussed by Sutton et al., is that in the presence of highly localized deformations (e.g., crack fronts), error can be reduced by minimizing the subset size. In other words, smaller subsets allow the more accurate resolution of localized deformations. Contrarily, the choice of optimal subset size has been widely studied and a general consensus is that larger subsets with more information content are less prone to random error. Thus, an optimal subset size balances the systematic error from under matched deformations with random error from measurement noise. The alternative approach pursued in the current work is to choose a small subset size and optimize the information content within (i.e., optimizing an applied DIC pattern), rather than finding an optimal subset size. In the literature, many pattern quality metrics have been proposed, e.g., sum of square intensity gradient (SSSIG), mean subset fluctuation, gray level co-occurrence, autocorrelation-based metrics, and speckle-based metrics. The majority of these metrics were developed to quantify the quality of common pseudo-random patterns after they have been applied, and were not created with the intent of pattern generation. As such, it is found that none of the metrics examined in this study are fit to be the objective function of a pattern generation optimization. In some cases, such as with speckle-based metrics, application to pixel by pixel patterns is ill-conditioned and requires somewhat arbitrary extensions. In other cases, such as with the SSSIG, it is shown that trivial solutions exist for the optimum of the metric which are ill-suited for DIC (such as a checkerboard pattern). In the current work, a multi-metric optimization method is proposed whereby quality is viewed as a combination of individual quality metrics. Specifically, SSSIG and two auto-correlation metrics are used which have generally competitive objectives. Thus, each metric could be viewed as a

  5. 76 FR 58520 - Proposed Collection; Comment Request; Cancer Risk in U.S. Radiologic Technologists: Fourth Survey...

    Science.gov (United States)

    2011-09-21

    ... carcinogenesis in women. The fourth survey will be administered by mail to approximately 93,000 living and... new cancers and other disease outcomes, detailed work patterns and practices from technologists who... following points: (1) Whether the proposed collection of information is necessary for the proper performance...

  6. Model Building – A Circular Approach to Evaluate Multidimensional Patterns and Operationalized Procedures

    Directory of Open Access Journals (Sweden)

    Franz HAAS

    2017-12-01

    Full Text Available Managers operate in highly different fields. Decision-making can be based on models reflecting in part these differences. The challenge is to connect the respective models without too great a disruption. A threefold procedural approach is proposed by chaining a scheme of modeling in a complex field to an operationalized model to statistical multivariate methods. Multivariate pattern-detecting methods offer the chance to evaluate patterns within the complex field partly. This step completes the cycle of research and improved models can be used in a further cycle.

  7. Face Recognition Using Local Quantized Patterns and Gabor Filters

    Science.gov (United States)

    Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

    2015-05-01

    The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.

  8. A Novel Biped Pattern Generator Based on Extended ZMP and Extended Cart-Table Model

    Directory of Open Access Journals (Sweden)

    Guangbin Sun

    2015-07-01

    Full Text Available This paper focuses on planning patterns for biped walking on complex terrains. Two problems are solved: ZMP (zero moment point cannot be used on uneven terrain, and the conventional cart-table model does not allow vertical CM (centre of mass motion. For the ZMP definition problem, we propose the extended ZMP (EZMP concept as an extension of ZMP to uneven terrains. It can be used to judge dynamic balance on universal terrains. We achieve a deeper insight into the connection and difference between ZMP and EZMP by adding different constraints. For the model problem, we extend the cart-table model by using a dynamic constraint instead of constant height constraint, which results in a mathematically symmetric set of three equations. In this way, the vertical motion is enabled and the resultant equations are still linear. Based on the extended ZMP concept and extended cart-table model, a biped pattern generator using triple preview controllers is constructed and implemented simultaneously to three dimensions. Using the proposed pattern generator, the Atlas robot is simulated. The simulation results show the robot can walk stably on rather complex terrains by accurately tracking extended ZMP.

  9. A More Realistic Lateral Load Pattern for Design of Reinforced Concrete Buildings with Moment Frames and Shear Walls

    International Nuclear Information System (INIS)

    Hosseini, Mahmood; Khosahmadi, Arash

    2008-01-01

    In this research it has been tried to find a more realistic distribution pattern for the seismic load in reinforced concrete (R/C) buildings, having moment frames with shear walls as their lateral resisting system, by using Nonlinear Time History Analyses (NLTHA). Having shear wall as lateral load bearing system decreases the effect of infill walls in the seismic behavior of the building, and therefore the case of buildings with shear walls has been considered for this study as the first stage of the studies on lateral load patterns for R/C buildings. For this purpose, by assuming three different numbers of bays in each direction and also three different numbers of stories for the buildings, several R/C buildings, have been studied. At first, the buildings have been designed by the Iranian National Code for R/C Buildings. Then they have been analyzed by a NLTHA software using the accelerograms of some well-known earthquakes. The used accelerograms have been also scaled to various levels of peak ground acceleration (PGA) such as 0.35 g, 0.50 g, and 0.70 g, to find out the effect of PGA in the seismic response. Numerical results have shown that firstly the values of natural period of the building and their shear force values, calculated by the code, are not appropriate in all cases. Secondly, it has been found out that the real lateral load pattern is quite different with the one suggested by the seismic code. Based on the NLTHA results a new lateral load pattern has been suggested for this kind of buildings, in the form of some story-dependent modification factors applied to the existing code formula. The effects of building's natural period, as well as its number of stories, are taken into account explicitly in the proposed new load pattern. The proposed load pattern has been employed to redesign the buildings and again by NLTHA the real lateral load distribution in each case has been obtained which has shown very good agreement with the proposed pattern

  10. Pseudo-stokes vector from complex signal representation of a speckle pattern and its applications to micro-displacement measurement

    DEFF Research Database (Denmark)

    Wang, W.; Ishijima, R.; Matsuda, A.

    2010-01-01

    As an improvement of the intensity correlation used widely in conventional electronic speckle photography, we propose a new technique for displacement measurement based on correlating Stokes-like parameters derivatives for transformed speckle patterns. The method is based on a Riesz transform of ...... are presented that demonstrate the validity and advantage of the proposed pseudo-Stokes vector correlation technique over conventional intensity correlation technique....... of the intensity speckle pattern, which converts the original real-valued signal into a complex signal. In closest analogy to the polarisation of a vector wave, the Stokes-like vector constructed from the spatial derivative of the generated complex signal has been applied for correlation. Experimental results...

  11. Theoretical consideration of the use of mode entangled states to beat the minimal period of an interference pattern

    International Nuclear Information System (INIS)

    Podoshvedov, Sergey A

    2005-01-01

    We propose to use multi-photon mode entangled states to beat the minimal period of an interference pattern. Using the multi-photon mode entangled states, we show that it is possible to observe an interference effect with a period of minimum size λ/2N in an N-photon absorbing substrate. In the framework of the method developed, we propose a simple scheme for a quantum encoder with a two-photon quantum channel for producing a desired N-photon mode entangled state on which to write an interference pattern with a smaller period, as compared with the one in the case of the use of classical light

  12. Pattern Recognition of Gene Expression with Singular Spectrum Analysis

    Directory of Open Access Journals (Sweden)

    Hossein Hassani

    2014-07-01

    Full Text Available Drosophila segmentation as a model organism is one of the most highly studied. Among many maternal segmentation coordinate genes, bicoid protein pattern plays a significant role during Drosophila embryogenesis, since this gradient determines most aspects of head and thorax development. Despite the fact that several models have been proposed to describe the bicoid gradient, due to its association with considerable error, each can only partially explain bicoid characteristics. In this paper, a modified version of singular spectrum analysis is examined for filtering and extracting the bicoid gene expression signal. The results with strong evidence indicate that the proposed technique is able to remove noise more effectively and can be considered as a promising method for filtering gene expression measurements for other applications.

  13. Directed self-assembly of block copolymers for use in bit patterned media fabrication

    International Nuclear Information System (INIS)

    Griffiths, Rhys Alun; Vijayaraghavan, Aravind; Thomson, Thomas; Williams, Aled; Oakland, Chloe; Roberts, Jonathan

    2013-01-01

    Reduction of the bit size in conventional magnetic recording media is becoming increasingly difficult due to the superparamagnetic limit. Bit patterned media (BPM) has been proposed as a replacement technology as it will enable hard disk areal densities to increase past 1 Tb in −2 . Block copolymer directed self-assembly (BCP DSA) is the leading candidate for forming BPM due to its ability to create uniform patterns over macroscopic areas. Here we review the latest research into two different BCP DSA techniques: graphoepitaxy and chemoepitaxy (or chemical prepatterning). In addition to assessing their potential for forming high density bit patterns, we also review current approaches using these techniques for forming servo patterns, which are required for hard disk drive (HDD) operation. Finally, we review the current state of UV nanoimprint lithography, which is the favoured technique for enabling mass production of BPM HDDs. (topical review)

  14. Pseudo-random arranged color filter array for controlling moiré patterns in display.

    Science.gov (United States)

    Zhou, Yangui; Fan, Hang; An, Sengzhong; Li, Juntao; Wang, Jiahui; Zhou, Jianying; Liu, Yikun

    2015-11-16

    Optical display quality can be degraded by the appearance of moiré pattern occurring in a display system consisting of a basic matrix superimposed with a functional structured optical layer. We propose in this paper a novel pseudo-random arranged color filter array with the table number arranged with an optimal design scenario. We show that the moiré pattern can be significantly reduced with the introduction of the special color filter array. The idea is tested with an experiment that gives rise to a substantially reduced moiré pattern in a display system. It is believed that the novel functional optical structures have significant impact to complex structured display system in general and to the autostereoscopic and integrated display systems in particular.

  15. Unstable patterns and robust synchronization in a model of motor pathway in birdsong

    International Nuclear Information System (INIS)

    Moukam Kakmeni, F.M.; Bowong, S.; Nana, L.; Kofane, T.C.

    2006-10-01

    This paper investigates the fundamental dynamical mechanism responsible for transition to chaos in periodically modulated Duffing-Van der Pol oscillator. It is shown that a modulationally unstable pattern appears into an initially stable motionless state. A further spatiotemporal transition occurs with a sharp interface from the selected stable pattern to a stabilized pattern or chaotic state. Also, the synchronization of the chaotic state of the model is investigated. The results are discussed in the context of generalized synchronization. The main idea is to construct an augmented dynamical system from the synchronization error system, which is itself uncertain. The advantage of this method over existing results is that the synchronization time is explicitly computed. Numerical simulations are provided to verify the operation of the proposed algorithm. (author)

  16. Privacy transparency patterns

    NARCIS (Netherlands)

    Siljee B.I.J.

    2015-01-01

    This paper describes two privacy patterns for creating privacy transparency: the Personal Data Table pattern and the Privacy Policy Icons pattern, as well as a full overview of privacy transparency patterns. It is a first step in creating a full set of privacy design patterns, which will aid

  17. Visual guidance of forward flight in hummingbirds reveals control based on image features instead of pattern velocity.

    Science.gov (United States)

    Dakin, Roslyn; Fellows, Tyee K; Altshuler, Douglas L

    2016-08-02

    Information about self-motion and obstacles in the environment is encoded by optic flow, the movement of images on the eye. Decades of research have revealed that flying insects control speed, altitude, and trajectory by a simple strategy of maintaining or balancing the translational velocity of images on the eyes, known as pattern velocity. It has been proposed that birds may use a similar algorithm but this hypothesis has not been tested directly. We examined the influence of pattern velocity on avian flight by manipulating the motion of patterns on the walls of a tunnel traversed by Anna's hummingbirds. Contrary to prediction, we found that lateral course control is not based on regulating nasal-to-temporal pattern velocity. Instead, birds closely monitored feature height in the vertical axis, and steered away from taller features even in the absence of nasal-to-temporal pattern velocity cues. For vertical course control, we observed that birds adjusted their flight altitude in response to upward motion of the horizontal plane, which simulates vertical descent. Collectively, our results suggest that birds avoid collisions using visual cues in the vertical axis. Specifically, we propose that birds monitor the vertical extent of features in the lateral visual field to assess distances to the side, and vertical pattern velocity to avoid collisions with the ground. These distinct strategies may derive from greater need to avoid collisions in birds, compared with small insects.

  18. Learning to Recognize Patterns: Changes in the Visual Field with Familiarity

    Science.gov (United States)

    Bebko, James M.; Uchikawa, Keiji; Saida, Shinya; Ikeda, Mitsuo

    1995-01-01

    Two studies were conducted to investigate changes which take place in the visual information processing of novel stimuli as they become familiar. Japanese writing characters (Hiragana and Kanji) which were unfamiliar to two native English speaking subjects were presented using a moving window technique to restrict their visual fields. Study time for visual recognition was recorded across repeated sessions, and with varying visual field restrictions. The critical visual field was defined as the size of the visual field beyond which further increases did not improve the speed of recognition performance. In the first study, when the Hiragana patterns were novel, subjects needed to see about half of the entire pattern simultaneously to maintain optimal performance. However, the critical visual field size decreased as familiarity with the patterns increased. These results were replicated in the second study with more complex Kanji characters. In addition, the critical field size decreased as pattern complexity decreased. We propose a three component model of pattern perception. In the first stage a representation of the stimulus must be constructed by the subject, and restricting of the visual field interferes dramatically with this component when stimuli are unfamiliar. With increased familiarity, subjects become able to reconstruct a previous representation from very small, unique segments of the pattern, analogous to the informativeness areas hypothesized by Loftus and Mackworth [J. Exp. Psychol., 4 (1978) 565].

  19. Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern.

    Science.gov (United States)

    Oh, Paul; Lee, Sukho; Kang, Moon Gi

    2017-06-28

    Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method.

  20. Uncovering stable and occasional human mobility patterns: A case study of the Beijing subway

    Science.gov (United States)

    Yong, Nuo; Ni, Shunjiang; Shen, Shifei; Chen, Peng; Ji, Xuewei

    2018-02-01

    There have generally been two kinds of approaches to the empirical study of human mobility. At the group level, some valuable information might be submerged in statistical noise, while due to the diversity of individual purpose and preference, there is still no general statistical regularity of human mobility at the individual level. In this paper, we considered group-level human mobility as the combination of several basic patterns and analyzed the collective mobility by category. Utilizing matrix factorization and correlation analysis, we extracted some of the stable/occasional components from the collective human mobility in the Beijing subway and found that the departure and arrival mobility patterns have different characteristics, both in time and space, under various conditions. We classified individual records into different patterns and analyzed the most likely trip distance by category. The proposed method can decompose stable/occasional mobility patterns from the collective mobility and identify passengers belonging to different patterns, helping us to better understand the origin of different mobility patterns and provide guidance for emergency management of large crowds.

  1. Muscle Sensor Model Using Small Scale Optical Device for Pattern Recognitions

    Directory of Open Access Journals (Sweden)

    Kreangsak Tamee

    2013-01-01

    Full Text Available A new sensor system for measuring contraction and relaxation of muscles by using a PANDA ring resonator is proposed. The small scale optical device is designed and configured to perform the coupling effects between the changes in optical device phase shift and human facial muscle movement, which can be used to form the relationship between optical phase shift and muscle movement. By using the Optiwave and MATLAB programs, the results obtained have shown that the measurement of the contraction and relaxation of muscles can be obtained after the muscle movements, in which the unique pattern of individual muscle movement from facial expression can be established. The obtained simulation results, that is, interference signal patterns, can be used to form the various pattern recognitions, which are useful for the human machine interface and the human computer interface application and discussed in detail.

  2. Entropic measures of individual mobility patterns

    International Nuclear Information System (INIS)

    Gallotti, Riccardo; Bazzani, Armando; Rambaldi, Sandro; Esposti, Mirko Degli

    2013-01-01

    Understanding human mobility from a microscopic point of view may represent a fundamental breakthrough for the development of a statistical physics for cognitive systems and it can shed light on the applicability of macroscopic statistical laws for social systems. Even if the complexity of individual behaviors prevents a true microscopic approach, the introduction of mesoscopic models allows the study of the dynamical properties for the non-stationary states of the considered system. We propose to compute various entropy measures of the individual mobility patterns obtained from GPS data that record the movements of private vehicles in the Florence district, in order to point out new features of human mobility related to the use of time and space and to define the dynamical properties of a stochastic model that could generate similar patterns. Moreover, we can relate the predictability properties of human mobility to the distribution of time passed between two successive trips. Our analysis suggests the existence of a hierarchical structure in the mobility patterns which divides the performed activities into three different categories, according to the time cost, with different information contents. We show that a Markov process defined by using the individual mobility network is not able to reproduce this hierarchy, which seems the consequence of different strategies in the activity choice. Our results could contribute to the development of governance policies for a sustainable mobility in modern cities. (paper)

  3. Atypical mitochondrial inheritance patterns in eukaryotes.

    Science.gov (United States)

    Breton, Sophie; Stewart, Donald T

    2015-10-01

    Mitochondrial DNA (mtDNA) is predominantly maternally inherited in eukaryotes. Diverse molecular mechanisms underlying the phenomenon of strict maternal inheritance (SMI) of mtDNA have been described, but the evolutionary forces responsible for its predominance in eukaryotes remain to be elucidated. Exceptions to SMI have been reported in diverse eukaryotic taxa, leading to the prediction that several distinct molecular mechanisms controlling mtDNA transmission are present among the eukaryotes. We propose that these mechanisms will be better understood by studying the deviations from the predominating pattern of SMI. This minireview summarizes studies on eukaryote species with unusual or rare mitochondrial inheritance patterns, i.e., other than the predominant SMI pattern, such as maternal inheritance of stable heteroplasmy, paternal leakage of mtDNA, biparental and strictly paternal inheritance, and doubly uniparental inheritance of mtDNA. The potential genes and mechanisms involved in controlling mitochondrial inheritance in these organisms are discussed. The linkage between mitochondrial inheritance and sex determination is also discussed, given that the atypical systems of mtDNA inheritance examined in this minireview are frequently found in organisms with uncommon sexual systems such as gynodioecy, monoecy, or andromonoecy. The potential of deviations from SMI for facilitating a better understanding of a number of fundamental questions in biology, such as the evolution of mtDNA inheritance, the coevolution of nuclear and mitochondrial genomes, and, perhaps, the role of mitochondria in sex determination, is considerable.

  4. Dynamical patterns of cattle trade movements.

    Directory of Open Access Journals (Sweden)

    Paolo Bajardi

    Full Text Available Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions.

  5. A Dynamic Control Strategy for Hybrid Electric Vehicles Based on Parameter Optimization for Multiple Driving Cycles and Driving Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Zhenzhen Lei

    2017-01-01

    Full Text Available The driving pattern has an important influence on the parameter optimization of the energy management strategy (EMS for hybrid electric vehicles (HEVs. A new algorithm using simulated annealing particle swarm optimization (SA-PSO is proposed for parameter optimization of both the power system and control strategy of HEVs based on multiple driving cycles in order to realize the minimum fuel consumption without impairing the dynamic performance. Furthermore, taking the unknown of the actual driving cycle into consideration, an optimization method of the dynamic EMS based on driving pattern recognition is proposed in this paper. The simulation verifications for the optimized EMS based on multiple driving cycles and driving pattern recognition are carried out using Matlab/Simulink platform. The results show that compared with the original EMS, the former strategy reduces the fuel consumption by 4.36% and the latter one reduces the fuel consumption by 11.68%. A road test on the prototype vehicle is conducted and the effectiveness of the proposed EMS is validated by the test data.

  6. Preparation of conductive Cu patterns by directly writing using nano-Cu ink

    Energy Technology Data Exchange (ETDEWEB)

    Li, Wei [School of Materials Science and Engineering, Tianjin University, Tianjin 300072 (China); Li, Wenjiang; Wei, Jun [School of Materials Science and Engineering, Tianjin University of Technology, Tianjin 300384 (China); Tan, Junjun [School of Chemical and Materials and Engineering, Hubei University of Technology, Hubei 435003 (China); Chen, Minfang, E-mail: mfchentj@126.com [School of Materials Science and Engineering, Tianjin University of Technology, Tianjin 300384 (China)

    2014-07-01

    Conductive and air-stable Cu patterns were directly made on ordinary photo paper using a roller pen filled with nano-Cu ink, which was mainly composed of metallic Cu nanoparticles (NPs) capped with poly(N-vinylpyrrolidone) (PVP). The nano-Cu NPs were obtained via the reduction of Cu{sup 2+} ions by using an excess of hydrazine and PVP. The low sintering temperature (160 °C) in Ar atmosphere played an important role for the preparation of air-stable Cu patterns. The conductivity of a radio-frequency identification antenna made from nano-Cu ink was tested by a lamp, and its resistivity achieved 13.4 ± 0.4 μΩ cm. The Cu NPs were confirmed by means of X-ray powder diffraction and X-ray photoelectron spectra, and the Cu patterns were characterized by scanning electron microscopy and energy dispersive X-ray spectrometry. A mechanism for the high conductivity of the Cu pattern made from Cu NPs is proposed. - Highlights: • The synthesis of pure Cu is related to the reducing agent and capping agent. • The sintering under Ar atmosphere prevents Cu pattern's rapid oxidation. • The formation of the bulk Cu decreases the resistivity of the Cu pattern.

  7. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    Science.gov (United States)

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  8. Hotspot detection using image pattern recognition based on higher-order local auto-correlation

    Science.gov (United States)

    Maeda, Shimon; Matsunawa, Tetsuaki; Ogawa, Ryuji; Ichikawa, Hirotaka; Takahata, Kazuhiro; Miyairi, Masahiro; Kotani, Toshiya; Nojima, Shigeki; Tanaka, Satoshi; Nakagawa, Kei; Saito, Tamaki; Mimotogi, Shoji; Inoue, Soichi; Nosato, Hirokazu; Sakanashi, Hidenori; Kobayashi, Takumi; Murakawa, Masahiro; Higuchi, Tetsuya; Takahashi, Eiichi; Otsu, Nobuyuki

    2011-04-01

    Below 40nm design node, systematic variation due to lithography must be taken into consideration during the early stage of design. So far, litho-aware design using lithography simulation models has been widely applied to assure that designs are printed on silicon without any error. However, the lithography simulation approach is very time consuming, and under time-to-market pressure, repetitive redesign by this approach may result in the missing of the market window. This paper proposes a fast hotspot detection support method by flexible and intelligent vision system image pattern recognition based on Higher-Order Local Autocorrelation. Our method learns the geometrical properties of the given design data without any defects as normal patterns, and automatically detects the design patterns with hotspots from the test data as abnormal patterns. The Higher-Order Local Autocorrelation method can extract features from the graphic image of design pattern, and computational cost of the extraction is constant regardless of the number of design pattern polygons. This approach can reduce turnaround time (TAT) dramatically only on 1CPU, compared with the conventional simulation-based approach, and by distributed processing, this has proven to deliver linear scalability with each additional CPU.

  9. Three-dimensional cell manipulation and patterning using dielectrophoresis via a multi-layer scaffold structure.

    Science.gov (United States)

    Chu, H K; Huan, Z; Mills, J K; Yang, J; Sun, D

    2015-02-07

    Cell manipulation is imperative to the areas of cellular biology and tissue engineering, providing them a useful tool for patterning cells into cellular patterns for different analyses and applications. This paper presents a novel approach to perform three-dimensional (3D) cell manipulation and patterning with a multi-layer engineered scaffold. This scaffold structure employed dielectrophoresis as the non-contact mechanism to manipulate cells in the 3D domain. Through establishing electric fields via this multi-layer structure, the cells in the medium became polarized and were attracted towards the interior part of the structure, forming 3D cellular patterns. Experiments were conducted to evaluate the manipulation and the patterning processes with the proposed structure. Results show that with the presence of a voltage input, this multi-layer structure was capable of manipulating different types of biological cells examined through dielectrophoresis, enabling automatic cell patterning in the time-scale of minutes. The effects of the voltage input on the resultant cellular pattern were examined and discussed. Viability test was performed after the patterning operation and the results confirmed that majority of the cells remained viable. After 7 days of culture, 3D cellular patterns were observed through SEM. The results suggest that this scaffold and its automated dielectrophoresis-based patterning mechanism can be used to construct artificial tissues for various tissue engineering applications.

  10. Wavefront correction performed by a deformable mirror of arbitrary actuator pattern within a multireflection waveguide.

    Science.gov (United States)

    Ma, Xingkun; Huang, Lei; Bian, Qi; Gong, Mali

    2014-09-10

    The wavefront correction ability of a deformable mirror with a multireflection waveguide was investigated and compared via simulations. By dividing a conventional actuator array into a multireflection waveguide that consisted of single-actuator units, an arbitrary actuator pattern could be achieved. A stochastic parallel perturbation algorithm was proposed to find the optimal actuator pattern for a particular aberration. Compared with conventional an actuator array, the multireflection waveguide showed significant advantages in correction of higher order aberrations.

  11. In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning

    OpenAIRE

    Pegorini, Vinicius; Karam, Leandro Zen; Pitta, Christiano Santos Rocha; Cardoso, Rafael; da Silva, Jean Carlos Cardozo; Kalinowski, Hypolito Jos?; Ribeiro, Richardson; Bertotti, F?bio Luiz; Assmann, Tangriani Simioni

    2015-01-01

    Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for th...

  12. Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

    Directory of Open Access Journals (Sweden)

    Qiang Yu

    Full Text Available A new learning rule (Precise-Spike-Driven (PSD Synaptic Plasticity is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

  13. Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

    Science.gov (United States)

    Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

    2013-01-01

    A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

  14. Arch-pattern based design and aspect-oriented implementation of Readers-Writers concurrent problem

    Directory of Open Access Journals (Sweden)

    Dumitru Ciorbă

    2007-11-01

    Full Text Available The classical problems of concurrent programming start from the design problems of operating systems in the 80-s. But today there are still proposed new solutions for these problems with the help of various design and programming approaches. The present article describes a solution which was designed according to some new object-oriented principles, based on design patterns and proposes two program solutions: firstly - an object-oriented implementation in Java language, the secondly – an aspect-oriented one in AspectJ language.

  15. A supervised learning rule for classification of spatiotemporal spike patterns.

    Science.gov (United States)

    Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

    2016-08-01

    This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

  16. Vision-Based Bicycle Detection Using Multiscale Block Local Binary Pattern

    Directory of Open Access Journals (Sweden)

    Hongyu Hu

    2014-01-01

    Full Text Available Bicycle traffic has heavy proportion among all travel modes in some developing countries, which is crucial for urban traffic control and management as well as facility design. This paper proposes a real-time multiple bicycle detection algorithm based on video. At first, an effective feature called multiscale block local binary pattern (MBLBP is extracted for representing the moving object, which is a well-classified feature to distinguish between bicycles and nonbicycles; then, a cascaded bicycle classifier trained by AdaBoost algorithm is proposed, which has a good computation efficiency. Finally, the method is tested with video sequence captured from the real-world traffic scenario. The bicycles in the test scenario are successfully detected.

  17. Demographic survey around proposed nuclear power plant site in Haryana covering 30 km radius area from the site

    International Nuclear Information System (INIS)

    Garg, V.K.

    2013-01-01

    This study was planned to have a demographic survey of the households living within 30 km radius of the proposed site. Objectives of the present study were to attain the quantitative baseline demographic data around (within 30 km radius) the proposed site of nuclear power plant, zone-wise and sector-wise distribution of the population around proposed site up to a distance of 30 km from the site, to obtain the data on socio-economic, cultural, and religious perspectives of the target populations, to obtain the data on disease/illness pattern in the target population, health status and mortality rate

  18. Tilted dipole model for bias-dependent photoluminescence pattern

    Energy Technology Data Exchange (ETDEWEB)

    Fujieda, Ichiro, E-mail: fujieda@se.ritsumei.ac.jp; Suzuki, Daisuke; Masuda, Taishi [Department of Electrical and Electronic Engineering, Ritsumeikan University, Kusatsu 525-8577 (Japan)

    2014-12-14

    In a guest-host system containing elongated dyes and a nematic liquid crystal, both molecules are aligned to each other. An external bias tilts these molecules and the radiation pattern of the system is altered. A model is proposed to describe this bias-dependent photoluminescence patterns. It divides the liquid crystal/dye layer into sub-layers that contain electric dipoles with specific tilt angles. Each sub-layer emits linearly polarized light. Its radiation pattern is toroidal and is determined by the tilt angle. Its intensity is assumed to be proportional to the power of excitation light absorbed by the sub-layer. This is calculated by the Lambert-Beer's Law. The absorption coefficient is assumed to be proportional to the cross-section of the tilted dipole moment, in analogy to the ellipsoid of refractive index, to evaluate the cross-section for each polarized component of the excitation light. Contributions from all the sub-layers are added to give a final expression for the radiation pattern. Self-absorption is neglected. The model is simplified by reducing the number of sub-layers. Analytical expressions are derived for a simple case that consists of a single layer with tilted dipoles sandwiched by two layers with horizontally-aligned dipoles. All the parameters except for the tilt angle can be determined by measuring transmittance of the excitation light. The model roughly reproduces the bias-dependent photoluminescence patterns of a cell containing 0.5 wt. % coumarin 6. It breaks down at large emission angles. Measured spectral changes suggest that the discrepancy is due to self-absorption and re-emission.

  19. Pattern recognition

    CERN Document Server

    Theodoridis, Sergios

    2003-01-01

    Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

  20. Suppression of fixed pattern noise for infrared image system

    Science.gov (United States)

    Park, Changhan; Han, Jungsoo; Bae, Kyung-Hoon

    2008-04-01

    In this paper, we propose suppression of fixed pattern noise (FPN) and compensation of soft defect for improvement of object tracking in cooled staring infrared focal plane array (IRFPA) imaging system. FPN appears an observable image which applies to non-uniformity compensation (NUC) by temperature. Soft defect appears glittering black and white point by characteristics of non-uniformity for IR detector by time. This problem is very important because it happen serious problem for object tracking as well as degradation for image quality. Signal processing architecture in cooled staring IRFPA imaging system consists of three tables: low, normal, high temperature for reference gain and offset values. Proposed method operates two offset tables for each table. This is method which operates six term of temperature on the whole. Proposed method of soft defect compensation consists of three stages: (1) separates sub-image for an image, (2) decides a motion distribution of object between each sub-image, (3) analyzes for statistical characteristic from each stationary fixed pixel. Based on experimental results, the proposed method shows an improved image which suppresses FPN by change of temperature distribution from an observational image in real-time.