Repetition suppression and multi-voxel pattern similarity differentially track implicit and explicit visual memory.

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Ward, Emily J; Chun, Marvin M; Kuhl, Brice A

2013-09-11

Repeated exposure to a visual stimulus is associated with corresponding reductions in neural activity, particularly within visual cortical areas. It has been argued that this phenomenon of repetition suppression is related to increases in processing fluency or implicit memory. However, repetition of a visual stimulus can also be considered in terms of the similarity of the pattern of neural activity elicited at each exposure--a measure that has recently been linked to explicit memory. Despite the popularity of each of these measures, direct comparisons between the two have been limited, and the extent to which they differentially (or similarly) relate to behavioral measures of memory has not been clearly established. In the present study, we compared repetition suppression and pattern similarity as predictors of both implicit and explicit memory. Using functional magnetic resonance imaging, we scanned 20 participants while they viewed and categorized repeated presentations of scenes. Repetition priming (facilitated categorization across repetitions) was used as a measure of implicit memory, and subsequent scene recognition was used as a measure of explicit memory. We found that repetition priming was predicted by repetition suppression in prefrontal, parietal, and occipitotemporal regions; however, repetition priming was not predicted by pattern similarity. In contrast, subsequent explicit memory was predicted by pattern similarity (across repetitions) in some of the same occipitotemporal regions that exhibited a relationship between priming and repetition suppression; however, explicit memory was not related to repetition suppression. This striking double dissociation indicates that repetition suppression and pattern similarity differentially track implicit and explicit learning.

Neural Global Pattern Similarity Underlies True and False Memories.

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Ye, Zhifang; Zhu, Bi; Zhuang, Liping; Lu, Zhonglin; Chen, Chuansheng; Xue, Gui

2016-06-22

The neural processes giving rise to human memory strength signals remain poorly understood. Inspired by formal computational models that posit a central role of global matching in memory strength, we tested a novel hypothesis that the strengths of both true and false memories arise from the global similarity of an item's neural activation pattern during retrieval to that of all the studied items during encoding (i.e., the encoding-retrieval neural global pattern similarity [ER-nGPS]). We revealed multiple ER-nGPS signals that carried distinct information and contributed differentially to true and false memories: Whereas the ER-nGPS in the parietal regions reflected semantic similarity and was scaled with the recognition strengths of both true and false memories, ER-nGPS in the visual cortex contributed solely to true memory. Moreover, ER-nGPS differences between the parietal and visual cortices were correlated with frontal monitoring processes. By combining computational and neuroimaging approaches, our results advance a mechanistic understanding of memory strength in recognition. What neural processes give rise to memory strength signals, and lead to our conscious feelings of familiarity? Using fMRI, we found that the memory strength of a given item depends not only on how it was encoded during learning, but also on the similarity of its neural representation with other studied items. The global neural matching signal, mainly in the parietal lobule, could account for the memory strengths of both studied and unstudied items. Interestingly, a different global matching signal, originated from the visual cortex, could distinguish true from false memories. The findings reveal multiple neural mechanisms underlying the memory strengths of events registered in the brain. Copyright © 2016 the authors 0270-6474/16/366792-11$15.00/0.

Assessment of Fluctuation Patterns Similarity in Temperature and Vapor Pressure Using Discrete Wavelet Transform

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A. Araghi

2014-12-01

Full Text Available Period and trend are two main effective and important factors in hydro-climatological time series and because of this importance, different methods have been introduced and applied to study of them, until now. Most of these methods are statistical basis and they are classified in the non-parametric tests. Wavelet transform is a mathematical based powerful method which has been widely used in signal processing and time series analysis in recent years. In this research, trend and main periodic patterns similarity in temperature and vapor pressure has been studied in Babolsar, Tehran and Shahroud synoptic stations during 55 years period (from 1956 to 2010, using wavelet method and the sequential Mann-Kendall trend test. The results show that long term fluctuation patterns in temperature and vapor pressure have more correlations in the arid and semi-arid climates, as well as short term oscillation patterns in temperature and vapor pressure in the humid climates, and these dominant periods increase with the aridity of region.

Global Neural Pattern Similarity as a Common Basis for Categorization and Recognition Memory

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Xue, Gui; Love, Bradley C.; Preston, Alison R.; Poldrack, Russell A.

2014-01-01

Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. PMID:24872552

Photonic Crystals with an Eye Pattern Similar to Peacock Tail Feathers

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Minghui Wang

2016-08-01

Full Text Available A facile fabrication of photonic crystals (PCs with an eye pattern similar to peacock tail feathers has been demonstrated by self-assembly of colloidal particles in a sandwich mode. The sandwich mode is formed by superhydrophilic flat substrate sandwiching the poly(styrene-methyl methacrylate-arylic acid (Poly(St-MMA-AA latex suspension (2 wt% by the hydrophobic one. The patterns are characterized by optical microscopy images, reflection spectra, and the relative scanning electronic microscope images. This work will provide beneficial help for the understanding of the self-assembly process of colloidal crystals.

Approach for a Pattern-Based Development of Frugal Innovations

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Anne-Christin Lehner

2018-04-01

Full Text Available Emerging markets have become increasingly interesting for companies from industrialized countries, but the requirements in these markets differ dramatically from those in the companies’ traditional markets. New products and services are demanded – so-called frugal innovations. Since the challenges for the development of frugal innovations are often quite similar – for example, low income of the target customer, poor infrastructure, etc. – the hypothesis appears that the solutions will also be similar. In our earlier TIM Review article (Lehner & Gausemeier, 2016, we showed how solution patterns for frugal innovations can be derived. The article at hand summarizes those findings and supplements an innovation process for frugal innovation using the solution patterns. The validation based on the example of telemedical assistant systems shows the benefit of the pattern-based development of frugal innovations. The article addresses managers and engineers who plan to introduce frugal innovations, as well as university-based researchers interested in the development of frugal innovations.

A Segment-Based Trajectory Similarity Measure in the Urban Transportation Systems.

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Mao, Yingchi; Zhong, Haishi; Xiao, Xianjian; Li, Xiaofang

2017-03-06

With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment-based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.

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

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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.

Neural pattern similarity underlies the mnemonic advantages for living words.

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Xiao, Xiaoqian; Dong, Qi; Chen, Chuansheng; Xue, Gui

2016-06-01

It has been consistently shown that words representing living things are better remembered than words representing nonliving things, yet the underlying cognitive and neural mechanisms have not been clearly elucidated. The present study used both univariate and multivariate pattern analyses to examine the hypotheses that living words are better remembered because (1) they draw more attention and/or (2) they share more overlapping semantic features. Subjects were asked to study a list of living and nonliving words during a semantic judgment task. An unexpected recognition test was administered 30 min later. We found that subjects recognized significantly more living words than nonliving words. Results supported the overlapping semantic feature hypothesis by showing that (a) semantic ratings showed greater semantic similarity for living words than for nonliving words, (b) there was also significantly greater neural global pattern similarity (nGPS) for living words than for nonliving words in the posterior portion of left parahippocampus (LpPHG), (c) the nGPS in the LpPHG reflected the rated semantic similarity, and also mediated the memory differences between two semantic categories, and (d) greater univariate activation was found for living words than for nonliving words in the left hippocampus (LHIP), which mediated the better memory performance for living words and might reflect greater semantic context binding. In contrast, although living words were processed faster and elicited a stronger activity in the dorsal attention network, these differences did not mediate the animacy effect in memory. Taken together, our results provide strong support to the overlapping semantic features hypothesis, and emphasize the important role of semantic organization in episodic memory encoding. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pattern-based information portal for business plan co-creation

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Bontchev, Boyan; Ruskov, Petko; Tanev, Stoyan

2011-03-01

Creation of business plans helps entrepreneurs in managing identification of business opportunities and committing necessary resources for process evolution. Applying patterns in business plan creation facilitates the identification of effective solutions that were adopted in the past and may provide a basis for adopting similar solutions in the future within given business context. The article presents the system design of an information portal for business plan co-creation based on patterns. The portal is going to provide start-up and entrepreneurs with ready-to-modify business plan patterns in order to help them in development of effective and efficient business plans. It will facilitate entrepreneurs in co-experimenting and co-learning more frequently and faster. Moreover, the paper focuses on the software architecture of the pattern based portal and explains the functionality of its modules, namely the pattern designer, pattern repository services and agent-based pattern implementers. It explains their role for business process co-creation, storing and managing patterns described formally, and selecting patterns best suited for specific business case. Thus, innovative entrepreneurs will be guided by the portal in co-writing winning business plans and staying competitive in the present day dynamic globalized environment.

Pattern formation in individual-based systems with time-varying parameters

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Ashcroft, Peter; Galla, Tobias

2013-12-01

We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

Pattern-based information portal for business plan co-creation

DEFF Research Database (Denmark)

Tanev, Stoyan; Bontchev, Boyan; Ruskov, Petko

2010-01-01

in order to help them in development of effective and efficient business plans. It will facilitate entrepreneurs in co-experimenting and co-learning more frequently and faster. Moreover, the paper focuses on the software architecture of the pattern based portal and explains the functionality of its modules......Creation of business plans helps entrepreneurs in managing identification of business opportunities and committing necessary resources for process evolution. Applying patterns in business plan creation facilitates the identification of effective solutions that were adopted in the past and may...... provide a basis for adopting similar solutions in the future within given business context. The article presents the system design of an information portal for business plan cocreation based on patterns. The portal is going to provide start-up and entrepreneurs with ready-to-modify business plan patterns...

SpolSimilaritySearch - A web tool to compare and search similarities between spoligotypes of Mycobacterium tuberculosis complex.

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Couvin, David; Zozio, Thierry; Rastogi, Nalin

2017-07-01

Spoligotyping is one of the most commonly used polymerase chain reaction (PCR)-based methods for identification and study of genetic diversity of Mycobacterium tuberculosis complex (MTBC). Despite its known limitations if used alone, the methodology is particularly useful when used in combination with other methods such as mycobacterial interspersed repetitive units - variable number of tandem DNA repeats (MIRU-VNTRs). At a worldwide scale, spoligotyping has allowed identification of information on 103,856 MTBC isolates (corresponding to 98049 clustered strains plus 5807 unique isolates from 169 countries of patient origin) contained within the SITVIT2 proprietary database of the Institut Pasteur de la Guadeloupe. The SpolSimilaritySearch web-tool described herein (available at: http://www.pasteur-guadeloupe.fr:8081/SpolSimilaritySearch) incorporates a similarity search algorithm allowing users to get a complete overview of similar spoligotype patterns (with information on presence or absence of 43 spacers) in the aforementioned worldwide database. This tool allows one to analyze spread and evolutionary patterns of MTBC by comparing similar spoligotype patterns, to distinguish between widespread, specific and/or confined patterns, as well as to pinpoint patterns with large deleted blocks, which play an intriguing role in the genetic epidemiology of M. tuberculosis. Finally, the SpolSimilaritySearch tool also provides with the country distribution patterns for each queried spoligotype. Copyright © 2017 Elsevier Ltd. All rights reserved.

A New Similarity Measure between Intuitionistic Fuzzy Sets and Its Application to Pattern Recognition

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Yafei Song

2014-01-01

Full Text Available As a generation of ordinary fuzzy set, the concept of intuitionistic fuzzy set (IFS, characterized both by a membership degree and by a nonmembership degree, is a more flexible way to cope with the uncertainty. Similarity measures of intuitionistic fuzzy sets are used to indicate the similarity degree between intuitionistic fuzzy sets. Although many similarity measures for intuitionistic fuzzy sets have been proposed in previous studies, some of those cannot satisfy the axioms of similarity or provide counterintuitive cases. In this paper, a new similarity measure and weighted similarity measure between IFSs are proposed. It proves that the proposed similarity measures satisfy the properties of the axiomatic definition for similarity measures. Comparison between the previous similarity measures and the proposed similarity measure indicates that the proposed similarity measure does not provide any counterintuitive cases. Moreover, it is demonstrated that the proposed similarity measure is capable of discriminating difference between patterns.

Examining the relationship between free recall and immediate serial recall: Similar patterns of rehearsal and similar effects of word length, presentation rate, and articulatory suppression.

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Bhatarah, Parveen; Ward, Geoff; Smith, Jessica; Hayes, Louise

2009-07-01

In five experiments, rehearsal and recall phenomena were examined using the free recall and immediate serial recall (ISR) tasks. In Experiment 1, participants were presented with lists of eight words, were precued or postcued to respond using free recall or ISR, and rehearsed out loud during presentation. The patterns of rehearsal were similar in all the conditions, and there was little difference between recall in the precued and postcued conditions. In Experiment 2, both free recall and ISR were sensitive to word length and presentation rate and showed similar patterns of rehearsal. In Experiment 3, both tasks were sensitive to word length and articulatory suppression. The word length effects generalized to 6-item (Experiment 4) and 12-item (Experiment 5) lists. These findings suggest that the two tasks are underpinned by highly similar rehearsal and recall processes.

Behavioral similarity measurement based on image processing for robots that use imitative learning

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Sterpin B., Dante G.; Martinez S., Fernando; Jacinto G., Edwar

2017-02-01

In the field of the artificial societies, particularly those are based on memetics, imitative behavior is essential for the development of cultural evolution. Applying this concept for robotics, through imitative learning, a robot can acquire behavioral patterns from another robot. Assuming that the learning process must have an instructor and, at least, an apprentice, the fact to obtain a quantitative measurement for their behavioral similarity, would be potentially useful, especially in artificial social systems focused on cultural evolution. In this paper the motor behavior of both kinds of robots, for two simple tasks, is represented by 2D binary images, which are processed in order to measure their behavioral similarity. The results shown here were obtained comparing some similarity measurement methods for binary images.

Case-based reasoning diagnostic technique based on multi-attribute similarity

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Makoto, Takahashi [Tohoku University, Miyagi (Japan); Akio, Gofuku [Okayama University, Okayamaa (Japan)

2014-08-15

Case-based diagnostic technique has been developed based on the multi-attribute similarity. Specific feature of the developed system is to use multiple attributes of process signals for similarity evaluation to retrieve a similar case stored in a case base. The present technique has been applied to the measurement data from Monju with some simulated anomalies. The results of numerical experiments showed that the present technique can be utilizes as one of the methods for a hybrid-type diagnosis system.

Similar Running Economy With Different Running Patterns Along the Aerial-Terrestrial Continuum.

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Lussiana, Thibault; Gindre, Cyrille; Hébert-Losier, Kim; Sagawa, Yoshimasa; Gimenez, Philippe; Mourot, Laurent

2017-04-01

No unique or ideal running pattern is the most economical for all runners. Classifying the global running patterns of individuals into 2 categories (aerial and terrestrial) using the Volodalen method could permit a better understanding of the relationship between running economy (RE) and biomechanics. The main purpose was to compare the RE of aerial and terrestrial runners. Two coaches classified 58 runners into aerial (n = 29) or terrestrial (n = 29) running patterns on the basis of visual observations. RE, muscle activity, kinematics, and spatiotemporal parameters of both groups were measured during a 5-min run at 12 km/h on a treadmill. Maximal oxygen uptake (V̇O 2 max) and peak treadmill speed (PTS) were assessed during an incremental running test. No differences were observed between aerial and terrestrial patterns for RE, V̇O 2 max, and PTS. However, at 12 km/h, aerial runners exhibited earlier gastrocnemius lateralis activation in preparation for contact, less dorsiflexion at ground contact, higher coactivation indexes, and greater leg stiffness during stance phase than terrestrial runners. Terrestrial runners had more pronounced semitendinosus activation at the start and end of the running cycle, shorter flight time, greater leg compression, and a more rear-foot strike. Different running patterns were associated with similar RE. Aerial runners appear to rely more on elastic energy utilization with a rapid eccentric-concentric coupling time, whereas terrestrial runners appear to propel the body more forward rather than upward to limit work against gravity. Excluding runners with a mixed running pattern from analyses did not affect study interpretation.

Average correlation clustering algorithm (ACCA) for grouping of co-regulated genes with similar pattern of variation in their expression values.

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Bhattacharya, Anindya; De, Rajat K

2010-08-01

Distance based clustering algorithms can group genes that show similar expression values under multiple experimental conditions. They are unable to identify a group of genes that have similar pattern of variation in their expression values. Previously we developed an algorithm called divisive correlation clustering algorithm (DCCA) to tackle this situation, which is based on the concept of correlation clustering. But this algorithm may also fail for certain cases. In order to overcome these situations, we propose a new clustering algorithm, called average correlation clustering algorithm (ACCA), which is able to produce better clustering solution than that produced by some others. ACCA is able to find groups of genes having more common transcription factors and similar pattern of variation in their expression values. Moreover, ACCA is more efficient than DCCA with respect to the time of execution. Like DCCA, we use the concept of correlation clustering concept introduced by Bansal et al. ACCA uses the correlation matrix in such a way that all genes in a cluster have the highest average correlation values with the genes in that cluster. We have applied ACCA and some well-known conventional methods including DCCA to two artificial and nine gene expression datasets, and compared the performance of the algorithms. The clustering results of ACCA are found to be more significantly relevant to the biological annotations than those of the other methods. Analysis of the results show the superiority of ACCA over some others in determining a group of genes having more common transcription factors and with similar pattern of variation in their expression profiles. Availability of the software: The software has been developed using C and Visual Basic languages, and can be executed on the Microsoft Windows platforms. The software may be downloaded as a zip file from http://www.isical.ac.in/~rajat. Then it needs to be installed. Two word files (included in the zip file) need to

Link-Based Similarity Measures Using Reachability Vectors

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Seok-Ho Yoon

2014-01-01

Full Text Available We present a novel approach for computing link-based similarities among objects accurately by utilizing the link information pertaining to the objects involved. We discuss the problems with previous link-based similarity measures and propose a novel approach for computing link based similarities that does not suffer from these problems. In the proposed approach each target object is represented by a vector. Each element of the vector corresponds to all the objects in the given data, and the value of each element denotes the weight for the corresponding object. As for this weight value, we propose to utilize the probability of reaching from the target object to the specific object, computed using the “Random Walk with Restart” strategy. Then, we define the similarity between two objects as the cosine similarity of the two vectors. In this paper, we provide examples to show that our approach does not suffer from the aforementioned problems. We also evaluate the performance of the proposed methods in comparison with existing link-based measures, qualitatively and quantitatively, with respect to two kinds of data sets, scientific papers and Web documents. Our experimental results indicate that the proposed methods significantly outperform the existing measures.

A GEOMETRICAL SIMILARITY PATTERN AS AN EXPERIMENTAL MODEL FOR SHAPES IN ARCHITECTURAL HERITAGE: A CASE STUDY OF THE BASE OF THE PILLARS IN THE CATHEDRAL OF SEVILLE AND THE CHURCH OF SANTIAGO IN JEREZ, SPAIN

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J. J. Moyano

2017-02-01

Full Text Available This paper proposes a procedure for the search of a geometrical similarity pattern in architectural heritage by means of calculating probability indexes to support hypotheses initially endorsed by documentary sources. The buildings analysed are the Cathedral of Seville and the Church of Santiago, in Jerez, Spain. The 3D models of their selected pillars are obtained by means of Terrestrial Laser Scanning (TLS, Optical Scanning (OS and photogrammetry through image-based modelling software (SFM-IBM. To this end, a procedure for the comparison of shapes is established. It is based on similarity statistics, the determination of homologous points and the agreement of characteristic sections. Here, two key aspects are considered: on the one hand, the metric standpoint; on the other hand, historical-graphical features of the 3D models: composition, techniques, styles, and historical-graphical documentary sources. Thus, putting aside the mere dimensional analysis, the sections are compared with graphical patterns and models of which the same authorship – stonemasons working in that age – is accurately known. As a result, the outcomes of this research reveal the geometrical similarity between the elements of the pillars of the Cathedral of Seville and the Church of Santiago.

Generalized sample entropy analysis for traffic signals based on similarity measure

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Shang, Du; Xu, Mengjia; Shang, Pengjian

2017-05-01

Sample entropy is a prevailing method used to quantify the complexity of a time series. In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as traffic signals. The method based on similarity distance presents a different way of signals patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic data and traffic signals for providing the comparative study, which is provided to show the power of the new method. Compared with previous sample entropy and surrogate data analysis, the new method has two main advantages. The first one is that it overcomes the limitation about the relationship between the dimension parameter and the length of series. The second one is that the modified sample entropy functions can be used to quantitatively distinguish time series from different complex systems by the similar measure.

Phishing Detection: Analysis of Visual Similarity Based Approaches

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Ankit Kumar Jain

2017-01-01

Full Text Available Phishing is one of the major problems faced by cyber-world and leads to financial losses for both industries and individuals. Detection of phishing attack with high accuracy has always been a challenging issue. At present, visual similarities based techniques are very useful for detecting phishing websites efficiently. Phishing website looks very similar in appearance to its corresponding legitimate website to deceive users into believing that they are browsing the correct website. Visual similarity based phishing detection techniques utilise the feature set like text content, text format, HTML tags, Cascading Style Sheet (CSS, image, and so forth, to make the decision. These approaches compare the suspicious website with the corresponding legitimate website by using various features and if the similarity is greater than the predefined threshold value then it is declared phishing. This paper presents a comprehensive analysis of phishing attacks, their exploitation, some of the recent visual similarity based approaches for phishing detection, and its comparative study. Our survey provides a better understanding of the problem, current solution space, and scope of future research to deal with phishing attacks efficiently using visual similarity based approaches.

Diversification patterns in cosmopolitan earthworms: similar mode but different tempo.

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Fernández, Rosa; Novo, Marta; Marchán, Daniel F; Díaz Cosín, Darío J

2016-01-01

Comparative phylogeography of widespread species that span the same geographic areas can elucidate the influence of historical events on current patterns of biodiversity, identify patterns of co-vicariance, and therefore aid the understanding of general evolutionary processes. Soil-dwelling animals present characteristics that make them suitable for testing the effect of the palaeogeographical events on their distribution and diversification, such as their low vagility and population structure. In this study, we shed light on the spatial lineage diversification and cladogenesis of two widely-distributed cosmopolitan and invasive earthworms (Aporrectodea rosea and A. trapezoides) in their putative ancestral area of origin, the Western Palearctic, and a few populations in North America. Molecular analyses were conducted on mitochondrial and nuclear markers from 220 (A. rosea) and 198 (A. trapezoides) individuals collected in 56 and 57 localities, respectively. We compared the lineage diversification pattern, genetic variability and cladogenesis in both species. Our findings showed that both species underwent a similar diversification from the Western Mediterranean plates to (i) Northern Europe and (ii) the Iberian Peninsula, establishing their two main lineages. Their diversification was in concordance with the main palaeogeographical events in the Iberian Peninsula and Western Mediterranean, followed by a later colonization of North America from individuals derived exclusively from the Eurosiberian lineage. Their diversification occurred at different times, with the diversification of A. rosea being potentially more ancient. Cladogenesis in both species seems to have been modelled only by the Mediterranean plate shifts, ignoring historical climatic oscillations such as the Messinian salinity crisis. Their high genetic variability, strong population structure, lack of gene flow and stepping-stone-like cladogenesis suggest the existence of different cryptic lineages

Similar Symmetries: The Role of Wallpaper Groups in Perceptual Texture Similarity

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Fraser Halley

2011-05-01

Full Text Available Periodic patterns and symmetries are striking visual properties that have been used decoratively around the world throughout human history. Periodic patterns can be mathematically classified into one of 17 different Wallpaper groups, and while computational models have been developed which can extract an image's symmetry group, very little work has been done on how humans perceive these patterns. This study presents the results from a grouping experiment using stimuli from the different wallpaper groups. We find that while different images from the same wallpaper group are perceived as similar to one another, not all groups have the same degree of self-similarity. The similarity relationships between wallpaper groups appear to be dominated by rotations.

Domain similarity based orthology detection.

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Bitard-Feildel, Tristan; Kemena, Carsten; Greenwood, Jenny M; Bornberg-Bauer, Erich

2015-05-13

Orthologous protein detection software mostly uses pairwise comparisons of amino-acid sequences to assert whether two proteins are orthologous or not. Accordingly, when the number of sequences for comparison increases, the number of comparisons to compute grows in a quadratic order. A current challenge of bioinformatic research, especially when taking into account the increasing number of sequenced organisms available, is to make this ever-growing number of comparisons computationally feasible in a reasonable amount of time. We propose to speed up the detection of orthologous proteins by using strings of domains to characterize the proteins. We present two new protein similarity measures, a cosine and a maximal weight matching score based on domain content similarity, and new software, named porthoDom. The qualities of the cosine and the maximal weight matching similarity measures are compared against curated datasets. The measures show that domain content similarities are able to correctly group proteins into their families. Accordingly, the cosine similarity measure is used inside porthoDom, the wrapper developed for proteinortho. porthoDom makes use of domain content similarity measures to group proteins together before searching for orthologs. By using domains instead of amino acid sequences, the reduction of the search space decreases the computational complexity of an all-against-all sequence comparison. We demonstrate that representing and comparing proteins as strings of discrete domains, i.e. as a concatenation of their unique identifiers, allows a drastic simplification of search space. porthoDom has the advantage of speeding up orthology detection while maintaining a degree of accuracy similar to proteinortho. The implementation of porthoDom is released using python and C++ languages and is available under the GNU GPL licence 3 at http://www.bornberglab.org/pages/porthoda .

An inter-comparison of similarity-based methods for organisation and classification of groundwater hydrographs

Science.gov (United States)

Haaf, Ezra; Barthel, Roland

2018-04-01

Classification and similarity based methods, which have recently received major attention in the field of surface water hydrology, namely through the PUB (prediction in ungauged basins) initiative, have not yet been applied to groundwater systems. However, it can be hypothesised, that the principle of "similar systems responding similarly to similar forcing" applies in subsurface hydrology as well. One fundamental prerequisite to test this hypothesis and eventually to apply the principle to make "predictions for ungauged groundwater systems" is efficient methods to quantify the similarity of groundwater system responses, i.e. groundwater hydrographs. In this study, a large, spatially extensive, as well as geologically and geomorphologically diverse dataset from Southern Germany and Western Austria was used, to test and compare a set of 32 grouping methods, which have previously only been used individually in local-scale studies. The resulting groupings are compared to a heuristic visual classification, which serves as a baseline. A performance ranking of these classification methods is carried out and differences in homogeneity of grouping results were shown, whereby selected groups were related to hydrogeological indices and geological descriptors. This exploratory empirical study shows that the choice of grouping method has a large impact on the object distribution within groups, as well as on the homogeneity of patterns captured in groups. The study provides a comprehensive overview of a large number of grouping methods, which can guide researchers when attempting similarity-based groundwater hydrograph classification.

A Feature-Based Structural Measure: An Image Similarity Measure for Face Recognition

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Noor Abdalrazak Shnain

2017-08-01

Full Text Available Facial recognition is one of the most challenging and interesting problems within the field of computer vision and pattern recognition. During the last few years, it has gained special attention due to its importance in relation to current issues such as security, surveillance systems and forensics analysis. Despite this high level of attention to facial recognition, the success is still limited by certain conditions; there is no method which gives reliable results in all situations. In this paper, we propose an efficient similarity index that resolves the shortcomings of the existing measures of feature and structural similarity. This measure, called the Feature-Based Structural Measure (FSM, combines the best features of the well-known SSIM (structural similarity index measure and FSIM (feature similarity index measure approaches, striking a balance between performance for similar and dissimilar images of human faces. In addition to the statistical structural properties provided by SSIM, edge detection is incorporated in FSM as a distinctive structural feature. Its performance is tested for a wide range of PSNR (peak signal-to-noise ratio, using ORL (Olivetti Research Laboratory, now AT&T Laboratory Cambridge and FEI (Faculty of Industrial Engineering, São Bernardo do Campo, São Paulo, Brazil databases. The proposed measure is tested under conditions of Gaussian noise; simulation results show that the proposed FSM outperforms the well-known SSIM and FSIM approaches in its efficiency of similarity detection and recognition of human faces.

Dynamics based alignment of proteins: an alternative approach to quantify dynamic similarity

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Lyngsø Rune

2010-04-01

Full Text Available Abstract Background The dynamic motions of many proteins are central to their function. It therefore follows that the dynamic requirements of a protein are evolutionary constrained. In order to assess and quantify this, one needs to compare the dynamic motions of different proteins. Comparing the dynamics of distinct proteins may also provide insight into how protein motions are modified by variations in sequence and, consequently, by structure. The optimal way of comparing complex molecular motions is, however, far from trivial. The majority of comparative molecular dynamics studies performed to date relied upon prior sequence or structural alignment to define which residues were equivalent in 3-dimensional space. Results Here we discuss an alternative methodology for comparative molecular dynamics that does not require any prior alignment information. We show it is possible to align proteins based solely on their dynamics and that we can use these dynamics-based alignments to quantify the dynamic similarity of proteins. Our method was tested on 10 representative members of the PDZ domain family. Conclusions As a result of creating pair-wise dynamics-based alignments of PDZ domains, we have found evolutionarily conserved patterns in their backbone dynamics. The dynamic similarity of PDZ domains is highly correlated with their structural similarity as calculated with Dali. However, significant differences in their dynamics can be detected indicating that sequence has a more refined role to play in protein dynamics than just dictating the overall fold. We suggest that the method should be generally applicable.

Gait Patterns in Twins with Cerebral Palsy: Similarities and Development over Time after Multilevel Surgery

Science.gov (United States)

van Drongelen, Stefan; Dreher, Thomas; Heitzmann, Daniel W. W.; Wolf, Sebastian I.

2013-01-01

To examine gait patterns and gait quality, 7 twins with cerebral palsy were measured preoperatively and after surgical intervention. The aim was to study differences and/or similarities in gait between twins, the influence of personal characteristics and birth conditions, and to describe the development of gait over time after single event…

Improved cosine similarity measures of simplified neutrosophic setsfor medical diagnoses

OpenAIRE

Jun Ye

2014-01-01

In pattern recognition and medical diagnosis, similarity measure is an important mathematicaltool. To overcome some disadvantages of existing cosine similarity measures of simplified neutrosophicsets (SNSs) in vector space, this paper proposed improved cosine similarity measures of SNSs based oncosine function, including single valued neutrosophic cosine similarity measures and interval neutro-sophic cosine similarity measures. Then, weighted cosine similarity measures of SNSs were introduced...

Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

Science.gov (United States)

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2017-12-01

The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Similar words analysis based on POS-CBOW language model

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Dongru RUAN

2015-10-01

Full Text Available Similar words analysis is one of the important aspects in the field of natural language processing, and it has important research and application values in text classification, machine translation and information recommendation. Focusing on the features of Sina Weibo's short text, this paper presents a language model named as POS-CBOW, which is a kind of continuous bag-of-words language model with the filtering layer and part-of-speech tagging layer. The proposed approach can adjust the word vectors' similarity according to the cosine similarity and the word vectors' part-of-speech metrics. It can also filter those similar words set on the base of the statistical analysis model. The experimental result shows that the similar words analysis algorithm based on the proposed POS-CBOW language model is better than that based on the traditional CBOW language model.

Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

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Denis Delisle-Rodriguez

2017-11-01

Full Text Available This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs based on Canonical Correlation Analysis (CCA to recognize 40 targets of steady-state visual evoked potential (SSVEP, providing an accuracy (ACC of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly ( p < 0.01 improved for most of the subjects ( A C C ≥ 74.79 % , when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry.

Dietary patterns and colorectal cancer: results from a Canadian population-based study.

Science.gov (United States)

Chen, Zhi; Wang, Peizhong Peter; Woodrow, Jennifer; Zhu, Yun; Roebothan, Barbara; Mclaughlin, John R; Parfrey, Patrick S

2015-01-15

The relationship between major dietary patterns and colorectal cancer (CRC) in other populations largely remains consistent across studies. The objective of the present study is to assess if dietary patterns are associated with the risk of CRC in the population of Newfoundland and Labrador (NL). Data from a population based case-control study in the province of NL were analyzed, including 506 CRC patients (306 men and 200 women) and 673 controls (400 men and 273 women), aged 20-74 years. Dietary habits were assessed by a 169-item food frequency questionnaire (FFQ). Logistic regression analyses were performed to investigate the association between dietary patterns and the CRC risk. Three major dietary patterns were derived using factor analysis, namely a Meat-diet pattern, a Plant-based diet pattern and a Sugary-diet pattern. In combination the three dietary patterns explained 74% of the total variance in food intake. Results suggest that the Meat-diet and the Sugary-diet increased the risk of CRC with corresponding odds ratios (ORs) of 1.84 (95% CI: 1.19-2.86) and 2.26 (95% CI: 1.39-3.66) for people in the highest intake quintile compared to those in the lowest. Whereas plant-based diet pattern decreases the risk of CRC with a corresponding OR of 0.55 (95% CI: 0.35-0.87). Even though odds ratios (ORs) were not always statistically significant, largely similar associations across three cancer sites were found: the proximal colon, the distal colon, and the rectum. The finding that Meat-diet/Sugary-diet patterns increased and Plant-based diet pattern decreased the risk of CRC would guide the promotion of healthy eating for primary prevention of CRC in this population.

Similarity-based Polymorphic Shellcode Detection

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Denis Yurievich Gamayunov

2013-02-01

Full Text Available In the work the method for polymorphic shellcode dedection based on the set of known shellcodes is proposed. The method’s main idea is in sequential applying of deobfuscating transformations to a data analyzed and then recognizing similarity with malware samples. The method has been tested on the sets of shellcodes generated using Metasploit Framework v.4.1.0 and PELock Obfuscator and shows 87 % precision with zero false positives rate.

Odour-based discrimination of similarity at the major histocompatibility complex in birds.

Science.gov (United States)

Leclaire, Sarah; Strandh, Maria; Mardon, Jérôme; Westerdahl, Helena; Bonadonna, Francesco

2017-01-11

Many animals are known to preferentially mate with partners that are dissimilar at the major histocompatibility complex (MHC) in order to maximize the antigen binding repertoire (or disease resistance) in their offspring. Although several mammals, fish or lizards use odour cues to assess MHC similarity with potential partners, the ability of birds to assess MHC similarity using olfactory cues has not yet been explored. Here we used a behavioural binary choice test and high-throughput-sequencing of MHC class IIB to determine whether blue petrels can discriminate MHC similarity based on odour cues alone. Blue petrels are seabirds with particularly good sense of smell, they have a reciprocal mate choice and are known to preferentially mate with MHC-dissimilar partners. Incubating males preferentially approached the odour of the more MHC-dissimilar female, whereas incubating females showed opposite preferences. Given their mating pattern, females were, however, expected to show preference for the odour of the more MHC-dissimilar male. Further studies are needed to determine whether, as in women and female mice, the preference varies with the reproductive cycle in blue petrel females. Our results provide the first evidence that birds can use odour cues only to assess MHC dissimilarity. © 2017 The Author(s).

Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

OpenAIRE

Zeng, Yong; Liu, Dacheng; Lei, Zhou

2014-01-01

The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history si...

Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM

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Yunyun Liang

2015-01-01

Full Text Available Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM. Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS, segmented PsePSSM, and segmented autocovariance transformation (ACT based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640 are adopted in this paper. Then a 700-dimensional (700D feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA. To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles.

Science.gov (United States)

Rácz, Anita; Andrić, Filip; Bajusz, Dávid; Héberger, Károly

2018-01-01

Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis. The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles. Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates. Baroni-Urbani-Buser (BUB) and Hawkins-Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis. Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

Scalar Similarity for Relaxed Eddy Accumulation Methods

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Ruppert, Johannes; Thomas, Christoph; Foken, Thomas

2006-07-01

The relaxed eddy accumulation (REA) method allows the measurement of trace gas fluxes when no fast sensors are available for eddy covariance measurements. The flux parameterisation used in REA is based on the assumption of scalar similarity, i.e., similarity of the turbulent exchange of two scalar quantities. In this study changes in scalar similarity between carbon dioxide, sonic temperature and water vapour were assessed using scalar correlation coefficients and spectral analysis. The influence on REA measurements was assessed by simulation. The evaluation is based on observations over grassland, irrigated cotton plantation and spruce forest. Scalar similarity between carbon dioxide, sonic temperature and water vapour showed a distinct diurnal pattern and change within the day. Poor scalar similarity was found to be linked to dissimilarities in the energy contained in the low frequency part of the turbulent spectra ( definition.

Expression Pattern Similarities Support the Prediction of Orthologs Retaining Common Functions after Gene Duplication Events1[OPEN

Science.gov (United States)

Haberer, Georg; Panda, Arup; Das Laha, Shayani; Ghosh, Tapas Chandra; Schäffner, Anton R.

2016-01-01

The identification of functionally equivalent, orthologous genes (functional orthologs) across genomes is necessary for accurate transfer of experimental knowledge from well-characterized organisms to others. This frequently relies on automated, coding sequence-based approaches such as OrthoMCL, Inparanoid, and KOG, which usually work well for one-to-one homologous states. However, this strategy does not reliably work for plants due to the occurrence of extensive gene/genome duplication. Frequently, for one query gene, multiple orthologous genes are predicted in the other genome, and it is not clear a priori from sequence comparison and similarity which one preserves the ancestral function. We have studied 11 organ-dependent and stress-induced gene expression patterns of 286 Arabidopsis lyrata duplicated gene groups and compared them with the respective Arabidopsis (Arabidopsis thaliana) genes to predict putative expressologs and nonexpressologs based on gene expression similarity. Promoter sequence divergence as an additional tool to substantiate functional orthology only partially overlapped with expressolog classification. By cloning eight A. lyrata homologs and complementing them in the respective four Arabidopsis loss-of-function mutants, we experimentally proved that predicted expressologs are indeed functional orthologs, while nonexpressologs or nonfunctionalized orthologs are not. Our study demonstrates that even a small set of gene expression data in addition to sequence homologies are instrumental in the assignment of functional orthologs in the presence of multiple orthologs. PMID:27303025

A Profile-Based Framework for Factorial Similarity and the Congruence Coefficient.

Science.gov (United States)

Hartley, Anselma G; Furr, R Michael

2017-01-01

We present a novel profile-based framework for understanding factorial similarity in the context of exploratory factor analysis in general, and for understanding the congruence coefficient (a commonly used index of factor similarity) specifically. First, we introduce the profile-based framework articulating factorial similarity in terms of 3 intuitive components: general saturation similarity, differential saturation similarity, and configural similarity. We then articulate the congruence coefficient in terms of these components, along with 2 additional profile-based components, and we explain how these components resolve ambiguities that can be-and are-found when using the congruence coefficient. Finally, we present secondary analyses revealing that profile-based components of factorial are indeed linked to experts' actual evaluations of factorial similarity. Overall, the profile-based approach we present offers new insights into the ways in which researchers can examine factor similarity and holds the potential to enhance researchers' ability to understand the congruence coefficient.

Automated pattern analysis in gesture research : similarity measuring in 3D motion capture models of communicative action

NARCIS (Netherlands)

Schueller, D.; Beecks, C.; Hassani, M.; Hinnell, J.; Brenger, B.; Seidl, T.; Mittelberg, I.

2017-01-01

The question of how to model similarity between gestures plays an important role in current studies in the domain of human communication. Most research into recurrent patterns in co-verbal gestures – manual communicative movements emerging spontaneously during conversation – is driven by qualitative

Extension of frequency-based dissimilarity for retrieving similar plasma waveforms

International Nuclear Information System (INIS)

Hochin, Teruhisa; Koyama, Katsumasa; Nakanishi, Hideya; Kojima, Mamoru

2008-01-01

Some computer-aided assistance in finding the waveforms similar to a waveform has become indispensable for accelerating data analysis in the plasma experiments. For the slowly-varying waveforms and those having time-sectional oscillation patterns, the methods using the Fourier series coefficients of waveforms in calculating the dissimilarity have successfully improved the performance in retrieving similar waveforms. This paper treats severely-varying waveforms, and proposes two extensions to the dissimilarity of waveforms. The first extension is to capture the difference of the importance of the Fourier series coefficients of waveforms against frequency. The second extension is to consider the outlines of waveforms. The correctness of the extended dissimilarity is experimentally evaluated by using the metrics used in evaluating that of the information retrieval, i.e. precision and recall. The experimental results show that the extended dissimilarity could improve the correctness of the similarity retrieval of plasma waveforms

Examining Similarity Structure: Multidimensional Scaling and Related Approaches in Neuroimaging

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Svetlana V. Shinkareva

2013-01-01

Full Text Available This paper covers similarity analyses, a subset of multivariate pattern analysis techniques that are based on similarity spaces defined by multivariate patterns. These techniques offer several advantages and complement other methods for brain data analyses, as they allow for comparison of representational structure across individuals, brain regions, and data acquisition methods. Particular attention is paid to multidimensional scaling and related approaches that yield spatial representations or provide methods for characterizing individual differences. We highlight unique contributions of these methods by reviewing recent applications to functional magnetic resonance imaging data and emphasize areas of caution in applying and interpreting similarity analysis methods.

Natural texture retrieval based on perceptual similarity measurement

Science.gov (United States)

Gao, Ying; Dong, Junyu; Lou, Jianwen; Qi, Lin; Liu, Jun

2018-04-01

A typical texture retrieval system performs feature comparison and might not be able to make human-like judgments of image similarity. Meanwhile, it is commonly known that perceptual texture similarity is difficult to be described by traditional image features. In this paper, we propose a new texture retrieval scheme based on texture perceptual similarity. The key of the proposed scheme is that prediction of perceptual similarity is performed by learning a non-linear mapping from image features space to perceptual texture space by using Random Forest. We test the method on natural texture dataset and apply it on a new wallpapers dataset. Experimental results demonstrate that the proposed texture retrieval scheme with perceptual similarity improves the retrieval performance over traditional image features.

Pattern centric design based sensitive patterns and process monitor in manufacturing

Science.gov (United States)

Hsiang, Chingyun; Cheng, Guojie; Wu, Kechih

2017-03-01

When design rule is mitigating to smaller dimension, process variation requirement is tighter than ever and challenges the limits of device yield. Masks, lithography, etching and other processes have to meet very tight specifications in order to keep defect and CD within the margins of the process window. Conventionally, Inspection and metrology equipments are utilized to monitor and control wafer quality in-line. In high throughput optical inspection, nuisance and review-classification become a tedious labor intensive job in manufacturing. Certain high-resolution SEM images are taken to validate defects after optical inspection. These high resolution SEM images catch not only optical inspection highlighted point, also its surrounding patterns. However, this pattern information is not well utilized in conventional quality control method. Using this complementary design based pattern monitor not only monitors and analyzes the variation of patterns sensitivity but also reduce nuisance and highlight defective patterns or killer defects. After grouping in either single or multiple layers, systematic defects can be identified quickly in this flow. In this paper, we applied design based pattern monitor in different layers to monitor process variation impacts on all kinds of patterns. First, the contour of high resolutions SEM image is extracted and aligned to design with offset adjustment and fine alignment [1]. Second, specified pattern rules can be applied on design clip area, the same size as SEM image, and form POI (pattern of interest) areas. Third, the discrepancy of contour and design measurement at different pattern types in measurement blocks. Fourth, defective patterns are reported by discrepancy detection criteria and pattern grouping [4]. Meanwhile, reported pattern defects are ranked by number and severity by discrepancy. In this step, process sensitive high repeatable systematic defects can be identified quickly Through this design based process pattern

Large-Scale Constraint-Based Pattern Mining

Science.gov (United States)

Zhu, Feida

2009-01-01

We studied the problem of constraint-based pattern mining for three different data formats, item-set, sequence and graph, and focused on mining patterns of large sizes. Colossal patterns in each data formats are studied to discover pruning properties that are useful for direct mining of these patterns. For item-set data, we observed robustness of…

External morphology of the adult of Dynamine postverta (Cramer (Lepidoptera, Nymphalidae, Biblidinae and patterns of morphological similarity among species from eight tribes of Nymphalidae

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Luis Anderson Ribeiro Leite

2013-06-01

Full Text Available External morphology of the adult of Dynamine postverta (Cramer (Lepidoptera, Nymphalidae, Biblidinae and patterns of morphological similarity among species from eight tribes of Nymphalidae. The external structure of the integument of Dynamine postverta postverta (Cramer, 1779 is based on detailed morphological drawings and scanning electron microscopy. The data are compared with other species belonging to eight tribes of Nymphalidae, to assist future studies on the taxonomy and systematics of Neotropical Biblidinae.

In silico pattern-based analysis of the human cytomegalovirus genome.

Science.gov (United States)

Rigoutsos, Isidore; Novotny, Jiri; Huynh, Tien; Chin-Bow, Stephen T; Parida, Laxmi; Platt, Daniel; Coleman, David; Shenk, Thomas

2003-04-01

More than 200 open reading frames (ORFs) from the human cytomegalovirus genome have been reported as potentially coding for proteins. We have used two pattern-based in silico approaches to analyze this set of putative viral genes. With the help of an objective annotation method that is based on the Bio-Dictionary, a comprehensive collection of amino acid patterns that describes the currently known natural sequence space of proteins, we have reannotated all of the previously reported putative genes of the human cytomegalovirus. Also, with the help of MUSCA, a pattern-based multiple sequence alignment algorithm, we have reexamined the original human cytomegalovirus gene family definitions. Our analysis of the genome shows that many of the coded proteins comprise amino acid combinations that are unique to either the human cytomegalovirus or the larger group of herpesviruses. We have confirmed that a surprisingly large portion of the analyzed ORFs encode membrane proteins, and we have discovered a significant number of previously uncharacterized proteins that are predicted to be G-protein-coupled receptor homologues. The analysis also indicates that many of the encoded proteins undergo posttranslational modifications such as hydroxylation, phosphorylation, and glycosylation. ORFs encoding proteins with similar functional behavior appear in neighboring regions of the human cytomegalovirus genome. All of the results of the present study can be found and interactively explored online (http://cbcsrv.watson.ibm.com/virus/).

K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering

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Lv Tao

2017-01-01

Full Text Available Stock price prediction based on K-line patterns is the essence of candlestick technical analysis. However, there are some disputes on whether the K-line patterns have predictive power in academia. To help resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering, and pattern knowledge mining to research the predictive power of K-line patterns. The similarity match model and nearest neighbor-clustering algorithm are proposed for solving the problem of similarity match and clustering of K-line series, respectively. The experiment includes testing the predictive power of the Three Inside Up pattern and Three Inside Down pattern with the testing dataset of the K-line series data of Shanghai 180 index component stocks over the latest 10 years. Experimental results show that (1 the predictive power of a pattern varies a great deal for different shapes and (2 each of the existing K-line patterns requires further classification based on the shape feature for improving the prediction performance.

Content Based Radiographic Images Indexing and Retrieval Using Pattern Orientation Histogram

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Abolfazl Lakdashti

2008-06-01

Full Text Available Introduction: Content Based Image Retrieval (CBIR is a method of image searching and retrieval in a  database. In medical applications, CBIR is a tool used by physicians to compare the previous and current  medical images associated with patients pathological conditions. As the volume of pictorial information  stored in medical image databases is in progress, efficient image indexing and retrieval is increasingly  becoming a necessity.  Materials and Methods: This paper presents a new content based radiographic image retrieval approach  based on histogram of pattern orientations, namely pattern orientation histogram (POH. POH represents  the  spatial  distribution  of  five  different  pattern  orientations:  vertical,  horizontal,  diagonal  down/left,  diagonal down/right and non-orientation. In this method, a given image is first divided into image-blocks  and  the  frequency  of  each  type  of  pattern  is  determined  in  each  image-block.  Then,  local  pattern  histograms for each of these image-blocks are computed.   Results: The method was compared to two well known texture-based image retrieval methods: Tamura  and  Edge  Histogram  Descriptors  (EHD  in  MPEG-7  standard.  Experimental  results  based  on  10000  IRMA  radiography  image  dataset,  demonstrate  that  POH  provides  better  precision  and  recall  rates  compared to Tamura and EHD. For some images, the recall and precision rates obtained by POH are,  respectively, 48% and 18% better than the best of the two above mentioned methods.    Discussion and Conclusion: Since we exploit the absolute location of the pattern in the image as well as  its global composition, the proposed matching method can retrieve semantically similar medical images.

Patterns in Gut Microbiota Similarity Associated with Degree of Sociality among Sex Classes of a Neotropical Primate.

Science.gov (United States)

Amato, Katherine R; Van Belle, Sarie; Di Fiore, Anthony; Estrada, Alejandro; Stumpf, Rebecca; White, Bryan; Nelson, Karen E; Knight, Rob; Leigh, Steven R

2017-07-01

Studies of human and domestic animal models indicate that related individuals and those that spend the most time in physical contact typically have more similar gut microbial communities. However, few studies have examined these factors in wild mammals where complex social dynamics and a variety of interacting environmental factors may impact the patterns observed in controlled systems. Here, we explore the effect of host kinship and time spent in social contact on the gut microbiota of wild, black howler monkeys (Alouatta pigra). Our results indicate that closely related individuals had less similar gut microbial communities than non-related individuals. However, the effect was small. In contrast, as previously reported in baboons and chimpanzees, individuals that spent more time in contact (0 m) and close proximity (0-1 m) had more similar gut microbial communities. This pattern was driven by adult female-adult female dyads, which generally spend more time in social contact than adult male-adult male dyads or adult male-adult female dyads. Relative abundances of individual microbial genera such as Bacteroides, Clostridium, and Streptococcus were also more similar in individuals that spent more time in contact or close proximity. Overall, our data suggest that even in arboreal primates that live in small social groups and spend a relatively low proportion of their time in physical contact, social interactions are associated with variation in gut microbiota composition. Additionally, these results demonstrate that within a given host species, subgroups of individuals may interact with the gut microbiota differently.

Branch length similarity entropy-based descriptors for shape representation

Science.gov (United States)

Kwon, Ohsung; Lee, Sang-Hee

2017-11-01

In previous studies, we showed that the branch length similarity (BLS) entropy profile could be successfully used for the shape recognition such as battle tanks, facial expressions, and butterflies. In the present study, we proposed new descriptors, roundness, symmetry, and surface roughness, for the recognition, which are more accurate and fast in the computation than the previous descriptors. The roundness represents how closely a shape resembles to a circle, the symmetry characterizes how much one shape is similar with another when the shape is moved in flip, and the surface roughness quantifies the degree of vertical deviations of a shape boundary. To evaluate the performance of the descriptors, we used the database of leaf images with 12 species. Each species consisted of 10 - 20 leaf images and the total number of images were 160. The evaluation showed that the new descriptors successfully discriminated the leaf species. We believe that the descriptors can be a useful tool in the field of pattern recognition.

Multicriteria decision-making method based on a cosine similarity ...

African Journals Online (AJOL)

the cosine similarity measure is often used in information retrieval, citation analysis, and automatic classification. However, it scarcely deals with trapezoidal fuzzy information and multicriteria decision-making problems. For this purpose, a cosine similarity measure between trapezoidal fuzzy numbers is proposed based on ...

Color-Based Image Retrieval from High-Similarity Image Databases

DEFF Research Database (Denmark)

Hansen, Michael Adsetts Edberg; Carstensen, Jens Michael

2003-01-01

Many image classification problems can fruitfully be thought of as image retrieval in a "high similarity image database" (HSID) characterized by being tuned towards a specific application and having a high degree of visual similarity between entries that should be distinguished. We introduce...... a method for HSID retrieval using a similarity measure based on a linear combination of Jeffreys-Matusita (JM) distances between distributions of color (and color derivatives) estimated from a set of automatically extracted image regions. The weight coefficients are estimated based on optimal retrieval...... performance. Experimental results on the difficult task of visually identifying clones of fungal colonies grown in a petri dish and categorization of pelts show a high retrieval accuracy of the method when combined with standardized sample preparation and image acquisition....

Evolutionary patterns of RNA-based duplication in non-mammalian chordates.

Directory of Open Access Journals (Sweden)

Ming Chen

Full Text Available The role of RNA-based duplication, or retroposition, in the evolution of new gene functions in mammals, plants, and Drosophila has been widely reported. However, little is known about RNA-based duplication in non-mammalian chordates. In this study, we screened ten non-mammalian chordate genomes for retrocopies and investigated their evolutionary patterns. We identified numerous retrocopies in these species. Examination of the age distribution of these retrocopies revealed no burst of young retrocopies in ancient chordate species. Upon comparing these non-mammalian chordate species to the mammalian species, we observed that a larger fraction of the non-mammalian retrocopies was under strong evolutionary constraints than mammalian retrocopies are, as evidenced by signals of purifying selection and expression profiles. For the Western clawed frog, Medaka, and Sea squirt, many retrogenes have evolved gonad and brain expression patterns, similar to what was observed in human. Testing of retrogene movement in the Medaka genome, where the nascent sex chrosomes have been well assembled, did not reveal any significant gene movement. Taken together, our analyses demonstrate that RNA-based duplication generates many functional genes and can make a significant contribution to the evolution of non-mammalian genomes.

Concept of a data base for signal patterns

International Nuclear Information System (INIS)

Olma, B.

1985-01-01

The many requirements made on the storage, administration and handling of signal patterns of stationary random signal patterns and multi-channel transient signal patterns are discussed. For the field of loose part detection, the concept of a data base is presented for structure-borne noise burst patterns. Chapter 2 describes the measuring principle of structure-borne noise monitoring. Chapter 3 gives a summary of the requirements made on the automation of measured data recording; chapter 4 compiles requirements made on the data base. Chapter 5 describes the concept developed for a burst pattern data base; chapter 6 shows the organization of the data base, and chapter 7 reflects the present state of application. (orig./HP) [de

A study of concept-based similarity approaches for recommending program examples

Science.gov (United States)

Hosseini, Roya; Brusilovsky, Peter

2017-07-01

This paper investigates a range of concept-based example recommendation approaches that we developed to provide example-based problem-solving support in the domain of programming. The goal of these approaches is to offer students a set of most relevant remedial examples when they have trouble solving a code comprehension problem where students examine a program code to determine its output or the final value of a variable. In this paper, we use the ideas of semantic-level similarity-based linking developed in the area of intelligent hypertext to generate examples for the given problem. To determine the best-performing approach, we explored two groups of similarity approaches for selecting examples: non-structural approaches focusing on examples that are similar to the problem in terms of concept coverage and structural approaches focusing on examples that are similar to the problem by the structure of the content. We also explored the value of personalized example recommendation based on student's knowledge levels and learning goal of the exercise. The paper presents concept-based similarity approaches that we developed, explains the data collection studies and reports the result of comparative analysis. The results of our analysis showed better ranking performance of the personalized structural variant of cosine similarity approach.

A pattern-based methodology for optimizing stitches in double-patterning technology

Science.gov (United States)

Wang, Lynn T.; Madhavan, Sriram; Dai, Vito; Capodieci, Luigi

2015-03-01

A pattern-based methodology for optimizing stitches is developed based on identifying stitch topologies and replacing them with pre-characterized fixing solutions in decomposed layouts. A topology-based library of stitches with predetermined fixing solutions is built. A pattern-based engine searches for matching topologies in the decomposed layouts. When a match is found, the engine opportunistically replaces the predetermined fixing solution: only a design rule check error-free replacement is preserved. The methodology is demonstrated on a 20nm layout design that contains over 67 million, first metal layer stitches. Results show that a small library containing 3 stitch topologies improves the stitch area regularity by 4x.

Concurrence of rule- and similarity-based mechanisms in artificial grammar learning.

Science.gov (United States)

Opitz, Bertram; Hofmann, Juliane

2015-03-01

A current theoretical debate regards whether rule-based or similarity-based learning prevails during artificial grammar learning (AGL). Although the majority of findings are consistent with a similarity-based account of AGL it has been argued that these results were obtained only after limited exposure to study exemplars, and performance on subsequent grammaticality judgment tests has often been barely above chance level. In three experiments the conditions were investigated under which rule- and similarity-based learning could be applied. Participants were exposed to exemplars of an artificial grammar under different (implicit and explicit) learning instructions. The analysis of receiver operating characteristics (ROC) during a final grammaticality judgment test revealed that explicit but not implicit learning led to rule knowledge. It also demonstrated that this knowledge base is built up gradually while similarity knowledge governed the initial state of learning. Together these results indicate that rule- and similarity-based mechanisms concur during AGL. Moreover, it could be speculated that two different rule processes might operate in parallel; bottom-up learning via gradual rule extraction and top-down learning via rule testing. Crucially, the latter is facilitated by performance feedback that encourages explicit hypothesis testing. Copyright © 2015 Elsevier Inc. All rights reserved.

A grammar-based semantic similarity algorithm for natural language sentences.

Science.gov (United States)

Lee, Ming Che; Chang, Jia Wei; Hsieh, Tung Cheng

2014-01-01

This paper presents a grammar and semantic corpus based similarity algorithm for natural language sentences. Natural language, in opposition to "artificial language", such as computer programming languages, is the language used by the general public for daily communication. Traditional information retrieval approaches, such as vector models, LSA, HAL, or even the ontology-based approaches that extend to include concept similarity comparison instead of cooccurrence terms/words, may not always determine the perfect matching while there is no obvious relation or concept overlap between two natural language sentences. This paper proposes a sentence similarity algorithm that takes advantage of corpus-based ontology and grammatical rules to overcome the addressed problems. Experiments on two famous benchmarks demonstrate that the proposed algorithm has a significant performance improvement in sentences/short-texts with arbitrary syntax and structure.

A similarity based agglomerative clustering algorithm in networks

Science.gov (United States)

Liu, Zhiyuan; Wang, Xiujuan; Ma, Yinghong

2018-04-01

The detection of clusters is benefit for understanding the organizations and functions of networks. Clusters, or communities, are usually groups of nodes densely interconnected but sparsely linked with any other clusters. To identify communities, an efficient and effective community agglomerative algorithm based on node similarity is proposed. The proposed method initially calculates similarities between each pair of nodes, and form pre-partitions according to the principle that each node is in the same community as its most similar neighbor. After that, check each partition whether it satisfies community criterion. For the pre-partitions who do not satisfy, incorporate them with others that having the biggest attraction until there are no changes. To measure the attraction ability of a partition, we propose an attraction index that based on the linked node's importance in networks. Therefore, our proposed method can better exploit the nodes' properties and network's structure. To test the performance of our algorithm, both synthetic and empirical networks ranging in different scales are tested. Simulation results show that the proposed algorithm can obtain superior clustering results compared with six other widely used community detection algorithms.

Fast Depiction Invariant Visual Similarity for Content Based Image Retrieval Based on Data-driven Visual Similarity using Linear Discriminant Analysis

Science.gov (United States)

Wihardi, Y.; Setiawan, W.; Nugraha, E.

2018-01-01

On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.

Similar Pregnancy Rates Between Different Endometrial Echo Patterns in ART

Directory of Open Access Journals (Sweden)

Serdar Ünlü

2008-08-01

CONCLUSION: As the morphological assessment of endometrium by sonography has a high inter observer variability and the influence of sonographic patterns of endometrium on pregnancy rates remains unclear, we conclude that evaluating endometrial patterns by sonography alone is not an optimal diagnostic procedure for determining the success of IVF outcome.

Temporal-pattern similarity analysis reveals the beneficial and detrimental effects of context reinstatement on human memory.

Science.gov (United States)

Staudigl, Tobias; Vollmar, Christian; Noachtar, Soheyl; Hanslmayr, Simon

2015-04-01

A powerful force in human memory is the context in which memories are encoded (Tulving and Thomson, 1973). Several studies suggest that the reinstatement of neural encoding patterns is beneficial for memory retrieval (Manning et al., 2011; Staresina et al., 2012; Jafarpour et al., 2014). However, reinstatement of the original encoding context is not always helpful, for instance, when retrieving a memory in a different contextual situation (Smith and Vela, 2001). It is an open question whether such context-dependent memory effects can be captured by the reinstatement of neural patterns. We investigated this question by applying temporal and spatial pattern similarity analysis in MEG and intracranial EEG in a context-match paradigm. Items (words) were tagged by individual dynamic context stimuli (movies). The results show that beta oscillatory phase in visual regions and the parahippocampal cortex tracks the incidental reinstatement of individual context trajectories on a single-trial level. Crucially, memory benefitted from reinstatement when the encoding and retrieval contexts matched but suffered from reinstatement when the contexts did not match. Copyright © 2015 the authors 0270-6474/15/355373-12$15.00/0.

Defining a similarity threshold for a functional proteinsequence pattern: The signal peptide cleavage site

DEFF Research Database (Denmark)

Nielsen, Henrik; Engelbrecht, Jacob; von Heijne, Gunnar

1996-01-01

When preparing data sets of amino acid or nucleotide sequences it is necessary to exclude redundant or homologous sequences in order to avoid overestimating the predictive performance of an algorithm. For some time methods for doing this have been available in the area of protein structure...... prediction. We have developed a similar procedure based on pair-wise alignments for sequences with functional sites. We show how a correlation coefficient between sequence similarity and functional homology can be used to compare the efficiency of different similarity measures and choose a nonarbitrary...

Intergenerational patterns of family violence related to alcohol abuse: a genogram-based study

Directory of Open Access Journals (Sweden)

Cláudia Silveira Tondowski

2014-12-01

Full Text Available The objective of this study was to analyze intergenerational patterns of alcohol related violence (ARV. An intentional sample comprising 42 family members was selected according to a set of criteria, including history of ARV. A genogram based on anonymous semi-structured taped interviews was created. The Content Analysis pointed to different patterns of repetition of intergenerational ARV. The most recurrent ones were those of lineal consanguinity (father/son and through marriage. We observed similarities over the generations of each family as regards the pattern of alcohol consumption; the type of violence; the family reaction and the family life cycle in which ARV was intensified. Our results confirm the intergenerational reproduction of ARV. In conclusion, it is important to create intervention strategies to prevent intergenerational repetition of this association of behaviors.

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.

A Grammar-Based Semantic Similarity Algorithm for Natural Language Sentences

Science.gov (United States)

Chang, Jia Wei; Hsieh, Tung Cheng

2014-01-01

This paper presents a grammar and semantic corpus based similarity algorithm for natural language sentences. Natural language, in opposition to “artificial language”, such as computer programming languages, is the language used by the general public for daily communication. Traditional information retrieval approaches, such as vector models, LSA, HAL, or even the ontology-based approaches that extend to include concept similarity comparison instead of cooccurrence terms/words, may not always determine the perfect matching while there is no obvious relation or concept overlap between two natural language sentences. This paper proposes a sentence similarity algorithm that takes advantage of corpus-based ontology and grammatical rules to overcome the addressed problems. Experiments on two famous benchmarks demonstrate that the proposed algorithm has a significant performance improvement in sentences/short-texts with arbitrary syntax and structure. PMID:24982952

A Grammar-Based Semantic Similarity Algorithm for Natural Language Sentences

Directory of Open Access Journals (Sweden)

Ming Che Lee

2014-01-01

Full Text Available This paper presents a grammar and semantic corpus based similarity algorithm for natural language sentences. Natural language, in opposition to “artificial language”, such as computer programming languages, is the language used by the general public for daily communication. Traditional information retrieval approaches, such as vector models, LSA, HAL, or even the ontology-based approaches that extend to include concept similarity comparison instead of cooccurrence terms/words, may not always determine the perfect matching while there is no obvious relation or concept overlap between two natural language sentences. This paper proposes a sentence similarity algorithm that takes advantage of corpus-based ontology and grammatical rules to overcome the addressed problems. Experiments on two famous benchmarks demonstrate that the proposed algorithm has a significant performance improvement in sentences/short-texts with arbitrary syntax and structure.

Similarity analysis between quantum images

Science.gov (United States)

Zhou, Ri-Gui; Liu, XingAo; Zhu, Changming; Wei, Lai; Zhang, Xiafen; Ian, Hou

2018-06-01

Similarity analyses between quantum images are so essential in quantum image processing that it provides fundamental research for the other fields, such as quantum image matching, quantum pattern recognition. In this paper, a quantum scheme based on a novel quantum image representation and quantum amplitude amplification algorithm is proposed. At the end of the paper, three examples and simulation experiments show that the measurement result must be 0 when two images are same, and the measurement result has high probability of being 1 when two images are different.

Trait similarity patterns within grass and grasshopper communities : Multitrophic community assembly at work

NARCIS (Netherlands)

van der Plas, F.; Anderson, T. M.; Olff, H.

Trait-based community assembly theory suggests that trait variation among co-occurring species is shaped by two main processes: abiotic filtering, important in stressful environments and promoting similarity, and competition, more important in productive environments and promoting dissimilarity.

Extending the similarity-based XML multicast approach with digital signatures

DEFF Research Database (Denmark)

Azzini, Antonia; Marrara, Stefania; Jensen, Meiko

2009-01-01

This paper investigates the interplay between similarity-based SOAP message aggregation and digital signature application. An overview on the approaches resulting from the different orders for the tasks of signature application, verification, similarity aggregation and splitting is provided....... Depending on the intersection between similarity-aggregated and signed SOAP message parts, the paper discusses three different cases of signature application, and sketches their applicability and performance implications....

Computational prediction of drug-drug interactions based on drugs functional similarities.

Science.gov (United States)

Ferdousi, Reza; Safdari, Reza; Omidi, Yadollah

2017-06-01

Therapeutic activities of drugs are often influenced by co-administration of drugs that may cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and identification of DDIs are extremely vital for the patient safety and success of treatment modalities. A number of computational methods have been employed for the prediction of DDIs based on drugs structures and/or functions. Here, we report on a computational method for DDIs prediction based on functional similarity of drugs. The model was set based on key biological elements including carriers, transporters, enzymes and targets (CTET). The model was applied for 2189 approved drugs. For each drug, all the associated CTETs were collected, and the corresponding binary vectors were constructed to determine the DDIs. Various similarity measures were conducted to detect DDIs. Of the examined similarity methods, the inner product-based similarity measures (IPSMs) were found to provide improved prediction values. Altogether, 2,394,766 potential drug pairs interactions were studied. The model was able to predict over 250,000 unknown potential DDIs. Upon our findings, we propose the current method as a robust, yet simple and fast, universal in silico approach for identification of DDIs. We envision that this proposed method can be used as a practical technique for the detection of possible DDIs based on the functional similarities of drugs. Copyright © 2017. Published by Elsevier Inc.

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%.

Efficient Algorithm for Computing Link-based Similarity in Real World Networks

DEFF Research Database (Denmark)

Cai, Yuanzhe; Cong, Gao; Xu, Jia

2009-01-01

Similarity calculation has many applications, such as information retrieval, and collaborative filtering, among many others. It has been shown that link-based similarity measure, such as SimRank, is very effective in characterizing the object similarities in networks, such as the Web, by exploiti...

Distributed open environment for data retrieval based on pattern recognition techniques

International Nuclear Information System (INIS)

Pereira, A.; Vega, J.; Castro, R.; Portas, A.

2010-01-01

Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, interoperability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE (Java 2 Enterprise Edition), which provides a mature standard framework and a modular architecture. It can handle transactions and concurrency of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows hiding of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests.

Distributed Open Environment for Data Retrieval based on Pattern Recognition Techniques

Energy Technology Data Exchange (ETDEWEB)

Pereira, A.; Vega, J.; Castro, R.; Portas, A. [Association EuratomCIEMAT para Fusion, Madrid (Spain)

2009-07-01

Full text of publication follows: Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, inter-operability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE, which provides a mature standard framework and a modular architecture. It can handle transactions and competition of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows concealment of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests. (authors)

Distributed open environment for data retrieval based on pattern recognition techniques

Energy Technology Data Exchange (ETDEWEB)

Pereira, A., E-mail: augusto.pereira@ciemat.e [Asociacion EURATOM/CIEMAT para Fusion, CIEMAT, Edificio 66, Avda. Complutense, 22, 28040 Madrid (Spain); Vega, J.; Castro, R.; Portas, A. [Asociacion EURATOM/CIEMAT para Fusion, CIEMAT, Edificio 66, Avda. Complutense, 22, 28040 Madrid (Spain)

2010-07-15

Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, interoperability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE (Java 2 Enterprise Edition), which provides a mature standard framework and a modular architecture. It can handle transactions and concurrency of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows hiding of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests.

An equilibrium-point model of electromyographic patterns during single-joint movements based on experimentally reconstructed control signals.

Science.gov (United States)

Latash, M L; Goodman, S R

1994-01-01

The purpose of this work has been to develop a model of electromyographic (EMG) patterns during single-joint movements based on a version of the equilibrium-point hypothesis, a method for experimental reconstruction of the joint compliant characteristics, the dual-strategy hypothesis, and a kinematic model of movement trajectory. EMG patterns are considered emergent properties of hypothetical control patterns that are equally affected by the control signals and peripheral feedback reflecting actual movement trajectory. A computer model generated the EMG patterns based on simulated movement kinematics and hypothetical control signals derived from the reconstructed joint compliant characteristics. The model predictions have been compared to published recordings of movement kinematics and EMG patterns in a variety of movement conditions, including movements over different distances, at different speeds, against different-known inertial loads, and in conditions of possible unexpected decrease in the inertial load. Changes in task parameters within the model led to simulated EMG patterns qualitatively similar to the experimentally recorded EMG patterns. The model's predictive power compares it favourably to the existing models of the EMG patterns. Copyright © 1994. Published by Elsevier Ltd.

Historical feature pattern extraction based network attack situation sensing algorithm.

Science.gov (United States)

Zeng, Yong; Liu, Dacheng; Lei, Zhou

2014-01-01

The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.

Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

Directory of Open Access Journals (Sweden)

Yong Zeng

2014-01-01

Full Text Available The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE. First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.

Calculating the knowledge-based similarity of functional groups using crystallographic data

Science.gov (United States)

Watson, Paul; Willett, Peter; Gillet, Valerie J.; Verdonk, Marcel L.

2001-09-01

A knowledge-based method for calculating the similarity of functional groups is described and validated. The method is based on experimental information derived from small molecule crystal structures. These data are used in the form of scatterplots that show the likelihood of a non-bonded interaction being formed between functional group A (the `central group') and functional group B (the `contact group' or `probe'). The scatterplots are converted into three-dimensional maps that show the propensity of the probe at different positions around the central group. Here we describe how to calculate the similarity of a pair of central groups based on these maps. The similarity method is validated using bioisosteric functional group pairs identified in the Bioster database and Relibase. The Bioster database is a critical compilation of thousands of bioisosteric molecule pairs, including drugs, enzyme inhibitors and agrochemicals. Relibase is an object-oriented database containing structural data about protein-ligand interactions. The distributions of the similarities of the bioisosteric functional group pairs are compared with similarities for all the possible pairs in IsoStar, and are found to be significantly different. Enrichment factors are also calculated showing the similarity method is statistically significantly better than random in predicting bioisosteric functional group pairs.

Image magnification based on similarity analogy

International Nuclear Information System (INIS)

Chen Zuoping; Ye Zhenglin; Wang Shuxun; Peng Guohua

2009-01-01

Aiming at the high time complexity of the decoding phase in the traditional image enlargement methods based on fractal coding, a novel image magnification algorithm is proposed in this paper, which has the advantage of iteration-free decoding, by using the similarity analogy between an image and its zoom-out and zoom-in. A new pixel selection technique is also presented to further improve the performance of the proposed method. Furthermore, by combining some existing fractal zooming techniques, an efficient image magnification algorithm is obtained, which can provides the image quality as good as the state of the art while greatly decrease the time complexity of the decoding phase.

Improved personalized recommendation based on a similarity network

Science.gov (United States)

Wang, Ximeng; Liu, Yun; Xiong, Fei

2016-08-01

A recommender system helps individual users find the preferred items rapidly and has attracted extensive attention in recent years. Many successful recommendation algorithms are designed on bipartite networks, such as network-based inference or heat conduction. However, most of these algorithms define the resource-allocation methods for an average allocation. That is not reasonable because average allocation cannot indicate the user choice preference and the influence between users which leads to a series of non-personalized recommendation results. We propose a personalized recommendation approach that combines the similarity function and bipartite network to generate a similarity network that improves the resource-allocation process. Our model introduces user influence into the recommender system and states that the user influence can make the resource-allocation process more reasonable. We use four different metrics to evaluate our algorithms for three benchmark data sets. Experimental results show that the improved recommendation on a similarity network can obtain better accuracy and diversity than some competing approaches.

Patient Similarity in Prediction Models Based on Health Data: A Scoping Review

Science.gov (United States)

Sharafoddini, Anis; Dubin, Joel A

2017-01-01

Background Physicians and health policy makers are required to make predictions during their decision making in various medical problems. Many advances have been made in predictive modeling toward outcome prediction, but these innovations target an average patient and are insufficiently adjustable for individual patients. One developing idea in this field is individualized predictive analytics based on patient similarity. The goal of this approach is to identify patients who are similar to an index patient and derive insights from the records of similar patients to provide personalized predictions.. Objective The aim is to summarize and review published studies describing computer-based approaches for predicting patients’ future health status based on health data and patient similarity, identify gaps, and provide a starting point for related future research. Methods The method involved (1) conducting the review by performing automated searches in Scopus, PubMed, and ISI Web of Science, selecting relevant studies by first screening titles and abstracts then analyzing full-texts, and (2) documenting by extracting publication details and information on context, predictors, missing data, modeling algorithm, outcome, and evaluation methods into a matrix table, synthesizing data, and reporting results. Results After duplicate removal, 1339 articles were screened in abstracts and titles and 67 were selected for full-text review. In total, 22 articles met the inclusion criteria. Within included articles, hospitals were the main source of data (n=10). Cardiovascular disease (n=7) and diabetes (n=4) were the dominant patient diseases. Most studies (n=18) used neighborhood-based approaches in devising prediction models. Two studies showed that patient similarity-based modeling outperformed population-based predictive methods. Conclusions Interest in patient similarity-based predictive modeling for diagnosis and prognosis has been growing. In addition to raw/coded health

A Similarity Analysis of Audio Signal to Develop a Human Activity Recognition Using Similarity Networks

Directory of Open Access Journals (Sweden)

Alejandra García-Hernández

2017-11-01

Full Text Available Human Activity Recognition (HAR is one of the main subjects of study in the areas of computer vision and machine learning due to the great benefits that can be achieved. Examples of the study areas are: health prevention, security and surveillance, automotive research, and many others. The proposed approaches are carried out using machine learning techniques and present good results. However, it is difficult to observe how the descriptors of human activities are grouped. In order to obtain a better understanding of the the behavior of descriptors, it is important to improve the abilities to recognize the human activities. This paper proposes a novel approach for the HAR based on acoustic data and similarity networks. In this approach, we were able to characterize the sound of the activities and identify those activities looking for similarity in the sound pattern. We evaluated the similarity of the sounds considering mainly two features: the sound location and the materials that were used. As a result, the materials are a good reference classifying the human activities compared with the location.

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity

Directory of Open Access Journals (Sweden)

Paolo Napoletano

2018-01-01

Full Text Available Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM imaging are the most effective. In this paper, we propose a region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs and self-similarity. The method evaluates the degree of abnormality of each subregion of an image under consideration by computing a CNN-based visual similarity with respect to a dictionary of anomaly-free subregions belonging to a training set. The proposed method outperforms the state of the art.

SHOP: scaffold hopping by GRID-based similarity searches

DEFF Research Database (Denmark)

Bergmann, Rikke; Linusson, Anna; Zamora, Ismael

2007-01-01

A new GRID-based method for scaffold hopping (SHOP) is presented. In a fully automatic manner, scaffolds were identified in a database based on three types of 3D-descriptors. SHOP's ability to recover scaffolds was assessed and validated by searching a database spiked with fragments of known...... scaffolds were in the 31 top-ranked scaffolds. SHOP also identified new scaffolds with substantially different chemotypes from the queries. Docking analysis indicated that the new scaffolds would have similar binding modes to those of the respective query scaffolds observed in X-ray structures...

Similar personality patterns are associated with empathy in four different countries

Directory of Open Access Journals (Sweden)

Martin Christoph Melchers

2016-03-01

Full Text Available Empathy is an important human ability associated with successful social interaction. It is currently unclear how to optimally measure individual differences in empathic processing. Although the Big Five model of personality is an effective model to explain individual differences in human experience and behavior, its relation to measures of empathy is currently not well understood. Therefore, the present study was designed to investigate the relationship between the Big Five personality concept and two commonly used measures for empathy (Empathy Quotient (EQ, Interpersonal Reactivity Index (IRI in four samples from China, Germany, Spain and the United States of America. This approach was designed to advance the way the Big Five personality model can be used to measure empathy. We found evidence of medium effect sizes for associations between personality and empathy, with agreeableness and conscientiousness as the most important predictors of affective and cognitive empathy (measured by the respective IRI subscales as well as a for a one-dimensional empathy score (measured by the EQ. Empathy in a fictional context was most closely related to openness to experience while personal distress was first of all related to neuroticism. In terms of culture, we did not observe any distinct pattern concerning cultural differences. These results support the cross-cultural applicability of the Empathy Quotient and the Interpersonal Reactivity Index and indicate structurally similar associations between personality and empathy across cultures.

Similarity-Based Interference and the Acquisition of Adjunct Control

Directory of Open Access Journals (Sweden)

Juliana Gerard

2017-10-01

Full Text Available Previous research on the acquisition of adjunct control has observed non-adultlike behavior for sentences like “John bumped Mary after tripping on the sidewalk.” While adults only allow a subject control interpretation for these sentences (that John tripped on the sidewalk, preschool-aged children have been reported to allow a much wider range of interpretations. A number of different tasks have been used with the aim of identifying a grammatical source of children’s errors. In this paper, we consider the role of extragrammatical factors. In two comprehension experiments, we demonstrate that error rates go up when the similarity increases between an antecedent and a linearly intervening noun phrase, first with similarity in gender, and next with similarity in number marking. This suggests that difficulties with adjunct control are to be explained (at least in part by the sentence processing mechanisms that underlie similarity-based interference in adults.

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.

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.

Machine Learning-based Individual Assessment of Cortical Atrophy Pattern in Alzheimer's Disease Spectrum: Development of the Classifier and Longitudinal Evaluation.

Science.gov (United States)

Lee, Jin San; Kim, Changsoo; Shin, Jeong-Hyeon; Cho, Hanna; Shin, Dae-Seock; Kim, Nakyoung; Kim, Hee Jin; Kim, Yeshin; Lockhart, Samuel N; Na, Duk L; Seo, Sang Won; Seong, Joon-Kyung

2018-03-07

To develop a new method for measuring Alzheimer's disease (AD)-specific similarity of cortical atrophy patterns at the individual-level, we employed an individual-level machine learning algorithm. A total of 869 cognitively normal (CN) individuals and 473 patients with probable AD dementia who underwent high-resolution 3T brain MRI were included. We propose a machine learning-based method for measuring the similarity of an individual subject's cortical atrophy pattern with that of a representative AD patient cohort. In addition, we validated this similarity measure in two longitudinal cohorts consisting of 79 patients with amnestic-mild cognitive impairment (aMCI) and 27 patients with probable AD dementia. Surface-based morphometry classifier for discriminating AD from CN showed sensitivity and specificity values of 87.1% and 93.3%, respectively. In the longitudinal validation study, aMCI-converts had higher atrophy similarity at both baseline (p < 0.001) and first year visits (p < 0.001) relative to non-converters. Similarly, AD patients with faster decline had higher atrophy similarity than slower decliners at baseline (p = 0.042), first year (p = 0.028), and third year visits (p = 0.027). The AD-specific atrophy similarity measure is a novel approach for the prediction of dementia risk and for the evaluation of AD trajectories on an individual subject level.

Information filtering based on transferring similarity.

Science.gov (United States)

Sun, Duo; Zhou, Tao; Liu, Jian-Guo; Liu, Run-Ran; Jia, Chun-Xiao; Wang, Bing-Hong

2009-07-01

In this Brief Report, we propose an index of user similarity, namely, the transferring similarity, which involves all high-order similarities between users. Accordingly, we design a modified collaborative filtering algorithm, which provides remarkably higher accurate predictions than the standard collaborative filtering. More interestingly, we find that the algorithmic performance will approach its optimal value when the parameter, contained in the definition of transferring similarity, gets close to its critical value, before which the series expansion of transferring similarity is convergent and after which it is divergent. Our study is complementary to the one reported in [E. A. Leicht, P. Holme, and M. E. J. Newman, Phys. Rev. E 73, 026120 (2006)], and is relevant to the missing link prediction problem.

Self-similar structure in the distribution and density of the partition function zeros

International Nuclear Information System (INIS)

Huang, M.-C.; Luo, Y.-P.; Liaw, T.-M.

2003-01-01

Based on the knowledge of the partition function zeros for the cell-decorated triangular Ising model, we analyze the similar structures contained in the distribution pattern and density function of the zeros. The two own the same symmetries, and the arising of the similar structure in the road toward the infinite decoration-level is exhibited explicitly. The distinct features of the formation of the self-similar structure revealed from this model may be quite general

Quality-Attribute-Based Economic Valuation of Architectural Patterns

National Research Council Canada - National Science Library

Ozkaya, Ipek; Kazman, Rick; Klein, Mark

2007-01-01

.... Architectural patterns can be used to achieve quality attribute requirements. Consequently, architectural patterns generate value based on the present and future utility of the quality attributes they achieve...

Abundance patterns of evolved stars with Hipparcos parallaxes and ages based on the APOGEE data base

Science.gov (United States)

Jia, Y. P.; Chen, Y. Q.; Zhao, G.; Bari, M. A.; Zhao, J. K.; Tan, K. F.

2018-01-01

We investigate the abundance patterns for four groups of stars at evolutionary phases from sub-giant to red clump (RC) and trace the chemical evolution of the disc by taking 21 individual elemental abundances from APOGEE and ages from evolutionary models with the aid of Hipparcos distances. We find that the abundances of six elements (Si, S, K, Ca, Mn and Ni) are similar from the sub-giant phase to the RC phase. In particular, we find that a group of stars with low [C/N] ratios, mainly from the second sequence of RC stars, show that there is a difference in the transfer efficiency of the C-N-O cycle between the main and the secondary RC sequences. We also compare the abundance patterns of C-N, Mg-Al and Na-O with giant stars in globular clusters from APOGEE and find that field stars follow similar patterns as M107, a metal-rich globular cluster with [M/H] ∼- 1.0, which shows that the self-enrichment mechanism represented by strong C-N, Mg-Al and Na-O anti-correlations may not be important as the metallicity reaches [M/H] > -1.0 dex. Based on the abundances of above-mentioned six elements and [Fe/H], we investigate age versus abundance relations and find some old super-metal-rich stars in our sample. Their properties of old age and being rich in metal are evidence for stellar migration. The age versus metallicity relations in low-[α/M] bins show unexpectedly positive slopes. We propose that the fresh metal-poor gas infalling on to the Galactic disc may be the precursor for this unexpected finding.

[-25]A Similarity Analysis of Audio Signal to Develop a Human Activity Recognition Using Similarity Networks.

Science.gov (United States)

García-Hernández, Alejandra; Galván-Tejada, Carlos E; Galván-Tejada, Jorge I; Celaya-Padilla, José M; Gamboa-Rosales, Hamurabi; Velasco-Elizondo, Perla; Cárdenas-Vargas, Rogelio

2017-11-21

Human Activity Recognition (HAR) is one of the main subjects of study in the areas of computer vision and machine learning due to the great benefits that can be achieved. Examples of the study areas are: health prevention, security and surveillance, automotive research, and many others. The proposed approaches are carried out using machine learning techniques and present good results. However, it is difficult to observe how the descriptors of human activities are grouped. In order to obtain a better understanding of the the behavior of descriptors, it is important to improve the abilities to recognize the human activities. This paper proposes a novel approach for the HAR based on acoustic data and similarity networks. In this approach, we were able to characterize the sound of the activities and identify those activities looking for similarity in the sound pattern. We evaluated the similarity of the sounds considering mainly two features: the sound location and the materials that were used. As a result, the materials are a good reference classifying the human activities compared with the location.

Biometric verification based on grip-pattern recognition

NARCIS (Netherlands)

Veldhuis, Raymond N.J.; Bazen, A.M.; Kauffman, J.A.; Hartel, Pieter H.; Delp, Edward J.; Wong, Ping W.

This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 x 44 piezoresistive elements is used to measure the grip pattern. An interface has been

Biometric verification based on grip-pattern recognition

NARCIS (Netherlands)

Veldhuis, Raymond N.J.; Bazen, A.M.; Kauffman, J.A.; Hartel, Pieter H.

This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 £ 44 piezoresistive elements is used to measure the grip pattern. An interface has been

Toward translational incremental similarity-based reasoning in breast cancer grading

Science.gov (United States)

Tutac, Adina E.; Racoceanu, Daniel; Leow, Wee-Keng; Müller, Henning; Putti, Thomas; Cretu, Vladimir

2009-02-01

One of the fundamental issues in bridging the gap between the proliferation of Content-Based Image Retrieval (CBIR) systems in the scientific literature and the deficiency of their usage in medical community is based on the characteristic of CBIR to access information by images or/and text only. Yet, the way physicians are reasoning about patients leads intuitively to a case representation. Hence, a proper solution to overcome this gap is to consider a CBIR approach inspired by Case-Based Reasoning (CBR), which naturally introduces medical knowledge structured by cases. Moreover, in a CBR system, the knowledge is incrementally added and learned. The purpose of this study is to initiate a translational solution from CBIR algorithms to clinical practice, using a CBIR/CBR hybrid approach. Therefore, we advance the idea of a translational incremental similarity-based reasoning (TISBR), using combined CBIR and CBR characteristics: incremental learning of medical knowledge, medical case-based structure of the knowledge (CBR), image usage to retrieve similar cases (CBIR), similarity concept (central for both paradigms). For this purpose, three major axes are explored: the indexing, the cases retrieval and the search refinement, applied to Breast Cancer Grading (BCG), a powerful breast cancer prognosis exam. The effectiveness of this strategy is currently evaluated over cases provided by the Pathology Department of Singapore National University Hospital, for the indexing. With its current accuracy, TISBR launches interesting perspectives for complex reasoning in future medical research, opening the way to a better knowledge traceability and a better acceptance rate of computer-aided diagnosis assistance among practitioners.

Representation of Semantic Similarity in the Left Intraparietal Sulcus: Functional Magnetic Resonance Imaging Evidence

Directory of Open Access Journals (Sweden)

Veerle Neyens

2017-08-01

Full Text Available According to a recent study, semantic similarity between concrete entities correlates with the similarity of activity patterns in left middle IPS during category naming. We examined the replicability of this effect under passive viewing conditions, the potential role of visuoperceptual similarity, where the effect is situated compared to regions that have been previously implicated in visuospatial attention, and how it compares to effects of object identity and location. Forty-six subjects participated. Subjects passively viewed pictures from two categories, musical instruments and vehicles. Semantic similarity between entities was estimated based on a concept-feature matrix obtained in more than 1,000 subjects. Visuoperceptual similarity was modeled based on the HMAX model, the AlexNet deep convolutional learning model, and thirdly, based on subjective visuoperceptual similarity ratings. Among the IPS regions examined, only left middle IPS showed a semantic similarity effect. The effect was significant in hIP1, hIP2, and hIP3. Visuoperceptual similarity did not correlate with similarity of activity patterns in left middle IPS. The semantic similarity effect in left middle IPS was significantly stronger than in the right middle IPS and also stronger than in the left or right posterior IPS. The semantic similarity effect was similar to that seen in the angular gyrus. Object identity effects were much more widespread across nearly all parietal areas examined. Location effects were relatively specific for posterior IPS and area 7 bilaterally. To conclude, the current findings replicate the semantic similarity effect in left middle IPS under passive viewing conditions, and demonstrate its anatomical specificity within a cytoarchitectonic reference frame. We propose that the semantic similarity effect in left middle IPS reflects the transient uploading of semantic representations in working memory.

A Signal Processing Method to Explore Similarity in Protein Flexibility

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Simina Vasilache

2010-01-01

Full Text Available Understanding mechanisms of protein flexibility is of great importance to structural biology. The ability to detect similarities between proteins and their patterns is vital in discovering new information about unknown protein functions. A Distance Constraint Model (DCM provides a means to generate a variety of flexibility measures based on a given protein structure. Although information about mechanical properties of flexibility is critical for understanding protein function for a given protein, the question of whether certain characteristics are shared across homologous proteins is difficult to assess. For a proper assessment, a quantified measure of similarity is necessary. This paper begins to explore image processing techniques to quantify similarities in signals and images that characterize protein flexibility. The dataset considered here consists of three different families of proteins, with three proteins in each family. The similarities and differences found within flexibility measures across homologous proteins do not align with sequence-based evolutionary methods.

Bottom-up fabrication of paper-based microchips by blade coating of cellulose microfibers on a patterned surface.

Science.gov (United States)

Gao, Bingbing; Liu, Hong; Gu, Zhongze

2014-12-23

We report a method for the bottom-up fabrication of paper-based capillary microchips by the blade coating of cellulose microfibers on a patterned surface. The fabrication process is similar to the paper-making process in which an aqueous suspension of cellulose microfibers is used as the starting material and is blade-coated onto a polypropylene substrate patterned using an inkjet printer. After water evaporation, the cellulose microfibers form a porous, hydrophilic, paperlike pattern that wicks aqueous solution by capillary action. This method enables simple, fast, inexpensive fabrication of paper-based capillary channels with both width and height down to about 10 μm. When this method is used, the capillary microfluidic chip for the colorimetric detection of glucose and total protein is fabricated, and the assay requires only 0.30 μL of sample, which is 240 times smaller than for paper devices fabricated using photolithography.

Similarity-based recommendation of new concepts to a terminology

NARCIS (Netherlands)

Chandar, Praveen; Yaman, Anil; Hoxha, Julia; He, Zhe; Weng, Chunhua

2015-01-01

Terminologies can suffer from poor concept coverage due to delays in addition of new concepts. This study tests a similarity-based approach to recommending concepts from a text corpus to a terminology. Our approach involves extraction of candidate concepts from a given text corpus, which are

Structure modulates similarity-based interference in sluicing: An eye tracking study.

Directory of Open Access Journals (Sweden)

Jesse A. Harris

2015-12-01

Full Text Available In cue-based content-addressable approaches to memory, a target and its competitors are retrieved in parallel from memory via a fast, associative cue-matching procedure under a severely limited focus of attention. Such a parallel matching procedure could in principle ignore the serial order or hierarchical structure characteristic of linguistic relations. I present an eye tracking while reading experiment that investigates whether the sentential position of a potential antecedent modulates the strength of similarity-based interference, a well-studied effect in which increased similarity in features between a target and its competitors results in slower and less accurate retrieval overall. The manipulation trades on an independently established Locality bias in sluiced structures to associate a wh-remnant (which ones in clausal ellipsis with the most local correlate (some wines, as in The tourists enjoyed some wines, but I don’t know which ones. The findings generally support cue-based parsing models of sentence processing that are subject to similarity-based interference in retrieval, and provide additional support to the growing body of evidence that retrieval is sensitive to both the structural position of a target antecedent and its competitors, and the specificity of retrieval cues.

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

Science.gov (United States)

Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

2015-01-01

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

Universal self-similarity of propagating populations.

Science.gov (United States)

Eliazar, Iddo; Klafter, Joseph

2010-07-01

This paper explores the universal self-similarity of propagating populations. The following general propagation model is considered: particles are randomly emitted from the origin of a d-dimensional Euclidean space and propagate randomly and independently of each other in space; all particles share a statistically common--yet arbitrary--motion pattern; each particle has its own random propagation parameters--emission epoch, motion frequency, and motion amplitude. The universally self-similar statistics of the particles' displacements and first passage times (FPTs) are analyzed: statistics which are invariant with respect to the details of the displacement and FPT measurements and with respect to the particles' underlying motion pattern. Analysis concludes that the universally self-similar statistics are governed by Poisson processes with power-law intensities and by the Fréchet and Weibull extreme-value laws.

Universal self-similarity of propagating populations

Science.gov (United States)

Eliazar, Iddo; Klafter, Joseph

2010-07-01

This paper explores the universal self-similarity of propagating populations. The following general propagation model is considered: particles are randomly emitted from the origin of a d -dimensional Euclidean space and propagate randomly and independently of each other in space; all particles share a statistically common—yet arbitrary—motion pattern; each particle has its own random propagation parameters—emission epoch, motion frequency, and motion amplitude. The universally self-similar statistics of the particles’ displacements and first passage times (FPTs) are analyzed: statistics which are invariant with respect to the details of the displacement and FPT measurements and with respect to the particles’ underlying motion pattern. Analysis concludes that the universally self-similar statistics are governed by Poisson processes with power-law intensities and by the Fréchet and Weibull extreme-value laws.

Similarity-based search of model organism, disease and drug effect phenotypes

KAUST Repository

Hoehndorf, Robert

2015-02-19

Background: Semantic similarity measures over phenotype ontologies have been demonstrated to provide a powerful approach for the analysis of model organism phenotypes, the discovery of animal models of human disease, novel pathways, gene functions, druggable therapeutic targets, and determination of pathogenicity. Results: We have developed PhenomeNET 2, a system that enables similarity-based searches over a large repository of phenotypes in real-time. It can be used to identify strains of model organisms that are phenotypically similar to human patients, diseases that are phenotypically similar to model organism phenotypes, or drug effect profiles that are similar to the phenotypes observed in a patient or model organism. PhenomeNET 2 is available at http://aber-owl.net/phenomenet. Conclusions: Phenotype-similarity searches can provide a powerful tool for the discovery and investigation of molecular mechanisms underlying an observed phenotypic manifestation. PhenomeNET 2 facilitates user-defined similarity searches and allows researchers to analyze their data within a large repository of human, mouse and rat phenotypes.

Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity

Directory of Open Access Journals (Sweden)

Xue Shan

2015-01-01

Full Text Available Although commercial recommendation system has made certain achievement in travelling route development, the recommendation system is facing a series of challenges because of people’s increasing interest in travelling. It is obvious that the core content of the recommendation system is recommendation algorithm. The advantages of recommendation algorithm can bring great effect to the recommendation system. Based on this, this paper applies traditional collaborative filtering algorithm for analysis. Besides, illustrating the deficiencies of the algorithm, such as the rating unicity and rating matrix sparsity, this paper proposes an improved algorithm combing the multi-similarity algorithm based on user and the element similarity algorithm based on user, so as to compensate for the deficiencies that traditional algorithm has within a controllable range. Experimental results have shown that the improved algorithm has obvious advantages in comparison with the traditional one. The improved algorithm has obvious effect on remedying the rating matrix sparsity and rating unicity.

A similarity-based data warehousing environment for medical images.

Science.gov (United States)

Teixeira, Jefferson William; Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Ricardo Rodrigues; Ciferri, Cristina Dutra de Aguiar

2015-11-01

A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

An Energy-Based Similarity Measure for Time Series

Directory of Open Access Journals (Sweden)

Pierre Brunagel

2007-11-01

Full Text Available A new similarity measure, called SimilB, for time series analysis, based on the cross-ΨB-energy operator (2004, is introduced. ΨB is a nonlinear measure which quantifies the interaction between two time series. Compared to Euclidean distance (ED or the Pearson correlation coefficient (CC, SimilB includes the temporal information and relative changes of the time series using the first and second derivatives of the time series. SimilB is well suited for both nonstationary and stationary time series and particularly those presenting discontinuities. Some new properties of ΨB are presented. Particularly, we show that ΨB as similarity measure is robust to both scale and time shift. SimilB is illustrated with synthetic time series and an artificial dataset and compared to the CC and the ED measures.

Searching for Contracting Patterns over Time: Do Prime Contractor and Subcontractor Relations Follow Similar Patterns for Professional Services Provision?

Science.gov (United States)

Ponomariov, Branco; Kingsley, Gordon; Boardman, Craig

2011-01-01

This paper compares over a 12-year period (1) patterns of contracting between a state transportation agency and its prime contractors providing engineering design services with (2) patterns between these prime contractors and their subcontractors. We find evidence of different contracting patterns at each level that emerge over time and coexist in…

Semantic similarity measures in the biomedical domain by leveraging a web search engine.

Science.gov (United States)

Hsieh, Sheau-Ling; Chang, Wen-Yung; Chen, Chi-Huang; Weng, Yung-Ching

2013-07-01

Various researches in web related semantic similarity measures have been deployed. However, measuring semantic similarity between two terms remains a challenging task. The traditional ontology-based methodologies have a limitation that both concepts must be resided in the same ontology tree(s). Unfortunately, in practice, the assumption is not always applicable. On the other hand, if the corpus is sufficiently adequate, the corpus-based methodologies can overcome the limitation. Now, the web is a continuous and enormous growth corpus. Therefore, a method of estimating semantic similarity is proposed via exploiting the page counts of two biomedical concepts returned by Google AJAX web search engine. The features are extracted as the co-occurrence patterns of two given terms P and Q, by querying P, Q, as well as P AND Q, and the web search hit counts of the defined lexico-syntactic patterns. These similarity scores of different patterns are evaluated, by adapting support vector machines for classification, to leverage the robustness of semantic similarity measures. Experimental results validating against two datasets: dataset 1 provided by A. Hliaoutakis; dataset 2 provided by T. Pedersen, are presented and discussed. In dataset 1, the proposed approach achieves the best correlation coefficient (0.802) under SNOMED-CT. In dataset 2, the proposed method obtains the best correlation coefficient (SNOMED-CT: 0.705; MeSH: 0.723) with physician scores comparing with measures of other methods. However, the correlation coefficients (SNOMED-CT: 0.496; MeSH: 0.539) with coder scores received opposite outcomes. In conclusion, the semantic similarity findings of the proposed method are close to those of physicians' ratings. Furthermore, the study provides a cornerstone investigation for extracting fully relevant information from digitizing, free-text medical records in the National Taiwan University Hospital database.

New Genome Similarity Measures based on Conserved Gene Adjacencies.

Science.gov (United States)

Doerr, Daniel; Kowada, Luis Antonio B; Araujo, Eloi; Deshpande, Shachi; Dantas, Simone; Moret, Bernard M E; Stoye, Jens

2017-06-01

Many important questions in molecular biology, evolution, and biomedicine can be addressed by comparative genomic approaches. One of the basic tasks when comparing genomes is the definition of measures of similarity (or dissimilarity) between two genomes, for example, to elucidate the phylogenetic relationships between species. The power of different genome comparison methods varies with the underlying formal model of a genome. The simplest models impose the strong restriction that each genome under study must contain the same genes, each in exactly one copy. More realistic models allow several copies of a gene in a genome. One speaks of gene families, and comparative genomic methods that allow this kind of input are called gene family-based. The most powerful-but also most complex-models avoid this preprocessing of the input data and instead integrate the family assignment within the comparative analysis. Such methods are called gene family-free. In this article, we study an intermediate approach between family-based and family-free genomic similarity measures. Introducing this simpler model, called gene connections, we focus on the combinatorial aspects of gene family-free genome comparison. While in most cases, the computational costs to the general family-free case are the same, we also find an instance where the gene connections model has lower complexity. Within the gene connections model, we define three variants of genomic similarity measures that have different expression powers. We give polynomial-time algorithms for two of them, while we show NP-hardness for the third, most powerful one. We also generalize the measures and algorithms to make them more robust against recent local disruptions in gene order. Our theoretical findings are supported by experimental results, proving the applicability and performance of our newly defined similarity measures.

MAC/FAC: A Model of Similarity-Based Retrieval

Science.gov (United States)

1994-10-01

Grapes (0.28) 327 Sour Grapes, analog The Taming of the Shrew (0.22), Merry Wives 251 (0.18), S[11 stories], Sour Grapes (-0.19) Sour Grapes, literal... The Institute for the 0 1 Learning Sciences Northwestern University CD• 00 MAC/FAC: A MODEL OF SIMILARITY-BASED RETRIEVAL Kenneth D. Forbus Dedre...Gentner Keith Law Technical Report #59 • October 1994 94-35188 wit Establisthed in 1989 with the support of Andersen Consulting Form Approved REPORT

Experimental Study of Dowel Bar Alternatives Based on Similarity Model Test

Directory of Open Access Journals (Sweden)

Chichun Hu

2017-01-01

Full Text Available In this study, a small-scaled accelerated loading test based on similarity theory and Accelerated Pavement Analyzer was developed to evaluate dowel bars with different materials and cross-sections. Jointed concrete specimen consisting of one dowel was designed as scaled model for the test, and each specimen was subjected to 864 thousand loading cycles. Deflections between jointed slabs were measured with dial indicators, and strains of the dowel bars were monitored with strain gauges. The load transfer efficiency, differential deflection, and dowel-concrete bearing stress for each case were calculated from these measurements. The test results indicated that the effect of the dowel modulus on load transfer efficiency can be characterized based on the similarity model test developed in the study. Moreover, round steel dowel was found to have similar performance to larger FRP dowel, and elliptical dowel can be preferentially considered in practice.

Spatial pattern evaluation of a calibrated national hydrological model - a remote-sensing-based diagnostic approach

Science.gov (United States)

Mendiguren, Gorka; Koch, Julian; Stisen, Simon

2017-11-01

Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds

Study on store-space assignment based on logistic AGV in e-commerce goods to person picking pattern

Science.gov (United States)

Xu, Lijuan; Zhu, Jie

2017-10-01

This paper studied on the store-space assignment based on logistic AGV in E-commerce goods to person picking pattern, and established the store-space assignment model based on the lowest picking cost, and design for store-space assignment algorithm after the cluster analysis based on similarity coefficient. And then through the example analysis, compared the picking cost between store-space assignment algorithm this paper design and according to item number and storage according to ABC classification allocation, and verified the effectiveness of the design of the store-space assignment algorithm.

Distributional and Knowledge-Based Approaches for Computing Portuguese Word Similarity

Directory of Open Access Journals (Sweden)

Hugo Gonçalo Oliveira

2018-02-01

Full Text Available Identifying similar and related words is not only key in natural language understanding but also a suitable task for assessing the quality of computational resources that organise words and meanings of a language, compiled by different means. This paper, which aims to be a reference for those interested in computing word similarity in Portuguese, presents several approaches for this task and is motivated by the recent availability of state-of-the-art distributional models of Portuguese words, which add to several lexical knowledge bases (LKBs for this language, available for a longer time. The previous resources were exploited to answer word similarity tests, which also became recently available for Portuguese. We conclude that there are several valid approaches for this task, but not one that outperforms all the others in every single test. Distributional models seem to capture relatedness better, while LKBs are better suited for computing genuine similarity, but, in general, better results are obtained when knowledge from different sources is combined.

The Evolution of Facultative Conformity Based on Similarity.

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Efferson, Charles; Lalive, Rafael; Cacault, Maria Paula; Kistler, Deborah

2016-01-01

Conformist social learning can have a pronounced impact on the cultural evolution of human societies, and it can shape both the genetic and cultural evolution of human social behavior more broadly. Conformist social learning is beneficial when the social learner and the demonstrators from whom she learns are similar in the sense that the same behavior is optimal for both. Otherwise, the social learner's optimum is likely to be rare among demonstrators, and conformity is costly. The trade-off between these two situations has figured prominently in the longstanding debate about the evolution of conformity, but the importance of the trade-off can depend critically on the flexibility of one's social learning strategy. We developed a gene-culture coevolutionary model that allows cognition to encode and process information about the similarity between naive learners and experienced demonstrators. Facultative social learning strategies that condition on perceived similarity evolve under certain circumstances. When this happens, facultative adjustments are often asymmetric. Asymmetric adjustments mean that the tendency to follow the majority when learners perceive demonstrators as similar is stronger than the tendency to follow the minority when learners perceive demonstrators as different. In an associated incentivized experiment, we found that social learners adjusted how they used social information based on perceived similarity, but adjustments were symmetric. The symmetry of adjustments completely eliminated the commonly assumed trade-off between cases in which learners and demonstrators share an optimum versus cases in which they do not. In a second experiment that maximized the potential for social learners to follow their preferred strategies, a few social learners exhibited an inclination to follow the majority. Most, however, did not respond systematically to social information. Additionally, in the complete absence of information about their similarity to

The Evolution of Facultative Conformity Based on Similarity.

Directory of Open Access Journals (Sweden)

Charles Efferson

Full Text Available Conformist social learning can have a pronounced impact on the cultural evolution of human societies, and it can shape both the genetic and cultural evolution of human social behavior more broadly. Conformist social learning is beneficial when the social learner and the demonstrators from whom she learns are similar in the sense that the same behavior is optimal for both. Otherwise, the social learner's optimum is likely to be rare among demonstrators, and conformity is costly. The trade-off between these two situations has figured prominently in the longstanding debate about the evolution of conformity, but the importance of the trade-off can depend critically on the flexibility of one's social learning strategy. We developed a gene-culture coevolutionary model that allows cognition to encode and process information about the similarity between naive learners and experienced demonstrators. Facultative social learning strategies that condition on perceived similarity evolve under certain circumstances. When this happens, facultative adjustments are often asymmetric. Asymmetric adjustments mean that the tendency to follow the majority when learners perceive demonstrators as similar is stronger than the tendency to follow the minority when learners perceive demonstrators as different. In an associated incentivized experiment, we found that social learners adjusted how they used social information based on perceived similarity, but adjustments were symmetric. The symmetry of adjustments completely eliminated the commonly assumed trade-off between cases in which learners and demonstrators share an optimum versus cases in which they do not. In a second experiment that maximized the potential for social learners to follow their preferred strategies, a few social learners exhibited an inclination to follow the majority. Most, however, did not respond systematically to social information. Additionally, in the complete absence of information about their

The Evolution of Facultative Conformity Based on Similarity

Science.gov (United States)

Efferson, Charles; Lalive, Rafael; Cacault, Maria Paula; Kistler, Deborah

2016-01-01

Conformist social learning can have a pronounced impact on the cultural evolution of human societies, and it can shape both the genetic and cultural evolution of human social behavior more broadly. Conformist social learning is beneficial when the social learner and the demonstrators from whom she learns are similar in the sense that the same behavior is optimal for both. Otherwise, the social learner’s optimum is likely to be rare among demonstrators, and conformity is costly. The trade-off between these two situations has figured prominently in the longstanding debate about the evolution of conformity, but the importance of the trade-off can depend critically on the flexibility of one’s social learning strategy. We developed a gene-culture coevolutionary model that allows cognition to encode and process information about the similarity between naive learners and experienced demonstrators. Facultative social learning strategies that condition on perceived similarity evolve under certain circumstances. When this happens, facultative adjustments are often asymmetric. Asymmetric adjustments mean that the tendency to follow the majority when learners perceive demonstrators as similar is stronger than the tendency to follow the minority when learners perceive demonstrators as different. In an associated incentivized experiment, we found that social learners adjusted how they used social information based on perceived similarity, but adjustments were symmetric. The symmetry of adjustments completely eliminated the commonly assumed trade-off between cases in which learners and demonstrators share an optimum versus cases in which they do not. In a second experiment that maximized the potential for social learners to follow their preferred strategies, a few social learners exhibited an inclination to follow the majority. Most, however, did not respond systematically to social information. Additionally, in the complete absence of information about their similarity to

Inference-Based Similarity Search in Randomized Montgomery Domains for Privacy-Preserving Biometric Identification.

Science.gov (United States)

Wang, Yi; Wan, Jianwu; Guo, Jun; Cheung, Yiu-Ming; C Yuen, Pong

2017-07-14

Similarity search is essential to many important applications and often involves searching at scale on high-dimensional data based on their similarity to a query. In biometric applications, recent vulnerability studies have shown that adversarial machine learning can compromise biometric recognition systems by exploiting the biometric similarity information. Existing methods for biometric privacy protection are in general based on pairwise matching of secured biometric templates and have inherent limitations in search efficiency and scalability. In this paper, we propose an inference-based framework for privacy-preserving similarity search in Hamming space. Our approach builds on an obfuscated distance measure that can conceal Hamming distance in a dynamic interval. Such a mechanism enables us to systematically design statistically reliable methods for retrieving most likely candidates without knowing the exact distance values. We further propose to apply Montgomery multiplication for generating search indexes that can withstand adversarial similarity analysis, and show that information leakage in randomized Montgomery domains can be made negligibly small. Our experiments on public biometric datasets demonstrate that the inference-based approach can achieve a search accuracy close to the best performance possible with secure computation methods, but the associated cost is reduced by orders of magnitude compared to cryptographic primitives.

Product design pattern based on big data-driven scenario

Directory of Open Access Journals (Sweden)

Conggang Yu

2016-07-01

Full Text Available This article discusses about new product design patterns in the big data era, gives designer a new rational thinking way, and is a new way to understand the design of the product. Based on the key criteria of the product design process, category, element, and product are used to input the data, which comprises concrete data and abstract data as an enlargement of the criteria of product design process for the establishment of a big data-driven product design pattern’s model. Moreover, an experiment and a product design case are conducted to verify the feasibility of the new pattern. Ultimately, we will conclude that the data-driven product design has two patterns: one is the concrete data supporting the product design, namely “product–data–product” pattern, and the second is based on the value of the abstract data for product design, namely “data–product–data” pattern. Through the data, users are involving themselves in the design development process. Data and product form a huge network, and data plays a role of connection or node. So the essence of the design is to find a new connection based on element, and to find a new node based on category.

Effect of acoustic similarity on short-term auditory memory in the monkey.

Science.gov (United States)

Scott, Brian H; Mishkin, Mortimer; Yin, Pingbo

2013-04-01

Recent evidence suggests that the monkey's short-term memory in audition depends on a passively retained sensory trace as opposed to a trace reactivated from long-term memory for use in working memory. Reliance on a passive sensory trace could render memory particularly susceptible to confusion between sounds that are similar in some acoustic dimension. If so, then in delayed matching-to-sample, the monkey's performance should be predicted by the similarity in the salient acoustic dimension between the sample and subsequent test stimulus, even at very short delays. To test this prediction and isolate the acoustic features relevant to short-term memory, we examined the pattern of errors made by two rhesus monkeys performing a serial, auditory delayed match-to-sample task with interstimulus intervals of 1 s. The analysis revealed that false-alarm errors did indeed result from similarity-based confusion between the sample and the subsequent nonmatch stimuli. Manipulation of the stimuli showed that removal of spectral cues was more disruptive to matching behavior than removal of temporal cues. In addition, the effect of acoustic similarity on false-alarm response was stronger at the first nonmatch stimulus than at the second one. This pattern of errors would be expected if the first nonmatch stimulus overwrote the sample's trace, and suggests that the passively retained trace is not only vulnerable to similarity-based confusion but is also highly susceptible to overwriting. Copyright © 2013 Elsevier B.V. All rights reserved.

An Enhanced Rule-Based Web Scanner Based on Similarity Score

Directory of Open Access Journals (Sweden)

LEE, M.

2016-08-01

Full Text Available This paper proposes an enhanced rule-based web scanner in order to get better accuracy in detecting web vulnerabilities than the existing tools, which have relatively high false alarm rate when the web pages are installed in unconventional directory paths. Using the proposed matching method based on similarity score, the proposed scheme can determine whether two pages have the same vulnerabilities or not. With this method, the proposed scheme is able to figure out the target web pages are vulnerable by comparing them to the web pages that are known to have vulnerabilities. We show the proposed scanner reduces 12% false alarm rate compared to the existing well-known scanner through the performance evaluation via various experiments. The proposed scheme is especially helpful in detecting vulnerabilities of the web applications which come from well-known open-source web applications after small customization, which happens frequently in many small-sized companies.

Characterisation of taro (Colocasia esculenta based on morphological and isozymic patterns markers

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SUGIYARTO

2011-03-01

Full Text Available Trimanto, Sajidan, Sugiyarto. 2011. Characterization of taro (Colocasia esculenta based on morphological and isozymic patterns markers. Nusantara Bioscience: 7-14. The aims of this research were to find out: (i the variety of Colocasia esculenta based on the morphological characteristics; (ii the variety of C. esculenta based on the isozymic banding pattern; and (iii the correlation of genetic distance based on the morphological characteristics and isozymic banding pattern. Survey research conducted in the Karanganyar district, which include high, medium and low altitude. The sample was taken using random purposive sampling technique, including 9 sampling points. The morphological data was elaborated descriptively and then made dendogram. The data on isozymic banding pattern was analyzed quantitatively based on the presence or absence of bands appeared on the gel, and then made dendogram. The correlation based on the morphological characteristics and isozymic banding pattern were analyzed based on the product-moment correlation coefficient with goodness of fit criterion. The result showed : (i in Karanganyar was founded 10 variety of C. esculenta; (ii morphological characteristics are not affected by altitude; (iii isozymic banding pattern of peroxides forms 14 banding patterns, esterase forms 11 banding patterns and shikimic dehydrogenase forms 15 banding patterns; (iv the correlation of morphological data and the isozymic banding pattern of peroxidase has good correlation (0.893542288 while esterase and shikimic dehydrogenase isozymes have very good correlation (0.917557716 and 0.9121985446; (v isozymic banding pattern of data supports the morphological character data.

Structural pattern recognition methods based on string comparison for fusion databases

International Nuclear Information System (INIS)

Dormido-Canto, S.; Farias, G.; Dormido, R.; Vega, J.; Sanchez, J.; Duro, N.; Vargas, H.; Ratta, G.; Pereira, A.; Portas, A.

2008-01-01

Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed

Structural pattern recognition methods based on string comparison for fusion databases

Energy Technology Data Exchange (ETDEWEB)

Dormido-Canto, S. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain)], E-mail: sebas@dia.uned.es; Farias, G.; Dormido, R. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain); Sanchez, J.; Duro, N.; Vargas, H. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Ratta, G.; Pereira, A.; Portas, A. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain)

2008-04-15

Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed.

Improved cosine similarity measures of simplified neutrosophic sets for medical diagnoses.

Science.gov (United States)

Ye, Jun

2015-03-01

In pattern recognition and medical diagnosis, similarity measure is an important mathematical tool. To overcome some disadvantages of existing cosine similarity measures of simplified neutrosophic sets (SNSs) in vector space, this paper proposed improved cosine similarity measures of SNSs based on cosine function, including single valued neutrosophic cosine similarity measures and interval neutrosophic cosine similarity measures. Then, weighted cosine similarity measures of SNSs were introduced by taking into account the importance of each element. Further, a medical diagnosis method using the improved cosine similarity measures was proposed to solve medical diagnosis problems with simplified neutrosophic information. The improved cosine similarity measures between SNSs were introduced based on cosine function. Then, we compared the improved cosine similarity measures of SNSs with existing cosine similarity measures of SNSs by numerical examples to demonstrate their effectiveness and rationality for overcoming some shortcomings of existing cosine similarity measures of SNSs in some cases. In the medical diagnosis method, we can find a proper diagnosis by the cosine similarity measures between the symptoms and considered diseases which are represented by SNSs. Then, the medical diagnosis method based on the improved cosine similarity measures was applied to two medical diagnosis problems to show the applications and effectiveness of the proposed method. Two numerical examples all demonstrated that the improved cosine similarity measures of SNSs based on the cosine function can overcome the shortcomings of the existing cosine similarity measures between two vectors in some cases. By two medical diagnoses problems, the medical diagnoses using various similarity measures of SNSs indicated the identical diagnosis results and demonstrated the effectiveness and rationality of the diagnosis method proposed in this paper. The improved cosine measures of SNSs based on cosine

Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures.

Science.gov (United States)

Zhang, Bijun; Vogt, Martin; Maggiora, Gerald M; Bajorath, Jürgen

2015-10-01

Chemical space networks (CSNs) have recently been introduced as an alternative to other coordinate-free and coordinate-based chemical space representations. In CSNs, nodes represent compounds and edges pairwise similarity relationships. In addition, nodes are annotated with compound property information such as biological activity. CSNs have been applied to view biologically relevant chemical space in comparison to random chemical space samples and found to display well-resolved topologies at low edge density levels. The way in which molecular similarity relationships are assessed is an important determinant of CSN topology. Previous CSN versions were based on numerical similarity functions or the assessment of substructure-based similarity. Herein, we report a new CSN design that is based upon combined numerical and substructure similarity evaluation. This has been facilitated by calculating numerical similarity values on the basis of maximum common substructures (MCSs) of compounds, leading to the introduction of MCS-based CSNs (MCS-CSNs). This CSN design combines advantages of continuous numerical similarity functions with a robust and chemically intuitive substructure-based assessment. Compared to earlier version of CSNs, MCS-CSNs are characterized by a further improved organization of local compound communities as exemplified by the delineation of drug-like subspaces in regions of biologically relevant chemical space.

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.

Cross-Platform Mobile Application Development: A Pattern-Based Approach

Science.gov (United States)

2012-03-01

TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE Cross-Platform Mobile Application Development: A Pattern-Based Approach 5. FUNDING...for public release; distribution is unlimited CROSS-PLATFORM MOBILE APPLICATION DEVELOPMENT: A PATTERN-BASED APPROACH Christian G. Acord...occurring design problems. We then discuss common approaches to mobile development, including common aspects of mobile application development, including

A new precipitation and drought climatology based on weather patterns.

Science.gov (United States)

Richardson, Douglas; Fowler, Hayley J; Kilsby, Christopher G; Neal, Robert

2018-02-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterize the broad-scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI-based drought months. The new weather-pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation-based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification-based analyses in the UK.

Semantic similarity measure in biomedical domain leverage web search engine.

Science.gov (United States)

Chen, Chi-Huang; Hsieh, Sheau-Ling; Weng, Yung-Ching; Chang, Wen-Yung; Lai, Feipei

2010-01-01

Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

Similarity of trajectories taking into account geographic context

Directory of Open Access Journals (Sweden)

Maike Buchin

2014-12-01

Full Text Available The movements of animals, people, and vehicles are embedded in a geographic context. This context influences the movement and may cause the formation of certain behavioral responses. Thus, it is essential to include context parameters in the study of movement and the development of movement pattern analytics. Advances in sensor technologies and positioning devices provide valuable data not only of moving agents but also of the circumstances embedding the movement in space and time. Developing knowledge discovery methods to investigate the relation between movement and its surrounding context is a major challenge in movement analysis today. In this paper we show how to integrate geographic context into the similarity analysis of movement data. For this, we discuss models for geographic context of movement data. Based on this we develop simple but efficient context-aware similarity measures for movement trajectories, which combine a spatial and a contextual distance. These are based on well-known similarity measures for trajectories, such as the Hausdorff, Fréchet, or equal time distance. We validate our approach by applying these measures to movement data of hurricanes and albatross.

Visual identification and similarity measures used for on-line motion planning of autonomous robots in unknown environments

Science.gov (United States)

Martínez, Fredy; Martínez, Fernando; Jacinto, Edwar

2017-02-01

In this paper we propose an on-line motion planning strategy for autonomous robots in dynamic and locally observable environments. In this approach, we first visually identify geometric shapes in the environment by filtering images. Then, an ART-2 network is used to establish the similarity between patterns. The proposed algorithm allows that a robot establish its relative location in the environment, and define its navigation path based on images of the environment and its similarity to reference images. This is an efficient and minimalist method that uses the similarity of landmark view patterns to navigate to the desired destination. Laboratory tests on real prototypes demonstrate the performance of the algorithm.

Neural Substrates of Similarity and Rule-based Strategies in Judgment

Directory of Open Access Journals (Sweden)

Bettina eVon Helversen

2014-10-01

Full Text Available Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI, we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved.

On distributional assumptions and whitened cosine similarities

DEFF Research Database (Denmark)

Loog, Marco

2008-01-01

Recently, an interpretation of the whitened cosine similarity measure as a Bayes decision rule was proposed (C. Liu, "The Bayes Decision Rule Induced Similarity Measures,'' IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 6, pp. 1086-1090, June 2007. This communication makes th...

Thai Language Sentence Similarity Computation Based on Syntactic Structure and Semantic Vector

Science.gov (United States)

Wang, Hongbin; Feng, Yinhan; Cheng, Liang

2018-03-01

Sentence similarity computation plays an increasingly important role in text mining, Web page retrieval, machine translation, speech recognition and question answering systems. Thai language as a kind of resources scarce language, it is not like Chinese language with HowNet and CiLin resources. So the Thai sentence similarity research faces some challenges. In order to solve this problem of the Thai language sentence similarity computation. This paper proposes a novel method to compute the similarity of Thai language sentence based on syntactic structure and semantic vector. This method firstly uses the Part-of-Speech (POS) dependency to calculate two sentences syntactic structure similarity, and then through the word vector to calculate two sentences semantic similarity. Finally, we combine the two methods to calculate two Thai language sentences similarity. The proposed method not only considers semantic, but also considers the sentence syntactic structure. The experiment result shows that this method in Thai language sentence similarity computation is feasible.

Aggregation Operator Based Fuzzy Pattern Classifier Design

DEFF Research Database (Denmark)

Mönks, Uwe; Larsen, Henrik Legind; Lohweg, Volker

2009-01-01

This paper presents a novel modular fuzzy pattern classifier design framework for intelligent automation systems, developed on the base of the established Modified Fuzzy Pattern Classifier (MFPC) and allows designing novel classifier models which are hardware-efficiently implementable....... The performances of novel classifiers using substitutes of MFPC's geometric mean aggregator are benchmarked in the scope of an image processing application against the MFPC to reveal classification improvement potentials for obtaining higher classification rates....

Mutational pattern of the nurse shark antigen receptor gene (NAR) is similar to that of mammalian Ig genes and to spontaneous mutations in evolution: the translesion synthesis model of somatic hypermutation.

Science.gov (United States)

Diaz, M; Velez, J; Singh, M; Cerny, J; Flajnik, M F

1999-05-01

The pattern of somatic mutations of shark and frog Ig is distinct from somatic hypermutation of Ig in mammals in that there is a bias to mutate GC base pairs and a low frequency of mutations. Previous analysis of the new antigen receptor gene in nurse sharks (NAR), however, revealed no bias to mutate GC base pairs and the frequency of mutation was comparable to that of mammalian IgG. Here, we analyzed 1023 mutations in NAR and found no targeting of the mechanism to any particular nucleotide but did obtain strong evidence for a transition bias and for strand polarity. As seen for all species studied to date, the serine codon AGC/T in NAR was a mutational hotspot. The NAR mutational pattern is most similar to that of mammalian IgG and furthermore both are strikingly akin to mutations acquired during the neutral evolution of nuclear pseudogenes, suggesting that a similar mechanism is at work for both processes. In yeast, most spontaneous mutations are introduced by the translesion synthesis DNA polymerase zeta (REV3) and in various DNA repair-deficient backgrounds transitions were more often REV3-dependent than were transversions. Therefore, we propose a model of somatic hypermutation where DNA polymerase zeta is recruited to the Ig locus. An excess of DNA glycosylases in germinal center reactions may further enhance the mutation frequency by a REV3-dependent mutagenic process known as imbalanced base excision repair.

Visualizing Article Similarities via Sparsified Article Network and Map Projection for Systematic Reviews.

Science.gov (United States)

Ji, Xiaonan; Machiraju, Raghu; Ritter, Alan; Yen, Po-Yin

2017-01-01

Systematic Reviews (SRs) of biomedical literature summarize evidence from high-quality studies to inform clinical decisions, but are time and labor intensive due to the large number of article collections. Article similarities established from textual features have been shown to assist in the identification of relevant articles, thus facilitating the article screening process efficiently. In this study, we visualized article similarities to extend its utilization in practical settings for SR researchers, aiming to promote human comprehension of article distributions and hidden patterns. To prompt an effective visualization in an interpretable, intuitive, and scalable way, we implemented a graph-based network visualization with three network sparsification approaches and a distance-based map projection via dimensionality reduction. We evaluated and compared three network sparsification approaches and the visualization types (article network vs. article map). We demonstrated the effectiveness in revealing article distribution and exhibiting clustering patterns of relevant articles with practical meanings for SRs.

How similar are recognition memory and inductive reasoning?

Science.gov (United States)

Hayes, Brett K; Heit, Evan

2013-07-01

Conventionally, memory and reasoning are seen as different types of cognitive activities driven by different processes. In two experiments, we challenged this view by examining the relationship between recognition memory and inductive reasoning involving multiple forms of similarity. A common study set (members of a conjunctive category) was followed by a test set containing old and new category members, as well as items that matched the study set on only one dimension. The study and test sets were presented under recognition or induction instructions. In Experiments 1 and 2, the inductive property being generalized was varied in order to direct attention to different dimensions of similarity. When there was no time pressure on decisions, patterns of positive responding were strongly affected by property type, indicating that different types of similarity were driving recognition and induction. By comparison, speeded judgments showed weaker property effects and could be explained by generalization based on overall similarity. An exemplar model, GEN-EX (GENeralization from EXamples), could account for both the induction and recognition data. These findings show that induction and recognition share core component processes, even when the tasks involve flexible forms of similarity.

Perception of similarity: a model for social network dynamics

International Nuclear Information System (INIS)

Javarone, Marco Alberto; Armano, Giuliano

2013-01-01

Some properties of social networks (e.g., the mixing patterns and the community structure) appear deeply influenced by the individual perception of people. In this work we map behaviors by considering similarity and popularity of people, also assuming that each person has his/her proper perception and interpretation of similarity. Although investigated in different ways (depending on the specific scientific framework), from a computational perspective similarity is typically calculated as a distance measure. In accordance with this view, to represent social network dynamics we developed an agent-based model on top of a hyperbolic space on which individual distance measures are calculated. Simulations, performed in accordance with the proposed model, generate small-world networks that exhibit a community structure. We deem this model to be valuable for analyzing the relevant properties of real social networks. (paper)

Dispersal similarly shapes both population genetics and community patterns in the marine realm

KAUST Repository

Chust, Guillem

2016-06-27

Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.

Dispersal similarly shapes both population genetics and community patterns in the marine realm

Science.gov (United States)

Chust, Guillem; Villarino, Ernesto; Chenuil, Anne; Irigoien, Xabier; Bizsel, Nihayet; Bode, Antonio; Broms, Cecilie; Claus, Simon; Fernández de Puelles, María L.; Fonda-Umani, Serena; Hoarau, Galice; Mazzocchi, Maria G.; Mozetič, Patricija; Vandepitte, Leen; Veríssimo, Helena; Zervoudaki, Soultana; Borja, Angel

2016-06-01

Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.

Dispersal similarly shapes both population genetics and community patterns in the marine realm

KAUST Repository

Chust, Guillem; Villarino, Ernesto; Chenuil, Anne; Irigoien, Xabier; Bizsel, Nihayet; Bode, Antonio; Broms, Cecilie; Claus, Simon; Ferná ndez de Puelles, Marí a L.; Fonda-Umani, Serena; Hoarau, Galice; Mazzocchi, Maria G.; Mozetič, Patricija; Vandepitte, Leen; Verí ssimo, Helena; Zervoudaki, Soultana; Borja, Angel

2016-01-01

Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.

PIXEL PATTERN BASED STEGANOGRAPHY ON IMAGES

Directory of Open Access Journals (Sweden)

R. Rejani

2015-02-01

Full Text Available One of the drawback of most of the existing steganography methods is that it alters the bits used for storing color information. Some of the examples include LSB or MSB based steganography. There are also various existing methods like Dynamic RGB Intensity Based Steganography Scheme, Secure RGB Image Steganography from Pixel Indicator to Triple Algorithm etc that can be used to find out the steganography method used and break it. Another drawback of the existing methods is that it adds noise to the image which makes the image look dull or grainy making it suspicious for a person about existence of a hidden message within the image. To overcome these shortcomings we have come up with a pixel pattern based steganography which involved hiding the message within in image by using the existing RGB values whenever possible at pixel level or with minimum changes. Along with the image a key will also be used to decrypt the message stored at pixel levels. For further protection, both the message stored as well as the key file will be in encrypted format which can have same or different keys or decryption. Hence we call it as a RGB pixel pattern based steganography.

Prosodic Similarity Effects in Short-Term Memory in Developmental Dyslexia.

Science.gov (United States)

Goswami, Usha; Barnes, Lisa; Mead, Natasha; Power, Alan James; Leong, Victoria

2016-11-01

Children with developmental dyslexia are characterized by phonological difficulties across languages. Classically, this 'phonological deficit' in dyslexia has been investigated with tasks using single-syllable words. Recently, however, several studies have demonstrated difficulties in prosodic awareness in dyslexia. Potential prosodic effects in short-term memory have not yet been investigated. Here we create a new instrument based on three-syllable words that vary in stress patterns, to investigate whether prosodic similarity (the same prosodic pattern of stressed and unstressed syllables) exerts systematic effects on short-term memory. We study participants with dyslexia and age-matched and younger reading-level-matched typically developing controls. We find that all participants, including dyslexic participants, show prosodic similarity effects in short-term memory. All participants exhibited better retention of words that differed in prosodic structure, although participants with dyslexia recalled fewer words accurately overall compared to age-matched controls. Individual differences in prosodic memory were predicted by earlier vocabulary abilities, by earlier sensitivity to syllable stress and by earlier phonological awareness. To our knowledge, this is the first demonstration of prosodic similarity effects in short-term memory. The implications of a prosodic similarity effect for theories of lexical representation and of dyslexia are discussed. © 2016 The Authors. Dyslexia published by John Wiley & Sons Ltd. © 2016 The Authors. Dyslexia published by John Wiley & Sons Ltd.

3D Facial Similarity Measure Based on Geodesic Network and Curvatures

Directory of Open Access Journals (Sweden)

Junli Zhao

2014-01-01

Full Text Available Automated 3D facial similarity measure is a challenging and valuable research topic in anthropology and computer graphics. It is widely used in various fields, such as criminal investigation, kinship confirmation, and face recognition. This paper proposes a 3D facial similarity measure method based on a combination of geodesic and curvature features. Firstly, a geodesic network is generated for each face with geodesics and iso-geodesics determined and these network points are adopted as the correspondence across face models. Then, four metrics associated with curvatures, that is, the mean curvature, Gaussian curvature, shape index, and curvedness, are computed for each network point by using a weighted average of its neighborhood points. Finally, correlation coefficients according to these metrics are computed, respectively, as the similarity measures between two 3D face models. Experiments of different persons’ 3D facial models and different 3D facial models of the same person are implemented and compared with a subjective face similarity study. The results show that the geodesic network plays an important role in 3D facial similarity measure. The similarity measure defined by shape index is consistent with human’s subjective evaluation basically, and it can measure the 3D face similarity more objectively than the other indices.

Genetic similarity among commercial oil palm materials based on microsatellite markers

Directory of Open Access Journals (Sweden)

Diana Arias

2012-08-01

Full Text Available Microsatellite markers are used to determine genetic similarities among individuals and might be used in various applications in breeding programs. For example, knowing the genetic similarity relationships of commercial planting materials helps to better understand their responses to environmental, agronomic and plant health factors. This study assessed 17 microsatellite markers in 9 crosses (D x P of Elaeis guineensis Jacq. from various commercial companies in Malaysia, France, Costa Rica and Colombia, in order to find possible genetic differences and/or similarities. Seventy-seven alleles were obtained, with an average of 4.5 alleles per primer and a range of 2-8 amplified alleles. The results show a significant reduction of alleles, compared to the number of alleles reported for wild oil palm populations. The obtained dendrogram shows the formation of two groups based on their genetic similarity. Group A, with ~76% similarity, contains the commercial material of 3 codes of Deli x La Mé crosses produced in France and Colombia, and group B, with ~66% genetic similarity, includes all the materials produced by commercial companies in Malaysia, France, Costa Rica and Colombia

Clustering Of Left Ventricular Wall Motion Patterns

Science.gov (United States)

Bjelogrlic, Z.; Jakopin, J.; Gyergyek, L.

1982-11-01

A method for detection of wall regions with similar motion was presented. A model based on local direction information was used to measure the left ventricular wall motion from cineangiographic sequence. Three time functions were used to define segmental motion patterns: distance of a ventricular contour segment from the mean contour, the velocity of a segment and its acceleration. Motion patterns were clustered by the UPGMA algorithm and by an algorithm based on K-nearest neighboor classification rule.

BnDGAT1s Function Similarly in Oil Deposition and Are Expressed with Uniform Patterns in Tissues of Brassica napus

Directory of Open Access Journals (Sweden)

Cuizhu Zhao

2017-12-01

Full Text Available As an allotetraploid oilcrop, Brassica napus contains four duplicated Acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1 genes, which catalyze one of the rate-limiting steps in triacylglycerol (TAG biosynthesis in plants. While all four BnDGAT1s have been expressed functionally in yeast, their expression patterns in different germplasms and tissues and also consequent contribution to seed oil accumulation in planta remain to be elucidated. In this study, the coding regions of the four BnDGAT1s were expressed in an Arabidopsis dgat1 mutant. All four BnDGAT1s showed similar effects on oil content and fatty acid composition, a result which is different from that observed in previous studies of their expression in yeast. Expression patterns of BnDGAT1s were analyzed in developing seeds of 34 B. napus inbred lines and in different tissues of 14 lines. Different expression patterns were observed for the four BnDGAT1s, which suggests that they express independently or randomly in different germplasm sources. Higher expression of BnDGAT1s was correlated with higher seed oil content lines. Tissue-specific analyses showed that the BnDGAT1s were expressed in a uniform pattern in different tissues. Our results suggest that it is important to maintain expression of the four BnDGAT1s for maximum return on oil content.

Diffraction-based overlay metrology for double patterning technologies

Science.gov (United States)

Dasari, Prasad; Korlahalli, Rahul; Li, Jie; Smith, Nigel; Kritsun, Oleg; Volkman, Cathy

2009-03-01

The extension of optical lithography to 32nm and beyond is made possible by Double Patterning Techniques (DPT) at critical levels of the process flow. The ease of DPT implementation is hindered by increased significance of critical dimension uniformity and overlay errors. Diffraction-based overlay (DBO) has shown to be an effective metrology solution for accurate determination of the overlay errors associated with double patterning [1, 2] processes. In this paper we will report its use in litho-freeze-litho-etch (LFLE) and spacer double patterning technology (SDPT), which are pitch splitting solutions that reduce the significance of overlay errors. Since the control of overlay between various mask/level combinations is critical for fabrication, precise and accurate assessment of errors by advanced metrology techniques such as spectroscopic diffraction based overlay (DBO) and traditional image-based overlay (IBO) using advanced target designs will be reported. A comparison between DBO, IBO and CD-SEM measurements will be reported. . A discussion of TMU requirements for 32nm technology and TMU performance data of LFLE and SDPT targets by different overlay approaches will be presented.

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...

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.

Assessing Gait Impairments Based on Auto-Encoded Patterns of Mahalanobis Distances from Consecutive Steps.

Science.gov (United States)

Muñoz-Organero, Mario; Davies, Richard; Mawson, Sue

2017-01-01

Insole pressure sensors capture the force distribution patterns during the stance phase while walking. By comparing patterns obtained from healthy individuals to patients suffering different medical conditions based on a given similarity measure, automatic impairment indexes can be computed in order to help in applications such as rehabilitation. This paper uses the data sensed from insole pressure sensors for a group of healthy controls to train an auto-encoder using patterns of stochastic distances in series of consecutive steps while walking at normal speeds. Two experiment groups are compared to the healthy control group: a group of patients suffering knee pain and a group of post-stroke survivors. The Mahalanobis distance is computed for every single step by each participant compared to the entire dataset sensed from healthy controls. The computed distances for consecutive steps are fed into the previously trained autoencoder and the average error is used to assess how close the walking segment is to the autogenerated model from healthy controls. The results show that automatic distortion indexes can be used to assess each participant as compared to normal patterns computed from healthy controls. The stochastic distances observed for the group of stroke survivors are bigger than those for the people with knee pain.

Nationwide and population-based prescription patterns in bipolar disorder

DEFF Research Database (Denmark)

Kessing, Lars Vedel; Vradi, Eleni; Andersen, Per Kragh

2016-01-01

OBJECTIVES: The aim of the present study was to describe prescription patterns and changes in these patterns over the last decade for patients diagnosed with bipolar disorder in mental healthcare, using population-based and nationwide data, and to relate the findings to recommendations from...... international guidelines. METHODS: A population-based, nationwide study was carried out. It included register-based longitudinal data on all patients with a first-ever contact with mental healthcare with a diagnosis of mania/bipolar disorder from the entire Danish population, and all prescription data...

Novel Agent Based-approach for Industrial Diagnosis: A Combined use Between Case-based Reasoning and Similarity Measure

Directory of Open Access Journals (Sweden)

Fatima Zohra Benkaddour

2016-12-01

Full Text Available In spunlace nonwovens industry, the maintenance task is very complex, it requires experts and operators collaboration. In this paper, we propose a new approach integrating an agent- based modelling with case-based reasoning that utilizes similarity measures and preferences module. The main purpose of our study is to compare and evaluate the most suitable similarity measure for our case. Furthermore, operators that are usually geographically dispersed, have to collaborate and negotiate to achieve mutual agreements, especially when their proposals (diagnosis lead to a conflicting situation. The experimentation shows that the suggested agent-based approach is very interesting and efficient for operators and experts who collaborate in INOTIS enterprise.

BSSF: a fingerprint based ultrafast binding site similarity search and function analysis server

Directory of Open Access Journals (Sweden)

Jiang Hualiang

2010-01-01

Full Text Available Abstract Background Genome sequencing and post-genomics projects such as structural genomics are extending the frontier of the study of sequence-structure-function relationship of genes and their products. Although many sequence/structure-based methods have been devised with the aim of deciphering this delicate relationship, there still remain large gaps in this fundamental problem, which continuously drives researchers to develop novel methods to extract relevant information from sequences and structures and to infer the functions of newly identified genes by genomics technology. Results Here we present an ultrafast method, named BSSF(Binding Site Similarity & Function, which enables researchers to conduct similarity searches in a comprehensive three-dimensional binding site database extracted from PDB structures. This method utilizes a fingerprint representation of the binding site and a validated statistical Z-score function scheme to judge the similarity between the query and database items, even if their similarities are only constrained in a sub-pocket. This fingerprint based similarity measurement was also validated on a known binding site dataset by comparing with geometric hashing, which is a standard 3D similarity method. The comparison clearly demonstrated the utility of this ultrafast method. After conducting the database searching, the hit list is further analyzed to provide basic statistical information about the occurrences of Gene Ontology terms and Enzyme Commission numbers, which may benefit researchers by helping them to design further experiments to study the query proteins. Conclusions This ultrafast web-based system will not only help researchers interested in drug design and structural genomics to identify similar binding sites, but also assist them by providing further analysis of hit list from database searching.

A path-based measurement for human miRNA functional similarities using miRNA-disease associations

Science.gov (United States)

Ding, Pingjian; Luo, Jiawei; Xiao, Qiu; Chen, Xiangtao

2016-09-01

Compared with the sequence and expression similarity, miRNA functional similarity is so important for biology researches and many applications such as miRNA clustering, miRNA function prediction, miRNA synergism identification and disease miRNA prioritization. However, the existing methods always utilized the predicted miRNA target which has high false positive and false negative to calculate the miRNA functional similarity. Meanwhile, it is difficult to achieve high reliability of miRNA functional similarity with miRNA-disease associations. Therefore, it is increasingly needed to improve the measurement of miRNA functional similarity. In this study, we develop a novel path-based calculation method of miRNA functional similarity based on miRNA-disease associations, called MFSP. Compared with other methods, our method obtains higher average functional similarity of intra-family and intra-cluster selected groups. Meanwhile, the lower average functional similarity of inter-family and inter-cluster miRNA pair is obtained. In addition, the smaller p-value is achieved, while applying Wilcoxon rank-sum test and Kruskal-Wallis test to different miRNA groups. The relationship between miRNA functional similarity and other information sources is exhibited. Furthermore, the constructed miRNA functional network based on MFSP is a scale-free and small-world network. Moreover, the higher AUC for miRNA-disease prediction indicates the ability of MFSP uncovering miRNA functional similarity.

Virtual drug screen schema based on multiview similarity integration and ranking aggregation.

Science.gov (United States)

Kang, Hong; Sheng, Zhen; Zhu, Ruixin; Huang, Qi; Liu, Qi; Cao, Zhiwei

2012-03-26

The current drug virtual screen (VS) methods mainly include two categories. i.e., ligand/target structure-based virtual screen and that, utilizing protein-ligand interaction fingerprint information based on the large number of complex structures. Since the former one focuses on the one-side information while the later one focuses on the whole complex structure, they are thus complementary and can be boosted by each other. However, a common problem faced here is how to present a comprehensive understanding and evaluation of the various virtual screen results derived from various VS methods. Furthermore, there is still an urgent need for developing an efficient approach to fully integrate various VS methods from a comprehensive multiview perspective. In this study, our virtual screen schema based on multiview similarity integration and ranking aggregation was tested comprehensively with statistical evaluations, providing several novel and useful clues on how to perform drug VS from multiple heterogeneous data sources. (1) 18 complex structures of HIV-1 protease with ligands from the PDB were curated as a test data set and the VS was performed with five different drug representations. Ritonavir ( 1HXW ) was selected as the query in VS and the weighted ranks of the query results were aggregated from multiple views through four similarity integration approaches. (2) Further, one of the ranking aggregation methods was used to integrate the similarity ranks calculated by gene ontology (GO) fingerprint and structural fingerprint on the data set from connectivity map, and two typical HDAC and HSP90 inhibitors were chosen as the queries. The results show that rank aggregation can enhance the result of similarity searching in VS when two or more descriptions are involved and provide a more reasonable similarity rank result. Our study shows that integrated VS based on multiple data fusion can achieve a remarkable better performance compared to that from individual ones and

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.

Evaluation of GO-based functional similarity measures using S. cerevisiae protein interaction and expression profile data

Directory of Open Access Journals (Sweden)

Du LinFang

2008-11-01

Full Text Available Abstract Background Researchers interested in analysing the expression patterns of functionally related genes usually hope to improve the accuracy of their results beyond the boundaries of currently available experimental data. Gene ontology (GO data provides a novel way to measure the functional relationship between gene products. Many approaches have been reported for calculating the similarities between two GO terms, known as semantic similarities. However, biologists are more interested in the relationship between gene products than in the scores linking the GO terms. To highlight the relationships among genes, recent studies have focused on functional similarities. Results In this study, we evaluated five functional similarity methods using both protein-protein interaction (PPI and expression data of S. cerevisiae. The receiver operating characteristics (ROC and correlation coefficient analysis of these methods showed that the maximum method outperformed the other methods. Statistical comparison of multiple- and single-term annotated proteins in biological process ontology indicated that genes with multiple GO terms may be more reliable for separating true positives from noise. Conclusion This study demonstrated the reliability of current approaches that elevate the similarity of GO terms to the similarity of proteins. Suggestions for further improvements in functional similarity analysis are also provided.

Protein-protein interaction network-based detection of functionally similar proteins within species.

Science.gov (United States)

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

Neutrosophic Similarity Score Based Weighted Histogram for Robust Mean-Shift Tracking

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Keli Hu

2017-10-01

Full Text Available Visual object tracking is a critical task in computer vision. Challenging things always exist when an object needs to be tracked. For instance, background clutter is one of the most challenging problems. The mean-shift tracker is quite popular because of its efficiency and performance in a range of conditions. However, the challenge of background clutter also disturbs its performance. In this article, we propose a novel weighted histogram based on neutrosophic similarity score to help the mean-shift tracker discriminate the target from the background. Neutrosophic set (NS is a new branch of philosophy for dealing with incomplete, indeterminate, and inconsistent information. In this paper, we utilize the single valued neutrosophic set (SVNS, which is a subclass of NS to improve the mean-shift tracker. First, two kinds of criteria are considered as the object feature similarity and the background feature similarity, and each bin of the weight histogram is represented in the SVNS domain via three membership functions T(Truth, I(indeterminacy, and F(Falsity. Second, the neutrosophic similarity score function is introduced to fuse those two criteria and to build the final weight histogram. Finally, a novel neutrosophic weighted mean-shift tracker is proposed. The proposed tracker is compared with several mean-shift based trackers on a dataset of 61 public sequences. The results revealed that our method outperforms other trackers, especially when confronting background clutter.

Generating "fragment-based virtual library" using pocket similarity search of ligand-receptor complexes.

Science.gov (United States)

Khashan, Raed S

2015-01-01

As the number of available ligand-receptor complexes is increasing, researchers are becoming more dedicated to mine these complexes to aid in the drug design and development process. We present free software which is developed as a tool for performing similarity search across ligand-receptor complexes for identifying binding pockets which are similar to that of a target receptor. The search is based on 3D-geometric and chemical similarity of the atoms forming the binding pocket. For each match identified, the ligand's fragment(s) corresponding to that binding pocket are extracted, thus forming a virtual library of fragments (FragVLib) that is useful for structure-based drug design. The program provides a very useful tool to explore available databases.

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

A Wavelet-Based Approach to Pattern Discovery in Melodies

DEFF Research Database (Denmark)

Velarde, Gissel; Meredith, David; Weyde, Tillman

2016-01-01

We present a computational method for pattern discovery based on the application of the wavelet transform to symbolic representations of melodies or monophonic voices. We model the importance of a discovered pattern in terms of the compression ratio that can be achieved by using it to describe...

Collaborative Filtering Recommendation Based on Trust Model with Fused Similar Factor

Directory of Open Access Journals (Sweden)

Ye Li

2017-01-01

Full Text Available Recommended system is beneficial to e-commerce sites, which provides customers with product information and recommendations; the recommendation system is currently widely used in many fields. In an era of information explosion, the key challenges of the recommender system is to obtain valid information from the tremendous amount of information and produce high quality recommendations. However, when facing the large mount of information, the traditional collaborative filtering algorithm usually obtains a high degree of sparseness, which ultimately lead to low accuracy recommendations. To tackle this issue, we propose a novel algorithm named Collaborative Filtering Recommendation Based on Trust Model with Fused Similar Factor, which is based on the trust model and is combined with the user similarity. The novel algorithm takes into account the degree of interest overlap between the two users and results in a superior performance to the recommendation based on Trust Model in criteria of Precision, Recall, Diversity and Coverage. Additionally, the proposed model can effectively improve the efficiency of collaborative filtering algorithm and achieve high performance.

DOSim: An R package for similarity between diseases based on Disease Ontology

Science.gov (United States)

2011-01-01

Background The construction of the Disease Ontology (DO) has helped promote the investigation of diseases and disease risk factors. DO enables researchers to analyse disease similarity by adopting semantic similarity measures, and has expanded our understanding of the relationships between different diseases and to classify them. Simultaneously, similarities between genes can also be analysed by their associations with similar diseases. As a result, disease heterogeneity is better understood and insights into the molecular pathogenesis of similar diseases have been gained. However, bioinformatics tools that provide easy and straight forward ways to use DO to study disease and gene similarity simultaneously are required. Results We have developed an R-based software package (DOSim) to compute the similarity between diseases and to measure the similarity between human genes in terms of diseases. DOSim incorporates a DO-based enrichment analysis function that can be used to explore the disease feature of an independent gene set. A multilayered enrichment analysis (GO and KEGG annotation) annotation function that helps users explore the biological meaning implied in a newly detected gene module is also part of the DOSim package. We used the disease similarity application to demonstrate the relationship between 128 different DO cancer terms. The hierarchical clustering of these 128 different cancers showed modular characteristics. In another case study, we used the gene similarity application on 361 obesity-related genes. The results revealed the complex pathogenesis of obesity. In addition, the gene module detection and gene module multilayered annotation functions in DOSim when applied on these 361 obesity-related genes helped extend our understanding of the complex pathogenesis of obesity risk phenotypes and the heterogeneity of obesity-related diseases. Conclusions DOSim can be used to detect disease-driven gene modules, and to annotate the modules for functions and

Similarities and Differences in Pacing Patterns in a 161-km and 101-km Ultra-Distance Road Race.

Science.gov (United States)

Tan, Philip L S; Tan, Frankie H Y; Bosch, Andrew N

2016-08-01

Tan, PLS, Tan, FHY, and Bosch, AN. Similarities and differences in pacing patterns in a 161-km and 101-km ultra-distance road race. J Strength Cond Res 30(8): 2145-2155, 2016-The purpose of this study was to establish and compare the pacing patterns of fast and slow finishers in a tropical ultra-marathon. Data were collected from the Craze Ultra-marathon held on the 22nd and 21st of September in 2012 and 2013, respectively. Finishers of the 161-km (N = 47) and 101-km (N = 120) categories of the race were divided into thirds (groups A-C) by merit of finishing time. Altogether, 17 and 11 split times were recorded for the 161-km and 101-km finishers, respectively, and used to calculate the mean running speed for each distance segment. Running speed for the first segment was normalized to 100, with all subsequent splits adjusted accordingly. Running speed during the last 5 km was calculated against the mean race pace to establish the existence of an end spurt. A reverse J-shaped pacing profile was demonstrated in all groups for both distance categories and only 38% of the finishers executed an end spurt. In the 101-km category, in comparison with groups B and C, group A maintained a significantly more even pace (p = 0.013 and 0.001, respectively) and completed the race at a significantly higher percent of initial starting speed (p = 0.001 and 0.001, respectively). Descriptive data also revealed that the top 5 finishers displayed a "herd-behavior" by staying close to the lead runner in the initial portion of the race. These findings demonstrate that to achieve a more even pace, recreational ultra-runners should adopt a patient sustainable starting speed, with less competitive runners setting realistic performance goals whereas competitive runners with a specific time goal to consider running in packs of similar pace.

Composites Similarity Analysis Method Based on Knowledge Set in Composites Quality Control

OpenAIRE

Li Haifeng

2016-01-01

Composites similarity analysis is an important link of composites review, it can not only to declare composites review rechecking, still help composites applicants promptly have the research content relevant progress and avoid duplication. This paper mainly studies the composites similarity model in composites review. With the actual experience of composites management, based on the author’s knowledge set theory, paper analyzes deeply knowledge set representation of composites knowledge, impr...

n-Order and maximum fuzzy similarity entropy for discrimination of signals of different complexity: Application to fetal heart rate signals.

Science.gov (United States)

Zaylaa, Amira; Oudjemia, Souad; Charara, Jamal; Girault, Jean-Marc

2015-09-01

This paper presents two new concepts for discrimination of signals of different complexity. The first focused initially on solving the problem of setting entropy descriptors by varying the pattern size instead of the tolerance. This led to the search for the optimal pattern size that maximized the similarity entropy. The second paradigm was based on the n-order similarity entropy that encompasses the 1-order similarity entropy. To improve the statistical stability, n-order fuzzy similarity entropy was proposed. Fractional Brownian motion was simulated to validate the different methods proposed, and fetal heart rate signals were used to discriminate normal from abnormal fetuses. In all cases, it was found that it was possible to discriminate time series of different complexity such as fractional Brownian motion and fetal heart rate signals. The best levels of performance in terms of sensitivity (90%) and specificity (90%) were obtained with the n-order fuzzy similarity entropy. However, it was shown that the optimal pattern size and the maximum similarity measurement were related to intrinsic features of the time series. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fabrication of graphene-based flexible devices utilizing a soft lithographic patterning method

International Nuclear Information System (INIS)

Wook Jung, Min; Myung, Sung; Woong Kim, Ki; Song, Wooseok; Suk Lee, Sun; Lim, Jongsun; An, Ki-Seok; Jo, You-Young; Park, Chong-Yun

2014-01-01

There has been considerable interest in soft lithographic patterning processing of large scale graphene sheets due to the low cost and simplicity of the patterning process along with the exceptional electrical or physical properties of graphene. These properties include an extremely high carrier mobility and excellent mechanical strength. Recently, a study has reported that single layer graphene grown via chemical vapor deposition (CVD) was patterned and transferred to a target surface by controlling the surface energy of the polydimethylsiloxane (PDMS) stamp. However, applications are limited because of the challenge of CVD-graphene functionalization for devices such as chemical or bio-sensors. In addition, graphene-based layers patterned with a micron scale width on the surface of biocompatible silk fibroin thin films, which are not suitable for conventional CMOS processes such as the patterning or etching of substrates, have yet to be reported. Herein, we developed a soft lithographic patterning process via surface energy modification for advanced graphene-based flexible devices such as transistors or chemical sensors. Using this approach, the surface of a relief-patterned elastomeric stamp was functionalized with hydrophilic dimethylsulfoxide molecules to enhance the surface energy of the stamp and to remove the graphene-based layer from the initial substrate and transfer it to a target surface. As a proof of concept using this soft lithographic patterning technique, we demonstrated a simple and efficient chemical sensor consisting of reduced graphene oxide and a metallic nanoparticle composite. A flexible graphene-based device on a biocompatible silk fibroin substrate, which is attachable to an arbitrary target surface, was also successfully fabricated. Briefly, a soft lithographic patterning process via surface energy modification was developed for advanced graphene-based flexible devices such as transistors or chemical sensors and attachable devices on a

Fabrication of graphene-based flexible devices utilizing a soft lithographic patterning method

Science.gov (United States)

Jung, Min Wook; Myung, Sung; Kim, Ki Woong; Song, Wooseok; Jo, You-Young; Lee, Sun Suk; Lim, Jongsun; Park, Chong-Yun; An, Ki-Seok

2014-07-01

There has been considerable interest in soft lithographic patterning processing of large scale graphene sheets due to the low cost and simplicity of the patterning process along with the exceptional electrical or physical properties of graphene. These properties include an extremely high carrier mobility and excellent mechanical strength. Recently, a study has reported that single layer graphene grown via chemical vapor deposition (CVD) was patterned and transferred to a target surface by controlling the surface energy of the polydimethylsiloxane (PDMS) stamp. However, applications are limited because of the challenge of CVD-graphene functionalization for devices such as chemical or bio-sensors. In addition, graphene-based layers patterned with a micron scale width on the surface of biocompatible silk fibroin thin films, which are not suitable for conventional CMOS processes such as the patterning or etching of substrates, have yet to be reported. Herein, we developed a soft lithographic patterning process via surface energy modification for advanced graphene-based flexible devices such as transistors or chemical sensors. Using this approach, the surface of a relief-patterned elastomeric stamp was functionalized with hydrophilic dimethylsulfoxide molecules to enhance the surface energy of the stamp and to remove the graphene-based layer from the initial substrate and transfer it to a target surface. As a proof of concept using this soft lithographic patterning technique, we demonstrated a simple and efficient chemical sensor consisting of reduced graphene oxide and a metallic nanoparticle composite. A flexible graphene-based device on a biocompatible silk fibroin substrate, which is attachable to an arbitrary target surface, was also successfully fabricated. Briefly, a soft lithographic patterning process via surface energy modification was developed for advanced graphene-based flexible devices such as transistors or chemical sensors and attachable devices on a

Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

Science.gov (United States)

Zhang, Shu-Bo; Tang, Qiang-Rong

2016-07-21

Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Statistical potential-based amino acid similarity matrices for aligning distantly related protein sequences.

Science.gov (United States)

Tan, Yen Hock; Huang, He; Kihara, Daisuke

2006-08-15

Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more experimentally solved structures are available as templates for protein structure modeling. Toward this end, recent structure prediction methods employ profile-profile alignments, and various ways of aligning two profiles have been developed. More fundamentally, a better amino acid similarity matrix can improve a profile itself; thereby resulting in more accurate profile-profile alignments. Here we have developed novel amino acid similarity matrices from knowledge-based amino acid contact potentials. Contact potentials are used because the contact propensity to the other amino acids would be one of the most conserved features of each position of a protein structure. The derived amino acid similarity matrices are tested on benchmark alignments at three different levels, namely, the family, the superfamily, and the fold level. Compared to BLOSUM45 and the other existing matrices, the contact potential-based matrices perform comparably in the family level alignments, but clearly outperform in the fold level alignments. The contact potential-based matrices perform even better when suboptimal alignments are considered. Comparing the matrices themselves with each other revealed that the contact potential-based matrices are very different from BLOSUM45 and the other matrices, indicating that they are located in a different basin in the amino acid similarity matrix space.

The Impact of Similarity-Based Interference in Processing Wh-Questions in Aphasia

Directory of Open Access Journals (Sweden)

Shannon Mackenzie

2014-04-01

than subject-extracted questions because the former are in non-canonical word order. Finally, the Intervener hypothesis suggests that only object-extracted Which-questions should be problematic, particularly for those participants with language disorders (e.g., Friedmann & Novogrodsky, 2011. An intervener is an NP that has similar properties to other NPs in the sentence, and thus results in similarity-based interference. Only object-extracted Which-questions contain an intervener (e.g., the fireman in (2b, which interferes with the chain consisting of the displaced Which-phrase, Which mailman, and its direct object gap occurring after the verb. Briefly here, only the Intervener Hypothesis was supported by our rich data set, and this was observed unambiguously for our participants with Broca’s aphasia. As an example (see Figure 1, we observed significantly greater proportion of gazes to the incorrect referent (i.e., the intervening NP in the object-extracted Which- relative to Who-questions beginning in the Verb-gap time window and extending throughout the remainder of the sentence and into the response period following the sentence. These patterns indicate lasting similarity-based interference effects during real-time sentence processing. The implications of our findings to extant accounts of sentence processing disruptions will be discussed, including accounts that root sentence comprehension impairments to memory-based interference.

Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks.

Science.gov (United States)

Arunraja, Muruganantham; Malathi, Veluchamy; Sakthivel, Erulappan

2015-11-01

Wireless sensor networks are engaged in various data gathering applications. The major bottleneck in wireless data gathering systems is the finite energy of sensor nodes. By conserving the on board energy, the life span of wireless sensor network can be well extended. Data communication being the dominant energy consuming activity of wireless sensor network, data reduction can serve better in conserving the nodal energy. Spatial and temporal correlation among the sensor data is exploited to reduce the data communications. Data similar cluster formation is an effective way to exploit spatial correlation among the neighboring sensors. By sending only a subset of data and estimate the rest using this subset is the contemporary way of exploiting temporal correlation. In Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks, we construct data similar iso-clusters with minimal communication overhead. The intra-cluster communication is reduced using adaptive-normalized least mean squares based dual prediction framework. The cluster head reduces the inter-cluster data payload using a lossless compressive forwarding technique. The proposed work achieves significant data reduction in both the intra-cluster and the inter-cluster communications, with the optimal data accuracy of collected data. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Neutrosophic Refined Similarity Measure Based on Cosine Function

Directory of Open Access Journals (Sweden)

Said Broumi

2014-12-01

Full Text Available In this paper, the cosine similarity measure of neutrosophic refined (multi- sets is proposed and its properties are studied. The concept of this cosine similarity measure of neutrosophic refined sets is the extension of improved cosine similarity measure of single valued neutrosophic. Finally, using this cosine similarity measure of neutrosophic refined set, the application of medical diagnosis is presented.

Melodic pattern discovery by structural analysis via wavelets and clustering techniques

DEFF Research Database (Denmark)

Velarde, Gissel; Meredith, David

We present an automatic method to support melodic pattern discovery by structural analysis of symbolic representations by means of wavelet analysis and clustering techniques. In previous work, we used the method to recognize the parent works of melodic segments, or to classify tunes into tune......-means to cluster melodic segments into groups of measured similarity and obtain a raking of the most prototypical melodic segments or patterns and their occurrences. We test the method on the JKU Patterns Development Database and evaluate it based on the ground truth defined by the MIREX 2013 Discovery of Repeated...... Themes & Sections task. We compare the results of our method to the output of geometric approaches. Finally, we discuss about the relevance of our wavelet-based analysis in relation to structure, pattern discovery, similarity and variation, and comment about the considerations of the method when used...

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.

The cell pattern correction through design-based metrology

Science.gov (United States)

Kim, Yonghyeon; Lee, Kweonjae; Chang, Jinman; Kim, Taeheon; Han, Daehan; Lee, Kyusun; Hong, Aeran; Kang, Jinyoung; Choi, Bumjin; Lee, Joosung; Yeom, Kyehee; Lee, Jooyoung; Hong, Hyeongsun; Lee, Kyupil; Jin, Gyoyoung

2015-03-01

Starting with the sub 2Xnm node, the process window becomes smaller and tighter than before. Pattern related error budget is required for accurate critical-dimension control of Cell layers. Therefore, lithography has been faced with its various difficulties, such as weird distribution, overlay error, patterning difficulty etc. The distribution of cell pattern and overlay management are the most important factors in DRAM field. We had been experiencing that the fatal risk is caused by the patterns located in the tail of the distribution. The overlay also induces the various defect sources and misalignment issues. Even though we knew that these elements are important, we could not classify the defect type of Cell patterns. Because there is no way to gather massive small pattern CD samples in cell unit block and to compare layout with cell patterns by the CD-SEM. The CD- SEM is used in order to gather these data through high resolution, but CD-SEM takes long time to inspect and extract data because it measures the small FOV. (Field Of View) However, the NGR(E-beam tool) provides high speed with large FOV and high resolution. Also, it's possible to measure an accurate overlay between the target layout and cell patterns because they provide DBM. (Design Based Metrology) By using massive measured data, we extract the result that it is persuasive by applying the various analysis techniques, as cell distribution and defects, the pattern overlay error correction etc. We introduce how to correct cell pattern, by using the DBM measurement, and new analysis methods.

Automated dating of the world’s language families based on lexical similarity

OpenAIRE

Holman, E.; Brown, C.; Wichmann, S.; Müller, A.; Velupillai, V.; Hammarström, H.; Sauppe, S.; Jung, H.; Bakker, D.; Brown, P.; Belyaev, O.; Urban, M.; Mailhammer, R.; List, J.; Egorov, D.

2011-01-01

This paper describes a computerized alternative to glottochronology for estimating elapsed time since parent languages diverged into daughter languages. The method, developed by the Automated Similarity Judgment Program (ASJP) consortium, is different from glottochronology in four major respects: (1) it is automated and thus is more objective, (2) it applies a uniform analytical approach to a single database of worldwide languages, (3) it is based on lexical similarity as determined from Leve...

PATTERN BASED DETECTION OF POTENTIALLY DRUGGABLE BINDING SITES BY LIGAND SCREENING

Directory of Open Access Journals (Sweden)

Uttam Pal

2018-03-01

Full Text Available This article describes an innovative way of finding the potentially druggable sites on a target protein, which can be used for orthosteric and allosteric lead detection in a single virtual screening setup. Druggability estimation for an alternate binding site other than the canonical ligand-binding pocket of an enzyme is rewarding for several inherent benefits. Allostery is a direct and efficient way of regulating biomacromolecule function. The allosteric modulators can fine-tune protein mechanics. Besides, allosteric sites are evolutionarily less conserved/more diverse even in very similarly related proteins, thus, provides high degree of specificity in targeting a particular protein. Therefore, targeting of allosteric sites is gaining attention as an emerging strategy in rational drug design. However, the experimental approaches provide a limited degree of characterization of new allosteric sites. Computational approaches are useful to analyze and select potential allosteric sites for drug discovery. Here, the use of molecular docking, which has become an integral part of the drug discovery process, has been discussed to predict the druggability of novel allosteric sites as well as the active site on target proteins by ligand screening. Genetic algorithm was used for docking and the whole protein was placed in the search space. For each ligand in the library of small molecules, the genetic algorithm was run for multiple times to populate all the druggable sites in the target protein, which was then translated into two dimensional density maps or “patterns”. High density clusters were observed for lead like molecules in these pattern diagrams. Each cluster in such a pattern diagram indicated a plausible binding site and the density gave its druggability score in terms of weighted probabilities. The patterns were filtered to find the leads for each of the druggable sites on the target protein. Such a novel pattern based analysis of the

Diffraction-based overlay for spacer patterning and double patterning technology

Science.gov (United States)

Lee, Byoung Hoon; Park, JeongSu; Lee, Jongsu; Park, Sarohan; Lim, ChangMoon; Yim, Dong-Gyu; Park, Sungki; Ryu, Chan-Ho; Morgan, Stephen; van de Schaar, Maurits; Fuchs, Andreas; Bhattacharyya, Kaustuve

2011-03-01

Overlay performance will be increasingly important for Spacer Patterning Technology (SPT) and Double Patterning Technology (DPT) as various Resolution Enhancement Techniques are employed to extend the resolution limits of lithography. Continuous shrinkage of devices makes overlay accuracy one of the most critical issues while overlay performance is completely dependent on exposure tool. Image Based Overlay (IBO) has been used as the mainstream metrology for overlay by the main memory IC companies, but IBO is not suitable for some critical layers due to the poor Tool Induced Shift (TIS) values. Hence new overlay metrology is required to improve the overlay measurement accuracy. Diffraction Based Overlay (DBO) is regarded to be an alternative metrology to IBO for more accurate measurements and reduction of reading errors. Good overlay performances of DBO have been reported in many articles. However applying DBO for SPT and DPT layers poses extra challenges for target design. New vernier designs are considered for different DPT and SPT schemes to meet overlay target in DBO system. In this paper, we optimize the design of the DBO target and the performance of DBO to meet the overlay specification of sub-3x nm devices which are using SPT and DPT processes. We show that the appropriate vernier design yields excellent overlay performance in residual and TIS. The paper also demonstrated the effects of vernier structure on overlay accuracy from SEM analysis.

Density-based similarity measures for content based search

Energy Technology Data Exchange (ETDEWEB)

Hush, Don R [Los Alamos National Laboratory; Porter, Reid B [Los Alamos National Laboratory; Ruggiero, Christy E [Los Alamos National Laboratory

2009-01-01

We consider the query by multiple example problem where the goal is to identify database samples whose content is similar to a coUection of query samples. To assess the similarity we use a relative content density which quantifies the relative concentration of the query distribution to the database distribution. If the database distribution is a mixture of the query distribution and a background distribution then it can be shown that database samples whose relative content density is greater than a particular threshold {rho} are more likely to have been generated by the query distribution than the background distribution. We describe an algorithm for predicting samples with relative content density greater than {rho} that is computationally efficient and possesses strong performance guarantees. We also show empirical results for applications in computer network monitoring and image segmentation.

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.

Approach for Text Classification Based on the Similarity Measurement between Normal Cloud Models

Directory of Open Access Journals (Sweden)

Jin Dai

2014-01-01

Full Text Available The similarity between objects is the core research area of data mining. In order to reduce the interference of the uncertainty of nature language, a similarity measurement between normal cloud models is adopted to text classification research. On this basis, a novel text classifier based on cloud concept jumping up (CCJU-TC is proposed. It can efficiently accomplish conversion between qualitative concept and quantitative data. Through the conversion from text set to text information table based on VSM model, the text qualitative concept, which is extraction from the same category, is jumping up as a whole category concept. According to the cloud similarity between the test text and each category concept, the test text is assigned to the most similar category. By the comparison among different text classifiers in different feature selection set, it fully proves that not only does CCJU-TC have a strong ability to adapt to the different text features, but also the classification performance is also better than the traditional classifiers.

Similarities and differences in coatings for magnesium-based stents and orthopaedic implants

Directory of Open Access Journals (Sweden)

Jun Ma

2014-07-01

Full Text Available Magnesium (Mg-based biodegradable materials are promising candidates for the new generation of implantable medical devices, particularly cardiovascular stents and orthopaedic implants. Mg-based cardiovascular stents represent the most innovative stent technology to date. However, these products still do not fully meet clinical requirements with regards to fast degradation rates, late restenosis, and thrombosis. Thus various surface coatings have been introduced to protect Mg-based stents from rapid corrosion and to improve biocompatibility. Similarly, different coatings have been used for orthopaedic implants, e.g., plates and pins for bone fracture fixation or as an interference screw for tendon-bone or ligament-bone insertion, to improve biocompatibility and corrosion resistance. Metal coatings, nanoporous inorganic coatings and permanent polymers have been proved to enhance corrosion resistance; however, inflammation and foreign body reactions have also been reported. By contrast, biodegradable polymers are more biocompatible in general and are favoured over permanent materials. Drugs are also loaded with biodegradable polymers to improve their performance. The key similarities and differences in coatings for Mg-based stents and orthopaedic implants are summarized.

Origin of magnetic switching field distribution in bit patterned media based on pre-patterned substrates

OpenAIRE

Pfau , B; Günther , C.M.; Guehrs , E; Hauet , Thomas; Yang , H; Vinh , L.; Xu , X; Yaney , D; Rick , R; Eisebitt , S; Hellwig , O

2011-01-01

International audience; Using a combination of synchrotron radiation based magnetic imaging and high-resolution transmission electron microscopy we reveal systematic correlations between the magnetic switching field and the internal nanoscale structure of individual islands in bit patterned media fabricated by Co/Pd-multilayer deposition onto pre-patterned substrates. We find that misaligned grains at the island periphery are a common feature independent of the island switching field, while i...

Robust recognition of degraded machine-printed characters using complementary similarity measure and error-correction learning

Science.gov (United States)

Hagita, Norihiro; Sawaki, Minako

1995-03-01

Most conventional methods in character recognition extract geometrical features such as stroke direction, connectivity of strokes, etc., and compare them with reference patterns in a stored dictionary. Unfortunately, geometrical features are easily degraded by blurs, stains and the graphical background designs used in Japanese newspaper headlines. This noise must be removed before recognition commences, but no preprocessing method is completely accurate. This paper proposes a method for recognizing degraded characters and characters printed on graphical background designs. This method is based on the binary image feature method and uses binary images as features. A new similarity measure, called the complementary similarity measure, is used as a discriminant function. It compares the similarity and dissimilarity of binary patterns with reference dictionary patterns. Experiments are conducted using the standard character database ETL-2 which consists of machine-printed Kanji, Hiragana, Katakana, alphanumeric, an special characters. The results show that this method is much more robust against noise than the conventional geometrical feature method. It also achieves high recognition rates of over 92% for characters with textured foregrounds, over 98% for characters with textured backgrounds, over 98% for outline fonts, and over 99% for reverse contrast characters.

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.

Structural similarities between prokaryotic and eukaryotic 5S ribosomal RNAs

International Nuclear Information System (INIS)

Welfle, H.; Boehm, S.; Damaschun, G.; Fabian, H.; Gast, K.; Misselwitz, R.; Mueller, J.J.; Zirwer, D.; Filimonov, V.V.; Venyaminov, S.Yu.; Zalkova, T.N.

1986-01-01

5S RNAs from rat liver and E. coli have been studied by diffuse X-ray and dynamic light scattering and by infrared and Raman spectroscopy. Identical structures at a resolution of 1 nm can be deduced from the comparison of the experimental X-ray scattering curves and electron distance distribution functions and from the agreement of the shape parameters. A flat shape model with a compact central region and two protruding arms was derived. Double helical stems are eleven-fold helices with a mean base pair distance of 0.28 nm. The number of base pairs (26 GC, 9 AU for E. coli; 27 GC, 9 AU for rat liver) and the degree of base stacking are the same within the experimental error. A very high regularity in the ribophosphate backbone is indicated for both 5S RNAs. The observed structural similarity and the consensus secondary structure pattern derived from comparative sequence analyses suggest the conclusion that prokaryotic and eukaryotic 5S RNAs are in general very similar with respect to their fundamental structural features. (author)

Similarity Measure of Graphs

Directory of Open Access Journals (Sweden)

Amine Labriji

2017-07-01

Full Text Available The topic of identifying the similarity of graphs was considered as highly recommended research field in the Web semantic, artificial intelligence, the shape recognition and information research. One of the fundamental problems of graph databases is finding similar graphs to a graph query. Existing approaches dealing with this problem are usually based on the nodes and arcs of the two graphs, regardless of parental semantic links. For instance, a common connection is not identified as being part of the similarity of two graphs in cases like two graphs without common concepts, the measure of similarity based on the union of two graphs, or the one based on the notion of maximum common sub-graph (SCM, or the distance of edition of graphs. This leads to an inadequate situation in the context of information research. To overcome this problem, we suggest a new measure of similarity between graphs, based on the similarity measure of Wu and Palmer. We have shown that this new measure satisfies the properties of a measure of similarities and we applied this new measure on examples. The results show that our measure provides a run time with a gain of time compared to existing approaches. In addition, we compared the relevance of the similarity values obtained, it appears that this new graphs measure is advantageous and  offers a contribution to solving the problem mentioned above.

EKF-GPR-Based Fingerprint Renovation for Subset-Based Indoor Localization with Adjusted Cosine Similarity.

Science.gov (United States)

Yang, Junhua; Li, Yong; Cheng, Wei; Liu, Yang; Liu, Chenxi

2018-01-22

Received Signal Strength Indicator (RSSI) localization using fingerprint has become a prevailing approach for indoor localization. However, the fingerprint-collecting work is repetitive and time-consuming. After the original fingerprint radio map is built, it is laborious to upgrade the radio map. In this paper, we describe a Fingerprint Renovation System (FRS) based on crowdsourcing, which avoids the use of manual labour to obtain the up-to-date fingerprint status. Extended Kalman Filter (EKF) and Gaussian Process Regression (GPR) in FRS are combined to calculate the current state based on the original fingerprinting radio map. In this system, a method of subset acquisition also makes an immediate impression to reduce the huge computation caused by too many reference points (RPs). Meanwhile, adjusted cosine similarity (ACS) is employed in the online phase to solve the issue of outliers produced by cosine similarity. Both experiments and analytical simulation in a real Wireless Fidelity (Wi-Fi) environment indicate the usefulness of our system to significant performance improvements. The results show that FRS improves the accuracy by 19.6% in the surveyed area compared to the radio map un-renovated. Moreover, the proposed subset algorithm can bring less computation.

EKF–GPR-Based Fingerprint Renovation for Subset-Based Indoor Localization with Adjusted Cosine Similarity

Science.gov (United States)

Yang, Junhua; Li, Yong; Cheng, Wei; Liu, Yang; Liu, Chenxi

2018-01-01

Received Signal Strength Indicator (RSSI) localization using fingerprint has become a prevailing approach for indoor localization. However, the fingerprint-collecting work is repetitive and time-consuming. After the original fingerprint radio map is built, it is laborious to upgrade the radio map. In this paper, we describe a Fingerprint Renovation System (FRS) based on crowdsourcing, which avoids the use of manual labour to obtain the up-to-date fingerprint status. Extended Kalman Filter (EKF) and Gaussian Process Regression (GPR) in FRS are combined to calculate the current state based on the original fingerprinting radio map. In this system, a method of subset acquisition also makes an immediate impression to reduce the huge computation caused by too many reference points (RPs). Meanwhile, adjusted cosine similarity (ACS) is employed in the online phase to solve the issue of outliers produced by cosine similarity. Both experiments and analytical simulation in a real Wireless Fidelity (Wi-Fi) environment indicate the usefulness of our system to significant performance improvements. The results show that FRS improves the accuracy by 19.6% in the surveyed area compared to the radio map un-renovated. Moreover, the proposed subset algorithm can bring less computation. PMID:29361805

Driving pattern analysis of Nordic region based on the national travel surveys for electric vehicle integration

DEFF Research Database (Denmark)

Liu, Zhaoxi; Wu, Qiuwei; Christensen, Linda

2015-01-01

to the power system. This paper presents a methodology to transform driving behavior of persons into the one of cars in order to analyze the driving pattern of electric vehicles (EVs) based on the National Travel Surveys. In the proposed methodology, a statistical process is used to obtain the driving behavior......EVs show great potential to cope with the intermittency of renewable energy sources (RES) and provide demand side flexibility required by the smart grid.On the other hand, the EVs will increase the electricity consumption. Large scale integration of EVs will probably have substantial impacts...... of cars by grouping the survey respondents according to the driving license number and car number and mapping the households with similar characteristics. The proposed methodology was used to carry out the driving pattern analysis in the Nordic region. The detailed driving requirements and the charging...

Distance and Density Similarity Based Enhanced k-NN Classifier for Improving Fault Diagnosis Performance of Bearings

Directory of Open Access Journals (Sweden)

Sharif Uddin

2016-01-01

Full Text Available An enhanced k-nearest neighbor (k-NN classification algorithm is presented, which uses a density based similarity measure in addition to a distance based similarity measure to improve the diagnostic performance in bearing fault diagnosis. Due to its use of distance based similarity measure alone, the classification accuracy of traditional k-NN deteriorates in case of overlapping samples and outliers and is highly susceptible to the neighborhood size, k. This study addresses these limitations by proposing the use of both distance and density based measures of similarity between training and test samples. The proposed k-NN classifier is used to enhance the diagnostic performance of a bearing fault diagnosis scheme, which classifies different fault conditions based upon hybrid feature vectors extracted from acoustic emission (AE signals. Experimental results demonstrate that the proposed scheme, which uses the enhanced k-NN classifier, yields better diagnostic performance and is more robust to variations in the neighborhood size, k.

A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

Science.gov (United States)

Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

2016-02-01

Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

SEM based overlay measurement between resist and buried patterns

Science.gov (United States)

Inoue, Osamu; Okagawa, Yutaka; Hasumi, Kazuhisa; Shao, Chuanyu; Leray, Philippe; Lorusso, Gian; Baudemprez, Bart

2016-03-01

With the continuous shrink in pattern size and increased density, overlay control has become one of the most critical issues in semiconductor manufacturing. Recently, SEM based overlay of AEI (After Etch Inspection) wafer has been used for reference and optimization of optical overlay (both Image Based Overlay (IBO) and Diffraction Based Overlay (DBO)). Overlay measurement at AEI stage contributes monitor and forecast the yield after formation by etch and calibrate optical measurement tools. however those overlay value seems difficult directly for feedback to a scanner. Therefore, there is a clear need to have SEM based overlay measurements of ADI (After Develop Inspection) wafers in order to serve as reference for optical overlay and make necessary corrections before wafers go to etch. Furthermore, to make the corrections as accurate as possible, actual device like feature dimensions need to be measured post ADI. This device size measurement is very unique feature of CDSEM , which can be measured with smaller area. This is currently possible only with the CD-SEM. This device size measurement is very unique feature of CD-SEM , which can be measured with smaller area. In this study, we assess SEM based overlay measurement of ADI and AEI wafer by using a sample from an N10 process flow. First, we demonstrate SEM based overlay performance at AEI by using dual damascene process for Via 0 (V0) and metal 1 (M1) layer. We also discuss the overlay measurements between litho-etch-litho stages of a triple patterned M1 layer and double pattern V0. Second, to illustrate the complexities in image acquisition and measurement we will measure overlay between M1B resist and buried M1A-Hard mask trench. Finally, we will show how high accelerating voltage can detect buried pattern information by BSE (Back Scattering Electron). In this paper we discuss the merits of this method versus standard optical metrology based corrections.

Patterns of technological innovation and evolution in the energy sector: A patent-based approach

International Nuclear Information System (INIS)

Lee, Kyungpyo; Lee, Sungjoo

2013-01-01

Given the ever-increasing pace and complexity of technological innovation in the energy sector, monitoring technological changes has become of strategic importance. One of the most common techniques for technology monitoring is patent analysis, which enables the identification of technological trends over time. However, few previous studies have carried out patent analysis in the energy sector. This study aims to explore patterns of innovation and of evolution in energy technologies, particularly focusing on similarities and differences across technologies. For this purpose, we first defined the relevant energy technologies and extracted the associated patent data from the United States Patents and Trademark Office (USPTO) and then adopted six patent indices and developed six patent maps to analyze their innovation characteristics. We then clustered energy technologies with similar characteristics, so defining innovation categories, and analyzed the changes in these characteristics over time to define their evolution categories. As one of the few attempts to investigate the overall trends in the energy sector's innovation and evolution, this study is expected to help develop an in-depth understanding of the energy industry, which will be useful in establishing technology strategies and policy in this rapidly changing sector. - Highlights: • We examined the patterns of innovation and evolution of energy technologies. • Six types of innovation patterns such as “competitive” or “mature” were identified. • Six types of evolution patterns such as “towards closed innovation” were identified. • The patterns of evolution were related to the patterns of innovation

Similarity measurement method of high-dimensional data based on normalized net lattice subspace

Institute of Scientific and Technical Information of China (English)

Li Wenfa; Wang Gongming; Li Ke; Huang Su

2017-01-01

The performance of conventional similarity measurement methods is affected seriously by the curse of dimensionality of high-dimensional data.The reason is that data difference between sparse and noisy dimensionalities occupies a large proportion of the similarity, leading to the dissimilarities between any results.A similarity measurement method of high-dimensional data based on normalized net lattice subspace is proposed.The data range of each dimension is divided into several intervals, and the components in different dimensions are mapped onto the corresponding interval.Only the component in the same or adjacent interval is used to calculate the similarity.To validate this meth-od, three data types are used, and seven common similarity measurement methods are compared. The experimental result indicates that the relative difference of the method is increasing with the di-mensionality and is approximately two or three orders of magnitude higher than the conventional method.In addition, the similarity range of this method in different dimensions is [0, 1], which is fit for similarity analysis after dimensionality reduction.

The contribution of a central pattern generator in a reflex-based neuromuscular model

Science.gov (United States)

Dzeladini, Florin; van den Kieboom, Jesse; Ijspeert, Auke

2014-01-01

Although the concept of central pattern generators (CPGs) controlling locomotion in vertebrates is widely accepted, the presence of specialized CPGs in human locomotion is still a matter of debate. An interesting numerical model developed in the 90s’ demonstrated the important role CPGs could play in human locomotion, both in terms of stability against perturbations, and in terms of speed control. Recently, a reflex-based neuro-musculo-skeletal model has been proposed, showing a level of stability to perturbations similar to the previous model, without any CPG components. Although exhibiting striking similarities with human gaits, the lack of CPG makes the control of speed/step length in the model difficult. In this paper, we hypothesize that a CPG component will offer a meaningful way of controlling the locomotion speed. After introducing the CPG component in the reflex model, and taking advantage of the resulting properties, a simple model for gait modulation is presented. The results highlight the advantages of a CPG as feedforward component in terms of gait modulation. PMID:25018712

The Contribution of a Central Pattern Generator in a Reflex-Based Neuromuscular Model

Directory of Open Access Journals (Sweden)

Florin eDzeladini

2014-06-01

Full Text Available Although the concept of central pattern generators (CPGs controlling locomotion in vertebrates is widely accepted, the presence of specialized CPGs in human locomotion is still a matter of debate. An interesting numerical model developed in the 90s' demonstrated the important role CPGs could play in human locomotion, both in terms of stability against perturbations, and in terms of speed control. Recently, a reflex-based neuro-musculo-skeletal model has been proposed, showing a level of stability to perturbations similar to the previous model, without any CPG components. Although exhibiting striking similarities with human gaits, the lack of CPG makes the control of speed/step length in the model difficult. In this paper, we hypothesize that a CPG component will offer a meaningful way of controlling the locomotion speed. After introducing the CPG component in the reflex model, and taking advantage of the resulting properties, a simple model for gait modulation is presented.The results highlight the advantages that a feedforward component can have in terms of gait modulation.

Midbrain and forebrain patterning delivers immunocytochemically and functionally similar populations of neuropeptide Y containing GABAergic neurons.

Science.gov (United States)

Khaira, S K; Nefzger, C M; Beh, S J; Pouton, C W; Haynes, J M

2011-09-01

Neurons differentiated in vitro from embryonic stem cells (ESCs) have the potential to serve both as models of disease states and in drug discovery programs. In this study, we use sonic hedgehog (SHH) and fibroblast growth factor 8 (FGF-8) to enrich for forebrain and midbrain phenotypes from mouse ESCs. We then investigate, using Ca(2+) imaging and [(3)H]-GABA release studies, whether the GABAergic neurons produced exhibit distinct functional phenotypes. At day 24 of differentiation, reverse transcriptase-PCR showed the presence of both forebrain (Bf-1, Hesx1, Pgc-1α, Six3) and midbrain (GATA2, GATA3) selective mRNA markers in developing forebrain-enriched cultures. All markers were present in midbrain cultures except for Bf-1 and Pgc-1α. Irrespective of culture conditions all GABA immunoreactive neurons were also immunoreactive to neuropeptide Y (NPY) antibodies. Forebrain and midbrain GABAergic neurons responded to ATP (1 mM), L-glutamate (30 μM), noradrenaline (30 μM), acetylcholine (30 μM) and dopamine (30 μM), with similar elevations of intracellular Ca(2+)([Ca(2+)](i)). The presence of GABA(A) and GABA(B) antagonists, bicuculline (30 μM) and CGP55845 (1 μM), increased the elevation of [Ca(2+)](i) in response to dopamine (30 μM) in midbrain, but not forebrain GABAergic neurons. All agonists, except dopamine, elicited similar [(3)H]-GABA release from forebrain and midbrain cultures. Dopamine (30 μM) did not stimulate significant [(3)H]-GABA release in midbrain cultures, although it was effective in forebrain cultures. This study shows that differentiating neurons toward a midbrain fate restricts the expression of forebrain markers. Forebrain differentiation results in the expression of forebrain and midbrain markers. All GABA(+) neurons contain NPY, and show similar agonist-induced elevations of [Ca(2+)](i) and [(3)H]-GABA release. This study indicates that the pharmacological phenotype of these particular neurons may be independent of the addition of

A general framework for regularized, similarity-based image restoration.

Science.gov (United States)

Kheradmand, Amin; Milanfar, Peyman

2014-12-01

Any image can be represented as a function defined on a weighted graph, in which the underlying structure of the image is encoded in kernel similarity and associated Laplacian matrices. In this paper, we develop an iterative graph-based framework for image restoration based on a new definition of the normalized graph Laplacian. We propose a cost function, which consists of a new data fidelity term and regularization term derived from the specific definition of the normalized graph Laplacian. The normalizing coefficients used in the definition of the Laplacian and associated regularization term are obtained using fast symmetry preserving matrix balancing. This results in some desired spectral properties for the normalized Laplacian such as being symmetric, positive semidefinite, and returning zero vector when applied to a constant image. Our algorithm comprises of outer and inner iterations, where in each outer iteration, the similarity weights are recomputed using the previous estimate and the updated objective function is minimized using inner conjugate gradient iterations. This procedure improves the performance of the algorithm for image deblurring, where we do not have access to a good initial estimate of the underlying image. In addition, the specific form of the cost function allows us to render the spectral analysis for the solutions of the corresponding linear equations. In addition, the proposed approach is general in the sense that we have shown its effectiveness for different restoration problems, including deblurring, denoising, and sharpening. Experimental results verify the effectiveness of the proposed algorithm on both synthetic and real examples.

Uncovering highly obfuscated plagiarism cases using fuzzy semantic-based similarity model

Directory of Open Access Journals (Sweden)

Salha M. Alzahrani

2015-07-01

Full Text Available Highly obfuscated plagiarism cases contain unseen and obfuscated texts, which pose difficulties when using existing plagiarism detection methods. A fuzzy semantic-based similarity model for uncovering obfuscated plagiarism is presented and compared with five state-of-the-art baselines. Semantic relatedness between words is studied based on the part-of-speech (POS tags and WordNet-based similarity measures. Fuzzy-based rules are introduced to assess the semantic distance between source and suspicious texts of short lengths, which implement the semantic relatedness between words as a membership function to a fuzzy set. In order to minimize the number of false positives and false negatives, a learning method that combines a permission threshold and a variation threshold is used to decide true plagiarism cases. The proposed model and the baselines are evaluated on 99,033 ground-truth annotated cases extracted from different datasets, including 11,621 (11.7% handmade paraphrases, 54,815 (55.4% artificial plagiarism cases, and 32,578 (32.9% plagiarism-free cases. We conduct extensive experimental verifications, including the study of the effects of different segmentations schemes and parameter settings. Results are assessed using precision, recall, F-measure and granularity on stratified 10-fold cross-validation data. The statistical analysis using paired t-tests shows that the proposed approach is statistically significant in comparison with the baselines, which demonstrates the competence of fuzzy semantic-based model to detect plagiarism cases beyond the literal plagiarism. Additionally, the analysis of variance (ANOVA statistical test shows the effectiveness of different segmentation schemes used with the proposed approach.

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)

PROSPECT improves cis-acting regulatory element prediction by integrating expression profile data with consensus pattern searches

Science.gov (United States)

Fujibuchi, Wataru; Anderson, John S. J.; Landsman, David

2001-01-01

Consensus pattern and matrix-based searches designed to predict cis-acting transcriptional regulatory sequences have historically been subject to large numbers of false positives. We sought to decrease false positives by incorporating expression profile data into a consensus pattern-based search method. We have systematically analyzed the expression phenotypes of over 6000 yeast genes, across 121 expression profile experiments, and correlated them with the distribution of 14 known regulatory elements over sequences upstream of the genes. Our method is based on a metric we term probabilistic element assessment (PEA), which is a ranking of potential sites based on sequence similarity in the upstream regions of genes with similar expression phenotypes. For eight of the 14 known elements that we examined, our method had a much higher selectivity than a naïve consensus pattern search. Based on our analysis, we have developed a web-based tool called PROSPECT, which allows consensus pattern-based searching of gene clusters obtained from microarray data. PMID:11574681

A comparison of heuristic and model-based clustering methods for dietary pattern analysis.

Science.gov (United States)

Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia

2016-02-01

Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.

Study on Base Management Pattern of Food Producing Enterprise

Science.gov (United States)

Zhang, Weibin

When the food producing enterprises often comply with food safety regulations and industry management system passively, we need to consider can they transform their production and business pattern in order to avoid the food safety incidents completely? The answer is yes. The food producing enterprises can develop to the two directions of material planting and products in circulation through base management pattern substituting for the original operation pattern of in-plant processing and outside sales. The food producing enterprises should establish coordination and safe supervision mechanisms in order to achieve the management objectives of unified production, controllable risks and scale magnitude.

Module-based complexity formation: periodic patterning in feathers and hairs.

Science.gov (United States)

Chuong, Cheng-Ming; Yeh, Chao-Yuan; Jiang, Ting-Xin; Widelitz, Randall

2013-01-01

Patterns describe order which emerges from homogeneity. Complex patterns on the integument are striking because of their visibility throughout an organism’s lifespan. Periodic patterning is an effective design because the ensemble of hair or feather follicles (modules) allows the generation of complexity, including regional variations and cyclic regeneration, giving the skin appendages a new lease on life. Spatial patterns include the arrangements of feathers and hairs in specific number, size, and spacing.We explorehowa field of equivalent progenitor cells can generate periodically arranged modules based on genetic information, physical–chemical rules and developmental timing. Reconstitution experiments suggest a competitive equilibrium regulated by activators/inhibitors involving Turing reaction-diffusion. Temporal patterns result from oscillating stem cell activities within each module (microenvironment regulation), reflected as growth (anagen) and resting (telogen) phases during the cycling of feather and hair follicles. Stimulating modules with activators initiates the spread of regenerative hair waves, while global inhibitors outside each module (macroenvironment) prevent this. Different wave patterns can be simulated by cellular automata principles. Hormonal status and seasonal changes can modulate appendage phenotypes, leading to ‘organ metamorphosis’, with multiple ectodermal organ phenotypes generated from the same precursors. We discuss potential novel evolutionary steps using this module-based complexity in several amniote integument organs, exemplified by the spectacular peacock feather pattern. We thus explore the application of the acquired knowledge of patterning in tissue engineering. New hair follicles can be generated after wounding. Hairs and feathers can be reconstituted through self-organization of dissociated progenitor cells. © 2012 Wiley Periodicals, Inc.

Content Based Retrieval Database Management System with Support for Similarity Searching and Query Refinement

National Research Council Canada - National Science Library

Ortega-Binderberger, Michael

2002-01-01

... as a critical area of research. This thesis explores how to enhance database systems with content based search over arbitrary abstract data types in a similarity based framework with query refinement...

Detecting groups of similar components in complex networks

International Nuclear Information System (INIS)

Wang Jiao; Lai, C-H

2008-01-01

We study how to detect groups in a complex network each of which consists of component nodes sharing a similar connection pattern. Based on the mixture models and the exploratory analysis set up by Newman and Leicht (2007 Proc. Natl. Acad. Sci. USA 104 9564), we develop an algorithm that is applicable to a network with any degree distribution. The partition of a network suggested by this algorithm also applies to its complementary network. In general, groups of similar components are not necessarily identical with the communities in a community network; thus partitioning a network into groups of similar components provides additional information of the network structure. The proposed algorithm can also be used for community detection when the groups and the communities overlap. By introducing a tunable parameter that controls the involved effects of the heterogeneity, we can also investigate conveniently how the group structure can be coupled with the heterogeneity characteristics. In particular, an interesting example shows a group partition can evolve into a community partition in some situations when the involved heterogeneity effects are tuned. The extension of this algorithm to weighted networks is discussed as well.

A Pattern Construction Scheme for Neural Network-Based Cognitive Communication

Directory of Open Access Journals (Sweden)

Ozgur Orcay

2011-01-01

Full Text Available Inefficient utilization of the frequency spectrum due to conventional regulatory limitations and physical performance limiting factors, mainly the Signal to Noise Ratio (SNR, are prominent restrictions in digital wireless communication. Pattern Based Communication System (PBCS is an adaptive and perceptual communication method based on a Cognitive Radio (CR approach. It intends an SNR oriented cognition mechanism in the physical layer for improvement of Link Spectral Efficiency (LSE. The key to this system is construction of optimal communication signals, which consist of encoded data in different pattern forms (waveforms depending on spectral availabilities. The signals distorted in the communication medium are recovered according to the pre-trained pattern glossary by the perceptual receiver. In this study, we have shown that it is possible to improve the bandwidth efficiency when largely uncorrelated signal patterns are chosen in order to form a glossary that represents symbols for different length data groups and the information can be recovered by the Artificial Neural Network (ANN in the receiver site.

Detecting Distortion: Bridging Visual and Quantitative Reasoning on Similarity Tasks

Science.gov (United States)

Cox, Dana C.; Lo, Jane-Jane

2014-01-01

This study is focused on identifying and describing the reasoning patterns of middle grade students when examining potentially similar figures. Described here is a framework that includes 11 strategies that students used during clinical interview to differentiate similar and non-similar figures. Two factors were found to influence the strategies…

Pattern Discovery in Time-Ordered Data; TOPICAL

International Nuclear Information System (INIS)

CONRAD, GREGORY N.; BRITANIK, JOHN M.; DELAND, SHARON M.; JENKIN, CHRISTINA L.

2002-01-01

This report describes the results of a Laboratory-Directed Research and Development project on techniques for pattern discovery in discrete event time series data. In this project, we explored two different aspects of the pattern matching/discovery problem. The first aspect studied was the use of Dynamic Time Warping for pattern matching in continuous data. In essence, DTW is a technique for aligning time series along the time axis to optimize the similarity measure. The second aspect studied was techniques for discovering patterns in discrete event data. We developed a pattern discovery tool based on adaptations of the A-priori and GSP (Generalized Sequential Pattern mining) algorithms. We then used the tool on three different application areas-unattended monitoring system data from a storage magazine, computer network intrusion detection, and analysis of robot training data

Quality assessment of protein model-structures based on structural and functional similarities.

Science.gov (United States)

Konopka, Bogumil M; Nebel, Jean-Christophe; Kotulska, Malgorzata

2012-09-21

Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. GOBA--Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and

Morphological similarities between DBM and a microeconomic model of sprawl

Science.gov (United States)

Caruso, Geoffrey; Vuidel, Gilles; Cavailhès, Jean; Frankhauser, Pierre; Peeters, Dominique; Thomas, Isabelle

2011-03-01

We present a model that simulates the growth of a metropolitan area on a 2D lattice. The model is dynamic and based on microeconomics. Households show preferences for nearby open spaces and neighbourhood density. They compete on the land market. They travel along a road network to access the CBD. A planner ensures the connectedness and maintenance of the road network. The spatial pattern of houses, green spaces and road network self-organises, emerging from agents individualistic decisions. We perform several simulations and vary residential preferences. Our results show morphologies and transition phases that are similar to Dieletric Breakdown Models (DBM). Such similarities were observed earlier by other authors, but we show here that it can be deducted from the functioning of the land market and thus explicitly connected to urban economic theory.

Power Terminal Communication Access Network Monitoring System Scheme Based on Design Patterns

Science.gov (United States)

Yan, Shengchao; Wu, Desheng; Zhu, Jiang

2018-01-01

In order to realize patterns design for terminal communication monitoring system, this paper introduces manager-workers, tasks-workers design patterns, based on common design patterns such as factory method, chain of responsibility, facade. Using these patterns, the communication monitoring system which combines module-groups like networking communication, business data processing and the peripheral support has been designed successfully. Using these patterns makes this system have great flexibility and scalability and improves the degree of systematic pattern design structure.

Running Improves Pattern Separation during Novel Object Recognition.

Science.gov (United States)

Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef

2015-10-09

Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.

Supervised and Unsupervised Classification for Pattern Recognition Purposes

Directory of Open Access Journals (Sweden)

Catalina COCIANU

2006-01-01

Full Text Available A cluster analysis task has to identify the grouping trends of data, to decide on the sound clusters as well as to validate somehow the resulted structure. The identification of the grouping tendency existing in a data collection assumes the selection of a framework stated in terms of a mathematical model allowing to express the similarity degree between couples of particular objects, quasi-metrics expressing the similarity between an object an a cluster and between clusters, respectively. In supervised classification, we are provided with a collection of preclassified patterns, and the problem is to label a newly encountered pattern. Typically, the given training patterns are used to learn the descriptions of classes which in turn are used to label a new pattern. The final section of the paper presents a new methodology for supervised learning based on PCA. The classes are represented in the measurement/feature space by a continuous repartitions

Testing surrogacy assumptions: can threatened and endangered plants be grouped by biological similarity and abundances?

Directory of Open Access Journals (Sweden)

Judy P Che-Castaldo

Full Text Available There is renewed interest in implementing surrogate species approaches in conservation planning due to the large number of species in need of management but limited resources and data. One type of surrogate approach involves selection of one or a few species to represent a larger group of species requiring similar management actions, so that protection and persistence of the selected species would result in conservation of the group of species. However, among the criticisms of surrogate approaches is the need to test underlying assumptions, which remain rarely examined. In this study, we tested one of the fundamental assumptions underlying use of surrogate species in recovery planning: that there exist groups of threatened and endangered species that are sufficiently similar to warrant similar management or recovery criteria. Using a comprehensive database of all plant species listed under the U.S. Endangered Species Act and tree-based random forest analysis, we found no evidence of species groups based on a set of distributional and biological traits or by abundances and patterns of decline. Our results suggested that application of surrogate approaches for endangered species recovery would be unjustified. Thus, conservation planning focused on individual species and their patterns of decline will likely be required to recover listed species.

The effect of four user interface concepts on visual scan pattern similarity and information foraging in a complex decision making task.

Science.gov (United States)

Starke, Sandra D; Baber, Chris

2018-07-01

User interface (UI) design can affect the quality of decision making, where decisions based on digitally presented content are commonly informed by visually sampling information through eye movements. Analysis of the resulting scan patterns - the order in which people visually attend to different regions of interest (ROIs) - gives an insight into information foraging strategies. In this study, we quantified scan pattern characteristics for participants engaging with conceptually different user interface designs. Four interfaces were modified along two dimensions relating to effort in accessing information: data presentation (either alpha-numerical data or colour blocks), and information access time (all information sources readily available or sequential revealing of information required). The aim of the study was to investigate whether a) people develop repeatable scan patterns and b) different UI concepts affect information foraging and task performance. Thirty-two participants (eight for each UI concept) were given the task to correctly classify 100 credit card transactions as normal or fraudulent based on nine transaction attributes. Attributes varied in their usefulness of predicting the correct outcome. Conventional and more recent (network analysis- and bioinformatics-based) eye tracking metrics were used to quantify visual search. Empirical findings were evaluated in context of random data and possible accuracy for theoretical decision making strategies. Results showed short repeating sequence fragments within longer scan patterns across participants and conditions, comprising a systematic and a random search component. The UI design concept showing alpha-numerical data in full view resulted in most complete data foraging, while the design concept showing colour blocks in full view resulted in the fastest task completion time. Decision accuracy was not significantly affected by UI design. Theoretical calculations showed that the difference in achievable

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.

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...

A Survey of Binary Similarity and Distance Measures

Directory of Open Access Journals (Sweden)

Seung-Seok Choi

2010-02-01

Full Text Available The binary feature vector is one of the most common representations of patterns and measuring similarity and distance measures play a critical role in many problems such as clustering, classification, etc. Ever since Jaccard proposed a similarity measure to classify ecological species in 1901, numerous binary similarity and distance measures have been proposed in various fields. Applying appropriate measures results in more accurate data analysis. Notwithstanding, few comprehensive surveys on binary measures have been conducted. Hence we collected 76 binary similarity and distance measures used over the last century and reveal their correlations through the hierarchical clustering technique.

Applying ligands profiling using multiple extended electron distribution based field templates and feature trees similarity searching in the discovery of new generation of urea-based antineoplastic kinase inhibitors.

Directory of Open Access Journals (Sweden)

Eman M Dokla

Full Text Available This study provides a comprehensive computational procedure for the discovery of novel urea-based antineoplastic kinase inhibitors while focusing on diversification of both chemotype and selectivity pattern. It presents a systematic structural analysis of the different binding motifs of urea-based kinase inhibitors and the corresponding configurations of the kinase enzymes. The computational model depends on simultaneous application of two protocols. The first protocol applies multiple consecutive validated virtual screening filters including SMARTS, support vector-machine model (ROC = 0.98, Bayesian model (ROC = 0.86 and structure-based pharmacophore filters based on urea-based kinase inhibitors complexes retrieved from literature. This is followed by hits profiling against different extended electron distribution (XED based field templates representing different kinase targets. The second protocol enables cancericidal activity verification by using the algorithm of feature trees (Ftrees similarity searching against NCI database. Being a proof-of-concept study, this combined procedure was experimentally validated by its utilization in developing a novel series of urea-based derivatives of strong anticancer activity. This new series is based on 3-benzylbenzo[d]thiazol-2(3H-one scaffold which has interesting chemical feasibility and wide diversification capability. Antineoplastic activity of this series was assayed in vitro against NCI 60 tumor-cell lines showing very strong inhibition of GI(50 as low as 0.9 uM. Additionally, its mechanism was unleashed using KINEX™ protein kinase microarray-based small molecule inhibitor profiling platform and cell cycle analysis showing a peculiar selectivity pattern against Zap70, c-src, Mink1, csk and MeKK2 kinases. Interestingly, it showed activity on syk kinase confirming the recent studies finding of the high activity of diphenyl urea containing compounds against this kinase. Allover, the new series

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.

2-gram-based Phonetic Feature Generation for Convolutional Neural Network in Assessment of Trademark Similarity

OpenAIRE

Ko, Kyung Pyo; Lee, Kwang Hee; Jang, Mi So; Park, Gun Hong

2018-01-01

A trademark is a mark used to identify various commodities. If same or similar trademark is registered for the same or similar commodity, the purchaser of the goods may be confused. Therefore, in the process of trademark registration examination, the examiner judges whether the trademark is the same or similar to the other applied or registered trademarks. The confusion in trademarks is based on the visual, phonetic or conceptual similarity of the marks. In this paper, we focus specifically o...

Base Station Antenna Pattern Distortion in Practical Urban Deployment Scenarios

DEFF Research Database (Denmark)

Rodriguez Larrad, Ignacio; Nguyen, Huan Cong; Sørensen, Troels Bundgaard

2014-01-01

In real urban deployments, base station antennas are typically not placed in free space conditions. Therefore, the radiation pattern can be affected by mounting structures and nearby obstacles located in the proximity of the antenna (near-field), which are often not taken into consideration. Also...... presents a combination of near-field and far-field simulations aimed to provide an overview of the distortion experienced by the base station antenna pattern in two different urban deployment scenarios: rooftop and telecommunications tower. The study illustrates how, in comparison with the near...

Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

Science.gov (United States)

Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

2016-08-01

The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

IntelliGO: a new vector-based semantic similarity measure including annotation origin

Directory of Open Access Journals (Sweden)

Devignes Marie-Dominique

2010-12-01

previously published measures. Conclusions The IntelliGO similarity measure provides a customizable and comprehensive method for quantifying gene similarity based on GO annotations. It also displays a robust set-discriminating power which suggests it will be useful for functional clustering. Availability An on-line version of the IntelliGO similarity measure is available at: http://bioinfo.loria.fr/Members/benabdsi/intelligo_project/

RNAPattMatch: a web server for RNA sequence/structure motif detection based on pattern matching with flexible gaps

Science.gov (United States)

Drory Retwitzer, Matan; Polishchuk, Maya; Churkin, Elena; Kifer, Ilona; Yakhini, Zohar; Barash, Danny

2015-01-01

Searching for RNA sequence-structure patterns is becoming an essential tool for RNA practitioners. Novel discoveries of regulatory non-coding RNAs in targeted organisms and the motivation to find them across a wide range of organisms have prompted the use of computational RNA pattern matching as an enhancement to sequence similarity. State-of-the-art programs differ by the flexibility of patterns allowed as queries and by their simplicity of use. In particular—no existing method is available as a user-friendly web server. A general program that searches for RNA sequence-structure patterns is RNA Structator. However, it is not available as a web server and does not provide the option to allow flexible gap pattern representation with an upper bound of the gap length being specified at any position in the sequence. Here, we introduce RNAPattMatch, a web-based application that is user friendly and makes sequence/structure RNA queries accessible to practitioners of various background and proficiency. It also extends RNA Structator and allows a more flexible variable gaps representation, in addition to analysis of results using energy minimization methods. RNAPattMatch service is available at http://www.cs.bgu.ac.il/rnapattmatch. A standalone version of the search tool is also available to download at the site. PMID:25940619

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.

Enhancing SAT-Based Test Pattern Generation

Institute of Scientific and Technical Information of China (English)

LIU Xin; XIONG You-lun

2005-01-01

This paper presents modeling tools based on Boolean satisfiability (SAT) to solve problems of test generation for combinational circuits. It exploits an added layer to maintain circuit-related information and value justification relations to a generic SAT algorithm. It dovetails binary decision graphs (BDD) and SAT techniques to improve the efficiency of automatic test pattern generation (ATPG). More specifically, it first exploits inexpensive reconvergent fanout analysis of circuit to gather information on the local signal correlation by using BDD learning, then uses the above learned information to restrict and focus the overall search space of SAT-based ATPG. Its learning technique is effective and lightweight. The experimental results demonstrate the effectiveness of the approach.

Music Retrieval based on Melodic Similarity

NARCIS (Netherlands)

Typke, R.

2007-01-01

This thesis introduces a method for measuring melodic similarity for notated music such as MIDI files. This music search algorithm views music as sets of notes that are represented as weighted points in the two-dimensional space of time and pitch. Two point sets can be compared by calculating how

Dietary Patterns Associated with Alzheimer’s Disease: Population Based Study

Directory of Open Access Journals (Sweden)

Katarzyna Gustaw-Rothenberg

2009-04-01

Full Text Available Recently dietary pattern analysis has emerged as a way for examining diet-disease relations in Alzheimer’s disease. In contrast with the conventional approach, which focuses on a single nutrient or a few nutrients or foods, this method considers overall eating patterns. We examined the dietary patterns defined by factor analysis using data collected with a food-frequency questionnaire in people with Alzheimer’s disease (AD as compared to healthy controls. The diet data were obtained during population based study of the prevalence of Alzheimer’s disease in a population in Poland. Stratified sampling and random selection strategies were combined to obtain a representative population for screening (age group > 55. From the population screened three times, 71 people were diagnosed with Alzheimer’s according to DSM-IV, and were recruited for further diet risk factors assessment. A group of people with Alzheimer disease (n = 71; F/M 42/29 and the same number of healthy, age and gender matched control were recruited for the study. Patients and their caregivers as well as controls were presented with a food frequency questionnaire based on the 12 food groups. Factor analysis (principal component was used to derive food patterns. The analysis was conducted using the factor procedure. The factors were rotated by an orthogonal transformation (Varimax rotation to achieve simpler structure with greater interpretability. Using factor analysis, we identified major eating patterns, one for Alzheimer’s patients and a different one for control group. The AD dietary pattern, FACTOR AD was characterized by a high intake of meat, butter, high-fat dairy products, eggs, and refined sugar, whereas the other pattern, (FACTOR C was characterized by a high intake of grains and vegetables. These data indicate the existence of dietary patterns defined by factor analysis with data from a food frequency questionnaire, characteristic for Alzheimer’s disease in a

Corpus-Based Rhythmic Pattern Analysis of Ragtime Syncopation

NARCIS (Netherlands)

Koops, Hendrik Vincent; Volk, A.; de Haas, W.B.

2015-01-01

This paper presents a corpus-based study on rhythmic patterns in the RAG-collection of approximately 11.000 symbolically encoded ragtime pieces. While characteristic musical features that define ragtime as a genre have been debated since its inception, musicologists argue that specific syncopation

Contrasting HIV phylogenetic relationships and V3 loop protein similarities

Energy Technology Data Exchange (ETDEWEB)

Korber, B. (Los Alamos National Lab., NM (United States) Santa Fe Inst., NM (United States)); Myers, G. (Los Alamos National Lab., NM (United States))

1992-01-01

At least five distinct sequence subtypes of HIV-I can be identified from the major centers of the AMS pandemic. While it is too early to tell whether these subtypes are serologically or phenotypically similar or distinct in terms of properties such as pathogenicity and transmissibility, we can begin to investigate their potential for phenotypic divergence at the protein sequence level. Phylogenetic analysis of HIV DNA sequences is being widely used to examine lineages of different viral strains as they evolve and spread throughout the globe. We have identified five distinct HIV-1 subtypes (designated A-E), or clades, based on phylogenetic clustering patterns generated from genetic information from both the gag and envelope (env) genes from a spectrum of international isolates. Our initial observations concerning both HIV-1 and HIV-2 sequences indicate that conserved patterns in protein chemistry may indeed exist across distant lineages. Such patterns in V3 loop amino acid chemistry may be indicative of stable lineages or convergence within this highly variable, though functionally and immunologically critical, region. We think that there may be parallels between the apparently stable HIV-2 V3 lineage and the previously mentioned HIV-1 V3 loops which are very similar at the protein level despite being distant by cladistic analysis, and which do not possess the distinctive positively charged residues. Highly conserved V3 loop protein sequences are also encountered in SIVAGMs and CIVs (chimpanzee viral strains), which do not appear to be pathogenic in their wild-caught natural hosts.

Contrasting HIV phylogenetic relationships and V3 loop protein similarities

Energy Technology Data Exchange (ETDEWEB)

Korber, B. [Los Alamos National Lab., NM (United States)]|[Santa Fe Inst., NM (United States); Myers, G. [Los Alamos National Lab., NM (United States)

1992-12-31

At least five distinct sequence subtypes of HIV-I can be identified from the major centers of the AMS pandemic. While it is too early to tell whether these subtypes are serologically or phenotypically similar or distinct in terms of properties such as pathogenicity and transmissibility, we can begin to investigate their potential for phenotypic divergence at the protein sequence level. Phylogenetic analysis of HIV DNA sequences is being widely used to examine lineages of different viral strains as they evolve and spread throughout the globe. We have identified five distinct HIV-1 subtypes (designated A-E), or clades, based on phylogenetic clustering patterns generated from genetic information from both the gag and envelope (env) genes from a spectrum of international isolates. Our initial observations concerning both HIV-1 and HIV-2 sequences indicate that conserved patterns in protein chemistry may indeed exist across distant lineages. Such patterns in V3 loop amino acid chemistry may be indicative of stable lineages or convergence within this highly variable, though functionally and immunologically critical, region. We think that there may be parallels between the apparently stable HIV-2 V3 lineage and the previously mentioned HIV-1 V3 loops which are very similar at the protein level despite being distant by cladistic analysis, and which do not possess the distinctive positively charged residues. Highly conserved V3 loop protein sequences are also encountered in SIVAGMs and CIVs (chimpanzee viral strains), which do not appear to be pathogenic in their wild-caught natural hosts.

Density-based retrieval from high-similarity image databases

DEFF Research Database (Denmark)

Hansen, Michael Edberg; Carstensen, Jens Michael

2004-01-01

Many image classification problems can fruitfully be thought of as image retrieval in a "high similarity image database" (HSID) characterized by being tuned towards a specific application and having a high degree of visual similarity between entries that should be distinguished. We introduce a me...

Personality traits across countries: Support for similarities rather than differences.

Science.gov (United States)

Kajonius, Petri; Mac Giolla, Erik

2017-01-01

In the current climate of migration and globalization, personality characteristics of individuals from different countries have received a growing interest. Previous research has established reliable differences in personality traits across countries. The present study extends this research by examining 30 personality traits in 22 countries, based on an online survey in English with large national samples (NTotal = 130,602). The instrument used was a comprehensive, open-source measure of the Five Factor Model (FFM) (IPIP-NEO-120). We postulated that differences in personality traits between countries would be small, labeling this a Similarities Hypothesis. We found support for this in three stages. First, similarities across countries were observed for model fits for each of the five personality trait structures. Second, within-country sex differences for the five personality traits showed similar patterns across countries. Finally, the overall the contribution to personality traits from countries was less than 2%. In other words, the relationship between a country and an individual's personality traits, however interesting, are small. We conclude that the most parsimonious explanation for the current and past findings is a cross-country personality Similarities Hypothesis.

Numerical study of similarity in prototype and model pumped turbines

International Nuclear Information System (INIS)

Li, Z J; Wang, Z W; Bi, H L

2014-01-01

Similarity study of prototype and model pumped turbines are performed by numerical simulation and the partial discharge case is analysed in detail. It is found out that in the RSI (rotor-stator interaction) region where the flow is convectively accelerated with minor flow separation, a high level of similarity in flow patterns and pressure fluctuation appear with relative pressure fluctuation amplitude of model turbine slightly higher than that of prototype turbine. As for the condition in the runner where the flow is convectively accelerated with severe separation, similarity fades substantially due to different topology of flow separation and vortex formation brought by distinctive Reynolds numbers of the two turbines. In the draft tube where the flow is diffusively decelerated, similarity becomes debilitated owing to different vortex rope formation impacted by Reynolds number. It is noted that the pressure fluctuation amplitude and characteristic frequency of model turbine are larger than those of prototype turbine. The differences in pressure fluctuation characteristics are discussed theoretically through dimensionless Navier-Stokes equation. The above conclusions are all made based on simulation without regard to the penstock response and resonance

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%.

Beyond common features: The role of roles in determining similarity1

Science.gov (United States)

Jones, Matt; Love, Bradley C.

2007-01-01

Historically, accounts of object representation and perceived similarity have focused on intrinsic features. Although more recent accounts have explored how objects, scenes, and situations containing common relational structures come to be perceived as similar, less is known about how the perceived similarity of parts or objects embedded within these relational systems is affected. The current studies test the hypothesis that objects situated in common relational systems come to be perceived as more similar. Similarity increases most for objects playing the same role within a relation (e.g., predator), but also increases for objects playing different roles within the same relation (e.g., the predator or prey role in the hunts relation) regardless of whether the objects participate in the same instance of the relation. This pattern of results can be captured by extending existing models that extract meaning from text corpora so that they are sensitive to the verb-specific thematic roles that objects fill. Alternative explanations based on analogical and inferential processes are also considered, as well as the implications of the current findings to research in language processing, personality and person perception, decision making, and category learning. PMID:17094958

Improved pattern recognition systems by hybrid methods

International Nuclear Information System (INIS)

Duerr, B.; Haettich, W.; Tropf, H.; Winkler, G.; Fraunhofer-Gesellschaft zur Foerderung der Angewandten Forschung e.V., Karlsruhe

1978-12-01

This report describes a combination of statistical and syntactical pattern recongition methods. The hierarchically structured recognition system consists of a conventional statistical classifier, a structural classifier analysing the topological composition of the patterns, a stage reducing the number of hypotheses made by the first two stages, and a mixed stage based on a search for maximum similarity between syntactically generated prototypes and patterns. The stages work on different principles to avoid mistakes made in one stage in the other stages. This concept is applied to the recognition of numerals written without constraints. If no samples are rejected, a recognition rate of 99,5% is obtained. (orig.) [de

A Two-Stage Composition Method for Danger-Aware Services Based on Context Similarity

Science.gov (United States)

Wang, Junbo; Cheng, Zixue; Jing, Lei; Ota, Kaoru; Kansen, Mizuo

Context-aware systems detect user's physical and social contexts based on sensor networks, and provide services that adapt to the user accordingly. Representing, detecting, and managing the contexts are important issues in context-aware systems. Composition of contexts is a useful method for these works, since it can detect a context by automatically composing small pieces of information to discover service. Danger-aware services are a kind of context-aware services which need description of relations between a user and his/her surrounding objects and between users. However when applying the existing composition methods to danger-aware services, they show the following shortcomings that (1) they have not provided an explicit method for representing composition of multi-user' contexts, (2) there is no flexible reasoning mechanism based on similarity of contexts, so that they can just provide services exactly following the predefined context reasoning rules. Therefore, in this paper, we propose a two-stage composition method based on context similarity to solve the above problems. The first stage is composition of the useful information to represent the context for a single user. The second stage is composition of multi-users' contexts to provide services by considering the relation of users. Finally the danger degree of the detected context is computed by using context similarity between the detected context and the predefined context. Context is dynamically represented based on two-stage composition rules and a Situation theory based Ontology, which combines the advantages of Ontology and Situation theory. We implement the system in an indoor ubiquitous environment, and evaluate the system through two experiments with the support of subjects. The experiment results show the method is effective, and the accuracy of danger detection is acceptable to a danger-aware system.

Object recognition based on Google's reverse image search and image similarity

Science.gov (United States)

Horváth, András.

2015-12-01

Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

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.

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.

The Energy Saving Potential of Occupancy-Based Lighting Control Strategies in Open-Plan Offices: The Influence of Occupancy Patterns

Directory of Open Access Journals (Sweden)

Christel de Bakker

2017-12-01

Full Text Available Occupancy-based lighting control strategies have been proven to be effective in diminishing offices’ energy consumption. These strategies have typically worked by controlling lighting at the room level but, recently, lighting systems have begun to be equipped with sensors on a more fine-grained level, enabling lighting control at the desk level. For some office cases, however, the savings gained using this strategy may not outweigh the costs and design efforts compared to room control. This is because, in some offices, individual occupancy patterns are similar, hence the difference in savings between desk and room control would be minimal. This study examined the influence of occupancy pattern variance within an office space on the relative energy savings of control strategies with different control zone sizes. We applied stochastic modeling to estimate the occupancy patterns, as this method can account for uncertainty. To validate our model, simulation results were compared to earlier studies and real measurements, which demonstrated that our simulations provided realistic occupancy patterns. Next, office cases varying in both job-function type distribution and office policy were investigated on energy savings potential to determine the influence of occupancy pattern variance. The relative energy savings potential of the different control strategies differed minimally for the test cases, suggesting that variations in individual occupancy patterns negligibly influence energy savings. In all cases, lighting control at the desk level showed a significantly higher energy savings potential than strategies with lower control zone granularity, suggesting that it is useful to implement occupancy-based lighting at the desk level in all office cases. This strategy should, thus, receive more attention from both researchers and lighting designers.

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.

Sub-30 nm patterning of molecular resists based on crosslinking through tip based oxidation

Science.gov (United States)

Lorenzoni, Matteo; Wagner, Daniel; Neuber, Christian; Schmidt, Hans-Werner; Perez-Murano, Francesc

2018-06-01

Oxidation Scanning Probe Lithography (o-SPL) is an established method employed for device patterning at the nanometer scale. It represents a feasible and inexpensive alternative to standard lithographic techniques such as electron beam lithography (EBL) and nanoimprint lithography (NIL). In this work we applied non-contact o-SPL to an engineered class of molecular resists in order to obtain crosslinking by electrochemical driven oxidation. By patterning and developing various resist formulas we were able to obtain a reliable negative tone resist behavior based on local oxidation. Under optimal conditions, directly written patterns can routinely reach sub-30 nm lateral resolution, while the final developed features result wider, approaching 50 nm width.

A method for rapid similarity analysis of RNA secondary structures

Directory of Open Access Journals (Sweden)

Liu Na

2006-11-01

Full Text Available Abstract Background Owing to the rapid expansion of RNA structure databases in recent years, efficient methods for structure comparison are in demand for function prediction and evolutionary analysis. Usually, the similarity of RNA secondary structures is evaluated based on tree models and dynamic programming algorithms. We present here a new method for the similarity analysis of RNA secondary structures. Results Three sets of real data have been used as input for the example applications. Set I includes the structures from 5S rRNAs. Set II includes the secondary structures from RNase P and RNase MRP. Set III includes the structures from 16S rRNAs. Reasonable phylogenetic trees are derived for these three sets of data by using our method. Moreover, our program runs faster as compared to some existing ones. Conclusion The famous Lempel-Ziv algorithm can efficiently extract the information on repeated patterns encoded in RNA secondary structures and makes our method an alternative to analyze the similarity of RNA secondary structures. This method will also be useful to researchers who are interested in evolutionary analysis.

Reducing 4D CT artifacts using optimized sorting based on anatomic similarity.

Science.gov (United States)

Johnston, Eric; Diehn, Maximilian; Murphy, James D; Loo, Billy W; Maxim, Peter G

2011-05-01

Four-dimensional (4D) computed tomography (CT) has been widely used as a tool to characterize respiratory motion in radiotherapy. The two most commonly used 4D CT algorithms sort images by the associated respiratory phase or displacement into a predefined number of bins, and are prone to image artifacts at transitions between bed positions. The purpose of this work is to demonstrate a method of reducing motion artifacts in 4D CT by incorporating anatomic similarity into phase or displacement based sorting protocols. Ten patient datasets were retrospectively sorted using both the displacement and phase based sorting algorithms. Conventional sorting methods allow selection of only the nearest-neighbor image in time or displacement within each bin. In our method, for each bed position either the displacement or the phase defines the center of a bin range about which several candidate images are selected. The two dimensional correlation coefficients between slices bordering the interface between adjacent couch positions are then calculated for all candidate pairings. Two slices have a high correlation if they are anatomically similar. Candidates from each bin are then selected to maximize the slice correlation over the entire data set using the Dijkstra's shortest path algorithm. To assess the reduction of artifacts, two thoracic radiation oncologists independently compared the resorted 4D datasets pairwise with conventionally sorted datasets, blinded to the sorting method, to choose which had the least motion artifacts. Agreement between reviewers was evaluated using the weighted kappa score. Anatomically based image selection resulted in 4D CT datasets with significantly reduced motion artifacts with both displacement (P = 0.0063) and phase sorting (P = 0.00022). There was good agreement between the two reviewers, with complete agreement 34 times and complete disagreement 6 times. Optimized sorting using anatomic similarity significantly reduces 4D CT motion

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

Application of Pattern Recognition Method for Color Assessment of Oriental Tobacco based on HPLC of Polyphenols

Directory of Open Access Journals (Sweden)

Dagnon S

2014-12-01

Full Text Available The color of Oriental tobaccos was organoleptically assayed, and high performance liquid chromatography (HPLC of polyphenols was performed. The major tobacco polyphenols (chlorogenic acid, its isomers, and rutin, as well as scopoletin and kaempferol-3-rutinoside were quantified. HPLC polyphenol profiles were processed by pattern recognition method (PRM, and the values of indexes of similarity (Is,% between the cultivars studied were determined. It was shown that data from organoleptic color assessment and from PRM based on HPLC profiles of polyphenols of the cultivars studied are largely compatible. Hence, PRM can be suggested as an additional tool for objective color evaluation and classification of Oriental tobacco.

Towards Personalized Medicine: Leveraging Patient Similarity and Drug Similarity Analytics

Science.gov (United States)

Zhang, Ping; Wang, Fei; Hu, Jianying; Sorrentino, Robert

2014-01-01

The rapid adoption of electronic health records (EHR) provides a comprehensive source for exploratory and predictive analytic to support clinical decision-making. In this paper, we investigate how to utilize EHR to tailor treatments to individual patients based on their likelihood to respond to a therapy. We construct a heterogeneous graph which includes two domains (patients and drugs) and encodes three relationships (patient similarity, drug similarity, and patient-drug prior associations). We describe a novel approach for performing a label propagation procedure to spread the label information representing the effectiveness of different drugs for different patients over this heterogeneous graph. The proposed method has been applied on a real-world EHR dataset to help identify personalized treatments for hypercholesterolemia. The experimental results demonstrate the effectiveness of the approach and suggest that the combination of appropriate patient similarity and drug similarity analytics could lead to actionable insights for personalized medicine. Particularly, by leveraging drug similarity in combination with patient similarity, our method could perform well even on new or rarely used drugs for which there are few records of known past performance. PMID:25717413

Similar digit-based working memory in deaf signers and hearing non-signers despite digit span differences

Directory of Open Access Journals (Sweden)

Josefine eAndin

2013-12-01

Full Text Available Similar working memory (WM for lexical items has been demonstrated for signers and non-signers while short-term memory (STM is regularly poorer in deaf than hearing individuals. In the present study, we investigated digit-based WM and STM in Swedish and British deaf signers and hearing non-signers. To maintain good experimental control we used printed stimuli throughout and held response mode constant across groups. We showed that deaf signers have similar digit-based WM performance, despite shorter digit spans, compared to well-matched hearing non-signers. We found no difference between signers and non-signers on STM span for letters chosen to minimize phonological similarity or in the effects of recall direction. This set of findings indicates that similar WM for signers and non-signers can be generalized from lexical items to digits and suggests that poorer STM in deaf signers compared to hearing non-signers may be due to differences in phonological similarity across the language modalities of sign and speech.

Personalized recommendation with corrected similarity

International Nuclear Information System (INIS)

Zhu, Xuzhen; Tian, Hui; Cai, Shimin

2014-01-01

Personalized recommendation has attracted a surge of interdisciplinary research. Especially, similarity-based methods in applications of real recommendation systems have achieved great success. However, the computations of similarities are overestimated or underestimated, in particular because of the defective strategy of unidirectional similarity estimation. In this paper, we solve this drawback by leveraging mutual correction of forward and backward similarity estimations, and propose a new personalized recommendation index, i.e., corrected similarity based inference (CSI). Through extensive experiments on four benchmark datasets, the results show a greater improvement of CSI in comparison with these mainstream baselines. And a detailed analysis is presented to unveil and understand the origin of such difference between CSI and mainstream indices. (paper)

Analysis and Modeling of Time-Correlated Characteristics of Rainfall-Runoff Similarity in the Upstream Red River Basin

Directory of Open Access Journals (Sweden)

Xiuli Sang

2012-01-01

Full Text Available We constructed a similarity model (based on Euclidean distance between rainfall and runoff to study time-correlated characteristics of rainfall-runoff similar patterns in the upstream Red River Basin and presented a detailed evaluation of the time correlation of rainfall-runoff similarity. The rainfall-runoff similarity was used to determine the optimum similarity. The results showed that a time-correlated model was found to be capable of predicting the rainfall-runoff similarity in the upstream Red River Basin in a satisfactory way. Both noised and denoised time series by thresholding the wavelet coefficients were applied to verify the accuracy of model. And the corresponding optimum similar sets obtained as the equation solution conditions showed an interesting and stable trend. On the whole, the annual mean similarity presented a gradually rising trend, for quantitatively estimating comprehensive influence of climate change and of human activities on rainfall-runoff similarity.

On Identifying Useful Patterns to Analyze Products in Retail Transaction Databases

Science.gov (United States)

Yun, Unil

Mining correlated patterns in large transaction databases is one of the essential tasks in data mining since a huge number of patterns are usually mined, but it is hard to find patterns with the correlation. The needed data analysis should be made according to the requirements of the particular real application. In previous mining approaches, patterns with the weak affinity are found even with a high minimum support. In this paper, we suggest weighted support affinity pattern mining in which a new measure, weighted support confidence (ws-confidence) is developed to identify correlated patterns with the weighted support affinity. To efficiently prune the weak affinity patterns, we prove that the ws-confidence measure satisfies the anti-monotone and cross weighted support properties which can be applied to eliminate patterns with dissimilar weighted support levels. Based on the two properties, we develop a weighted support affinity pattern mining algorithm (WSP). The weighted support affinity patterns can be useful to answer the comparative analysis queries such as finding itemsets containing items which give similar total selling expense levels with an acceptable error range α% and detecting item lists with similar levels of total profits. In addition, our performance study shows that WSP is efficient and scalable for mining weighted support affinity patterns.

Optimizing top precision performance measure of content-based image retrieval by learning similarity function

KAUST Repository

Liang, Ru-Ze

2017-04-24

In this paper we study the problem of content-based image retrieval. In this problem, the most popular performance measure is the top precision measure, and the most important component of a retrieval system is the similarity function used to compare a query image against a database image. However, up to now, there is no existing similarity learning method proposed to optimize the top precision measure. To fill this gap, in this paper, we propose a novel similarity learning method to maximize the top precision measure. We model this problem as a minimization problem with an objective function as the combination of the losses of the relevant images ranked behind the top-ranked irrelevant image, and the squared Frobenius norm of the similarity function parameter. This minimization problem is solved as a quadratic programming problem. The experiments over two benchmark data sets show the advantages of the proposed method over other similarity learning methods when the top precision is used as the performance measure.

Optimizing top precision performance measure of content-based image retrieval by learning similarity function

KAUST Repository

Liang, Ru-Ze; Shi, Lihui; Wang, Haoxiang; Meng, Jiandong; Wang, Jim Jing-Yan; Sun, Qingquan; Gu, Yi

2017-01-01

In this paper we study the problem of content-based image retrieval. In this problem, the most popular performance measure is the top precision measure, and the most important component of a retrieval system is the similarity function used to compare a query image against a database image. However, up to now, there is no existing similarity learning method proposed to optimize the top precision measure. To fill this gap, in this paper, we propose a novel similarity learning method to maximize the top precision measure. We model this problem as a minimization problem with an objective function as the combination of the losses of the relevant images ranked behind the top-ranked irrelevant image, and the squared Frobenius norm of the similarity function parameter. This minimization problem is solved as a quadratic programming problem. The experiments over two benchmark data sets show the advantages of the proposed method over other similarity learning methods when the top precision is used as the performance measure.

Size-based predictions of food web patterns

DEFF Research Database (Denmark)

Zhang, Lai; Hartvig, Martin; Knudsen, Kim

2014-01-01

We employ size-based theoretical arguments to derive simple analytic predictions of ecological patterns and properties of natural communities: size-spectrum exponent, maximum trophic level, and susceptibility to invasive species. The predictions are brought about by assuming that an infinite number...... of species are continuously distributed on a size-trait axis. It is, however, an open question whether such predictions are valid for a food web with a finite number of species embedded in a network structure. We address this question by comparing the size-based predictions to results from dynamic food web...... simulations with varying species richness. To this end, we develop a new size- and trait-based food web model that can be simplified into an analytically solvable size-based model. We confirm existing solutions for the size distribution and derive novel predictions for maximum trophic level and invasion...

Passive Forensics for Region Duplication Image Forgery Based on Harris Feature Points and Local Binary Patterns

Directory of Open Access Journals (Sweden)

Jie Zhao

2013-01-01

Full Text Available Nowadays the demand for identifying the authenticity of an image is much increased since advanced image editing software packages are widely used. Region duplication forgery is one of the most common and immediate tampering attacks which are frequently used. Several methods to expose this forgery have been developed to detect and locate the tampered region, while most methods do fail when the duplicated region undergoes rotation or flipping before being pasted. In this paper, an efficient method based on Harris feature points and local binary patterns is proposed. First, the image is filtered with a pixelwise adaptive Wiener method, and then dense Harris feature points are employed in order to obtain a sufficient number of feature points with approximately uniform distribution. Feature vectors for a circle patch around each feature point are extracted using local binary pattern operators, and the similar Harris points are matched based on their representation feature vectors using the BBF algorithm. Finally, RANSAC algorithm is employed to eliminate the possible erroneous matches. Experiment results demonstrate that the proposed method can effectively detect region duplication forgery, even when an image was distorted by rotation, flipping, blurring, AWGN, JPEG compression, and their mixed operations, especially resistant to the forgery with the flat area of little visual structures.

Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach.

Science.gov (United States)

Pasupa, Kitsuchart; Kudisthalert, Wasu

2018-01-01

Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets-Maximum Unbiased Validation Dataset-which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6.

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.

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.

A Combination of Central Pattern Generator-based and Reflex-based Neural Networks for Dynamic, Adaptive, Robust Bipedal Locomotion

DEFF Research Database (Denmark)

Di Canio, Giuliano; Larsen, Jørgen Christian; Wörgötter, Florentin

2016-01-01

Robotic systems inspired from humans have always been lightening up the curiosity of engineers and scientists. Of many challenges, human locomotion is a very difficult one where a number of different systems needs to interact in order to generate a correct and balanced pattern. To simulate...... the interaction of these systems, implementations with reflexbased or central pattern generator (CPG)-based controllers have been tested on bipedal robot systems. In this paper we will combine the two controller types, into a controller that works with both reflex and CPG signals. We use a reflex-based neural...... network to generate basic walking patterns of a dynamic bipedal walking robot (DACBOT) and then a CPG-based neural network to ensure robust walking behavior...

MotionFlow: Visual Abstraction and Aggregation of Sequential Patterns in Human Motion Tracking Data.

Science.gov (United States)

Jang, Sujin; Elmqvist, Niklas; Ramani, Karthik

2016-01-01

Pattern analysis of human motions, which is useful in many research areas, requires understanding and comparison of different styles of motion patterns. However, working with human motion tracking data to support such analysis poses great challenges. In this paper, we propose MotionFlow, a visual analytics system that provides an effective overview of various motion patterns based on an interactive flow visualization. This visualization formulates a motion sequence as transitions between static poses, and aggregates these sequences into a tree diagram to construct a set of motion patterns. The system also allows the users to directly reflect the context of data and their perception of pose similarities in generating representative pose states. We provide local and global controls over the partition-based clustering process. To support the users in organizing unstructured motion data into pattern groups, we designed a set of interactions that enables searching for similar motion sequences from the data, detailed exploration of data subsets, and creating and modifying the group of motion patterns. To evaluate the usability of MotionFlow, we conducted a user study with six researchers with expertise in gesture-based interaction design. They used MotionFlow to explore and organize unstructured motion tracking data. Results show that the researchers were able to easily learn how to use MotionFlow, and the system effectively supported their pattern analysis activities, including leveraging their perception and domain knowledge.

Attention-based image similarity measure with application to content-based information retrieval

Science.gov (United States)

Stentiford, Fred W. M.

2003-01-01

Whilst storage and capture technologies are able to cope with huge numbers of images, image retrieval is in danger of rendering many repositories valueless because of the difficulty of access. This paper proposes a similarity measure that imposes only very weak assumptions on the nature of the features used in the recognition process. This approach does not make use of a pre-defined set of feature measurements which are extracted from a query image and used to match those from database images, but instead generates features on a trial and error basis during the calculation of the similarity measure. This has the significant advantage that features that determine similarity can match whatever image property is important in a particular region whether it be a shape, a texture, a colour or a combination of all three. It means that effort is expended searching for the best feature for the region rather than expecting that a fixed feature set will perform optimally over the whole area of an image and over every image in a database. The similarity measure is evaluated on a problem of distinguishing similar shapes in sets of black and white symbols.

Shape-based hand recognition approach using the morphological pattern spectrum

Science.gov (United States)

Ramirez-Cortes, Juan Manuel; Gomez-Gil, Pilar; Sanchez-Perez, Gabriel; Prieto-Castro, Cesar

2009-01-01

We propose the use of the morphological pattern spectrum, or pecstrum, as the base of a biometric shape-based hand recognition system. The system receives an image of the right hand of a subject in an unconstrained pose, which is captured with a commercial flatbed scanner. According to pecstrum property of invariance to translation and rotation, the system does not require the use of pegs for a fixed hand position, which simplifies the image acquisition process. This novel feature-extraction method is tested using a Euclidean distance classifier for identification and verification cases, obtaining 97% correct identification, and an equal error rate (EER) of 0.0285 (2.85%) for the verification mode. The obtained results indicate that the pattern spectrum represents a good feature-extraction alternative for low- and medium-level hand-shape-based biometric applications.

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.

Similarity-Based Unification: A Multi-Adjoint Approach

Czech Academy of Sciences Publication Activity Database

Medina, J.; Ojeda-Aciego, M.; Vojtáš, Peter

2004-01-01

Roč. 146, č. 1 (2004), s. 43-62 ISSN 0165-0114 Source of funding: V - iné verejné zdroje Keywords : similarity * fuzzy unification Subject RIV: BA - General Mathematics Impact factor: 0.734, year: 2004

Lesser Neural Pattern Similarity across Repeated Tests Is Associated with Better Long-Term Memory Retention.

Science.gov (United States)

Karlsson Wirebring, Linnea; Wiklund-Hörnqvist, Carola; Eriksson, Johan; Andersson, Micael; Jonsson, Bert; Nyberg, Lars

2015-07-01

Encoding and retrieval processes enhance long-term memory performance. The efficiency of encoding processes has recently been linked to representational consistency: the reactivation of a representation that gets more specific each time an item is further studied. Here we examined the complementary hypothesis of whether the efficiency of retrieval processes also is linked to representational consistency. Alternatively, recurrent retrieval might foster representational variability--the altering or adding of underlying memory representations. Human participants studied 60 Swahili-Swedish word pairs before being scanned with fMRI the same day and 1 week later. On Day 1, participants were tested three times on each word pair, and on Day 7 each pair was tested once. A BOLD signal change in right superior parietal cortex was associated with subsequent memory on Day 1 and with successful long-term retention on Day 7. A representational similarity analysis in this parietal region revealed that beneficial recurrent retrieval was associated with representational variability, such that the pattern similarity on Day 1 was lower for retrieved words subsequently remembered compared with those subsequently forgotten. This was mirrored by a monotonically decreased BOLD signal change in dorsolateral prefrontal cortex on Day 1 as a function of repeated successful retrieval for words subsequently remembered, but not for words subsequently forgotten. This reduction in prefrontal response could reflect reduced demands on cognitive control. Collectively, the results offer novel insights into why memory retention benefits from repeated retrieval, and they suggest fundamental differences between repeated study and repeated testing. Repeated testing is known to produce superior long-term retention of the to-be-learned material compared with repeated encoding and other learning techniques, much because it fosters repeated memory retrieval. This study demonstrates that repeated memory

Similar effects of feature-based attention on motion perception and pursuit eye movements at different levels of awareness.

Science.gov (United States)

Spering, Miriam; Carrasco, Marisa

2012-05-30

Feature-based attention enhances visual processing and improves perception, even for visual features that we are not aware of. Does feature-based attention also modulate motor behavior in response to visual information that does or does not reach awareness? Here we compare the effect of feature-based attention on motion perception and smooth-pursuit eye movements in response to moving dichoptic plaids--stimuli composed of two orthogonally drifting gratings, presented separately to each eye--in human observers. Monocular adaptation to one grating before the presentation of both gratings renders the adapted grating perceptually weaker than the unadapted grating and decreases the level of awareness. Feature-based attention was directed to either the adapted or the unadapted grating's motion direction or to both (neutral condition). We show that observers were better at detecting a speed change in the attended than the unattended motion direction, indicating that they had successfully attended to one grating. Speed change detection was also better when the change occurred in the unadapted than the adapted grating, indicating that the adapted grating was perceptually weaker. In neutral conditions, perception and pursuit in response to plaid motion were dissociated: While perception followed one grating's motion direction almost exclusively (component motion), the eyes tracked the average of both gratings (pattern motion). In attention conditions, perception and pursuit were shifted toward the attended component. These results suggest that attention affects perception and pursuit similarly even though only the former reflects awareness. The eyes can track an attended feature even if observers do not perceive it.

Comparison of two structured illumination techniques based on different 3D illumination patterns

Science.gov (United States)

Shabani, H.; Patwary, N.; Doblas, A.; Saavedra, G.; Preza, C.

2017-02-01

Manipulating the excitation pattern in optical microscopy has led to several super-resolution techniques. Among different patterns, the lateral sinusoidal excitation was used for the first demonstration of structured illumination microscopy (SIM), which provides the fastest SIM acquisition system (based on the number of raw images required) compared to the multi-spot illumination approach. Moreover, 3D patterns that include lateral and axial variations in the illumination have attracted more attention recently as they address resolution enhancement in three dimensions. A threewave (3W) interference technique based on coherent illumination has already been shown to provide super-resolution and optical sectioning in 3D-SIM. In this paper, we investigate a novel tunable technique that creates a 3D pattern from a set of multiple incoherently illuminated parallel slits that act as light sources for a Fresnel biprism. This setup is able to modulate the illumination pattern in the object space both axially and laterally with adjustable modulation frequencies. The 3D forward model for the new system is developed here to consider the effect of the axial modulation due to the 3D patterned illumination. The performance of 3D-SIM based on 3W interference and the tunable system are investigated in simulation and compared based on two different criteria. First, restored images obtained for both 3D-SIM systems using a generalized Wiener filter are compared to determine the effect of the illumination pattern on the reconstruction. Second, the effective frequency response of both systems is studied to determine the axial and lateral resolution enhancement that is obtained in each case.

Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms

International Nuclear Information System (INIS)

Tourassi, Georgia D.; Harrawood, Brian; Singh, Swatee; Lo, Joseph Y.; Floyd, Carey E.

2007-01-01

The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrieval precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses

[Wetland landscape pattern change based on GIS and RS: a review].

Science.gov (United States)

Kong, Fan-Ting; Xi, Min; Li, Yue; Kong, Fan-Long; Chen, Wan

2013-04-01

Wetland is an ecological landscape with most biodiversity in nature, which has unique ecological structure and function, and contains abundant natural resources to provide material guarantee for human's living and development. Wetland landscape pattern is the comprehensive result of various ecological processes, and has become a hot issue in wetland ecological study. At present, the combination of geographic information system (GIS) and remote sensing (RS) technologies is an important way to study the wetland landscape pattern change. This paper reviewed the research progress in the wetland landscape change based on GIS and RS from the aspects of the research methods of wetland landscape pattern, index of wetland landscape pattern, and driving forces of wetland landscape pattern evolution, and discussed the applications of the combination of GIS and RS in monitoring the wetland landscape pattern change, the index selection of wetland landscape pattern, and the driving mechanisms of the combined action of human and nature. Some deficiencies in the current studies were put forward, and the directions of the future-studies were prospected.

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.

Dietary patterns and adult asthma: population-based case-control study.

Science.gov (United States)

Bakolis, I; Hooper, R; Thompson, R L; Shaheen, S O

2010-05-01

Epidemiological studies of diet and asthma have focused on relations with intakes of individual nutrients and foods and evidence has been conflicting. Few studies have examined associations with dietary patterns. We carried out a population-based case-control study of asthma in adults aged between 16 and 50 in South London, UK. Information about usual diet was obtained by food frequency questionnaire and we used principal components analysis to define five dietary patterns in controls. We used logistic and linear regression, controlling for confounders, to relate these patterns to asthma, asthma severity, rhinitis and chronic bronchitis in 599 cases and 854 controls. Overall, there was weak evidence that a 'vegetarian' dietary pattern was positively associated with asthma [adjusted odds ratio comparing top vs bottom quintile of pattern score 1.43 (95% CI: 0.93-2.20), P trend 0.075], and a 'traditional' pattern (meat and vegetables) was negatively associated [OR 0.68 (0.45-1.03), P trend 0.071]. These associations were stronger amongst nonsupplement users (P trend 0.030 and 0.001, respectively), and the association with the 'vegetarian' pattern was stronger amongst whites (P trend 0.008). No associations were observed with asthma severity. A 'prudent' dietary pattern (wholemeal bread, fish and vegetables) was positively associated with chronic bronchitis [OR 2.61 (1.13-6.05), P trend 0.025], especially amongst nonsupplement users (P trend 0.002). Overall there were no clear relations between dietary patterns and adult asthma; associations in nonsupplement users and whites require confirmation. The finding for chronic bronchitis was unexpected and also requires replication.

A Novel Approach to Semantic Similarity Measurement Based on a Weighted Concept Lattice: Exemplifying Geo-Information

Directory of Open Access Journals (Sweden)

Jia Xiao

2017-11-01

Full Text Available The measurement of semantic similarity has been widely recognized as having a fundamental and key role in information science and information systems. Although various models have been proposed to measure semantic similarity, these models are not able effectively to quantify the weights of relevant factors that impact on the judgement of semantic similarity, such as the attributes of concepts, application context, and concept hierarchy. In this paper, we propose a novel approach that comprehensively considers the effects of various factors on semantic similarity judgment, which we name semantic similarity measurement based on a weighted concept lattice (SSMWCL. A feature model and network model are integrated together in SSMWCL. Based on the feature model, the combined weight of each attribute of the concepts is calculated by merging its information entropy and inclusion-degree importance in a specific application context. By establishing the weighted concept lattice, the relative hierarchical depths of concepts for comparison are computed according to the principle of the network model. The integration of feature model and network model enables SSMWCL to take account of differences in concepts more comprehensively in semantic similarity measurement. Additionally, a workflow of SSMWCL is designed to demonstrate these procedures and a case study of geo-information is conducted to assess the approach.

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.

Efficient constraint-based Sequential Pattern Mining (SPM algorithm to understand customers’ buying behaviour from time stamp-based sequence dataset

Directory of Open Access Journals (Sweden)

Niti Ashish Kumar Desai

2015-12-01

Full Text Available Business Strategies are formulated based on an understanding of customer needs. This requires development of a strategy to understand customer behaviour and buying patterns, both current and future. This involves understanding, first how an organization currently understands customer needs and second predicting future trends to drive growth. This article focuses on purchase trend of customer, where timing of purchase is more important than association of item to be purchased, and which can be found out with Sequential Pattern Mining (SPM methods. Conventional SPM algorithms worked purely on frequency identifying patterns that were more frequent but suffering from challenges like generation of huge number of uninteresting patterns, lack of user’s interested patterns, rare item problem, etc. Article attempts a solution through development of a SPM algorithm based on various constraints like Gap, Compactness, Item, Recency, Profitability and Length along with Frequency constraint. Incorporation of six additional constraints is as well to ensure that all patterns are recently active (Recency, active for certain time span (Compactness, profitable and indicative of next timeline for purchase (Length―Item―Gap. The article also attempts to throw light on how proposed Constraint-based Prefix Span algorithm is helpful to understand buying behaviour of customer which is in formative stage.

Molecular basis sets - a general similarity-based approach for representing chemical spaces.

Science.gov (United States)

Raghavendra, Akshay S; Maggiora, Gerald M

2007-01-01

A new method, based on generalized Fourier analysis, is described that utilizes the concept of "molecular basis sets" to represent chemical space within an abstract vector space. The basis vectors in this space are abstract molecular vectors. Inner products among the basis vectors are determined using an ansatz that associates molecular similarities between pairs of molecules with their corresponding inner products. Moreover, the fact that similarities between pairs of molecules are, in essentially all cases, nonzero implies that the abstract molecular basis vectors are nonorthogonal, but since the similarity of a molecule with itself is unity, the molecular vectors are normalized to unity. A symmetric orthogonalization procedure, which optimally preserves the character of the original set of molecular basis vectors, is used to construct appropriate orthonormal basis sets. Molecules can then be represented, in general, by sets of orthonormal "molecule-like" basis vectors within a proper Euclidean vector space. However, the dimension of the space can become quite large. Thus, the work presented here assesses the effect of basis set size on a number of properties including the average squared error and average norm of molecular vectors represented in the space-the results clearly show the expected reduction in average squared error and increase in average norm as the basis set size is increased. Several distance-based statistics are also considered. These include the distribution of distances and their differences with respect to basis sets of differing size and several comparative distance measures such as Spearman rank correlation and Kruscal stress. All of the measures show that, even though the dimension can be high, the chemical spaces they represent, nonetheless, behave in a well-controlled and reasonable manner. Other abstract vector spaces analogous to that described here can also be constructed providing that the appropriate inner products can be directly

Love flows downstream: mothers' and children's neural representation similarity in perceiving distress of self and family.

Science.gov (United States)

Lee, Tae-Ho; Qu, Yang; Telzer, Eva H

2017-12-01

The current study aimed to capture empathy processing in an interpersonal context. Mother-adolescent dyads (N = 22) each completed an empathy task during fMRI, in which they imagined the target person in distressing scenes as either themselves or their family (i.e. child for the mother, mother for the child). Using multi-voxel pattern approach, we compared neural pattern similarity for the self and family conditions and found that mothers showed greater perceptual similarity between self and child in the fusiform face area (FFA), representing high self-child overlap, whereas adolescents showed significantly less self-mother overlap. Adolescents' pattern similarity was dependent upon family relationship quality, such that they showed greater self-mother overlap with higher relationship quality, whereas mothers' pattern similarity was independent of relationship quality. Furthermore, adolescents' perceptual similarity in the FFA was associated with increased social brain activation (e.g. temporal parietal junction). Mediation analyses indicated that high relationship quality was associated with greater social brain activation, which was mediated by greater self-mother overlap in the FFA. Our findings suggest that adolescents show more distinct neural patterns in perceiving their own vs their mother's distress, and such distinction is sensitive to mother-child relationship quality. In contrast, mothers' perception for their own and child's distress is highly similar and unconditional. © The Author (2017). Published by Oxford University Press.

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

Generalized method for sorting Shack-Hartmann spot patterns using local similarity

International Nuclear Information System (INIS)

Smith, Daniel G.; Greivenkamp, John E.

2008-01-01

The sensitivity and dynamic range of a Shack-Hartmann wavefront sensor is enhanced when the spots produced by the lenslet array are allowed to shift more than one lenslet radius from their on-axis positions. However, this presents the problem of accurately and robustly associating the spots with their respective subapertures. This paper describes a method for sorting spots that takes advantage of the local spot position distortions to unwrap the spot pattern. The described algorithm is both simple and robust and also applicable to any lenslet array geometry that can be described as a two-dimensional lattice, including hexagonal arrays, which are shown here to be more efficient than square arrays

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...

Characteristics of InGaN-Based Light-Emitting Diodes on Patterned Sapphire Substrates with Various Pattern Heights

Directory of Open Access Journals (Sweden)

Sheng-Fu Yu

2012-01-01

Full Text Available The optical and electrical characteristics of InGaN-based blue light-emitting diodes (LEDs grown on patterned sapphire substrates (PSSs with different pattern heights and on planar sapphire by atmospheric-pressure metal-organic chemical vapor deposition were investigated. Compared with planar sapphire, it was found that the LED electroluminescence intensity is significantly enhanced on PSSs with pattern heights of 0.5 (21%, 1.1 (57%, 1.5 (81%, and 1.9 (91% μm at an injected current of 20 mA. The increased light intensity exhibits the same trend in a TracePro simulation. In addition, it was also found that the level of leakage current depends on the density of V-shape defects, which were measured by scanning electron microscopy.

Dynamics-based sequential memory: Winnerless competition of patterns

International Nuclear Information System (INIS)

Seliger, Philip; Tsimring, Lev S.; Rabinovich, Mikhail I.

2003-01-01

We introduce a biologically motivated dynamical principle of sequential memory which is based on winnerless competition (WLC) of event images. This mechanism is implemented in a two-layer neural model of sequential spatial memory. We present the learning dynamics which leads to the formation of a WLC network. After learning, the system is capable of associative retrieval of prerecorded sequences of patterns

Human-based percussion and self-similarity detection in electroacoustic music

Science.gov (United States)

Mills, John Anderson, III

Electroacoustic music is music that uses electronic technology for the compositional manipulation of sound, and is a unique genre of music for many reasons. Analyzing electroacoustic music requires special measures, some of which are integrated into the design of a preliminary percussion analysis tool set for electroacoustic music. This tool set is designed to incorporate the human processing of music and sound. Models of the human auditory periphery are used as a front end to the analysis algorithms. The audio properties of percussivity and self-similarity are chosen as the focus because these properties are computable and informative. A collection of human judgments about percussion was undertaken to acquire clearly specified, sound-event dimensions that humans use as a percussive cue. A total of 29 participants was asked to make judgments about the percussivity of 360 pairs of synthesized snare-drum sounds. The grouped results indicate that of the dimensions tested rise time is the strongest cue for percussivity. String resonance also has a strong effect, but because of the complex nature of string resonance, it is not a fundamental dimension of a sound event. Gross spectral filtering also has an effect on the judgment of percussivity but the effect is weaker than for rise time and string resonance. Gross spectral filtering also has less effect when the stronger cue of rise time is modified simultaneously. A percussivity-profile algorithm (PPA) is designed to identify those instants in pieces of music that humans also would identify as percussive. The PPA is implemented using a time-domain, channel-based approach and psychoacoustic models. The input parameters are tuned to maximize performance at matching participants' choices in the percussion-judgment collection. After the PPA is tuned, the PPA then is used to analyze pieces of electroacoustic music. Real electroacoustic music introduces new challenges for the PPA, though those same challenges might affect

Similar patterns of neural activity predict memory function during encoding and retrieval.

Science.gov (United States)

Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-Attribute Decision Making Based on Several Trigonometric Hamming Similarity Measures under Interval Rough Neutrosophic Environment

Directory of Open Access Journals (Sweden)

Surapati Pramanik

2018-03-01

Full Text Available In this paper, the sine, cosine and cotangent similarity measures of interval rough neutrosophic sets is proposed. Some properties of the proposed measures are discussed. We have proposed multi attribute decision making approaches based on proposed similarity measures. To demonstrate the applicability, a numerical example is solved.

Alteration of gene conversion patterns in Sordaria fimicola by supplementation with DNA bases.

Science.gov (United States)

Kitani, Y; Olive, L S

1970-08-01

Supplementation with DNA bases in crosses of Sordaria fimicola heterozygous for spore color markers (g(1), h(2)) within the gray-spore (g) locus has been found to cause significant alterations in patterns of gene conversion at the two mutant sites. Each base had its own characteristic effect in altering the conversion pattern, and responses of the two mutant sites to the four bases were different in several ways. Also, the responses of the two involved chromatids of the meiotic bivalent were different.

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.

Enhanced performance of VOx-based bolometer using patterned gold black absorber

Science.gov (United States)

Smith, Evan M.; Panjwani, Deep; Ginn, James; Warren, Andrew; Long, Christopher; Figuieredo, Pedro; Smith, Christian; Perlstein, Joshua; Walter, Nick; Hirschmugl, Carol; Peale, Robert E.; Shelton, David J.

2015-06-01

Patterned highly absorbing gold black film has been selectively deposited on the active surfaces of a vanadium-oxide-based infrared bolometer array. Patterning by metal lift-off relies on protection of the fragile gold black with an evaporated oxide, which preserves gold black's near unity absorption. This patterned gold black also survives the dry-etch removal of the sacrificial polyimide used to fabricate the air-bridge bolometers. Infrared responsivity is substantially improved by the gold black coating without significantly increasing noise. The increase in the time constant caused by the additional mass of gold black is a modest 14%.

Cognitive dissonance and the development of a sustainable consumption pattern

DEFF Research Database (Denmark)

Thøgersen, John

This paper reports a study of mental prerequisites for the development of a sustainable con-sumption pattern. Based on cognitive dissonance theory it is hypothesized that when two environmentally relevant activities are perceived as similar, behaving in an environmentally friendly way in one...

Discovery of spatio-temporal patterns from location-based social networks

Science.gov (United States)

Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

2016-03-01

Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

BicPAMS: software for biological data analysis with pattern-based biclustering.

Science.gov (United States)

Henriques, Rui; Ferreira, Francisco L; Madeira, Sara C

2017-02-02

Biclustering has been largely applied for the unsupervised analysis of biological data, being recognised today as a key technique to discover putative modules in both expression data (subsets of genes correlated in subsets of conditions) and network data (groups of coherently interconnected biological entities). However, given its computational complexity, only recent breakthroughs on pattern-based biclustering enabled efficient searches without the restrictions that state-of-the-art biclustering algorithms place on the structure and homogeneity of biclusters. As a result, pattern-based biclustering provides the unprecedented opportunity to discover non-trivial yet meaningful biological modules with putative functions, whose coherency and tolerance to noise can be tuned and made problem-specific. To enable the effective use of pattern-based biclustering by the scientific community, we developed BicPAMS (Biclustering based on PAttern Mining Software), a software that: 1) makes available state-of-the-art pattern-based biclustering algorithms (BicPAM (Henriques and Madeira, Alg Mol Biol 9:27, 2014), BicNET (Henriques and Madeira, Alg Mol Biol 11:23, 2016), BicSPAM (Henriques and Madeira, BMC Bioinforma 15:130, 2014), BiC2PAM (Henriques and Madeira, Alg Mol Biol 11:1-30, 2016), BiP (Henriques and Madeira, IEEE/ACM Trans Comput Biol Bioinforma, 2015), DeBi (Serin and Vingron, AMB 6:1-12, 2011) and BiModule (Okada et al., IPSJ Trans Bioinf 48(SIG5):39-48, 2007)); 2) consistently integrates their dispersed contributions; 3) further explores additional accuracy and efficiency gains; and 4) makes available graphical and application programming interfaces. Results on both synthetic and real data confirm the relevance of BicPAMS for biological data analysis, highlighting its essential role for the discovery of putative modules with non-trivial yet biologically significant functions from expression and network data. BicPAMS is the first biclustering tool offering the

A knowledge based method for nuclear plant loading pattern determination

International Nuclear Information System (INIS)

Dauboin, P.

1990-01-01

This paper deals with the design of a knowledge based system for solving an industrial problem which occurs in nuclear fuel management. The problem lies in determining satisfactory loading patterns for nuclear plants. Its primary feature consists in the huge search space involved. Conventional resolution processes are formally defined and analyzed: there is no general algorithm which guarantees to always provide a reasonable solution in each situation. We propose a new approach to solve this constrained search problem using domain-specific knowledge and general constraint-based heuristics. During a preprocessing step, a problem dependent search algorithm is designed. This procedure is then automatically implemented in FORTRAN. The generated routines have proved to be very efficient finding solutions which could not have been provided using logic programming. A prototype expert system has already been applied to actual reload pattern searches. While combining efficiency and flexibility, this knowledge based system enables human experts to rapidly match new constraints and requirements

Traditional and robust vector selection methods for use with similarity based models

International Nuclear Information System (INIS)

Hines, J. W.; Garvey, D. R.

2006-01-01

Vector selection, or instance selection as it is often called in the data mining literature, performs a critical task in the development of nonparametric, similarity based models. Nonparametric, similarity based modeling (SBM) is a form of 'lazy learning' which constructs a local model 'on the fly' by comparing a query vector to historical, training vectors. For large training sets the creation of local models may become cumbersome, since each training vector must be compared to the query vector. To alleviate this computational burden, varying forms of training vector sampling may be employed with the goal of selecting a subset of the training data such that the samples are representative of the underlying process. This paper describes one such SBM, namely auto-associative kernel regression (AAKR), and presents five traditional vector selection methods and one robust vector selection method that may be used to select prototype vectors from a larger data set in model training. The five traditional vector selection methods considered are min-max, vector ordering, combination min-max and vector ordering, fuzzy c-means clustering, and Adeli-Hung clustering. Each method is described in detail and compared using artificially generated data and data collected from the steam system of an operating nuclear power plant. (authors)

High-power Yb-fiber comb based on pre-chirped-management self-similar amplification

Science.gov (United States)

Luo, Daping; Liu, Yang; Gu, Chenglin; Wang, Chao; Zhu, Zhiwei; Zhang, Wenchao; Deng, Zejiang; Zhou, Lian; Li, Wenxue; Zeng, Heping

2018-02-01

We report a fiber self-similar-amplification (SSA) comb system that delivers a 250-MHz, 109-W, 42-fs pulse train with a 10-dB spectral width of 85 nm at 1056 nm. A pair of grisms is employed to compensate the group velocity dispersion and third-order dispersion of pre-amplified pulses for facilitating a self-similar evolution and a self-phase modulation (SPM). Moreover, we analyze the stabilities and noise characteristics of both the locked carrier envelope phase and the repetition rate, verifying the stability of the generated high-power comb. The demonstration of the SSA comb at such high power proves the feasibility of the SPM-based low-noise ultrashort comb.

Design of patterned sapphire substrates for GaN-based light-emitting diodes

International Nuclear Information System (INIS)

Wang Hai-Yan; Lin Zhi-Ting; Han Jing-Lei; Zhong Li-Yi; Li Guo-Qiang

2015-01-01

A new method for patterned sapphire substrate (PSS) design is developed and proven to be reliable and cost-effective. As progress is made with LEDs’ luminous efficiency, the pattern units of PSS become more complicated, and the effect of complicated geometrical features is almost impossible to study systematically by experiments only. By employing our new method, the influence of pattern parameters can be systematically studied, and various novel patterns are designed and optimized within a reasonable time span, with great improvement in LEDs’ light extraction efficiency (LEE). Clearly, PSS pattern design with such a method deserves particular attention. We foresee that GaN-based LEDs on these newly designed PSSs will achieve more progress in the coming years. (topical review)

Similar expression patterns of bestrophin-4 and cGMP dependent Ca2+-activated chloride channel activity in the vasculature

DEFF Research Database (Denmark)

Bouzinova, Elena V.; Larsen, Per; Matchkov, Vladimir

2008-01-01

(abstract by Matchkov et. al) that siRNA mediated downregulation of bestrophin-4 is associated with the disappearance of a recently demonstrated2 cGMP-dependent Ca2+-activated Cl- current in vascular smooth muscle cells (SMCs). Here we study the distribution of bestrophin-4-and cGMP dependent Cl- channel...... expressed epitope) Western blot detected a ~65 kDa band in cell lysates from rat mesenteric small arteries and aorta, which was not seen in pulmonary arteries and when preincubated with the immunizing peptide. The distribution of bestrophin-4 mRNA and protein has a pattern similar to the cGMP-dependent Cl......- current in SMCs of different origins. Immunohistochemistry identified bestrophin-4 both in endothelial and SMCs of the vascular tree in the brain, heart, kidney and mesentery, but not in the lungs. We suggest that bestrophin-4 is important for the cGMP dependent, Ca2+ activated Cl- conductance in many...

Similar-Case-Based Optimization of Beam Arrangements in Stereotactic Body Radiotherapy for Assisting Treatment Planners

Directory of Open Access Journals (Sweden)

Taiki Magome

2013-01-01

Full Text Available Objective. To develop a similar-case-based optimization method for beam arrangements in lung stereotactic body radiotherapy (SBRT to assist treatment planners. Methods. First, cases that are similar to an objective case were automatically selected based on geometrical features related to a planning target volume (PTV location, PTV shape, lung size, and spinal cord position. Second, initial beam arrangements were determined by registration of similar cases with the objective case using a linear registration technique. Finally, beam directions of the objective case were locally optimized based on the cost function, which takes into account the radiation absorption in normal tissues and organs at risk. The proposed method was evaluated with 10 test cases and a treatment planning database including 81 cases, by using 11 planning evaluation indices such as tumor control probability and normal tissue complication probability (NTCP. Results. The procedure for the local optimization of beam arrangements improved the quality of treatment plans with significant differences (P<0.05 in the homogeneity index and conformity index for the PTV, V10, V20, mean dose, and NTCP for the lung. Conclusion. The proposed method could be usable as a computer-aided treatment planning tool for the determination of beam arrangements in SBRT.

A measure of association between vectors based on "similarity covariance"

OpenAIRE

Pascual-Marqui, Roberto D.; Lehmann, Dietrich; Kochi, Kieko; Kinoshita, Toshihiko; Yamada, Naoto

2013-01-01

The "maximum similarity correlation" definition introduced in this study is motivated by the seminal work of Szekely et al on "distance covariance" (Ann. Statist. 2007, 35: 2769-2794; Ann. Appl. Stat. 2009, 3: 1236-1265). Instead of using Euclidean distances "d" as in Szekely et al, we use "similarity", which can be defined as "exp(-d/s)", where the scaling parameter s>0 controls how rapidly the similarity falls off with distance. Scale parameters are chosen by maximizing the similarity corre...

Computer-aided beam arrangement based on similar cases in radiation treatment-planning databases for stereotactic lung radiation therapy

International Nuclear Information System (INIS)

Magome, Taiki; Shioyama, Yoshiyuki; Arimura, Hidetaka

2013-01-01

The purpose of this study was to develop a computer-aided method for determination of beam arrangements based on similar cases in a radiotherapy treatment-planning database for stereotactic lung radiation therapy. Similar-case-based beam arrangements were automatically determined based on the following two steps. First, the five most similar cases were searched, based on geometrical features related to the location, size and shape of the planning target volume, lung and spinal cord. Second, five beam arrangements of an objective case were automatically determined by registering five similar cases with the objective case, with respect to lung regions, by means of a linear registration technique. For evaluation of the beam arrangements five treatment plans were manually created by applying the beam arrangements determined in the second step to the objective case. The most usable beam arrangement was selected by sorting the five treatment plans based on eight plan evaluation indices, including the D95, mean lung dose and spinal cord maximum dose. We applied the proposed method to 10 test cases, by using an RTP database of 81 cases with lung cancer, and compared the eight plan evaluation indices between the original treatment plan and the corresponding most usable similar-case-based treatment plan. As a result, the proposed method may provide usable beam arrangements, which have no statistically significant differences from the original beam arrangements (P>0.05) in terms of the eight plan evaluation indices. Therefore, the proposed method could be employed as an educational tool for less experienced treatment planners. (author)

SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer.

Science.gov (United States)

Petricoin, Emanuel F; Liotta, Lance A

2004-02-01

Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity-based processes. Serum proteomic pattern diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. This approach has recently shown tremendous promise in the detection of early-stage cancers. The biomarkers found by SELDI-TOF-based pattern recognition analysis are mostly low molecular weight fragments produced at the specific tumor microenvironment.

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.

Areal Feature Matching Based on Similarity Using Critic Method

Science.gov (United States)

Kim, J.; Yu, K.

2015-10-01

In this paper, we propose an areal feature matching method that can be applied for many-to-many matching, which involves matching a simple entity with an aggregate of several polygons or two aggregates of several polygons with fewer user intervention. To this end, an affine transformation is applied to two datasets by using polygon pairs for which the building name is the same. Then, two datasets are overlaid with intersected polygon pairs that are selected as candidate matching pairs. If many polygons intersect at this time, we calculate the inclusion function between such polygons. When the value is more than 0.4, many of the polygons are aggregated as single polygons by using a convex hull. Finally, the shape similarity is calculated between the candidate pairs according to the linear sum of the weights computed in CRITIC method and the position similarity, shape ratio similarity, and overlap similarity. The candidate pairs for which the value of the shape similarity is more than 0.7 are determined as matching pairs. We applied the method to two geospatial datasets: the digital topographic map and the KAIS map in South Korea. As a result, the visual evaluation showed two polygons that had been well detected by using the proposed method. The statistical evaluation indicates that the proposed method is accurate when using our test dataset with a high F-measure of 0.91.

Looking Similar Promotes Group Stability in a Game-Based Virtual Community.

Science.gov (United States)

Lortie, Catherine L; Guitton, Matthieu J

2012-08-01

Online support groups are popular Web-based resources that provide tailored information and peer support through virtual communities and fulfill the users' needs for empowerment and belonging. However, the therapeutic potential of online support groups is at present limited by the lack of systematic research on the cognitive mechanisms underlying social group cohesion in virtual communities. We might increase the benefits of participation in online support groups if we gain more insight into the factors that promote long-term commitment to peer support. One approach to foster the therapeutic potential of online support groups could be to increase social selection based on visual similarity. We performed a case study using the popular virtual setting of "World of Warcraft" (Blizzard Entertainment, Irvine, CA). We monitored the social dynamics of a virtual community composed of avatars whose appearance was identical during a period of 3 months, biweekly, for a total of 24 measures. We observed that this homogeneous community displayed a very high level of group stability over time in terms of the total number of members, the number of members that stayed the same, and the number of arrivals and departures, despite the fact that belonging to a heterogeneous group typically favors the success of the group with respect to game progression. Our results confirm that appearance can trigger social selection in online virtual communities. Displaying a similar appearance could be one way to strengthen social bonds among peers who share various health and well-being issues. Thus, the therapeutic potential of online support groups could be promoted through visual cohesion.

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.

Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images.

Directory of Open Access Journals (Sweden)

Jiaqian Li

Full Text Available Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and it is found that the technique of the combination of the local binary pattern and the k-nearest neighbor algorithm achieve the best performance. Relying on the results of block pattern classification, experiments on the whole images show that classifier fusion rules are able to identify the staining patterns of the whole well (specimen image with a total accuracy of about 94.62%.

Improvement of potato based cropping patterns by inclusion of short duration Mungbean and T. Aman rice in Monga prone areas of Rangpur

Directory of Open Access Journals (Sweden)

M.K. Islam

2014-12-01

Full Text Available The experiment was carried out to compare the improved cropping patterns against the farmers existing potato based cropping patterns having no mungbean/brown manure crop for higher yield, economic return and income generation in agricultural field in the off period following RCBD design with three replications at farmer’s field at Paikan Gangachara, Rangpur district during September- October. The treatments (cropping patterns were T1 = T. aman rice (BINA 7 - Potato - Mungbean (BARI mungbean 6 (Improved pattern, T2 = T. aman rice (BR11 - Potato - Fallow (Farmers pattern, T3 = T. aman rice (BINA 7 - Potato + Maize intercrop - Mungbean (Improved pattern and T4 = T. aman rice (BR11 - Potato / Maize relay (Farmers pattern. The highest yield (4.16 t ha-1 was recorded in T2 (BR11 which is statistically at par with T4 (4.15 t ha-1 but higher than the other treatments. Early planting sole potato (T1 gave highest yield (26.10 t ha-1 which was significantly higher than all other treatments. Late planting sole potato (T2, intercropped early potato (T3 and relay potato (T4 showed similar yield (23.61 – 24.79 t ha-1. Intercropped (T3 and Relay (T4 maize did not vary significantly in the studied parameters and yields were 8.21 and 7.92 t ha-1, respectively. Mungbean after sole potato (T1 gave higher number of pods/plant (17.25, and yield (1.47 t ha-1 which is significantly higher than those of T3 (14.89 and 1.28 t ha-1, respectively. Highest gross return (GR (Tk. 417720 and gross margin (GM (Tk. 220220 were calculated in improved pattern T3 and the lowest of those (Tk. 289670, Tk. 146020 in farmers pattern T2 . The other improved pattern T3 was the second highest performer considering GR and GM. But BCR (2.21 was highest in T1 and second highest in T3. The results indicated that the improved patterns (T1, T3 were better than farmers pattern (T2, T4. The improved pattern (T1 gave GR Tk. 67890 and GM Tk. 51785 higher than farmers pattern (T2. Similarly, the

Experimental study of circle grid fractal pattern on turbulent intensity in pipe flow

International Nuclear Information System (INIS)

Manshoor, B; Zaman, I; Othman, M F; Khalid, Amir

2013-01-01

Fractal turbulence is deemed much more efficient than grid turbulence in terms of a turbulence generation. In this paper, the hotwire experimental results for the circle grids fractal pattern as a turbulent generator will be presented. The self-similar edge characteristic of the circle grid fractal pattern is thought to play a vital role in the enhancement of turbulent intensity. Three different beta ratios of perforated plates based on circle grids fractal pattern were used in the experimental work and each paired with standard circle grids with similar porosity. The objectives were to study the fractal scaling influence on the flow and also to explore the potential of the circle grids fractal pattern in enhancing the turbulent intensity. The results provided an excellent insight of the fractal generated turbulence and the fractal flow physics. Across the circle grids fractal pattern, the pressure drop was lower but the turbulent intensity was higher than those across the paired standard circle grids

Patch Similarity Modulus and Difference Curvature Based Fourth-Order Partial Differential Equation for Image Denoising

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Yunjiao Bai

2015-01-01

Full Text Available The traditional fourth-order nonlinear diffusion denoising model suffers the isolated speckles and the loss of fine details in the processed image. For this reason, a new fourth-order partial differential equation based on the patch similarity modulus and the difference curvature is proposed for image denoising. First, based on the intensity similarity of neighbor pixels, this paper presents a new edge indicator called patch similarity modulus, which is strongly robust to noise. Furthermore, the difference curvature which can effectively distinguish between edges and noise is incorporated into the denoising algorithm to determine the diffusion process by adaptively adjusting the size of the diffusion coefficient. The experimental results show that the proposed algorithm can not only preserve edges and texture details, but also avoid isolated speckles and staircase effect while filtering out noise. And the proposed algorithm has a better performance for the images with abundant details. Additionally, the subjective visual quality and objective evaluation index of the denoised image obtained by the proposed algorithm are higher than the ones from the related methods.

Hilar cholangiocarcinoma is pathologically similar to pancreatic duct adenocarcinoma: suggestions of similar background and development.

Science.gov (United States)

Nakanuma, Yasuni; Sato, Yasunori

2014-07-01

Routine experiences suggest that cholangiocarcinomas (CCAs) show different clinicopathological behaviors along the biliary tree, and hilar CCA apparently resembles pancreatic duct adenocarcinoma (PDAC). Herein, the backgrounds for these similarities were reviewed. While all cases of PDAC, hilar CCA, intrahepatic CCA (ICCA) and CCA components of combined hepatocellular-cholangiocarcinoma (cHC-CCA) were adenocarcinomas, micropapillary patterns and columnar carcinoma cells were common in PDAC and hilar CCA, and trabecular components and cuboidal carcinoma cells were common in ICCA and CCA components of cHC-CCA. Anterior gradient protein-2 and S100P were frequently expressed in perihilar CCA and PDAC, while neural cell adhesion molecule and luminal epithelial membrane antigen were common in CCA components of c-HC-CCA. Pdx1 and Hes1 were frequently and markedly expressed aberrantly in PDAC and perihilar CCA, although their expression was rare and mild in CCA components in cHC-CCA and ICCA. Hilar CCA showed a similar postoperative prognosis to PDAC but differed from ICCA and cHC-CCA. Taken together, hilar CCA may differ from ICCA and CCA components of cHC-CCA but have a similar development to PDAC. These similarities may be explained by the unique anatomical, embryological and reactive nature of the pancreatobiliary tract. Further studies of these intractable malignancies are warranted. © 2014 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

Identifying typical patterns of vulnerability: A 5-step approach based on cluster analysis

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Sietz, Diana; Lüdeke, Matthias; Kok, Marcel; Lucas, Paul; Carsten, Walther; Janssen, Peter

2013-04-01

Specific processes that shape the vulnerability of socio-ecological systems to climate, market and other stresses derive from diverse background conditions. Within the multitude of vulnerability-creating mechanisms, distinct processes recur in various regions inspiring research on typical patterns of vulnerability. The vulnerability patterns display typical combinations of the natural and socio-economic properties that shape a systems' vulnerability to particular stresses. Based on the identification of a limited number of vulnerability patterns, pattern analysis provides an efficient approach to improving our understanding of vulnerability and decision-making for vulnerability reduction. However, current pattern analyses often miss explicit descriptions of their methods and pay insufficient attention to the validity of their groupings. Therefore, the question arises as to how do we identify typical vulnerability patterns in order to enhance our understanding of a systems' vulnerability to stresses? A cluster-based pattern recognition applied at global and local levels is scrutinised with a focus on an applicable methodology and practicable insights. Taking the example of drylands, this presentation demonstrates the conditions necessary to identify typical vulnerability patterns. They are summarised in five methodological steps comprising the elicitation of relevant cause-effect hypotheses and the quantitative indication of mechanisms as well as an evaluation of robustness, a validation and a ranking of the identified patterns. Reflecting scale-dependent opportunities, a global study is able to support decision-making with insights into the up-scaling of interventions when available funds are limited. In contrast, local investigations encourage an outcome-based validation. This constitutes a crucial step in establishing the credibility of the patterns and hence their suitability for informing extension services and individual decisions. In this respect, working at

OS2: Oblivious similarity based searching for encrypted data outsourced to an untrusted domain

Science.gov (United States)

Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Ramzan, Naeem

2017-01-01

Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search (OS2) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, OS2 ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables OS2 to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of OS2 is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations. PMID:28692697

Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity.

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Yee, Yohan; Fernandes, Darren J; French, Leon; Ellegood, Jacob; Cahill, Lindsay S; Vousden, Dulcie A; Spencer Noakes, Leigh; Scholz, Jan; van Eede, Matthijs C; Nieman, Brian J; Sled, John G; Lerch, Jason P

2018-05-18

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the

Molecular identification of similar species of the genus Biomphalaria (Mollusca: Planorbidae determined by a polymerase chain reaction-restriction fragment length polymorphism

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Caldeira Roberta Lima

1998-01-01

Full Text Available The freshwater snails Biomphalaria straminea, B. intermedia, B. kuhniana and B. peregrina, are morphologically similar; based on this similarity the first three species were therefore grouped in the complex B. straminea. The morphological identification of these species is based on characters such as vaginal wrinkling, relation between prepuce: penial sheath:deferens vas and number of muscle layers in the penis wall. In this study the polymerase chain reaction restriction fragment length polymorphism technique was used for molecular identification of these molluscs. This technique is based on the amplification of the internal transcribed spacer regions ITS1 e ITS2 of the ribosomal RNA gene and subsequent digestion of these fragments by restriction enzymes. Six enzymes were tested: Dde I, Mnl I, Hae III, Rsa I, Hpa II e Alu I. The restriction patterns obtained with DdeI presented the best profile for separation of the four species of Biomphalaria. The profiles obtained with all the enzymes were used to estimate the genetic distances among the species through analysis of common banding patterns.

AREAL FEATURE MATCHING BASED ON SIMILARITY USING CRITIC METHOD

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J. Kim

2015-10-01

Full Text Available In this paper, we propose an areal feature matching method that can be applied for many-to-many matching, which involves matching a simple entity with an aggregate of several polygons or two aggregates of several polygons with fewer user intervention. To this end, an affine transformation is applied to two datasets by using polygon pairs for which the building name is the same. Then, two datasets are overlaid with intersected polygon pairs that are selected as candidate matching pairs. If many polygons intersect at this time, we calculate the inclusion function between such polygons. When the value is more than 0.4, many of the polygons are aggregated as single polygons by using a convex hull. Finally, the shape similarity is calculated between the candidate pairs according to the linear sum of the weights computed in CRITIC method and the position similarity, shape ratio similarity, and overlap similarity. The candidate pairs for which the value of the shape similarity is more than 0.7 are determined as matching pairs. We applied the method to two geospatial datasets: the digital topographic map and the KAIS map in South Korea. As a result, the visual evaluation showed two polygons that had been well detected by using the proposed method. The statistical evaluation indicates that the proposed method is accurate when using our test dataset with a high F-measure of 0.91.

Identifying mechanistic similarities in drug responses

KAUST Repository

Zhao, C.

2012-05-15

Motivation: In early drug development, it would be beneficial to be able to identify those dynamic patterns of gene response that indicate that drugs targeting a particular gene will be likely or not to elicit the desired response. One approach would be to quantitate the degree of similarity between the responses that cells show when exposed to drugs, so that consistencies in the regulation of cellular response processes that produce success or failure can be more readily identified.Results: We track drug response using fluorescent proteins as transcription activity reporters. Our basic assumption is that drugs inducing very similar alteration in transcriptional regulation will produce similar temporal trajectories on many of the reporter proteins and hence be identified as having similarities in their mechanisms of action (MOA). The main body of this work is devoted to characterizing similarity in temporal trajectories/signals. To do so, we must first identify the key points that determine mechanistic similarity between two drug responses. Directly comparing points on the two signals is unrealistic, as it cannot handle delays and speed variations on the time axis. Hence, to capture the similarities between reporter responses, we develop an alignment algorithm that is robust to noise, time delays and is able to find all the contiguous parts of signals centered about a core alignment (reflecting a core mechanism in drug response). Applying the proposed algorithm to a range of real drug experiments shows that the result agrees well with the prior drug MOA knowledge. © The Author 2012. Published by Oxford University Press. All rights reserved.

An experimental comparison of three wire beam electrode based methods for determining corrosion rates and patterns

International Nuclear Information System (INIS)

Tan, Y.-J.

2005-01-01

Laboratory experiments have been carried out to examine the advantages and limitations of three wire beam electrode (WBE) based techniques, including the noise resistance R n -WBE method, the overpotential-galvanic current method, and the galvanic current method, in determining corrosion rates and patterns. These techniques have been applied simultaneously to several selected corrosion systems of different characteristics. It has been found that the R n -WBE method has advantages over other WBE based methods when applying to WBE surfaces under uniform corrosion. However, the R n -WBE method has been found to be unsuitable for low noise level corrosion systems. It has also been found that both R n -WBE and overpotential-galvanic current methods are similarly applicable to WBE surfaces under nonuniform corrosion. However, the galvanic current method has been found to be suitable only for WBE surfaces under highly localised corrosion. Some related issues regarding R n calculation such as trend removal and its effects on corrosion mapping have also been discussed

Validation of the Mnemonic Similarity Task – Context Version

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Giulia A. Aldi

2018-02-01

Full Text Available Objective: Pattern separation (PS is the ability to represent similar experiences as separate, non-overlapping representations. It is usually assessed via the Mnemonic Similarity Task – Object Version (MST-O which, however, assesses PS performance without taking behavioral context discrimination into account, since it is based on pictures of everyday simple objects on a white background. We here present a validation study for a new task, the Mnemonic Similarity Task – Context Version (MST-C, which is designed to measure PS while taking behavioral context discrimination into account by using real-life context photographs. Methods: Fifty healthy subjects underwent the two MST tasks to assess convergent evidence. Instruments assessing memory and attention were also administered to study discriminant evidence. The test-retest reliability of MST-C was analyzed. Results: Weak evidence supports convergent validity between the MST-C task and the MST-O as measures of PS (rs = 0.464; p < 0.01; PS performance assessed via the MST-C did not correlate with memory or attention; a moderate test-retest reliability was found (rs = 0.595; p < 0.01. Conclusion: The MST-C seems useful for assessing PS performance conceptualized as the ability to discriminate complex and realistic spatial contexts. Future studies are welcome to evaluate the validity of the MST-C task as a measure of PS in clinical populations.

Micro-patterned graphene-based sensing skins for human physiological monitoring

Science.gov (United States)

Wang, Long; Loh, Kenneth J.; Chiang, Wei-Hung; Manna, Kausik

2018-03-01

Ultrathin, flexible, conformal, and skin-like electronic transducers are emerging as promising candidates for noninvasive and nonintrusive human health monitoring. In this work, a wearable sensing membrane is developed by patterning a graphene-based solution onto ultrathin medical tape, which can then be attached to the skin for monitoring human physiological parameters and physical activity. Here, the sensor is validated for monitoring finger bending/movements and for recognizing hand motion patterns, thereby demonstrating its future potential for evaluating athletic performance, physical therapy, and designing next-generation human-machine interfaces. Furthermore, this study also quantifies the sensor’s ability to monitor eye blinking and radial pulse in real-time, which can find broader applications for the healthcare sector. Overall, the printed graphene-based sensing skin is highly conformable, flexible, lightweight, nonintrusive, mechanically robust, and is characterized by high strain sensitivity.

In the pursuit of a semantic similarity metric based on UMLS annotations for articles in PubMed Central Open Access.

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Garcia Castro, Leyla Jael; Berlanga, Rafael; Garcia, Alexander

2015-10-01

Although full-text articles are provided by the publishers in electronic formats, it remains a challenge to find related work beyond the title and abstract context. Identifying related articles based on their abstract is indeed a good starting point; this process is straightforward and does not consume as many resources as full-text based similarity would require. However, further analyses may require in-depth understanding of the full content. Two articles with highly related abstracts can be substantially different regarding the full content. How similarity differs when considering title-and-abstract versus full-text and which semantic similarity metric provides better results when dealing with full-text articles are the main issues addressed in this manuscript. We have benchmarked three similarity metrics - BM25, PMRA, and Cosine, in order to determine which one performs best when using concept-based annotations on full-text documents. We also evaluated variations in similarity values based on title-and-abstract against those relying on full-text. Our test dataset comprises the Genomics track article collection from the 2005 Text Retrieval Conference. Initially, we used an entity recognition software to semantically annotate titles and abstracts as well as full-text with concepts defined in the Unified Medical Language System (UMLS®). For each article, we created a document profile, i.e., a set of identified concepts, term frequency, and inverse document frequency; we then applied various similarity metrics to those document profiles. We considered correlation, precision, recall, and F1 in order to determine which similarity metric performs best with concept-based annotations. For those full-text articles available in PubMed Central Open Access (PMC-OA), we also performed dispersion analyses in order to understand how similarity varies when considering full-text articles. We have found that the PubMed Related Articles similarity metric is the most suitable for

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

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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

Acousto-electrical speckle pattern in Lorentz force electrical impedance tomography

International Nuclear Information System (INIS)

Grasland-Mongrain, Pol; Destrempes, François; Cloutier, Guy; Mari, Jean-Martial; Souchon, Rémi; Catheline, Stefan; Chapelon, Jean-Yves; Lafon, Cyril

2015-01-01

Ultrasound speckle is a granular texture pattern appearing in ultrasound imaging. It can be used to distinguish tissues and identify pathologies. Lorentz force electrical impedance tomography is an ultrasound-based medical imaging technique of the tissue electrical conductivity. It is based on the application of an ultrasound wave in a medium placed in a magnetic field and on the measurement of the induced electric current due to Lorentz force. Similarly to ultrasound imaging, we hypothesized that a speckle could be observed with Lorentz force electrical impedance tomography imaging. In this study, we first assessed the theoretical similarity between the measured signals in Lorentz force electrical impedance tomography and in ultrasound imaging modalities. We then compared experimentally the signal measured in both methods using an acoustic and electrical impedance interface. Finally, a bovine muscle sample was imaged using the two methods. Similar speckle patterns were observed. This indicates the existence of an ‘acousto-electrical speckle’ in the Lorentz force electrical impedance tomography with spatial characteristics driven by the acoustic parameters but due to electrical impedance inhomogeneities instead of acoustic ones as is the case of ultrasound imaging. (paper)

Acousto-electrical speckle pattern in Lorentz force electrical impedance tomography

Science.gov (United States)

Grasland-Mongrain, Pol; Destrempes, François; Mari, Jean-Martial; Souchon, Rémi; Catheline, Stefan; Chapelon, Jean-Yves; Lafon, Cyril; Cloutier, Guy

2015-05-01

Ultrasound speckle is a granular texture pattern appearing in ultrasound imaging. It can be used to distinguish tissues and identify pathologies. Lorentz force electrical impedance tomography is an ultrasound-based medical imaging technique of the tissue electrical conductivity. It is based on the application of an ultrasound wave in a medium placed in a magnetic field and on the measurement of the induced electric current due to Lorentz force. Similarly to ultrasound imaging, we hypothesized that a speckle could be observed with Lorentz force electrical impedance tomography imaging. In this study, we first assessed the theoretical similarity between the measured signals in Lorentz force electrical impedance tomography and in ultrasound imaging modalities. We then compared experimentally the signal measured in both methods using an acoustic and electrical impedance interface. Finally, a bovine muscle sample was imaged using the two methods. Similar speckle patterns were observed. This indicates the existence of an ‘acousto-electrical speckle’ in the Lorentz force electrical impedance tomography with spatial characteristics driven by the acoustic parameters but due to electrical impedance inhomogeneities instead of acoustic ones as is the case of ultrasound imaging.

Faces in places: humans and machines make similar face detection errors.

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Bernard Marius 't Hart

Full Text Available The human visual system seems to be particularly efficient at detecting faces. This efficiency sometimes comes at the cost of wrongfully seeing faces in arbitrary patterns, including famous examples such as a rock configuration on Mars or a toast's roast patterns. In machine vision, face detection has made considerable progress and has become a standard feature of many digital cameras. The arguably most wide-spread algorithm for such applications ("Viola-Jones" algorithm achieves high detection rates at high computational efficiency. To what extent do the patterns that the algorithm mistakenly classifies as faces also fool humans? We selected three kinds of stimuli from real-life, first-person perspective movies based on the algorithm's output: correct detections ("real faces", false positives ("illusory faces" and correctly rejected locations ("non faces". Observers were shown pairs of these for 20 ms and had to direct their gaze to the location of the face. We found that illusory faces were mistaken for faces more frequently than non faces. In addition, rotation of the real face yielded more errors, while rotation of the illusory face yielded fewer errors. Using colored stimuli increases overall performance, but does not change the pattern of results. When replacing the eye movement by a manual response, however, the preference for illusory faces over non faces disappeared. Taken together, our data show that humans make similar face-detection errors as the Viola-Jones algorithm, when directing their gaze to briefly presented stimuli. In particular, the relative spatial arrangement of oriented filters seems of relevance. This suggests that efficient face detection in humans is likely to be pre-attentive and based on rather simple features as those encoded in the early visual system.

Similarity in Bilateral Isolated Internal Orbital Fractures.

Science.gov (United States)

Chen, Hung-Chang; Cox, Jacob T; Sanyal, Abanti; Mahoney, Nicholas R

2018-04-13

In evaluating patients sustaining bilateral isolated internal orbital fractures, the authors have observed both similar fracture locations and also similar expansion of orbital volumes. In this study, we aim to investigate if there is a propensity for the 2 orbits to fracture in symmetrically similar patterns when sustaining similar trauma. A retrospective chart review was performed studying all cases at our institution of bilateral isolated internal orbital fractures involving the medial wall and/or the floor at the time of presentation. The similarity of the bilateral fracture locations was evaluated using the Fisher's exact test. The bilateral expanded orbital volumes were analyzed using the Wilcoxon signed-rank test to assess for orbital volume similarity. Twenty-four patients with bilateral internal orbital fractures were analyzed for fracture location similarity. Seventeen patients (70.8%) had 100% concordance in the orbital subregion fractured, and the association between the right and the left orbital fracture subregion locations was statistically significant (P < 0.0001). Fifteen patients were analyzed for orbital volume similarity. The average orbital cavity volume was 31.2 ± 3.8 cm on the right and 32.0 ± 3.7 cm on the left. There was a statistically significant difference between right and left orbital cavity volumes (P = 0.0026). The data from this study suggest that an individual who suffers isolated bilateral internal orbital fractures has a statistically significant similarity in the location of their orbital fractures. However, there does not appear to be statistically significant similarity in the expansion of the orbital volumes in these patients.

PTree: pattern-based, stochastic search for maximum parsimony phylogenies

Directory of Open Access Journals (Sweden)

Ivan Gregor

2013-06-01

Full Text Available Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we describe a stochastic search method for a maximum parsimony tree, implemented in a software package we named PTree. Our method is based on a new pattern-based technique that enables us to infer intermediate sequences efficiently where the incorporation of these sequences in the current tree topology yields a phylogenetic tree with a lower cost. Evaluation across multiple datasets showed that our method is comparable to the algorithms implemented in PAUP* or TNT, which are widely used by the bioinformatics community, in terms of topological accuracy and runtime. We show that our method can process large-scale datasets of 1,000–8,000 sequences. We believe that our novel pattern-based method enriches the current set of tools and methods for phylogenetic tree inference. The software is available under: http://algbio.cs.uni-duesseldorf.de/webapps/wa-download/.

PTree: pattern-based, stochastic search for maximum parsimony phylogenies.

Science.gov (United States)

Gregor, Ivan; Steinbrück, Lars; McHardy, Alice C

2013-01-01

Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we describe a stochastic search method for a maximum parsimony tree, implemented in a software package we named PTree. Our method is based on a new pattern-based technique that enables us to infer intermediate sequences efficiently where the incorporation of these sequences in the current tree topology yields a phylogenetic tree with a lower cost. Evaluation across multiple datasets showed that our method is comparable to the algorithms implemented in PAUP* or TNT, which are widely used by the bioinformatics community, in terms of topological accuracy and runtime. We show that our method can process large-scale datasets of 1,000-8,000 sequences. We believe that our novel pattern-based method enriches the current set of tools and methods for phylogenetic tree inference. The software is available under: http://algbio.cs.uni-duesseldorf.de/webapps/wa-download/.

An efficient similarity measure for content based image retrieval using memetic algorithm

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Mutasem K. Alsmadi

2017-06-01

Full Text Available Content based image retrieval (CBIR systems work by retrieving images which are related to the query image (QI from huge databases. The available CBIR systems extract limited feature sets which confine the retrieval efficacy. In this work, extensive robust and important features were extracted from the images database and then stored in the feature repository. This feature set is composed of color signature with the shape and color texture features. Where, features are extracted from the given QI in the similar fashion. Consequently, a novel similarity evaluation using a meta-heuristic algorithm called a memetic algorithm (genetic algorithm with great deluge is achieved between the features of the QI and the features of the database images. Our proposed CBIR system is assessed by inquiring number of images (from the test dataset and the efficiency of the system is evaluated by calculating precision-recall value for the results. The results were superior to other state-of-the-art CBIR systems in regard to precision.

Automatic SIMD parallelization of embedded applications based on pattern recognition

NARCIS (Netherlands)

Manniesing, R.; Karkowski, I.P.; Corporaal, H.

2000-01-01

This paper investigates the potential for automatic mapping of typical embedded applications to architectures with multimedia instruction set extensions. For this purpose a (pattern matching based) code transformation engine is used, which involves a three-step process of matching, condition

A similarity measure method combining location feature for mammogram retrieval.

Science.gov (United States)

Wang, Zhiqiong; Xin, Junchang; Huang, Yukun; Li, Chen; Xu, Ling; Li, Yang; Zhang, Hao; Gu, Huizi; Qian, Wei

2018-05-28

Breast cancer, the most common malignancy among women, has a high mortality rate in clinical practice. Early detection, diagnosis and treatment can reduce the mortalities of breast cancer greatly. The method of mammogram retrieval can help doctors to find the early breast lesions effectively and determine a reasonable feature set for image similarity measure. This will improve the accuracy effectively for mammogram retrieval. This paper proposes a similarity measure method combining location feature for mammogram retrieval. Firstly, the images are pre-processed, the regions of interest are detected and the lesions are segmented in order to get the center point and radius of the lesions. Then, the method, namely Coherent Point Drift, is used for image registration with the pre-defined standard image. The center point and radius of the lesions after registration are obtained and the standard location feature of the image is constructed. This standard location feature can help figure out the location similarity between the image pair from the query image to each dataset image in the database. Next, the content feature of the image is extracted, including the Histogram of Oriented Gradients, the Edge Direction Histogram, the Local Binary Pattern and the Gray Level Histogram, and the image pair content similarity can be calculated using the Earth Mover's Distance. Finally, the location similarity and content similarity are fused to form the image fusion similarity, and the specified number of the most similar images can be returned according to it. In the experiment, 440 mammograms, which are from Chinese women in Northeast China, are used as the database. When fusing 40% lesion location feature similarity and 60% content feature similarity, the results have obvious advantages. At this time, precision is 0.83, recall is 0.76, comprehensive indicator is 0.79, satisfaction is 96.0%, mean is 4.2 and variance is 17.7. The results show that the precision and recall of this

Stochastic Modeling of Usage Patterns in a Web-Based Information System.

Science.gov (United States)

Chen, Hui-Min; Cooper, Michael D.

2002-01-01

Uses continuous-time stochastic models, mainly based on semi-Markov chains, to derive user state transition patterns, both in rates and in probabilities, in a Web-based information system. Describes search sessions from transaction logs of the University of California's MELVYL library catalog system and discusses sequential dependency. (Author/LRW)

Measuring time series regularity using nonlinear similarity-based sample entropy

International Nuclear Information System (INIS)

Xie Hongbo; He Weixing; Liu Hui

2008-01-01

Sampe Entropy (SampEn), a measure quantifying regularity and complexity, is believed to be an effective analyzing method of diverse settings that include both deterministic chaotic and stochastic processes, particularly operative in the analysis of physiological signals that involve relatively small amount of data. However, the similarity definition of vectors is based on Heaviside function, of which the boundary is discontinuous and hard, may cause some problems in the validity and accuracy of SampEn. Sigmoid function is a smoothed and continuous version of Heaviside function. To overcome the problems SampEn encountered, a modified SampEn (mSampEn) based on nonlinear Sigmoid function was proposed. The performance of mSampEn was tested on the independent identically distributed (i.i.d.) uniform random numbers, the MIX stochastic model, the Rossler map, and the Hennon map. The results showed that mSampEn was superior to SampEn in several aspects, including giving entropy definition in case of small parameters, better relative consistency, robust to noise, and more independence on record length when characterizing time series generated from either deterministic or stochastic system with different regularities

Application of ann-based decision making pattern recognition to fishing operations

Energy Technology Data Exchange (ETDEWEB)

Akhlaghinia, M.; Torabi, F.; Wilton, R.R. [University of Regina, Saskatchewan (Canada). Faculty of Engineering. Dept. of Petroleum Engineering], e-mail: Farshid.Torabi@uregina.ca

2010-10-15

Decision making is a crucial part of fishing operations. Proper decisions should be made to prevent wasted time and associated costs on unsuccessful operations. This paper presents a novel model to help drilling managers decide when to commence and when to quit a fishing operation. A decision making model based on Artificial Neural Network (ANN) has been developed that utilizes Pattern Recognition based on 181 fishing incidents from one of the most fish-prone fields of the southwest of Iran. All parameters chosen to train the ANN-Based Pattern Recognition Tool are assumed to play a role in the success of the fishing operation and are therefore used to decide whether a fishing operation should be performed or not. If the tool deems the operation suitable for consideration, a cost analysis of the fishing operation can then be performed to justify its overall cost. (author)

A column generation-based heuristic for rostering with work patterns

DEFF Research Database (Denmark)

Lusby, Richard Martin; Dohn, Anders Høeg; Range, Troels Martin

2012-01-01

This paper addresses the Ground Crew Rostering Problem with Work Patterns, an important manpower planning problem arising in the ground operations of airline companies. We present a cutting stock-based integer programming formulation of the problem and describe a powerful heuristic decomposition...

Self-similar continued root approximants

International Nuclear Information System (INIS)

Gluzman, S.; Yukalov, V.I.

2012-01-01

A novel method of summing asymptotic series is advanced. Such series repeatedly arise when employing perturbation theory in powers of a small parameter for complicated problems of condensed matter physics, statistical physics, and various applied problems. The method is based on the self-similar approximation theory involving self-similar root approximants. The constructed self-similar continued roots extrapolate asymptotic series to finite values of the expansion parameter. The self-similar continued roots contain, as a particular case, continued fractions and Padé approximants. A theorem on the convergence of the self-similar continued roots is proved. The method is illustrated by several examples from condensed-matter physics.

Sleep Patterns in Chinese Preschool Children: A Population-Based Study.

Science.gov (United States)

Wu, Ran; Wang, Guang-Hai; Zhu, Hong; Jiang, Fan; Jiang, Chun-Lei

2018-04-15

This study aimed to (1) provide data on normal sleep patterns in Chinese preschool children, (2) identify cross-cultural differences of sleep patterns among children from China and other countries, (3) estimate the prevalence of sleep duration not meeting the optimal amount, and (4) characterize delayed weekend sleep pattern. A population-based sample of 1,610 children aged 3-6 years was recruited from 10 cities across China. Parents completed questions about their child's sleep patterns adapted from the Children's Sleep Habits Questionnaire (CSHQ). The mean bedtime was 9:31 PM, wake time was 7:27 AM, nighttime sleep duration was 9 hours 30 minutes, daytime sleep duration was 1 hour 31 minutes, and total sleep duration was 11 hours 2 minutes. The children had a shorter nighttime sleep duration but longer daytime naps, resulting in no differences in total sleep duration compared with counterparts predominantly in the west. Of the children, 85.3% met the recommended amount of sleep of 10 to 13 hours, and 10.8% slept fewer than 10 hours. The prevalence of sleep less than 10 hours was higher in older children and children from eastern China. Children went to bed and woke up more than 30 minutes later on weekends than weekdays, accounting for 40.1% and 50%, respectively. Children in western China showed longer delay than children in eastern China ( P < .05). Age- and region-specific variability of sleep patterns are reported as well as insufficient sleep and delayed weekend sleep pattern in Chinese preschool children. The cross-cultural difference of sleep patterns was in temporal placement rather than sleep duration. © 2018 American Academy of Sleep Medicine.

K2 and K2*: efficient alignment-free sequence similarity measurement based on Kendall statistics.

Science.gov (United States)

Lin, Jie; Adjeroh, Donald A; Jiang, Bing-Hua; Jiang, Yue

2018-05-15

Alignment-free sequence comparison methods can compute the pairwise similarity between a huge number of sequences much faster than sequence-alignment based methods. We propose a new non-parametric alignment-free sequence comparison method, called K2, based on the Kendall statistics. Comparing to the other state-of-the-art alignment-free comparison methods, K2 demonstrates competitive performance in generating the phylogenetic tree, in evaluating functionally related regulatory sequences, and in computing the edit distance (similarity/dissimilarity) between sequences. Furthermore, the K2 approach is much faster than the other methods. An improved method, K2*, is also proposed, which is able to determine the appropriate algorithmic parameter (length) automatically, without first considering different values. Comparative analysis with the state-of-the-art alignment-free sequence similarity methods demonstrates the superiority of the proposed approaches, especially with increasing sequence length, or increasing dataset sizes. The K2 and K2* approaches are implemented in the R language as a package and is freely available for open access (http://community.wvu.edu/daadjeroh/projects/K2/K2_1.0.tar.gz). yueljiang@163.com. Supplementary data are available at Bioinformatics online.

Reactor power distribution pattern judging device

International Nuclear Information System (INIS)

Ikehara, Tadashi.

1992-01-01

The judging device of the present invention comprises a power distribution readout system for intaking a power value from a fuel segment, a neural network having an experience learning function for receiving a power distribution value as an input variant, mapping it into a desirable property and self-organizing the map, and a learning date base storing a plurality of learnt samples. The read power distribution is classified depending on the similarity thereof with any one of representative learnt power distribution, and the corresponding state of the reactor core is outputted as a result of the judgement. When an error is found in the classified judging operation, erroneous cases are additionally learnt by using the experience and learning function, thereby improving the accuracy of the reactor core characteristic estimation operation. Since the device is mainly based on the neural network having a self-learning function and a pattern classification and judging function, a judging device having a human's intuitive pattern recognition performance and a pattern experience and learning performance is obtainable, thereby enabling to judge the state of the reactor core accurately. (N.H.)

Computational mining for hypothetical patterns of amino acid side chains in protein data bank (PDB)

Science.gov (United States)

Ghani, Nur Syatila Ab; Firdaus-Raih, Mohd

2018-04-01

The three-dimensional structure of a protein can provide insights regarding its function. Functional relationship between proteins can be inferred from fold and sequence similarities. In certain cases, sequence or fold comparison fails to conclude homology between proteins with similar mechanism. Since the structure is more conserved than the sequence, a constellation of functional residues can be similarly arranged among proteins of similar mechanism. Local structural similarity searches are able to detect such constellation of amino acids among distinct proteins, which can be useful to annotate proteins of unknown function. Detection of such patterns of amino acids on a large scale can increase the repertoire of important 3D motifs since available known 3D motifs currently, could not compensate the ever-increasing numbers of uncharacterized proteins to be annotated. Here, a computational platform for an automated detection of 3D motifs is described. A fuzzy-pattern searching algorithm derived from IMagine an Amino Acid 3D Arrangement search EnGINE (IMAAAGINE) was implemented to develop an automated method for searching of hypothetical patterns of amino acid side chains in Protein Data Bank (PDB), without the need for prior knowledge on related sequence or structure of pattern of interest. We present an example of the searches, which is the detection of a hypothetical pattern derived from known structural motif of C2H2 structural pattern from zinc fingers. The conservation of particular patterns of amino acid side chains in unrelated proteins is highlighted. This approach can act as a complementary method for available structure- and sequence-based platforms and may contribute in improving functional association between proteins.

A camera-phone based study reveals erratic eating pattern and disrupted daily eating-fasting cycle among adults in India.

Directory of Open Access Journals (Sweden)

Neelu Jain Gupta

Full Text Available The daily rhythm of feeding-fasting and meal-timing are emerging as important determinants of health. Circadian rhythm research in animal models and retrospective analyses of human nutrition data have shown that reduced length of overnight fasting or increased late night eating increases risk for metabolic diseases including obesity and diabetes. However, the daily rhythm in eating pattern in humans is rarely measured. Traditional methods to collect nutrition information through food diary and food log pay little attention to the timing of eating which may also change from day to day. We adopted a novel cell-phone based approach to longitudinally record all events of food and beverage intake in adults. In a feasibility study daily food-eating patterns of 93 healthy individuals were recorded for 21 days using camera phones. Analysis of the daily eating patterns of these individuals indicates deviation from conventional assumption that people eat three meals-a-day within a 12 h interval. We found that eating events are widespread throughout the day, with 30% consumed in evening and late night hours. There was little difference in eating pattern between weekdays and weekends. In this cohort more than 50% of people spread their caloric intake events over 15 h or longer. One decile of the cohort who were spouses of shift-workers or had flexible work schedule spread their caloric intake over 20 h. Although the nutrition quality and diversity of food consumed is different between South-East Asian and Western countries, such overall disruption of daily eating-fasting rhythm is similar. Therefore, in view of hypothesis that disrupted daily eating pattern may contribute to the global increase in metabolic diseases and modification of daily eating pattern is a potential modifiable behavior to contain these diseases, monitoring eating pattern is an important aspect of lifestyle.

A camera-phone based study reveals erratic eating pattern and disrupted daily eating-fasting cycle among adults in India.

Science.gov (United States)

Gupta, Neelu Jain; Kumar, Vinod; Panda, Satchidananda

2017-01-01

The daily rhythm of feeding-fasting and meal-timing are emerging as important determinants of health. Circadian rhythm research in animal models and retrospective analyses of human nutrition data have shown that reduced length of overnight fasting or increased late night eating increases risk for metabolic diseases including obesity and diabetes. However, the daily rhythm in eating pattern in humans is rarely measured. Traditional methods to collect nutrition information through food diary and food log pay little attention to the timing of eating which may also change from day to day. We adopted a novel cell-phone based approach to longitudinally record all events of food and beverage intake in adults. In a feasibility study daily food-eating patterns of 93 healthy individuals were recorded for 21 days using camera phones. Analysis of the daily eating patterns of these individuals indicates deviation from conventional assumption that people eat three meals-a-day within a 12 h interval. We found that eating events are widespread throughout the day, with 30% consumed in evening and late night hours. There was little difference in eating pattern between weekdays and weekends. In this cohort more than 50% of people spread their caloric intake events over 15 h or longer. One decile of the cohort who were spouses of shift-workers or had flexible work schedule spread their caloric intake over 20 h. Although the nutrition quality and diversity of food consumed is different between South-East Asian and Western countries, such overall disruption of daily eating-fasting rhythm is similar. Therefore, in view of hypothesis that disrupted daily eating pattern may contribute to the global increase in metabolic diseases and modification of daily eating pattern is a potential modifiable behavior to contain these diseases, monitoring eating pattern is an important aspect of lifestyle.

Adaptive Human aware Navigation based on Motion Pattern Analysis

DEFF Research Database (Denmark)

Tranberg, Søren; Svenstrup, Mikael; Andersen, Hans Jørgen

2009-01-01

Respecting people’s social spaces is an important prerequisite for acceptable and natural robot navigation in human environments. In this paper, we describe an adaptive system for mobile robot navigation based on estimates of whether a person seeks to interact with the robot or not. The estimates...... are based on run-time motion pattern analysis compared to stored experience in a database. Using a potential field centered around the person, the robot positions itself at the most appropriate place relative to the person and the interaction status. The system is validated through qualitative tests...

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

Science.gov (United States)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

Optimizing pattern recognition-based control for partial-hand prosthesis application.

Science.gov (United States)

Earley, Eric J; Adewuyi, Adenike A; Hargrove, Levi J

2014-01-01

Partial-hand amputees often retain good residual wrist motion, which is essential for functional activities involving use of the hand. Thus, a crucial design criterion for a myoelectric, partial-hand prosthesis control scheme is that it allows the user to retain residual wrist motion. Pattern recognition (PR) of electromyographic (EMG) signals is a well-studied method of controlling myoelectric prostheses. However, wrist motion degrades a PR system's ability to correctly predict hand-grasp patterns. We studied the effects of (1) window length and number of hand-grasps, (2) static and dynamic wrist motion, and (3) EMG muscle source on the ability of a PR-based control scheme to classify functional hand-grasp patterns. Our results show that training PR classifiers with both extrinsic and intrinsic muscle EMG yields a lower error rate than training with either group by itself (pgrasps available to the classifier significantly decrease classification error (pgrasp.

Seasonal Differences in Determinants of Time Location Patterns in an Urban Population: A Large Population-Based Study in Korea.

Science.gov (United States)

Lee, Sewon; Lee, Kiyoung

2017-06-22

Time location patterns are a significant factor for exposure assessment models of air pollutants. Factors associated with time location patterns in urban populations are typically due to high air pollution levels in urban areas. The objective of this study was to determine the seasonal differences in time location patterns in two urban cities. A Time Use Survey of Korean Statistics (KOSTAT) was conducted in the summer, fall, and winter of 2014. Time location data from Seoul and Busan were collected, together with demographic information obtained by diaries and questionnaires. Determinants of the time spent at each location were analyzed by multiple linear regression and the stepwise method. Seoul and Busan participants had similar time location profiles over the three seasons. The time spent at own home, other locations, workplace/school and during walk were similar over the three seasons in both the Seoul and Busan participants. The most significant time location pattern factors were employment status, age, gender, monthly income, and spouse. Season affected the time spent at the workplace/school and other locations in the Seoul participants, but not in the Busan participants. The seasons affected each time location pattern of the urban population slightly differently, but overall there were few differences.

Seasonal Differences in Determinants of Time Location Patterns in an Urban Population: A Large Population-Based Study in Korea

Directory of Open Access Journals (Sweden)

Sewon Lee

2017-06-01

Full Text Available Time location patterns are a significant factor for exposure assessment models of air pollutants. Factors associated with time location patterns in urban populations are typically due to high air pollution levels in urban areas. The objective of this study was to determine the seasonal differences in time location patterns in two urban cities. A Time Use Survey of Korean Statistics (KOSTAT was conducted in the summer, fall, and winter of 2014. Time location data from Seoul and Busan were collected, together with demographic information obtained by diaries and questionnaires. Determinants of the time spent at each location were analyzed by multiple linear regression and the stepwise method. Seoul and Busan participants had similar time location profiles over the three seasons. The time spent at own home, other locations, workplace/school and during walk were similar over the three seasons in both the Seoul and Busan participants. The most significant time location pattern factors were employment status, age, gender, monthly income, and spouse. Season affected the time spent at the workplace/school and other locations in the Seoul participants, but not in the Busan participants. The seasons affected each time location pattern of the urban population slightly differently, but overall there were few differences.

The role of the ventral dentate gyrus in olfactory pattern separation.

Science.gov (United States)

Weeden, Christy S S; Hu, Nathan J; Ho, Liana U N; Kesner, Raymond P

2014-05-01

Dorsoventral lesion studies of the hippocampus have indicated that the dorsal axis of the hippocampus is important for spatial processing and the ventral axis of the hippocampus is important for olfactory learning and memory and anxiety. There is some evidence to suggest that the ventral CA3 and ventral CA1 conduct parallel processes for pattern completion and temporal processing, respectively. Studies have indicated that the dorsal dentate gyrus (DG) is importantly involved in processes reflecting underlying pattern separation activity for spatial information. However, the ventral DG is less understood. The current study investigated the less-understood role of the ventral DG in olfactory pattern separation. A series of odor stimuli that varied on only one level, number of carbon chains (methyl groups), was used in a matching-to-sample paradigm in order to investigate ventral DG involvement in working memory for similar and less similar odors. Rats with ventral DG lesions were impaired at delays of 60 sec, but not at delays of 15 sec. A memory-based pattern separation effect was observed performance was poorest with only one carbon chain separation between trial odors and was highest for trials with four separations. The present study indicates that the ventral DG plays an important role in olfactory learning and memory processes for highly similar odors. The results also indicate a role for the ventral DG in pattern separation for odor information, which may have further implications for parallel processing across the dorsoventral axis for the DG in spatial (dorsal) and olfactory (ventral) pattern separation. Copyright © 2014 Wiley Periodicals, Inc.

Patterns of malaria related mortality based on verbal autopsy in ...

African Journals Online (AJOL)

Patterns of malaria related mortality based on verbal autopsy in Muleba District, north-western Tanzania. G.M Kaatano, F.M Mashauri, S.M Kinung'hi, J.R Mwanga, R.C Malima, C Kishamawe, S.E Nnko, S.M Magesa, L.E.G Mboera ...

Threshold Research on Highway Length under Typical Landscape Patterns Based on Drivers’ Physiological Performance

Directory of Open Access Journals (Sweden)

Xia Zhao

2015-01-01

Full Text Available The appropriately landscaped highway scenes may not only help improve road safety and comfort but also help protect ecological environment. Yet there is very little research data on highway length threshold with consideration of distinctive landscape patterns. Against this backdrop, the paper aims to quantitatively analyze highway landscape’s effect on driving behavior based on drivers’ physiological performance and quantify highway length thresholds under three typical landscape patterns, namely, “open,” “semiopen,” and “vertical” ones. The statistical analysis was based on data collected in a driving simulator and electrocardiograph. Specifically, vehicle-related data, ECG data, and supplemental subjective stress perception were collected. The study extracted two characteristic indices, lane deviation and LF/HF, and extrapolated the drivers’ U-shaped physiological response to landscape patterns. Models on highway length were built based on LF/HF’s variation trend with highway length. The results revealed that the theoretical highway length threshold tended to increase when the landscape pattern was switched to open, semiopen, and vertical ones. And the reliability and accuracy of the results were validated by questionnaires and field operational tests. Findings from this research will assist practitioners in taking active environmental countermeasures pertaining to different roadside landscape patterns.

Using register data to deduce patterns of social exchange.

Science.gov (United States)

Jansson, Fredrik

2017-07-01

This paper presents a novel method for deducting propensities for social exchange between individuals based on the choices they make, and based on factors such as country of origin, sex, school grades and socioeconomic background. The objective here is to disentangle the effect of social ties from the other factors, in order to find patterns of social exchange. This is done through a control-treatment design on analysing available data, where the 'treatment' is similarity of choices between socially connected individuals, and the control is similarity of choices between non-connected individuals. Structural dependencies are controlled for and effects from different classes are pooled through a mix of methods from network and meta-analysis. The method is demonstrated and tested on Swedish register data on students at upper secondary school. The results show that having similar grades is a predictor of social exchange. Also, previous results from Norwegian data are replicated, showing that students cluster based on country of origin.

CodonLogo: a sequence logo-based viewer for codon patterns.

Science.gov (United States)

Sharma, Virag; Murphy, David P; Provan, Gregory; Baranov, Pavel V

2012-07-15

Conserved patterns across a multiple sequence alignment can be visualized by generating sequence logos. Sequence logos show each column in the alignment as stacks of symbol(s) where the height of a stack is proportional to its informational content, whereas the height of each symbol within the stack is proportional to its frequency in the column. Sequence logos use symbols of either nucleotide or amino acid alphabets. However, certain regulatory signals in messenger RNA (mRNA) act as combinations of codons. Yet no tool is available for visualization of conserved codon patterns. We present the first application which allows visualization of conserved regions in a multiple sequence alignment in the context of codons. CodonLogo is based on WebLogo3 and uses the same heuristics but treats codons as inseparable units of a 64-letter alphabet. CodonLogo can discriminate patterns of codon conservation from patterns of nucleotide conservation that appear indistinguishable in standard sequence logos. The CodonLogo source code and its implementation (in a local version of the Galaxy Browser) are available at http://recode.ucc.ie/CodonLogo and through the Galaxy Tool Shed at http://toolshed.g2.bx.psu.edu/.

Diversity patterns and freshwater molluscs similarities in small water reservoirs

Directory of Open Access Journals (Sweden)

Tomáš Čejka

2011-02-01

Full Text Available The survey presents the molluscan fauna from six impoundment systems of two sides (NW and SE of the Small Carpathians. Altogether 25 species (15 gastropod and 10 bivalve species were identified in reservoirs and their subsystems (inflows and outlets. The number of species per site ranged from 2 to 12, the mean number of species per site was 7. The mean number of individuals per site ranged from 15 to 905 (mean 174 ind/m2. Radix auricularia, R. ovata, Gyraulus albus, Gyraulus parvus/laevis, Hippeutis complanatus and Pisidium casertanum were present in more than 50% of reservoirs. The most abundant and frequent species in the entire area and all subsystems were Pisidium casertanum, Pisidium subtruncatum and Gyraulus parvus/laevis. Faunistic similarity indices indicate moderate degree of beta diversity i.e., differentiation among the sites; good separation of sites by cluster analysis indicates a different composition among inflows/outlets and littoral molluscan faunas of reservoirs.

Research on CPFR pattern of the Internet of things based on B2C

Science.gov (United States)

Zhou, Ling; Yang, Jie

2013-03-01

The CPFR pattern proposed by this article is based on the internet of things platform, using frontier technology of internet of things to realize real-time monitoring and the feedback in logistics, information stream in B2C mode, and simultaneously construct an e-business mode which takes the customer guidance as the center to be possible to meet the customers' need and realize the service made by customer. This new pattern uses the coordination, plan, prediction and replenishment of CPFR to realize custom-made stock based on B2C for terminal customer and specialized service for commodity stock. Moreover, it can bring suppliers real-time monitoring of terminal logistics, storage and users' notes for use, and feed back users' bugs, adjustment of orders and plan of replenishment. Furthermore, based on new pattern, we can data min users' interests and undertake a study in increment modeling, process reengineering in enterprise, optimizing enterprise's interior resources and conformity industry of supply chain. Above all it provides a new mentality and the operation pattern for the electronic commerce marketing.

Research on electric and thermal characteristics of plasma torch based on similarity theory

International Nuclear Information System (INIS)

Cheng Changming; Tang Deli; Lan Wei

2007-01-01

Configuration and working principle of a DC non-transferred plasma torch have been introduced. Based on similarity theory, connections between the electric-thermal characteristics and operational parameter such as flowing gas rate and arc power have been investigated. Calculation and experiment are compared. The results indicate that the calculation results are in agreement with experimental ones. The formulas can be used for plasma torch improvement and optimization. (authors)

Holographic images reconstructed from GMR-based fringe pattern

Directory of Open Access Journals (Sweden)

Kikuchi Hiroshi

2013-01-01

Full Text Available We have developed a magneto-optical spatial light modulator (MOSLM using giant magneto-resistance (GMR structures for realizing a holographic three-dimensional (3D display. For practical applications, reconstructed image of hologram consisting of GMR structures should be investigated in order to study the feasibility of the MOSLM. In this study, we fabricated a hologram with GMR based fringe-pattern and demonstrated a reconstructed image. A fringe-pattern convolving a crossshaped image was calculated by a conventional binary computer generated hologram (CGH technique. The CGH-pattern has 2,048 × 2,048 with 5 μm pixel pitch. The GMR stack consists of a Tb-Fe-Co/CoFe pinned layer, a Ag spacer, a Gd-Fe free layer for light modulation, and a Ru capping layer, was deposited by dc-magnetron sputtering. The GMR hologram was formed using photo-lithography and Krion milling processes, followed by the deposition of a Tb-Fe-Co reference layer with large coercivity and the same Kerr-rotation angle compared to the free layer, and a lift-off process. The reconstructed image of the ON-state was clearly observed and successfully distinguished from the OFF-state by switching the magnetization direction of the free-layer with an external magnetic field. These results indicate the possibility of realizing a holographic 3D display by the MOSLM using the GMR structures.

Three dimensional pattern recognition using feature-based indexing and rule-based search

Science.gov (United States)

Lee, Jae-Kyu

In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size

Fast protein tertiary structure retrieval based on global surface shape similarity.

Science.gov (United States)

Sael, Lee; Li, Bin; La, David; Fang, Yi; Ramani, Karthik; Rustamov, Raif; Kihara, Daisuke

2008-09-01

Characterization and identification of similar tertiary structure of proteins provides rich information for investigating function and evolution. The importance of structure similarity searches is increasing as structure databases continue to expand, partly due to the structural genomics projects. A crucial drawback of conventional protein structure comparison methods, which compare structures by their main-chain orientation or the spatial arrangement of secondary structure, is that a database search is too slow to be done in real-time. Here we introduce a global surface shape representation by three-dimensional (3D) Zernike descriptors, which represent a protein structure compactly as a series expansion of 3D functions. With this simplified representation, the search speed against a few thousand structures takes less than a minute. To investigate the agreement between surface representation defined by 3D Zernike descriptor and conventional main-chain based representation, a benchmark was performed against a protein classification generated by the combinatorial extension algorithm. Despite the different representation, 3D Zernike descriptor retrieved proteins of the same conformation defined by combinatorial extension in 89.6% of the cases within the top five closest structures. The real-time protein structure search by 3D Zernike descriptor will open up new possibility of large-scale global and local protein surface shape comparison. 2008 Wiley-Liss, Inc.

Realization of spin-dependent splitting with arbitrary intensity patterns based on all-dielectric metasurfaces

Energy Technology Data Exchange (ETDEWEB)

Ke, Yougang; Liu, Yachao; He, Yongli; Zhou, Junxiao; Luo, Hailu, E-mail: hailuluo@hnu.edu.cn; Wen, Shuangchun [Laboratory for Spin Photonics, School of Physics and Electronics, Hunan University, Changsha 410082 (China)

2015-07-27

We report the realization of spin-dependent splitting with arbitrary intensity patterns based on all-dielectric metasurfaces. Compared with the plasmonic metasurfaces, the all-dielectric metasurface exhibits more high transmission efficiency and conversion efficiency, which makes it possible to achieve the spin-dependent splitting with arbitrary intensity patterns. Our findings suggest a way for generation and manipulation of spin photons, and thereby offer the possibility of developing spin-based nanophotonic applications.

Dimensionality Reduction of Hyperspectral Image with Graph-Based Discriminant Analysis Considering Spectral Similarity

Directory of Open Access Journals (Sweden)

Fubiao Feng

2017-03-01

Full Text Available Recently, graph embedding has drawn great attention for dimensionality reduction in hyperspectral imagery. For example, locality preserving projection (LPP utilizes typical Euclidean distance in a heat kernel to create an affinity matrix and projects the high-dimensional data into a lower-dimensional space. However, the Euclidean distance is not sufficiently correlated with intrinsic spectral variation of a material, which may result in inappropriate graph representation. In this work, a graph-based discriminant analysis with spectral similarity (denoted as GDA-SS measurement is proposed, which fully considers curves changing description among spectral bands. Experimental results based on real hyperspectral images demonstrate that the proposed method is superior to traditional methods, such as supervised LPP, and the state-of-the-art sparse graph-based discriminant analysis (SGDA.

LDA-Based Unified Topic Modeling for Similar TV User Grouping and TV Program Recommendation.

Science.gov (United States)

Pyo, Shinjee; Kim, Eunhui; Kim, Munchurl

2015-08-01

Social TV is a social media service via TV and social networks through which TV users exchange their experiences about TV programs that they are viewing. For social TV service, two technical aspects are envisioned: grouping of similar TV users to create social TV communities and recommending TV programs based on group and personal interests for personalizing TV. In this paper, we propose a unified topic model based on grouping of similar TV users and recommending TV programs as a social TV service. The proposed unified topic model employs two latent Dirichlet allocation (LDA) models. One is a topic model of TV users, and the other is a topic model of the description words for viewed TV programs. The two LDA models are then integrated via a topic proportion parameter for TV programs, which enforces the grouping of similar TV users and associated description words for watched TV programs at the same time in a unified topic modeling framework. The unified model identifies the semantic relation between TV user groups and TV program description word groups so that more meaningful TV program recommendations can be made. The unified topic model also overcomes an item ramp-up problem such that new TV programs can be reliably recommended to TV users. Furthermore, from the topic model of TV users, TV users with similar tastes can be grouped as topics, which can then be recommended as social TV communities. To verify our proposed method of unified topic-modeling-based TV user grouping and TV program recommendation for social TV services, in our experiments, we used real TV viewing history data and electronic program guide data from a seven-month period collected by a TV poll agency. The experimental results show that the proposed unified topic model yields an average 81.4% precision for 50 topics in TV program recommendation and its performance is an average of 6.5% higher than that of the topic model of TV users only. For TV user prediction with new TV programs, the average

Quantum beating patterns observed in the energetics of Pb film nanostructures

International Nuclear Information System (INIS)

Czoschke, P.; Basile, L.; Chiang, T.-C.; Hong, Hawoong

2004-01-01

We have studied the nanoscale structural evolution of Pb films grown at 110 K on a Si(111) substrate as they are annealed to increasingly higher temperatures. Surface x-ray diffraction from a synchrotron source is used to observe the morphology evolve from an initial smooth film through various metastable states before reaching a state of local equilibrium, at which point the coverage of different height Pb structures is analyzed and related to the thickness-dependent surface energy. Rich patterns are seen in the resulting energy landscape similar to the beating patterns heard from the interference of two musical notes of similar pitch. The explanation is, however, very simple, as demonstrated by a model calculation based on the confinement of free electrons to a quantum well

Mapping Rice Cropping Systems in Vietnam Using an NDVI-Based Time-Series Similarity Measurement Based on DTW Distance

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Xudong Guan

2016-01-01

Full Text Available Normalized Difference Vegetation Index (NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS time-series data has been widely used in the fields of crop and rice classification. The cloudy and rainy weather characteristics of the monsoon season greatly reduce the likelihood of obtaining high-quality optical remote sensing images. In addition, the diverse crop-planting system in Vietnam also hinders the comparison of NDVI among different crop stages. To address these problems, we apply a Dynamic Time Warping (DTW distance-based similarity measure approach and use the entire yearly NDVI time series to reduce the inaccuracy of classification using a single image. We first de-noise the NDVI time series using S-G filtering based on the TIMESAT software. Then, a standard NDVI time-series base for rice growth is established based on field survey data and Google Earth sample data. NDVI time-series data for each pixel are constructed and the DTW distance with the standard rice growth NDVI time series is calculated. Then, we apply thresholds to extract rice growth areas. A qualitative assessment using statistical data and a spatial assessment using sampled data from the rice-cropping map reveal a high mapping accuracy at the national scale between the statistical data, with the corresponding R2 being as high as 0.809; however, the mapped rice accuracy decreased at the provincial scale due to the reduced number of rice planting areas per province. An analysis of the results indicates that the 500-m resolution MODIS data are limited in terms of mapping scattered rice parcels. The results demonstrate that the DTW-based similarity measure of the NDVI time series can be effectively used to map large-area rice cropping systems with diverse cultivation processes.

A Self-Organizing Map-Based Approach to Generating Reduced-Size, Statistically Similar Climate Datasets

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Cabell, R.; Delle Monache, L.; Alessandrini, S.; Rodriguez, L.

2015-12-01

Climate-based studies require large amounts of data in order to produce accurate and reliable results. Many of these studies have used 30-plus year data sets in order to produce stable and high-quality results, and as a result, many such data sets are available, generally in the form of global reanalyses. While the analysis of these data lead to high-fidelity results, its processing can be very computationally expensive. This computational burden prevents the utilization of these data sets for certain applications, e.g., when rapid response is needed in crisis management and disaster planning scenarios resulting from release of toxic material in the atmosphere. We have developed a methodology to reduce large climate datasets to more manageable sizes while retaining statistically similar results when used to produce ensembles of possible outcomes. We do this by employing a Self-Organizing Map (SOM) algorithm to analyze general patterns of meteorological fields over a regional domain of interest to produce a small set of "typical days" with which to generate the model ensemble. The SOM algorithm takes as input a set of vectors and generates a 2D map of representative vectors deemed most similar to the input set and to each other. Input predictors are selected that are correlated with the model output, which in our case is an Atmospheric Transport and Dispersion (T&D) model that is highly dependent on surface winds and boundary layer depth. To choose a subset of "typical days," each input day is assigned to its closest SOM map node vector and then ranked by distance. Each node vector is treated as a distribution and days are sampled from them by percentile. Using a 30-node SOM, with sampling every 20th percentile, we have been able to reduce 30 years of the Climate Forecast System Reanalysis (CFSR) data for the month of October to 150 "typical days." To estimate the skill of this approach, the "Measure of Effectiveness" (MOE) metric is used to compare area and overlap

Activation analysis. A basis for chemical similarity and classification

Energy Technology Data Exchange (ETDEWEB)

Beeck, J OP de [Ghent Rijksuniversiteit (Belgium). Instituut voor Kernwetenschappen

1977-01-01

It is shown that activation analysis is especially suited to serve as a basis for determining the chemical similarity between samples defined by their trace-element concentration patterns. The general problem of classification and identification is discussed. The nature of possible classification structures and their appropriate clustering strategies is considered. A practical computer method is suggested and its application as well as the graphical representation of classification results are given. The possibility for classification using information theory is mentioned. Classification of chemical elements is discussed and practically realized after Hadamard transformation of the concentration variation patterns in a series of samples.

Is there an association between food patterns and life satisfaction among Norway's inhabitants ages 65 years and older?

Science.gov (United States)

André, Beate; Canhão, Helena; Espnes, Geir A; Ferreira Rodrigues, Ana Maria; Gregorio, Maria João; Nguyen, Camilla; Sousa, Rute; Grønning, Kjersti

2017-03-01

The lack of information regarding older adults' health and lifestyles makes it difficult to design suitable interventions for people at risk of developing unhealth lifestyles. Therefore, there is a need to increase knowledge about older adults' food patterns and quality of life. Our aim was to determine associations among food patterns, anxiety, depression, and life satisfaction in Norwegian inhabitants ages 65+. The Nord-Trøndelag Health Study (The HUNT Study) is a large, population-based cohort study that includes data for 125 000 Norwegian participants. The cohort used for this study is wave three of the study, consisting of 11 619 participants age 65 and over. Cluster analysis was used to categorize the participants based on similarities in food consumption; two clusters were identified based on similarities regarding food consumption among participants. Significant differences between the clusters were found, as participants in the healthy food-patterns cluster had higher life satisfaction and lower anxiety and depression than those in the unhealthy food-patterns cluster. The associations among food patterns, anxiety, depression, and life satisfaction among older adults show the need for increased focus on interactions among food patterns, food consumption, and life satisfaction among the elderly in order to explore how society can influence these patterns. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

It's about time: a comparison of Canadian and American time-activity patterns.

Science.gov (United States)

Leech, Judith A; Nelson, William C; Burnett, Richard T; Aaron, Shawn; Raizenne, Mark E

2002-11-01

This study compares two North American time-activity data bases: the National Human Activity Pattern Survey (NHAPS) of 9386 interviewees in 1992-1994 in the continental USA with the Canadian Human Activity Pattern Survey (CHAPS) of 2381 interviewees in 1996-1997 in four major Canadian cities. Identical surveys and methodology were used to collect this data: random sample telephone selection within the identified telephone exchanges, computer-assisted telephone interviews, overselection of children and weekends in the 24-h recall diary and the same interviewers. Very similar response rates were obtained: 63% (NHAPS) and 64.5% (CHAPS). Results of comparisons by age within major activity and location groups suggest activity and location patterns are very similar (most differences being less than 1% or 14 min in a 24-h day) with the exception of seasonal differences. Canadians spend less time outdoors in winter and less time indoors in summer than their U.S. counterparts. When exposure assessments use time of year or outdoor/indoor exposure gradients, these differences may result in significant differences in exposure assessments. Otherwise, the 24-h time activity patterns of North Americans are remarkably similar and use of the combined data set for some exposure assessments may be feasible.

Multilayered epithelium in a rat model and human Barrett's esophagus: Similar expression patterns of transcription factors and differentiation markers

Directory of Open Access Journals (Sweden)

Yang Chung S

2008-01-01

Full Text Available Abstract Background In rats, esophagogastroduodenal anastomosis (EGDA without concomitant chemical carcinogen treatment leads to gastroesophageal reflux disease, multilayered epithelium (MLE, a presumed precursor in intestinal metaplasia, columnar-lined esophagus, dysplasia, and esophageal adenocarcinoma. Previously we have shown that columnar-lined esophagus in EGDA rats resembled human Barrett's esophagus (BE in its morphology, mucin features and expression of differentiation markers (Lab. Invest. 2004;84:753–765. The purpose of this study was to compare the phenotype of rat MLE with human MLE, in order to gain insight into the nature of MLE and its potential role in the development of BE. Methods Serial sectioning was performed on tissue samples from 32 EGDA rats and 13 patients with established BE. Tissue sections were immunohistochemically stained for a variety of transcription factors and differentiation markers of esophageal squamous epithelium and intestinal columnar epithelium. Results We detected MLE in 56.3% (18/32 of EGDA rats, and in all human samples. As expected, both rat and human squamous epithelium, but not intestinal metaplasia, expressed squamous transcription factors and differentiation markers (p63, Sox2, CK14 and CK4 in all cases. Both rat and human intestinal metaplasia, but not squamous epithelium, expressed intestinal transcription factors and differentiation markers (Cdx2, GATA4, HNF1α, villin and Muc2 in all cases. Rat MLE shared expression patterns of Sox2, CK4, Cdx2, GATA4, villin and Muc2 with human MLE. However, p63 and CK14 were expressed in a higher proportion of rat MLE compared to humans. Conclusion These data indicate that rat MLE shares similar properties to human MLE in its expression pattern of these markers, not withstanding small differences, and support the concept that MLE may be a transitional stage in the metaplastic conversion of squamous to columnar epithelium in BE.

Similarity score computation for minutiae-based fingerprint recognition

CSIR Research Space (South Africa)

Khanyile, NP

2014-09-01

Full Text Available This paper identifies and analyses the factors that contribute to the similarity between two sets of minutiae points as well as the probability that two sets of minutiae points were extracted from fingerprints of the same finger. Minutiae...

Neutrosophic Cubic MCGDM Method Based on Similarity Measure

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Surapati Pramanik

2017-06-01

Full Text Available The notion of neutrosophic cubic set is originated from the hybridization of the concept of neutrosophic set and interval valued neutrosophic set. We define similarity measure for neutrosophic cubic sets and prove some of its basic properties.

Inferring biodiversity maintenance mechanisms from ecological pattern

Science.gov (United States)

Ostling, Annette

Among a set of competitors for a single common resource, the best will simply exclude the others. Yet in nature we can see astounding diversity of competing species. Do close similarities in species' response to the local environment primarily explain their coexistence? Or is this diversity possible because of differences between species that stabilize their coexistence? And if so, what particular differences between species are important in particular communities? Some ecological communities lend themselves to experimental manipulation to begin to answer these questions. Yet for many other communities, such as tree species in forests, the logistical hurdles to this approach are daunting. Faster progress could be made in ecology if insight into biodiversity maintenance mechanisms could be gained from patterns exhibited in local ecological communities, such as how coexisting species are distributed in their ecological traits and relative abundance. Hurdles that we need to overcome to be able to gain such insight include: 1) further developing neutral theory, a quantitative process-based null model of community pattern resulting when species similarities are what allow their coexistence, and 2) better understanding what patterns to expect when species differences dominate instead, particularly in the context of stochasticity and immigration. I will describe our ongoing research to overcome these hurdles, to provide better tools for analyzing observed pattern. National Science Foundation Advancing Theory in Biology Grant 1038678, Danish National Research Foundation Grant DNRF 96 for the Center of Macroecology, Evolution and Climate.

Type 2 Diabetes Mellitus Treatment Patterns Across Europe: A Population-based Multi-database Study.

Science.gov (United States)

Overbeek, Jetty A; Heintjes, Edith M; Prieto-Alhambra, Daniel; Blin, Patrick; Lassalle, Régis; Hall, Gillian C; Lapi, Francesco; Bianchini, Elisa; Hammar, Niklas; Bezemer, Irene D; Herings, Ron M C

2017-04-01

The aim of this study was to determine the similarities and differences of type 2 diabetes mellitus (T2DM) treatment patterns in daily practice in 5 European countries and whether these reflect differences in guidelines. Prescriptions for drugs used in diabetes treatment during a 5-year study period were obtained from electronic databases. Patients initiating T2DM treatment during the study period were included. An SAS analysis tool was developed to create episodes of use of drug classes, which resulted in treatment patterns. A total of 253,530 patients initiating T2DM treatment during the study period were included; 52% to 55% were male, and the mean age ranged from 62 to 67 years. Metformin was the most common initial treatment in all countries. After initial therapy, most patients in the Netherlands, Spain, and the United Kingdom switched to a combination of metformin + a sulfonylurea derivative (SU). In Italy, metformin in combination with an SU was outnumbered by "other treatment," mainly because of repaglinide use. In France, treatments including dipeptidyl peptidase-4 inhibitors were most frequent as second- and fourth-line treatment. Metformin monotherapy was again most commonly observed as the third line of treatment in all countries. Fourth treatment was a combination of metformin + an SU in the Netherlands and Spain; in the United Kingdom and France, dipeptidyl peptidase-4 inhibitors were the most frequently used fourth line of treatment. This study provides a comprehensive overview of T2DM treatment patterns among patients initiating T2DM treatment in 5 European countries. There were differences, especially regarding the uptake of newer incretin-based treatments, which are usually prescribed as a second and/or third treatment in agreement with local guidelines. These variations reflect the differences between the national guidelines of these countries. Copyright © 2017 Elsevier HS Journals, Inc. All rights reserved.

A New Similarity Measure of Interval-Valued Intuitionistic Fuzzy Sets Considering Its Hesitancy Degree and Applications in Expert Systems

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Chong Wu

2014-01-01

Full Text Available As an important content in fuzzy mathematics, similarity measure is used to measure the similarity degree between two fuzzy sets. Considering the existing similarity measures, most of them do not consider the hesitancy degree and some methods considering the hesitancy degree are based on the intuitionistic fuzzy sets, intuitionistic fuzzy values. It may cause some counterintuitive results in some cases. In order to make up for the drawback, we present a new approach to construct the similarity measure between two interval-valued intuitionistic fuzzy sets using the entropy measure and considering the hesitancy degree. In particular, the proposed measure was demonstrated to yield a similarity measure. Besides, some examples are given to prove the practicality and effectiveness of the new measure. We also apply the similarity measure to expert system to solve the problems on pattern recognition and the multicriteria group decision making. In these examples, we also compare it with existing methods such as other similarity measures and the ideal point method.

Patterns of care in radiation therapy of adenocarcinoma of the endometrium

International Nuclear Information System (INIS)

Luk, K.H.; Fuller, D.E.; Kramer, S.; Davis, L.W.; Herring, D.F.; Delclos, L.; Dobelbower, R.R.; Lustig, R.

1980-01-01

In 1974 the Patterns of Care Study began investigating radiation therapy of endometrial cancers in the United States. This endeavor required development of a methodology to survey the care of patients who had similar disease and who were treated at various institutions. Analysis of 919 questionnaires revealed a substantial difference nationwide in treatment approaches to this site. Outcome studies and ongoing research projects, combined with this survey of Patterns of Care, can provide a sound base for educational efforts to improve patient care

Self-similar factor approximants

International Nuclear Information System (INIS)

Gluzman, S.; Yukalov, V.I.; Sornette, D.

2003-01-01

The problem of reconstructing functions from their asymptotic expansions in powers of a small variable is addressed by deriving an improved type of approximants. The derivation is based on the self-similar approximation theory, which presents the passage from one approximant to another as the motion realized by a dynamical system with the property of group self-similarity. The derived approximants, because of their form, are called self-similar factor approximants. These complement the obtained earlier self-similar exponential approximants and self-similar root approximants. The specific feature of self-similar factor approximants is that their control functions, providing convergence of the computational algorithm, are completely defined from the accuracy-through-order conditions. These approximants contain the Pade approximants as a particular case, and in some limit they can be reduced to the self-similar exponential approximants previously introduced by two of us. It is proved that the self-similar factor approximants are able to reproduce exactly a wide class of functions, which include a variety of nonalgebraic functions. For other functions, not pertaining to this exactly reproducible class, the factor approximants provide very accurate approximations, whose accuracy surpasses significantly that of the most accurate Pade approximants. This is illustrated by a number of examples showing the generality and accuracy of the factor approximants even when conventional techniques meet serious difficulties

Topographic deformation patterns of knee cartilage after exercises with high knee flexion: an in vivo 3D MRI study using voxel-based analysis at 3T

International Nuclear Information System (INIS)

Horng, Annie; Stockinger, M.; Notohamiprodjo, M.; Raya, J.G.; Pietschmann, M.; Hoehne-Hueckstaedt, U.; Glitsch, U.; Ellegast, R.; Hering, K.G.; Glaser, C.

2015-01-01

To implement a novel voxel-based technique to identify statistically significant local cartilage deformation and analyze in-vivo topographic knee cartilage deformation patterns using a voxel-based thickness map approach for high-flexion postures. Sagittal 3T 3D-T1w-FLASH-WE-sequences of 10 healthy knees were acquired before and immediately after loading (kneeling/squatting/heel sitting/knee bends). After cartilage segmentation, 3D-reconstruction and 3D-registration, colour-coded deformation maps were generated by voxel-based subtraction of loaded from unloaded datasets to visualize cartilage thickness changes in all knee compartments. Compression areas were found bifocal at the peripheral medial/caudolateral patella, both posterior femoral condyles and both anterior/central tibiae. Local cartilage thickening were found adjacent to the compression areas. Significant local strain ranged from +13 to -15 %. Changes were most pronounced after squatting, least after knee bends. Shape and location of deformation areas varied slightly with the loading paradigm, but followed a similar pattern consistent between different individuals. Voxel-based deformation maps identify individual in-vivo load-specific and posture-associated strain distribution in the articular cartilage. The data facilitate understanding individual knee loading properties and contribute to improve biomechanical 3 models. They lay a base to investigate the relationship between cartilage degeneration patterns in common osteoarthritis and areas at risk of cartilage wear due to mechanical loading in work-related activities. (orig.)

Topographic deformation patterns of knee cartilage after exercises with high knee flexion: an in vivo 3D MRI study using voxel-based analysis at 3T

Energy Technology Data Exchange (ETDEWEB)

Horng, Annie; Stockinger, M.; Notohamiprodjo, M. [Ludwig-Maximilians-University Hospital Munich, Institute for Clinical Radiology, Munich (Germany); Raya, J.G. [New York University Langone Medical Center, Center for Biomedical Imaging, New York, NY (United States); Pietschmann, M. [Ludwig-Maximilians-University Hospital Munich, Department of Orthopedic Surgery, Munich (Germany); Hoehne-Hueckstaedt, U.; Glitsch, U.; Ellegast, R. [Institute for Occupational Safety and Health of the German Social Accident Insurance (IFA), Sankt Augustin (Germany); Hering, K.G. [Miner' s Hospital, Department of Diagnostic Radiology, Dortmund (Germany); Glaser, C. [Ludwig-Maximilians-University Hospital Munich, Institute for Clinical Radiology, Munich (Germany); RZM Zentrum, Munich (Germany)

2015-06-01

To implement a novel voxel-based technique to identify statistically significant local cartilage deformation and analyze in-vivo topographic knee cartilage deformation patterns using a voxel-based thickness map approach for high-flexion postures. Sagittal 3T 3D-T1w-FLASH-WE-sequences of 10 healthy knees were acquired before and immediately after loading (kneeling/squatting/heel sitting/knee bends). After cartilage segmentation, 3D-reconstruction and 3D-registration, colour-coded deformation maps were generated by voxel-based subtraction of loaded from unloaded datasets to visualize cartilage thickness changes in all knee compartments. Compression areas were found bifocal at the peripheral medial/caudolateral patella, both posterior femoral condyles and both anterior/central tibiae. Local cartilage thickening were found adjacent to the compression areas. Significant local strain ranged from +13 to -15 %. Changes were most pronounced after squatting, least after knee bends. Shape and location of deformation areas varied slightly with the loading paradigm, but followed a similar pattern consistent between different individuals. Voxel-based deformation maps identify individual in-vivo load-specific and posture-associated strain distribution in the articular cartilage. The data facilitate understanding individual knee loading properties and contribute to improve biomechanical 3 models. They lay a base to investigate the relationship between cartilage degeneration patterns in common osteoarthritis and areas at risk of cartilage wear due to mechanical loading in work-related activities. (orig.)

Convenience-based food purchase patterns: identification and associations with dietary quality, sociodemographic factors and attitudes.

Science.gov (United States)

Peltner, Jonas; Thiele, Silke

2018-02-01

The present study aimed to derive food purchase patterns considering the convenience level of foods. Associations between identified patterns and dietary quality were analysed, as well as household characteristics associated with the dietary patterns. A Convenience Food Classification Scheme (CFCS) was developed. After classifying basic food groups into the CFCS, the formed groups were used to apply a factor analysis to identify convenience-based food purchase patterns. For these patterns nutrient and energy densities were examined. Using regression analysis, associations between the adherence to the patterns and household characteristic and attitude variables were analysed. The study used representative German food purchase data from 2011. Approximately 12 million purchases of 13 131 households were recorded in these data. Three convenience-based patterns were identified: a low-convenience, a semi-convenience and a ready-to-eat food pattern. Tighter adherence to the semi-convenience pattern was shown to result in the lowest nutrient and highest energy densities. Important factors influencing adherence to the patterns were household size, presence of children and attitudes. Working full-time was negatively associated with adherence to the low-convenience pattern and positively with the ready-to-eat pattern. Convenience foods were an important part of households' food baskets which in some cases led to lower nutritional quality. Therefore, it is important to offer convenience foods higher in nutrient density and lower in energy density. Interventions targeted on enhancing cooking skills could be an effective strategy to increase purchases of unprocessed foods, which, in turn, could also contribute to an improved diet quality.

Creating Usage Context-Based Object Similarities to Boost Recommender Systems in Technology Enhanced Learning