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

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)

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.

Comparison of computational performance of GA and PSO optimization techniques when designing similar systems - Typical PWR core case

Energy Technology Data Exchange (ETDEWEB)

Souza Lima, Carlos A. [Instituto de Engenharia Nuclear - Divisao de Reatores/PPGIEN, Rua Helio de Almeida 75, Cidade Universitaria - Ilha do Fundao, P.O. Box: 68550 - Zip Code: 21941-972, Rio de Janeiro (Brazil); Instituto Politecnico, Universidade do Estado do Rio de Janeiro, Pos-Graduacao em Modelagem Computacional, Rua Alberto Rangel - s/n, Vila Nova, Nova Friburgo, Zip Code: 28630-050, Nova Friburgo (Brazil); Lapa, Celso Marcelo F.; Pereira, Claudio Marcio do N.A. [Instituto de Engenharia Nuclear - Divisao de Reatores/PPGIEN, Rua Helio de Almeida 75, Cidade Universitaria - Ilha do Fundao, P.O. Box: 68550 - Zip Code: 21941-972, Rio de Janeiro (Brazil); Instituto Nacional de Ciencia e Tecnologia de Reatores Nucleares Inovadores (INCT) (Brazil); Cunha, Joao J. da [Eletronuclear Eletrobras Termonuclear - Gerencia de Analise de Seguranca Nuclear, Rua da Candelaria, 65, 7 andar. Centro, Zip Code: 20091-906, Rio de Janeiro (Brazil); Alvim, Antonio Carlos M. [Universidade Federal do Rio de Janeiro, COPPE/Nuclear, Cidade Universitaria - Ilha do Fundao s/n, P.O.Box 68509 - Zip Code: 21945-970, Rio de Janeiro (Brazil); Instituto Nacional de Ciencia e Tecnologia de Reatores Nucleares Inovadores (INCT) (Brazil)

2011-06-15

Research highlights: > Performance of PSO and GA techniques applied to similar system design. > This work uses ANGRA1 (two loop PWR) core as a prototype. > Results indicate that PSO technique is more adequate than GA to solve this kind of problem. - Abstract: This paper compares the performance of two optimization techniques, particle swarm optimization (PSO) and genetic algorithm (GA) applied to the design a typical reduced scale two loop Pressurized Water Reactor (PWR) core, at full power in single phase forced circulation flow. This comparison aims at analyzing the performance in reaching the global optimum, considering that both heuristics are based on population search methods, that is, methods whose population (candidate solution set) evolve from one generation to the next using a combination of deterministic and probabilistic rules. The simulated PWR, similar to ANGRA 1 power plant, was used as a case example to compare the performance of PSO and GA. Results from simulations indicated that PSO is more adequate to solve this kind of problem.

Gender similarities and differences.

Science.gov (United States)

Hyde, Janet Shibley

2014-01-01

Whether men and women are fundamentally different or similar has been debated for more than a century. This review summarizes major theories designed to explain gender differences: evolutionary theories, cognitive social learning theory, sociocultural theory, and expectancy-value theory. The gender similarities hypothesis raises the possibility of theorizing gender similarities. Statistical methods for the analysis of gender differences and similarities are reviewed, including effect sizes, meta-analysis, taxometric analysis, and equivalence testing. Then, relying mainly on evidence from meta-analyses, gender differences are reviewed in cognitive performance (e.g., math performance), personality and social behaviors (e.g., temperament, emotions, aggression, and leadership), and psychological well-being. The evidence on gender differences in variance is summarized. The final sections explore applications of intersectionality and directions for future research.

Comparison of computational performance of GA and PSO optimization techniques when designing similar systems - Typical PWR core case

International Nuclear Information System (INIS)

Souza Lima, Carlos A.; Lapa, Celso Marcelo F.; Pereira, Claudio Marcio do N.A.; Cunha, Joao J. da; Alvim, Antonio Carlos M.

2011-01-01

Research highlights: → Performance of PSO and GA techniques applied to similar system design. → This work uses ANGRA1 (two loop PWR) core as a prototype. → Results indicate that PSO technique is more adequate than GA to solve this kind of problem. - Abstract: This paper compares the performance of two optimization techniques, particle swarm optimization (PSO) and genetic algorithm (GA) applied to the design a typical reduced scale two loop Pressurized Water Reactor (PWR) core, at full power in single phase forced circulation flow. This comparison aims at analyzing the performance in reaching the global optimum, considering that both heuristics are based on population search methods, that is, methods whose population (candidate solution set) evolve from one generation to the next using a combination of deterministic and probabilistic rules. The simulated PWR, similar to ANGRA 1 power plant, was used as a case example to compare the performance of PSO and GA. Results from simulations indicated that PSO is more adequate to solve this kind of problem.

Usefulness of computerized method for lung nodule detection on digital chest radiographs using similar subtraction images from different patients

International Nuclear Information System (INIS)

Aoki, Takatoshi; Oda, Nobuhiro; Yamashita, Yoshiko; Yamamoto, Keiji; Korogi, Yukunori

2012-01-01

Purpose: The purpose of this study is to evaluate the usefulness of a novel computerized method to select automatically the similar chest radiograph for image subtraction in the patients who have no previous chest radiographs and to assist the radiologists’ interpretation by presenting the “similar subtraction image” from different patients. Materials and methods: Institutional review board approval was obtained, and the requirement for informed patient consent was waived. A large database of approximately 15,000 normal chest radiographs was used for searching similar images of different patients. One hundred images of candidates were selected according to two clinical parameters and similarity of the lung field in the target image. We used the correlation value of chest region in the 100 images for searching the most similar image. The similar subtraction images were obtained by subtracting the similar image selected from the target image. Thirty cases with lung nodules and 30 cases without lung nodules were used for an observer performance test. Four attending radiologists and four radiology residents participated in this observer performance test. Results: The AUC for all radiologists increased significantly from 0.925 to 0.974 with the CAD (P = .004). When the computer output images were available, the average AUC for the residents was more improved (0.960 vs. 0.890) than for the attending radiologists (0.987 vs. 0.960). Conclusion: The novel computerized method for lung nodule detection using similar subtraction images from different patients would be useful to detect lung nodules on digital chest radiographs, especially for less experienced readers.

Comparative analysis of chemical similarity methods for modular natural products with a hypothetical structure enumeration algorithm.

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Skinnider, Michael A; Dejong, Chris A; Franczak, Brian C; McNicholas, Paul D; Magarvey, Nathan A

2017-08-16

Natural products represent a prominent source of pharmaceutically and industrially important agents. Calculating the chemical similarity of two molecules is a central task in cheminformatics, with applications at multiple stages of the drug discovery pipeline. Quantifying the similarity of natural products is a particularly important problem, as the biological activities of these molecules have been extensively optimized by natural selection. The large and structurally complex scaffolds of natural products distinguish their physical and chemical properties from those of synthetic compounds. However, no analysis of the performance of existing methods for molecular similarity calculation specific to natural products has been reported to date. Here, we present LEMONS, an algorithm for the enumeration of hypothetical modular natural product structures. We leverage this algorithm to conduct a comparative analysis of molecular similarity methods within the unique chemical space occupied by modular natural products using controlled synthetic data, and comprehensively investigate the impact of diverse biosynthetic parameters on similarity search. We additionally investigate a recently described algorithm for natural product retrobiosynthesis and alignment, and find that when rule-based retrobiosynthesis can be applied, this approach outperforms conventional two-dimensional fingerprints, suggesting it may represent a valuable approach for the targeted exploration of natural product chemical space and microbial genome mining. Our open-source algorithm is an extensible method of enumerating hypothetical natural product structures with diverse potential applications in bioinformatics.

Improvement of training set structure in fusion data cleaning using Time-Domain Global Similarity method

International Nuclear Information System (INIS)

Liu, J.; Lan, T.; Qin, H.

2017-01-01

Traditional data cleaning identifies dirty data by classifying original data sequences, which is a class-imbalanced problem since the proportion of incorrect data is much less than the proportion of correct ones for most diagnostic systems in Magnetic Confinement Fusion (MCF) devices. When using machine learning algorithms to classify diagnostic data based on class-imbalanced training set, most classifiers are biased towards the major class and show very poor classification rates on the minor class. By transforming the direct classification problem about original data sequences into a classification problem about the physical similarity between data sequences, the class-balanced effect of Time-Domain Global Similarity (TDGS) method on training set structure is investigated in this paper. Meanwhile, the impact of improved training set structure on data cleaning performance of TDGS method is demonstrated with an application example in EAST POlarimetry-INTerferometry (POINT) system.

Methods of Evaluating Performances for Marketing Strategies

OpenAIRE

Ioan Cucu

2005-01-01

There are specific methods for assessing and improving the effectiveness of a marketing strategy. A marketer should state in the marketing plan what a marketing strategy is supposed to accomplish. These statements should set forth performance standards, which usually are stated in terms of profits, sales, or costs. Actual performance must be measured in similar terms so that comparisons are possible. This paper describes sales analysis and cost analysis, two general ways of evaluating the act...

Genomic similarity and kernel methods I: advancements by building on mathematical and statistical foundations.

Science.gov (United States)

Schaid, Daniel J

2010-01-01

Measures of genomic similarity are the basis of many statistical analytic methods. We review the mathematical and statistical basis of similarity methods, particularly based on kernel methods. A kernel function converts information for a pair of subjects to a quantitative value representing either similarity (larger values meaning more similar) or distance (smaller values meaning more similar), with the requirement that it must create a positive semidefinite matrix when applied to all pairs of subjects. This review emphasizes the wide range of statistical methods and software that can be used when similarity is based on kernel methods, such as nonparametric regression, linear mixed models and generalized linear mixed models, hierarchical models, score statistics, and support vector machines. The mathematical rigor for these methods is summarized, as is the mathematical framework for making kernels. This review provides a framework to move from intuitive and heuristic approaches to define genomic similarities to more rigorous methods that can take advantage of powerful statistical modeling and existing software. A companion paper reviews novel approaches to creating kernels that might be useful for genomic analyses, providing insights with examples [1]. Copyright © 2010 S. Karger AG, Basel.

Estimation of Cross-Lingual News Similarities Using Text-Mining Methods

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Zhouhao Wang

2018-01-01

Full Text Available In this research, two estimation algorithms for extracting cross-lingual news pairs based on machine learning from financial news articles have been proposed. Every second, innumerable text data, including all kinds news, reports, messages, reviews, comments, and tweets are generated on the Internet, and these are written not only in English but also in other languages such as Chinese, Japanese, French, etc. By taking advantage of multi-lingual text resources provided by Thomson Reuters News, we developed two estimation algorithms for extracting cross-lingual news pairs from multilingual text resources. In our first method, we propose a novel structure that uses the word information and the machine learning method effectively in this task. Simultaneously, we developed a bidirectional Long Short-Term Memory (LSTM based method to calculate cross-lingual semantic text similarity for long text and short text, respectively. Thus, when an important news article is published, users can read similar news articles that are written in their native language using our method.

Comparing the performance of biomedical clustering methods

DEFF Research Database (Denmark)

Wiwie, Christian; Baumbach, Jan; Röttger, Richard

2015-01-01

expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future......Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene....... This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide...

Renewing the Respect for Similarity

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Shimon eEdelman

2012-07-01

Full Text Available In psychology, the concept of similarity has traditionally evoked a mixture of respect, stemmingfrom its ubiquity and intuitive appeal, and concern, due to its dependence on the framing of the problemat hand and on its context. We argue for a renewed focus on similarity as an explanatory concept, bysurveying established results and new developments in the theory and methods of similarity-preservingassociative lookup and dimensionality reduction — critical components of many cognitive functions, aswell as of intelligent data management in computer vision. We focus in particular on the growing familyof algorithms that support associative memory by performing hashing that respects local similarity, andon the uses of similarity in representing structured objects and scenes. Insofar as these similarity-basedideas and methods are useful in cognitive modeling and in AI applications, they should be included inthe core conceptual toolkit of computational neuroscience.

Face Recognition Performance Improvement using a Similarity Score of Feature Vectors based on Probabilistic Histograms

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SRIKOTE, G.

2016-08-01

Full Text Available This paper proposes an improved performance algorithm of face recognition to identify two face mismatch pairs in cases of incorrect decisions. The primary feature of this method is to deploy the similarity score with respect to Gaussian components between two previously unseen faces. Unlike the conventional classical vector distance measurement, our algorithms also consider the plot of summation of the similarity index versus face feature vector distance. A mixture of Gaussian models of labeled faces is also widely applicable to different biometric system parameters. By comparative evaluations, it has been shown that the efficiency of the proposed algorithm is superior to that of the conventional algorithm by an average accuracy of up to 1.15% and 16.87% when compared with 3x3 Multi-Region Histogram (MRH direct-bag-of-features and Principal Component Analysis (PCA-based face recognition systems, respectively. The experimental results show that similarity score consideration is more discriminative for face recognition compared to feature distance. Experimental results of Labeled Face in the Wild (LFW data set demonstrate that our algorithms are suitable for real applications probe-to-gallery identification of face recognition systems. Moreover, this proposed method can also be applied to other recognition systems and therefore additionally improves recognition scores.

Multi-Scale Scattering Transform in Music Similarity Measuring

Science.gov (United States)

Wang, Ruobai

Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.

Employment of kernel methods on wind turbine power performance assessment

DEFF Research Database (Denmark)

Skrimpas, Georgios Alexandros; Sweeney, Christian Walsted; Marhadi, Kun S.

2015-01-01

A power performance assessment technique is developed for the detection of power production discrepancies in wind turbines. The method employs a widely used nonparametric pattern recognition technique, the kernel methods. The evaluation is based on the trending of an extracted feature from...... the kernel matrix, called similarity index, which is introduced by the authors for the first time. The operation of the turbine and consequently the computation of the similarity indexes is classified into five power bins offering better resolution and thus more consistent root cause analysis. The accurate...

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.

MEASURING THE PERFORMANCE OF SIMILARITY PROPAGATION IN AN SEMANTIC SEARCH ENGINE

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S. K. Jayanthi

2013-10-01

Full Text Available In the current scenario, web page result personalization is playing a vital role. Nearly 80 % of the users expect the best results in the first page itself without having any persistence to browse longer in URL mode. This research work focuses on two main themes: Semantic web search through online and Domain based search through offline. The first part is to find an effective method which allows grouping similar results together using BookShelf Data Structure and organizing the various clusters. The second one is focused on the academic domain based search through offline. This paper focuses on finding documents which are similar and how Vector space can be used to solve it. So more weightage is given for the principles and working methodology of similarity propagation. Cosine similarity measure is used for finding the relevancy among the documents.

Performative Schizoid Method

DEFF Research Database (Denmark)

Svabo, Connie

2016-01-01

is presented and an example is provided of a first exploratory engagement with it. The method is used in a specific project Becoming Iris, making inquiry into arts-based knowledge creation during a three month visiting scholarship at a small, independent visual art academy. Using the performative schizoid......A performative schizoid method is developed as a method contribution to performance as research. The method is inspired by contemporary research in the human and social sciences urging experimentation and researcher engagement with creative and artistic practice. In the article, the method...... method in Becoming Iris results in four audio-visual and performance-based productions, centered on an emergent theme of the scholartist as a bird in borrowed feathers. Interestingly, the moral lesson of the fable about the vain jackdaw, who dresses in borrowed peacock feathers and becomes a castout...

Technological Similarity, Post-acquisition R&D Reorganization, and Innovation Performance in Horizontal Acquisition

DEFF Research Database (Denmark)

Colombo, Massimo G.; Rabbiosi, Larissa

2014-01-01

This paper aims to disentangle the mechanisms through which technological similarity between acquiring and acquired firms influences innovation in horizontal acquisitions. We develop a theoretical model that links technological similarity to: (i) two key aspects of post-acquisition reorganization...... of acquired R&D operations – the rationalization of the R&D operations and the replacement of the R&D top manager, and (ii) two intermediate effects that are closely associated with the post-acquisition innovation performance of the combined firm – improvements in R&D productivity and disruptions in R......&D personnel. We rely on PLS techniques to test our theoretical model using detailed information on 31 horizontal acquisitions in high- and medium-tech industries. Our results indicate that in horizontal acquisitions, technological similarity negatively affects post-acquisition innovation performance...

Unveiling Music Structure Via PLSA Similarity Fusion

DEFF Research Database (Denmark)

Arenas-García, Jerónimo; Meng, Anders; Petersen, Kaare Brandt

2007-01-01

Nowadays there is an increasing interest in developing methods for building music recommendation systems. In order to get a satisfactory performance from such a system, one needs to incorporate as much information about songs similarity as possible; however, how to do so is not obvious. In this p......Nowadays there is an increasing interest in developing methods for building music recommendation systems. In order to get a satisfactory performance from such a system, one needs to incorporate as much information about songs similarity as possible; however, how to do so is not obvious...... observed similarities can be satisfactorily explained using the latent semantics. Additionally, this approach significantly simplifies the song retrieval phase, leading to a more practical system implementation. The suitability of the PLSA model for representing music structure is studied in a simplified...

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.

Walking on a user similarity network towards personalized recommendations.

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Mingxin Gan

Full Text Available Personalized recommender systems have been receiving more and more attention in addressing the serious problem of information overload accompanying the rapid evolution of the world-wide-web. Although traditional collaborative filtering approaches based on similarities between users have achieved remarkable success, it has been shown that the existence of popular objects may adversely influence the correct scoring of candidate objects, which lead to unreasonable recommendation results. Meanwhile, recent advances have demonstrated that approaches based on diffusion and random walk processes exhibit superior performance over collaborative filtering methods in both the recommendation accuracy and diversity. Building on these results, we adopt three strategies (power-law adjustment, nearest neighbor, and threshold filtration to adjust a user similarity network from user similarity scores calculated on historical data, and then propose a random walk with restart model on the constructed network to achieve personalized recommendations. We perform cross-validation experiments on two real data sets (MovieLens and Netflix and compare the performance of our method against the existing state-of-the-art methods. Results show that our method outperforms existing methods in not only recommendation accuracy and diversity, but also retrieval performance.

Walking on a user similarity network towards personalized recommendations.

Science.gov (United States)

Gan, Mingxin

2014-01-01

Personalized recommender systems have been receiving more and more attention in addressing the serious problem of information overload accompanying the rapid evolution of the world-wide-web. Although traditional collaborative filtering approaches based on similarities between users have achieved remarkable success, it has been shown that the existence of popular objects may adversely influence the correct scoring of candidate objects, which lead to unreasonable recommendation results. Meanwhile, recent advances have demonstrated that approaches based on diffusion and random walk processes exhibit superior performance over collaborative filtering methods in both the recommendation accuracy and diversity. Building on these results, we adopt three strategies (power-law adjustment, nearest neighbor, and threshold filtration) to adjust a user similarity network from user similarity scores calculated on historical data, and then propose a random walk with restart model on the constructed network to achieve personalized recommendations. We perform cross-validation experiments on two real data sets (MovieLens and Netflix) and compare the performance of our method against the existing state-of-the-art methods. Results show that our method outperforms existing methods in not only recommendation accuracy and diversity, but also retrieval performance.

IntNetLncSim: an integrative network analysis method to infer human lncRNA functional similarity.

Science.gov (United States)

Cheng, Liang; Shi, Hongbo; Wang, Zhenzhen; Hu, Yang; Yang, Haixiu; Zhou, Chen; Sun, Jie; Zhou, Meng

2016-07-26

Increasing evidence indicated that long non-coding RNAs (lncRNAs) were involved in various biological processes and complex diseases by communicating with mRNAs/miRNAs each other. Exploiting interactions between lncRNAs and mRNA/miRNAs to lncRNA functional similarity (LFS) is an effective method to explore function of lncRNAs and predict novel lncRNA-disease associations. In this article, we proposed an integrative framework, IntNetLncSim, to infer LFS by modeling the information flow in an integrated network that comprises both lncRNA-related transcriptional and post-transcriptional information. The performance of IntNetLncSim was evaluated by investigating the relationship of LFS with the similarity of lncRNA-related mRNA sets (LmRSets) and miRNA sets (LmiRSets). As a result, LFS by IntNetLncSim was significant positively correlated with the LmRSet (Pearson correlation γ2=0.8424) and LmiRSet (Pearson correlation γ2=0.2601). Particularly, the performance of IntNetLncSim is superior to several previous methods. In the case of applying the LFS to identify novel lncRNA-disease relationships, we achieved an area under the ROC curve (0.7300) in experimentally verified lncRNA-disease associations based on leave-one-out cross-validation. Furthermore, highly-ranked lncRNA-disease associations confirmed by literature mining demonstrated the excellent performance of IntNetLncSim. Finally, a web-accessible system was provided for querying LFS and potential lncRNA-disease relationships: http://www.bio-bigdata.com/IntNetLncSim.

Resisting distraction and response inhibition trigger similar enhancements of future performance.

Science.gov (United States)

Bissett, Patrick G; Grant, Lauren D; Weissman, Daniel H

2017-10-01

Resisting distraction and response inhibition are crucial aspects of cognitive control. Interestingly, each of these abilities transiently improves just after it is utilized. Competing views differ, however, as to whether utilizing either of these abilities (e.g., resisting distraction) enhances future performance involving the other ability (e.g., response inhibition). To distinguish between these views, we combined a Stroop-like task that requires resisting distraction with a restraint variant of the stop-signal task that requires response inhibition. We observed similar sequential-trial effects (i.e., performance enhancements) following trials in which participants (a) resisted distraction (i.e., incongruent go trials) and (b) inhibited a response (i.e., congruent stop trials). First, the congruency effect in go trials, which indexes overall distractibility, was smaller after both incongruent go trials and congruent stop trials than it was after congruent go trials. Second, stop failures were less frequent after both incongruent go trials and congruent stop trials than after congruent go trials. A control experiment ruled out the possibility that perceptual conflict or surprise engendered by occasional stop signals triggers sequential-trial effects independent of stopping. Thus, our findings support a novel, integrated view in which resisting distraction and response inhibition trigger similar sequential enhancements of future performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic Time Warping Distance Method for Similarity Test of Multipoint Ground Motion Field

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Yingmin Li

2010-01-01

Full Text Available The reasonability of artificial multi-point ground motions and the identification of abnormal records in seismic array observations, are two important issues in application and analysis of multi-point ground motion fields. Based on the dynamic time warping (DTW distance method, this paper discusses the application of similarity measurement in the similarity analysis of simulated multi-point ground motions and the actual seismic array records. Analysis results show that the DTW distance method not only can quantitatively reflect the similarity of simulated ground motion field, but also offers advantages in clustering analysis and singularity recognition of actual multi-point ground motion field.

SVMTriP: a method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity.

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Bo Yao

Full Text Available Identifying protein surface regions preferentially recognizable by antibodies (antigenic epitopes is at the heart of new immuno-diagnostic reagent discovery and vaccine design, and computational methods for antigenic epitope prediction provide crucial means to serve this purpose. Many linear B-cell epitope prediction methods were developed, such as BepiPred, ABCPred, AAP, BCPred, BayesB, BEOracle/BROracle, and BEST, towards this goal. However, effective immunological research demands more robust performance of the prediction method than what the current algorithms could provide. In this work, a new method to predict linear antigenic epitopes is developed; Support Vector Machine has been utilized by combining the Tri-peptide similarity and Propensity scores (SVMTriP. Applied to non-redundant B-cell linear epitopes extracted from IEDB, SVMTriP achieves a sensitivity of 80.1% and a precision of 55.2% with a five-fold cross-validation. The AUC value is 0.702. The combination of similarity and propensity of tri-peptide subsequences can improve the prediction performance for linear B-cell epitopes. Moreover, SVMTriP is capable of recognizing viral peptides from a human protein sequence background. A web server based on our method is constructed for public use. The server and all datasets used in the current study are available at http://sysbio.unl.edu/SVMTriP.

Similarity-based pattern analysis and recognition

CERN Document Server

Pelillo, Marcello

2013-01-01

This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification alg

Operator performance evaluation using multi criteria decision making methods

Science.gov (United States)

Rani, Ruzanita Mat; Ismail, Wan Rosmanira; Razali, Siti Fatihah

2014-06-01

Operator performance evaluation is a very important operation in labor-intensive manufacturing industry because the company's productivity depends on the performance of its operators. The aims of operator performance evaluation are to give feedback to operators on their performance, to increase company's productivity and to identify strengths and weaknesses of each operator. In this paper, six multi criteria decision making methods; Analytical Hierarchy Process (AHP), fuzzy AHP (FAHP), ELECTRE, PROMETHEE II, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) are used to evaluate the operators' performance and to rank the operators. The performance evaluation is based on six main criteria; competency, experience and skill, teamwork and time punctuality, personal characteristics, capability and outcome. The study was conducted at one of the SME food manufacturing companies in Selangor. From the study, it is found that AHP and FAHP yielded the "outcome" criteria as the most important criteria. The results of operator performance evaluation showed that the same operator is ranked the first using all six methods.

A novel method to remove GPR background noise based on the similarity of non-neighboring regions

Science.gov (United States)

Montiel-Zafra, V.; Canadas-Quesada, F. J.; Vera-Candeas, P.; Ruiz-Reyes, N.; Rey, J.; Martinez, J.

2017-09-01

Ground penetrating radar (GPR) is a non-destructive technique that has been widely used in many areas of research, such as landmine detection or subsurface anomalies, where it is required to locate targets embedded within a background medium. One of the major challenges in the research of GPR data remains the improvement of the image quality of stone materials by means of detection of true anisotropies since most of the errors are caused by an incorrect interpretation by the users. However, it is complicated due to the interference of the horizontal background noise, e.g., the air-ground interface, that reduces the high-resolution quality of radargrams. Thus, weak or deep anisotropies are often masked by this type of noise. In order to remove the background noise obtained by GPR, this work proposes a novel background removal method assuming that the horizontal noise shows repetitive two-dimensional regions along the movement of the GPR antenna. Specifically, the proposed method, based on the non-local similarity of regions over the distance, computes similarities between different regions of the same depth in order to identify most repetitive regions using a criterion to avoid closer regions. Evaluations are performed using a set of synthetic and real GPR data. Experimental results show that the proposed method obtains promising results compared to the classic background removal techniques and the most recently published background removal methods.

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.

Prioritization of candidate disease genes by combining topological similarity and semantic similarity.

Science.gov (United States)

Liu, Bin; Jin, Min; Zeng, Pan

2015-10-01

The identification of gene-phenotype relationships is very important for the treatment of human diseases. Studies have shown that genes causing the same or similar phenotypes tend to interact with each other in a protein-protein interaction (PPI) network. Thus, many identification methods based on the PPI network model have achieved good results. However, in the PPI network, some interactions between the proteins encoded by candidate gene and the proteins encoded by known disease genes are very weak. Therefore, some studies have combined the PPI network with other genomic information and reported good predictive performances. However, we believe that the results could be further improved. In this paper, we propose a new method that uses the semantic similarity between the candidate gene and known disease genes to set the initial probability vector of a random walk with a restart algorithm in a human PPI network. The effectiveness of our method was demonstrated by leave-one-out cross-validation, and the experimental results indicated that our method outperformed other methods. Additionally, our method can predict new causative genes of multifactor diseases, including Parkinson's disease, breast cancer and obesity. The top predictions were good and consistent with the findings in the literature, which further illustrates the effectiveness of our method. Copyright © 2015 Elsevier Inc. All rights reserved.

Similarity Digest Search: A Survey and Comparative Analysis of Strategies to Perform Known File Filtering Using Approximate Matching

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Vitor Hugo Galhardo Moia

2017-01-01

Full Text Available Digital forensics is a branch of Computer Science aiming at investigating and analyzing electronic devices in the search for crime evidence. There are several ways to perform this search. Known File Filter (KFF is one of them, where a list of interest objects is used to reduce/separate data for analysis. Holding a database of hashes of such objects, the examiner performs lookups for matches against the target device. However, due to limitations over hash functions (inability to detect similar objects, new methods have been designed, called approximate matching. This sort of function has interesting characteristics for KFF investigations but suffers mainly from high costs when dealing with huge data sets, as the search is usually done by brute force. To mitigate this problem, strategies have been developed to better perform lookups. In this paper, we present the state of the art of similarity digest search strategies, along with a detailed comparison involving several aspects, as time complexity, memory requirement, and search precision. Our results show that none of the approaches address at least these main aspects. Finally, we discuss future directions and present requirements for a new strategy aiming to fulfill current limitations.

A FAST METHOD FOR MEASURING THE SIMILARITY BETWEEN 3D MODEL AND 3D POINT CLOUD

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Z. Zhang

2016-06-01

Full Text Available This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC. It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data.

[Baking method of Platycladi Cacumen Carbonisatum based on similarity of UPLC fingerprints].

Science.gov (United States)

Shan, Mingqiu; Chen, Chao; Yao, Xiaodong; Ding, Anwei

2010-09-01

To establish a baking method of Platycladi Cacumen Carbonisatum for providing a new idea to Carbonic Herbs' research. Samples were prepared in an oven for different time at different temperatures separately. Then the fingerprints of the samples were determined by UPLC. According to the standard fingerprint, the similarities of the samples' fingerprints were compared. The similarities of 3 samples, which were baked at 230 degrees C for 20 min, 30 min and at 240 degrees C for 20 min, were above 0.96. According to the similarities of the fingerprints and in view of the appearances, Platycladi Cacumen Carbonizing should be baked at 230 degrees C for 20 min.

Improving performance of content-based image retrieval schemes in searching for similar breast mass regions: an assessment

International Nuclear Information System (INIS)

Wang Xiaohui; Park, Sang Cheol; Zheng Bin

2009-01-01

This study aims to assess three methods commonly used in content-based image retrieval (CBIR) schemes and investigate the approaches to improve scheme performance. A reference database involving 3000 regions of interest (ROIs) was established. Among them, 400 ROIs were randomly selected to form a testing dataset. Three methods, namely mutual information, Pearson's correlation and a multi-feature-based k-nearest neighbor (KNN) algorithm, were applied to search for the 15 'the most similar' reference ROIs to each testing ROI. The clinical relevance and visual similarity of searching results were evaluated using the areas under receiver operating characteristic (ROC) curves (A Z ) and average mean square difference (MSD) of the mass boundary spiculation level ratings between testing and selected ROIs, respectively. The results showed that the A Z values were 0.893 ± 0.009, 0.606 ± 0.021 and 0.699 ± 0.026 for the use of KNN, mutual information and Pearson's correlation, respectively. The A Z values increased to 0.724 ± 0.017 and 0.787 ± 0.016 for mutual information and Pearson's correlation when using ROIs with the size adaptively adjusted based on actual mass size. The corresponding MSD values were 2.107 ± 0.718, 2.301 ± 0.733 and 2.298 ± 0.743. The study demonstrates that due to the diversity of medical images, CBIR schemes using multiple image features and mass size-based ROIs can achieve significantly improved performance.

Similar estimates of temperature impacts on global wheat yield by three independent methods

DEFF Research Database (Denmark)

Liu, Bing; Asseng, Senthold; Müller, Christoph

2016-01-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produ......-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.......The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce...... similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries...

Logarithmic Similarity Measure between Interval-Valued Fuzzy Sets and Its Fault Diagnosis Method

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Zhikang Lu

2018-02-01

Full Text Available Fault diagnosis is an important task for the normal operation and maintenance of equipment. In many real situations, the diagnosis data cannot provide deterministic values and are usually imprecise or uncertain. Thus, interval-valued fuzzy sets (IVFSs are very suitable for expressing imprecise or uncertain fault information in real problems. However, existing literature scarcely deals with fault diagnosis problems, such as gasoline engines and steam turbines with IVFSs. However, the similarity measure is one of the important tools in fault diagnoses. Therefore, this paper proposes a new similarity measure of IVFSs based on logarithmic function and its fault diagnosis method for the first time. By the logarithmic similarity measure between the fault knowledge and some diagnosis-testing samples with interval-valued fuzzy information and its relation indices, we can determine the fault type and ranking order of faults corresponding to the relation indices. Then, the misfire fault diagnosis of the gasoline engine and the vibrational fault diagnosis of a turbine are presented to demonstrate the simplicity and effectiveness of the proposed diagnosis method. The fault diagnosis results of gasoline engine and steam turbine show that the proposed diagnosis method not only gives the main fault types of the gasoline engine and steam turbine but also provides useful information for multi-fault analyses and predicting future fault trends. Hence, the logarithmic similarity measure and its fault diagnosis method are main contributions in this study and they provide a useful new way for the fault diagnosis with interval-valued fuzzy information.

A new method for brain tumor detection using the Bhattacharyya similarity coefficient, color conversions and neural network

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Bahman Mansori

2015-10-01

Full Text Available Background: Magnetic resonance imaging (MRI is widely applied for examination and diagnosis of brain tumors based on its advantages of high resolution in detecting the soft tissues and especially of its harmless radiation damages to human bodies. The goal of the processing of images is automatic segmentation of brain edema and tumors, in different dimensions of the magnetic resonance images. Methods: The proposed method is based on the unsupervised method which discovers the tumor region, if there is any, by analyzing the similarities between two hemispheres and computes the image size of the goal function based on Bhattacharyya coefficient which is used in the next stage to detect the tumor region or some part of it. In this stage, for reducing the color variation, the gray brain image is segmented, then it is turned to gray again. The self-organizing map (SOM neural network is used the segmented brain image is colored and finally the tumor is detected by matching the detected region and the colored image. This method is proposed to analyze MRI images for discovering brain tumors, and done in Bu Ali Sina University, Hamedan, Iran, in 2014. Results: The results for 30 randomly selected images from data bank of MRI center in Hamedan was compared with manually segmentation of experts. The results showed that, our proposed method had the accuracy of more than 94% at Jaccard similarity index (JSI, 97% at Dice similarity score (DSS, and 98% and 99% at two measures of specificity and sensitivity. Conclusion: The experimental results showed that it was satisfactory and can be used in automatic separation of tumor from normal brain tissues and therefore it can be used in practical applications. The results showed that the use of SOM neural network to classify useful magnetic resonance imaging of the brain and demonstrated a good performance.

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

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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.

The New Performance Calculation Method of Fouled Axial Flow Compressor

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Huadong Yang

2014-01-01

Full Text Available Fouling is the most important performance degradation factor, so it is necessary to accurately predict the effect of fouling on engine performance. In the previous research, it is very difficult to accurately model the fouled axial flow compressor. This paper develops a new performance calculation method of fouled multistage axial flow compressor based on experiment result and operating data. For multistage compressor, the whole compressor is decomposed into two sections. The first section includes the first 50% stages which reflect the fouling level, and the second section includes the last 50% stages which are viewed as the clean stage because of less deposits. In this model, the performance of the first section is obtained by combining scaling law method and linear progression model with traditional stage stacking method; simultaneously ambient conditions and engine configurations are considered. On the other hand, the performance of the second section is calculated by averaged infinitesimal stage method which is based on Reynolds’ law of similarity. Finally, the model is successfully applied to predict the 8-stage axial flow compressor and 16-stage LM2500-30 compressor. The change of thermodynamic parameters such as pressure ratio, efficiency with the operating time, and stage number is analyzed in detail.

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.

Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods

Science.gov (United States)

Liu, Bing; Asseng, Senthold; Muller, Christoph; Ewart, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.;

Similar estimates of temperature impacts on global wheat yield by three independent methods

Science.gov (United States)

Liu, Bing; Asseng, Senthold; Müller, Christoph; Ewert, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; Rosenzweig, Cynthia; Aggarwal, Pramod K.; Alderman, Phillip D.; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andy; Deryng, Delphine; Sanctis, Giacomo De; Doltra, Jordi; Fereres, Elias; Folberth, Christian; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A.; Izaurralde, Roberto C.; Jabloun, Mohamed; Jones, Curtis D.; Kersebaum, Kurt C.; Kimball, Bruce A.; Koehler, Ann-Kristin; Kumar, Soora Naresh; Nendel, Claas; O'Leary, Garry J.; Olesen, Jørgen E.; Ottman, Michael J.; Palosuo, Taru; Prasad, P. V. Vara; Priesack, Eckart; Pugh, Thomas A. M.; Reynolds, Matthew; Rezaei, Ehsan E.; Rötter, Reimund P.; Schmid, Erwin; Semenov, Mikhail A.; Shcherbak, Iurii; Stehfest, Elke; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wall, Gerard W.; Wang, Enli; White, Jeffrey W.; Wolf, Joost; Zhao, Zhigan; Zhu, Yan

2016-12-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify `method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

Enzyme sequence similarity improves the reaction alignment method for cross-species pathway comparison

Energy Technology Data Exchange (ETDEWEB)

Ovacik, Meric A. [Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854 (United States); Androulakis, Ioannis P., E-mail: yannis@rci.rutgers.edu [Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854 (United States); Biomedical Engineering Department, Rutgers University, Piscataway, NJ 08854 (United States)

2013-09-15

Pathway-based information has become an important source of information for both establishing evolutionary relationships and understanding the mode of action of a chemical or pharmaceutical among species. Cross-species comparison of pathways can address two broad questions: comparison in order to inform evolutionary relationships and to extrapolate species differences used in a number of different applications including drug and toxicity testing. Cross-species comparison of metabolic pathways is complex as there are multiple features of a pathway that can be modeled and compared. Among the various methods that have been proposed, reaction alignment has emerged as the most successful at predicting phylogenetic relationships based on NCBI taxonomy. We propose an improvement of the reaction alignment method by accounting for sequence similarity in addition to reaction alignment method. Using nine species, including human and some model organisms and test species, we evaluate the standard and improved comparison methods by analyzing glycolysis and citrate cycle pathways conservation. In addition, we demonstrate how organism comparison can be conducted by accounting for the cumulative information retrieved from nine pathways in central metabolism as well as a more complete study involving 36 pathways common in all nine species. Our results indicate that reaction alignment with enzyme sequence similarity results in a more accurate representation of pathway specific cross-species similarities and differences based on NCBI taxonomy.

Enzyme sequence similarity improves the reaction alignment method for cross-species pathway comparison

International Nuclear Information System (INIS)

Ovacik, Meric A.; Androulakis, Ioannis P.

2013-01-01

Pathway-based information has become an important source of information for both establishing evolutionary relationships and understanding the mode of action of a chemical or pharmaceutical among species. Cross-species comparison of pathways can address two broad questions: comparison in order to inform evolutionary relationships and to extrapolate species differences used in a number of different applications including drug and toxicity testing. Cross-species comparison of metabolic pathways is complex as there are multiple features of a pathway that can be modeled and compared. Among the various methods that have been proposed, reaction alignment has emerged as the most successful at predicting phylogenetic relationships based on NCBI taxonomy. We propose an improvement of the reaction alignment method by accounting for sequence similarity in addition to reaction alignment method. Using nine species, including human and some model organisms and test species, we evaluate the standard and improved comparison methods by analyzing glycolysis and citrate cycle pathways conservation. In addition, we demonstrate how organism comparison can be conducted by accounting for the cumulative information retrieved from nine pathways in central metabolism as well as a more complete study involving 36 pathways common in all nine species. Our results indicate that reaction alignment with enzyme sequence similarity results in a more accurate representation of pathway specific cross-species similarities and differences based on NCBI taxonomy

Performance study of Active Queue Management methods: Adaptive GRED, REDD, and GRED-Linear analytical model

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Hussein Abdel-jaber

2015-10-01

Full Text Available Congestion control is one of the hot research topics that helps maintain the performance of computer networks. This paper compares three Active Queue Management (AQM methods, namely, Adaptive Gentle Random Early Detection (Adaptive GRED, Random Early Dynamic Detection (REDD, and GRED Linear analytical model with respect to different performance measures. Adaptive GRED and REDD are implemented based on simulation, whereas GRED Linear is implemented as a discrete-time analytical model. Several performance measures are used to evaluate the effectiveness of the compared methods mainly mean queue length, throughput, average queueing delay, overflow packet loss probability, and packet dropping probability. The ultimate aim is to identify the method that offers the highest satisfactory performance in non-congestion or congestion scenarios. The first comparison results that are based on different packet arrival probability values show that GRED Linear provides better mean queue length; average queueing delay and packet overflow probability than Adaptive GRED and REDD methods in the presence of congestion. Further and using the same evaluation measures, Adaptive GRED offers a more satisfactory performance than REDD when heavy congestion is present. When the finite capacity of queue values varies the GRED Linear model provides the highest satisfactory performance with reference to mean queue length and average queueing delay and all the compared methods provide similar throughput performance. However, when the finite capacity value is large, the compared methods have similar results in regard to probabilities of both packet overflowing and packet dropping.

Local non-similarity method through the Crocco's transformation in boundary layer problem

International Nuclear Information System (INIS)

Jardim, R.G.M.

1981-04-01

The coordinate transformation developed by L. Crocco to obtain the solution of the compressible fluid flows over isotermal flat plates is originally employed in the present work, with the purpose of adding its inherent advantage to the Non-Similarity Method idealized by E.M. Sparrow, in the solution of the incompressible non-similar boundary layers. The Crocco's transformation is applied to the conservation equation for forced convection, laminar, constant properties and two-dimensional flows over solids. Two non-similar problems arisen from freestream velocity distribution, the cylinder in crossflow and the Howarth's retarded flow, are solved with a view to illustrating the new procedure. In those solutions the effect of frictional heat is also considered. The results of hydrodynamic and thermal problems are compared with available published information and good agreement was observed. (Author) [pt

The effect of target and non-target similarity on neural classification performance: A boost from confidence

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Amar R Marathe

2015-08-01

Full Text Available Brain computer interaction (BCI technologies have proven effective in utilizing single-trial classification algorithms to detect target images in rapid serial visualization presentation tasks. While many factors contribute to the accuracy of these algorithms, a critical aspect that is often overlooked concerns the feature similarity between target and non-target images. In most real-world environments there are likely to be many shared features between targets and non-targets resulting in similar neural activity between the two classes. It is unknown how current neural-based target classification algorithms perform when qualitatively similar target and non-target images are presented. This study address this question by comparing behavioral and neural classification performance across two conditions: first, when targets were the only infrequent stimulus presented amongst frequent background distracters; and second when targets were presented together with infrequent non-targets containing similar visual features to the targets. The resulting findings show that behavior is slower and less accurate when targets are presented together with similar non-targets; moreover, single-trial classification yielded high levels of misclassification when infrequent non-targets are included. Furthermore, we present an approach to mitigate the image misclassification. We use confidence measures to assess the quality of single-trial classification, and demonstrate that a system in which low confidence trials are reclassified through a secondary process can result in improved performance.

Priming of disability and elderly stereotype in motor performance: similar or specific effects?

Science.gov (United States)

Ginsberg, Frederik; Rohmer, Odile; Louvet, Eva

2012-04-01

In three experimental studies, the effects of priming participants with the disability stereotype were investigated with respect to their subsequent motor performance. Also explored were effects of activating two similar stereotypes, persons with a disability and elderly people. In Study 1, participants were primed with the disability stereotype versus with a neutral prime, and then asked to perform on a motor coordination task. In Studies 2 and 3, a third condition was introduced: priming participants with the elderly stereotype. Results indicated that priming participants with the disability stereotype altered their motor performance: they showed decreased manual dexterity and performed slower than the non-primed participants. Priming with the elderly stereotype decreased only performance speed. These findings underline that prime-to-behavior effects may depend on activation of specific stereotype content.

Dimensional analysis and self-similarity methods for engineers and scientists

CERN Document Server

Zohuri, Bahman

2015-01-01

This ground-breaking reference provides an overview of key concepts in dimensional analysis, and then pushes well beyond traditional applications in fluid mechanics to demonstrate how powerful this tool can be in solving complex problems across many diverse fields. Of particular interest is the book's coverage of  dimensional analysis and self-similarity methods in nuclear and energy engineering. Numerous practical examples of dimensional problems are presented throughout, allowing readers to link the book's theoretical explanations and step-by-step mathematical solutions to practical impleme

A Method for Generating Approximate Similarity Solutions of Nonlinear Partial Differential Equations

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Mazhar Iqbal

2014-01-01

Full Text Available Standard application of similarity method to find solutions of PDEs mostly results in reduction to ODEs which are not easily integrable in terms of elementary or tabulated functions. Such situations usually demand solving reduced ODEs numerically. However, there are no systematic procedures available to utilize these numerical solutions of reduced ODE to obtain the solution of original PDE. A practical and tractable approach is proposed to deal with such situations and is applied to obtain approximate similarity solutions to different cases of an initial-boundary value problem of unsteady gas flow through a semi-infinite porous medium.

A shortest-path graph kernel for estimating gene product semantic similarity

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Alvarez Marco A

2011-07-01

Full Text Available Abstract Background Existing methods for calculating semantic similarity between gene products using the Gene Ontology (GO often rely on external resources, which are not part of the ontology. Consequently, changes in these external resources like biased term distribution caused by shifting of hot research topics, will affect the calculation of semantic similarity. One way to avoid this problem is to use semantic methods that are "intrinsic" to the ontology, i.e. independent of external knowledge. Results We present a shortest-path graph kernel (spgk method that relies exclusively on the GO and its structure. In spgk, a gene product is represented by an induced subgraph of the GO, which consists of all the GO terms annotating it. Then a shortest-path graph kernel is used to compute the similarity between two graphs. In a comprehensive evaluation using a benchmark dataset, spgk compares favorably with other methods that depend on external resources. Compared with simUI, a method that is also intrinsic to GO, spgk achieves slightly better results on the benchmark dataset. Statistical tests show that the improvement is significant when the resolution and EC similarity correlation coefficient are used to measure the performance, but is insignificant when the Pfam similarity correlation coefficient is used. Conclusions Spgk uses a graph kernel method in polynomial time to exploit the structure of the GO to calculate semantic similarity between gene products. It provides an alternative to both methods that use external resources and "intrinsic" methods with comparable performance.

Method of synthesis of abstract images with high self-similarity

Science.gov (United States)

Matveev, Nikolay V.; Shcheglov, Sergey A.; Romanova, Galina E.; Koneva, Ð.¢atiana A.

2017-06-01

Abstract images with high self-similarity could be used for drug-free stress therapy. This based on the fact that a complex visual environment has a high affective appraisal. To create such an image we can use the setup based on the three laser sources of small power and different colors (Red, Green, Blue), the image is the pattern resulting from the reflecting and refracting by the complicated form object placed into the laser ray paths. The images were obtained experimentally which showed the good therapy effect. However, to find and to choose the object which gives needed image structure is very difficult and requires many trials. The goal of the work is to develop a method and a procedure of finding the object form which if placed into the ray paths can provide the necessary structure of the image In fact the task means obtaining the necessary irradiance distribution on the given surface. Traditionally such problems are solved using the non-imaging optics methods. In the given case this task is very complicated because of the complicated structure of the illuminance distribution and its high non-linearity. Alternative way is to use the projected image of a mask with a given structure. We consider both ways and discuss how they can help to speed up the synthesis procedure for the given abstract image of the high self-similarity for the setups of drug-free therapy.

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.

SemFunSim: a new method for measuring disease similarity by integrating semantic and gene functional association.

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Liang Cheng

Full Text Available Measuring similarity between diseases plays an important role in disease-related molecular function research. Functional associations between disease-related genes and semantic associations between diseases are often used to identify pairs of similar diseases from different perspectives. Currently, it is still a challenge to exploit both of them to calculate disease similarity. Therefore, a new method (SemFunSim that integrates semantic and functional association is proposed to address the issue.SemFunSim is designed as follows. First of all, FunSim (Functional similarity is proposed to calculate disease similarity using disease-related gene sets in a weighted network of human gene function. Next, SemSim (Semantic Similarity is devised to calculate disease similarity using the relationship between two diseases from Disease Ontology. Finally, FunSim and SemSim are integrated to measure disease similarity.The high average AUC (area under the receiver operating characteristic curve (96.37% shows that SemFunSim achieves a high true positive rate and a low false positive rate. 79 of the top 100 pairs of similar diseases identified by SemFunSim are annotated in the Comparative Toxicogenomics Database (CTD as being targeted by the same therapeutic compounds, while other methods we compared could identify 35 or less such pairs among the top 100. Moreover, when using our method on diseases without annotated compounds in CTD, we could confirm many of our predicted candidate compounds from literature. This indicates that SemFunSim is an effective method for drug repositioning.

Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

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Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

2018-01-01

Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.

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

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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.

Evolutionary conservatism and convergence both lead to striking similarity in ecology, morphology and performance across continents in frogs.

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Moen, Daniel S; Irschick, Duncan J; Wiens, John J

2013-12-22

Many clades contain ecologically and phenotypically similar species across continents, yet the processes generating this similarity are largely unstudied, leaving fundamental questions unanswered. Is similarity in morphology and performance across assemblages caused by evolutionary convergence or by biogeographic dispersal of evolutionarily conserved ecotypes? Does convergence to new ecological conditions erase evidence of past adaptation? Here, we analyse ecology, morphology and performance in frog assemblages from three continents (Asia, Australia and South America), assessing the importance of dispersal and convergent evolution in explaining similarity across regions. We find three striking results. First, species using the same microhabitat type are highly similar in morphology and performance across both clades and continents. Second, some species on different continents owe their similarity to dispersal and evolutionary conservatism (rather than evolutionary convergence), even over vast temporal and spatial scales. Third, in one case, an ecologically specialized ancestor radiated into diverse ecotypes that have converged with those on other continents, largely erasing traces of past adaptation to their ancestral ecology. Overall, our study highlights the roles of both evolutionary conservatism and convergence in explaining similarity in species traits over large spatial and temporal scales and demonstrates a statistical framework for addressing these questions in other systems.

Similar judgment method of brain neural pathway using DT-MRI

International Nuclear Information System (INIS)

Watashiba, Yasuhiro; Sakamoto, Naohisa; Sakai, Koji; Koyamada, Koji; Kanazawa, Masanori; Doi, Akio

2008-01-01

Nowadays, the visualization of brain neural pathway extracted by the tractography technology is thought as a useful effective tool for the detection of involved area and the analysis of sick cause by comparison of difference of normal and patient's nerve fiber configurations and for the support of the surgery planning and the forecast of progress after an operation. So far, for the observation of the brain neural pathway, the method of the user's subjectively judging the 3D shape of them displayed in the image has been used. However, in this kind of subjective observation, verification of the propriety for the diagnostic result is difficult, in addition it cannot obtain sufficient reliability. Therefore, we think that the system to compare the shape based on a quantitative evaluation is necessary. To resolve this problem, we propose the system that enables the shape of the brain neural pathway extracted by the tractography technology to be compared quantitatively. The proposed system realized to calculate similarity between two neural pathways, and to display the difference area according to the similarity. (author)

Discovering Music Structure via Similarity Fusion

DEFF Research Database (Denmark)

for representing music structure is studied in a simplified scenario consisting of 4412 songs and two similarity measures among them. The results suggest that the PLSA model is a useful framework to combine different sources of information, and provides a reasonable space for song representation.......Automatic methods for music navigation and music recommendation exploit the structure in the music to carry out a meaningful exploration of the “song space”. To get a satisfactory performance from such systems, one should incorporate as much information about songs similarity as possible; however...... semantics”, in such a way that all observed similarities can be satisfactorily explained using the latent semantics. Therefore, one can think of these semantics as the real structure in music, in the sense that they can explain the observed similarities among songs. The suitability of the PLSA model...

Discovering Music Structure via Similarity Fusion

DEFF Research Database (Denmark)

Arenas-García, Jerónimo; Parrado-Hernandez, Emilio; Meng, Anders

Automatic methods for music navigation and music recommendation exploit the structure in the music to carry out a meaningful exploration of the “song space”. To get a satisfactory performance from such systems, one should incorporate as much information about songs similarity as possible; however...... semantics”, in such a way that all observed similarities can be satisfactorily explained using the latent semantics. Therefore, one can think of these semantics as the real structure in music, in the sense that they can explain the observed similarities among songs. The suitability of the PLSA model...... for representing music structure is studied in a simplified scenario consisting of 4412 songs and two similarity measures among them. The results suggest that the PLSA model is a useful framework to combine different sources of information, and provides a reasonable space for song representation....

A unified frame of predicting side effects of drugs by using linear neighborhood similarity.

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Zhang, Wen; Yue, Xiang; Liu, Feng; Chen, Yanlin; Tu, Shikui; Zhang, Xining

2017-12-14

Drug side effects are one of main concerns in the drug discovery, which gains wide attentions. Investigating drug side effects is of great importance, and the computational prediction can help to guide wet experiments. As far as we known, a great number of computational methods have been proposed for the side effect predictions. The assumption that similar drugs may induce same side effects is usually employed for modeling, and how to calculate the drug-drug similarity is critical in the side effect predictions. In this paper, we present a novel measure of drug-drug similarity named "linear neighborhood similarity", which is calculated in a drug feature space by exploring linear neighborhood relationship. Then, we transfer the similarity from the feature space into the side effect space, and predict drug side effects by propagating known side effect information through a similarity-based graph. Under a unified frame based on the linear neighborhood similarity, we propose method "LNSM" and its extension "LNSM-SMI" to predict side effects of new drugs, and propose the method "LNSM-MSE" to predict unobserved side effect of approved drugs. We evaluate the performances of LNSM and LNSM-SMI in predicting side effects of new drugs, and evaluate the performances of LNSM-MSE in predicting missing side effects of approved drugs. The results demonstrate that the linear neighborhood similarity can improve the performances of side effect prediction, and the linear neighborhood similarity-based methods can outperform existing side effect prediction methods. More importantly, the proposed methods can predict side effects of new drugs as well as unobserved side effects of approved drugs under a unified frame.

Prospective and retrospective ECG-gating for CT coronary angiography perform similarly accurate at low heart rates

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Stolzmann, Paul, E-mail: paul.stolzmann@usz.ch [Institute of Diagnostic Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich (Switzerland); Goetti, Robert; Baumueller, Stephan [Institute of Diagnostic Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich (Switzerland); Plass, Andre; Falk, Volkmar [Clinic for Cardiovascular Surgery, University Hospital Zurich (Switzerland); Scheffel, Hans; Feuchtner, Gudrun; Marincek, Borut [Institute of Diagnostic Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich (Switzerland); Alkadhi, Hatem [Institute of Diagnostic Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich (Switzerland); Cardiac MR PET CT Program, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Leschka, Sebastian [Institute of Diagnostic Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich (Switzerland)

2011-07-15

Objective: To compare, in patients with suspicion of coronary artery disease (CAD) and low heart rates, image quality, diagnostic performance, and radiation dose values of prospectively and retrospectively electrocardiography (ECG)-gated dual-source computed tomography coronary angiography (CTCA) for the diagnosis of significant coronary stenoses. Materials and methods: Two-hundred consecutive patients with heart rates {<=}70 bpm were retrospectively enrolled; 100 patients undergoing prospectively ECG-gated CTCA (group 1) and 100 patients undergoing retrospectively-gated CTCA (group 2). Coronary artery segments were assessed for image quality and significant luminal diameter narrowing. Sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and accuracy of both CTCA groups were determined using conventional catheter angiography (CCA) as reference standard. Radiation dose values were calculated. Results: Both groups were comparable regarding gender, body weight, cardiovascular risk profile, severity of CAD, mean heart rate, heart rate variability, and Agatston score (all p > 0.05). There was no significant difference in the rate of non-assessable coronary segments between group 1 (1.6%, 24/1404) and group 2 (1.4%, 19/1385; p = 0.77); non-diagnostic image quality was significantly (p < 0.001) more often attributed to stair step artifacts in group 1. Segment-based sensitivity, specificity, PPV, NPV, and accuracy were 98%, 98%, 88%, 100%, and 100% among group 1; 96%, 99%, 90%, 100%, and 98% among group 2, respectively. Parameters of diagnostic performance were similar (all p > 0.05). Mean effective radiation dose of prospectively ECG-gated CTCA (2.2 {+-} 0.4 mSv) was significantly (p < 0.0001) smaller than that of retrospectively ECG-gated CTCA (8.1 {+-} 0.6 mSv). Conclusion: Prospectively ECG-gated CTCA yields similar image quality, performs as accurately as retrospectively ECG-gated CTCA in patients having heart rates {<=}70 bpm

User recommendation in healthcare social media by assessing user similarity in heterogeneous network.

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Jiang, Ling; Yang, Christopher C

2017-09-01

The rapid growth of online health social websites has captured a vast amount of healthcare information and made the information easy to access for health consumers. E-patients often use these social websites for informational and emotional support. However, health consumers could be easily overwhelmed by the overloaded information. Healthcare information searching can be very difficult for consumers, not to mention most of them are not skilled information searcher. In this work, we investigate the approaches for measuring user similarity in online health social websites. By recommending similar users to consumers, we can help them to seek informational and emotional support in a more efficient way. We propose to represent the healthcare social media data as a heterogeneous healthcare information network and introduce the local and global structural approaches for measuring user similarity in a heterogeneous network. We compare the proposed structural approaches with the content-based approach. Experiments were conducted on a dataset collected from a popular online health social website, and the results showed that content-based approach performed better for inactive users, while structural approaches performed better for active users. Moreover, global structural approach outperformed local structural approach for all user groups. In addition, we conducted experiments on local and global structural approaches using different weight schemas for the edges in the network. Leverage performed the best for both local and global approaches. Finally, we integrated different approaches and demonstrated that hybrid method yielded better performance than the individual approach. The results indicate that content-based methods can effectively capture the similarity of inactive users who usually have focused interests, while structural methods can achieve better performance when rich structural information is available. Local structural approach only considers direct connections

A vertex similarity index for better personalized recommendation

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Chen, Ling-Jiao; Zhang, Zi-Ke; Liu, Jin-Hu; Gao, Jian; Zhou, Tao

2017-01-01

Recommender systems benefit us in tackling the problem of information overload by predicting our potential choices among diverse niche objects. So far, a variety of personalized recommendation algorithms have been proposed and most of them are based on similarities, such as collaborative filtering and mass diffusion. Here, we propose a novel vertex similarity index named CosRA, which combines advantages of both the cosine index and the resource-allocation (RA) index. By applying the CosRA index to real recommender systems including MovieLens, Netflix and RYM, we show that the CosRA-based method has better performance in accuracy, diversity and novelty than some benchmark methods. Moreover, the CosRA index is free of parameters, which is a significant advantage in real applications. Further experiments show that the introduction of two turnable parameters cannot remarkably improve the overall performance of the CosRA index.

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

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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.

Systematic characterizations of text similarity in full text biomedical publications.

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Sun, Zhaohui; Errami, Mounir; Long, Tara; Renard, Chris; Choradia, Nishant; Garner, Harold

2010-09-15

Computational methods have been used to find duplicate biomedical publications in MEDLINE. Full text articles are becoming increasingly available, yet the similarities among them have not been systematically studied. Here, we quantitatively investigated the full text similarity of biomedical publications in PubMed Central. 72,011 full text articles from PubMed Central (PMC) were parsed to generate three different datasets: full texts, sections, and paragraphs. Text similarity comparisons were performed on these datasets using the text similarity algorithm eTBLAST. We measured the frequency of similar text pairs and compared it among different datasets. We found that high abstract similarity can be used to predict high full text similarity with a specificity of 20.1% (95% CI [17.3%, 23.1%]) and sensitivity of 99.999%. Abstract similarity and full text similarity have a moderate correlation (Pearson correlation coefficient: -0.423) when the similarity ratio is above 0.4. Among pairs of articles in PMC, method sections are found to be the most repetitive (frequency of similar pairs, methods: 0.029, introduction: 0.0076, results: 0.0043). In contrast, among a set of manually verified duplicate articles, results are the most repetitive sections (frequency of similar pairs, results: 0.94, methods: 0.89, introduction: 0.82). Repetition of introduction and methods sections is more likely to be committed by the same authors (odds of a highly similar pair having at least one shared author, introduction: 2.31, methods: 1.83, results: 1.03). There is also significantly more similarity in pairs of review articles than in pairs containing one review and one nonreview paper (frequency of similar pairs: 0.0167 and 0.0023, respectively). While quantifying abstract similarity is an effective approach for finding duplicate citations, a comprehensive full text analysis is necessary to uncover all potential duplicate citations in the scientific literature and is helpful when

Testing statistical significance scores of sequence comparison methods with structure similarity

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Leunissen Jack AM

2006-10-01

Full Text Available Abstract Background In the past years the Smith-Waterman sequence comparison algorithm has gained popularity due to improved implementations and rapidly increasing computing power. However, the quality and sensitivity of a database search is not only determined by the algorithm but also by the statistical significance testing for an alignment. The e-value is the most commonly used statistical validation method for sequence database searching. The CluSTr database and the Protein World database have been created using an alternative statistical significance test: a Z-score based on Monte-Carlo statistics. Several papers have described the superiority of the Z-score as compared to the e-value, using simulated data. We were interested if this could be validated when applied to existing, evolutionary related protein sequences. Results All experiments are performed on the ASTRAL SCOP database. The Smith-Waterman sequence comparison algorithm with both e-value and Z-score statistics is evaluated, using ROC, CVE and AP measures. The BLAST and FASTA algorithms are used as reference. We find that two out of three Smith-Waterman implementations with e-value are better at predicting structural similarities between proteins than the Smith-Waterman implementation with Z-score. SSEARCH especially has very high scores. Conclusion The compute intensive Z-score does not have a clear advantage over the e-value. The Smith-Waterman implementations give generally better results than their heuristic counterparts. We recommend using the SSEARCH algorithm combined with e-values for pairwise sequence comparisons.

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....

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.

Pilates and Proprioceptive Neuromuscular Facilitation Methods Induce Similar Strength Gains but Different Neuromuscular Adaptations in Elderly Women.

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Teixeira de Carvalho, Fabiana; de Andrade Mesquita, Laiana Sepúlveda; Pereira, Rafael; Neto, Osmar Pinto; Amaro Zangaro, Renato

2017-01-01

Background/Study Context: The aging process is associated with a decline in muscle mass, strength, and conditioning. Two training methods that may be useful to improve muscle function are Pilates and proprioceptive neuromuscular facilitation (PNF). Thus, the present study aimed to compare the influence of training programs using Pilates and PNF methods with elderly women. Sixty healthy elderly women were randomly divided into three groups: Pilates group, PNF group, and control group. Pilates and PNF groups underwent 1-month training programs with Pilates and PNF methods, respectively. The control group received no intervention during the 1 month. The maximal isometric force levels from knee extension and flexion, as well as the electromyography (EMG) signals from quadriceps and biceps femoris, were recorded before and after the 1-month intervention period. A two-way analysis of variance revealed that the Pilates and PNF methods induced similar strength gains from knee flexors and extensors, but Pilates exhibited greater low-gamma drive (i.e., oscillations in 30-60 Hz) in the EMG power spectrum after the training period. These results support use of both Pilates and PNF methods to enhance lower limb muscle strength in older groups, which is very important for gait, postural stability, and performance of daily life activities.

Phoneme Similarity and Confusability

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Bailey, T.M.; Hahn, U.

2005-01-01

Similarity between component speech sounds influences language processing in numerous ways. Explanation and detailed prediction of linguistic performance consequently requires an understanding of these basic similarities. The research reported in this paper contrasts two broad classes of approach to the issue of phoneme similarity-theoretically…

[Similarity system theory to evaluate similarity of chromatographic fingerprints of traditional Chinese medicine].

Science.gov (United States)

Liu, Yongsuo; Meng, Qinghua; Jiang, Shumin; Hu, Yuzhu

2005-03-01

The similarity evaluation of the fingerprints is one of the most important problems in the quality control of the traditional Chinese medicine (TCM). Similarity measures used to evaluate the similarity of the common peaks in the chromatogram of TCM have been discussed. Comparative studies were carried out among correlation coefficient, cosine of the angle and an improved extent similarity method using simulated data and experimental data. Correlation coefficient and cosine of the angle are not sensitive to the differences of the data set. They are still not sensitive to the differences of the data even after normalization. According to the similarity system theory, an improved extent similarity method was proposed. The improved extent similarity is more sensitive to the differences of the data sets than correlation coefficient and cosine of the angle. And the character of the data sets needs not to be changed compared with log-transformation. The improved extent similarity can be used to evaluate the similarity of the chromatographic fingerprints of TCM.

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.

New Similarity Functions

DEFF Research Database (Denmark)

Yazdani, Hossein; Ortiz-Arroyo, Daniel; Kwasnicka, Halina

2016-01-01

spaces, in addition to their similarity in the vector space. Prioritized Weighted Feature Distance (PWFD) works similarly as WFD, but provides the ability to give priorities to desirable features. The accuracy of the proposed functions are compared with other similarity functions on several data sets....... Our results show that the proposed functions work better than other methods proposed in the literature....

Rational Selection, Criticality Assessment, and Tiering of Quality Attributes and Test Methods for Analytical Similarity Evaluation of Biosimilars.

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Vandekerckhove, Kristof; Seidl, Andreas; Gutka, Hiten; Kumar, Manish; Gratzl, Gyöngyi; Keire, David; Coffey, Todd; Kuehne, Henriette

2018-05-10

Leading regulatory agencies recommend biosimilar assessment to proceed in a stepwise fashion, starting with a detailed analytical comparison of the structural and functional properties of the proposed biosimilar and reference product. The degree of analytical similarity determines the degree of residual uncertainty that must be addressed through downstream in vivo studies. Substantive evidence of similarity from comprehensive analytical testing may justify a targeted clinical development plan, and thus enable a shorter path to licensing. The importance of a careful design of the analytical similarity study program therefore should not be underestimated. Designing a state-of-the-art analytical similarity study meeting current regulatory requirements in regions such as the USA and EU requires a methodical approach, consisting of specific steps that far precede the work on the actual analytical study protocol. This white paper discusses scientific and methodological considerations on the process of attribute and test method selection, criticality assessment, and subsequent assignment of analytical measures to US FDA's three tiers of analytical similarity assessment. Case examples of selection of critical quality attributes and analytical methods for similarity exercises are provided to illustrate the practical implementation of the principles discussed.

A Novel Drug-Mouse Phenotypic Similarity Method Detects Molecular Determinants of Drug Effects.

Directory of Open Access Journals (Sweden)

Jeanette Prinz

2016-09-01

Full Text Available The molecular mechanisms that translate drug treatment into beneficial and unwanted effects are largely unknown. We present here a novel approach to detect gene-drug and gene-side effect associations based on the phenotypic similarity of drugs and single gene perturbations in mice that account for the polypharmacological property of drugs. We scored the phenotypic similarity of human side effect profiles of 1,667 small molecules and biologicals to profiles of phenotypic traits of 5,384 mouse genes. The benchmarking with known relationships revealed a strong enrichment of physical and indirect drug-target connections, causative drug target-side effect links as well as gene-drug links involved in pharmacogenetic associations among phenotypically similar gene-drug pairs. The validation by in vitro assays and the experimental verification of an unknown connection between oxandrolone and prokineticin receptor 2 reinforces the ability of this method to provide new molecular insights underlying drug treatment. Thus, this approach may aid in the proposal of novel and personalized treatments.

Learning Faster by Discovering and Exploiting Object Similarities

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Tadej Janež

2013-03-01

Full Text Available In this paper we explore the question: “Is it possible to speed up the learning process of an autonomous agent by performing experiments in a more complex environment (i.e., an environment with a greater number of different objects?” To this end, we use a simple robotic domain, where the robot has to learn a qualitative model predicting the change in the robot's distance to an object. To quantify the environment's complexity, we defined cardinal complexity as the number of objects in the robot's world, and behavioural complexity as the number of objects' distinct behaviours. We propose Error reduction merging (ERM, a new learning method that automatically discovers similarities in the structure of the agent's environment. ERM identifies different types of objects solely from the data measured and merges the observations of objects that behave in the same or similar way in order to speed up the agent's learning. We performed a series of experiments in worlds of increasing complexity. The results in our simple domain indicate that ERM was capable of discovering structural similarities in the data which indeed made the learning faster, clearly superior to conventional learning. This observed trend occurred with various machine learning algorithms used inside the ERM method.

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

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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.

Performance prediction of electrohydrodynamic thrusters by the perturbation method

International Nuclear Information System (INIS)

Shibata, H.; Watanabe, Y.; Suzuki, K.

2016-01-01

In this paper, we present a novel method for analyzing electrohydrodynamic (EHD) thrusters. The method is based on a perturbation technique applied to a set of drift-diffusion equations, similar to the one introduced in our previous study on estimating breakdown voltage. The thrust-to-current ratio is generalized to represent the performance of EHD thrusters. We have compared the thrust-to-current ratio obtained theoretically with that obtained from the proposed method under atmospheric air conditions, and we have obtained good quantitative agreement. Also, we have conducted a numerical simulation in more complex thruster geometries, such as the dual-stage thruster developed by Masuyama and Barrett [Proc. R. Soc. A 469, 20120623 (2013)]. We quantitatively clarify the fact that if the magnitude of a third electrode voltage is low, the effective gap distance shortens, whereas if the magnitude of the third electrode voltage is sufficiently high, the effective gap distance lengthens.

A COMPARISON OF SEMANTIC SIMILARITY MODELS IN EVALUATING CONCEPT SIMILARITY

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Q. X. Xu

2012-08-01

Full Text Available The semantic similarities are important in concept definition, recognition, categorization, interpretation, and integration. Many semantic similarity models have been established to evaluate semantic similarities of objects or/and concepts. To find out the suitability and performance of different models in evaluating concept similarities, we make a comparison of four main types of models in this paper: the geometric model, the feature model, the network model, and the transformational model. Fundamental principles and main characteristics of these models are introduced and compared firstly. Land use and land cover concepts of NLCD92 are employed as examples in the case study. The results demonstrate that correlations between these models are very high for a possible reason that all these models are designed to simulate the similarity judgement of human mind.

Similarity and symmetry methods applications in elasticity and mechanics of materials

CERN Document Server

Mladenov, Ivaïlo

2014-01-01

The principle aim of the book is to present a self-contained, modern account of similarity and symmetry methods, which are important mathematical tools for both physicists, engineers and applied mathematicians. The idea is to provide a balanced presentation of the mathematical techniques and applications of symmetry methods in mathematics, physics and engineering. That is why it includes recent developments and many examples in finding systematically conservation laws, local and nonlocal symmetries for ordinary and partial differential equations. The role of continuous symmetries in classical and quantum field theories is exposed at a technical level accessible even for non specialists. The importance of symmetries in continuum mechanics and mechanics of materials is highlighted through recent developments, such as the construction of constitutive models for various materials combining Lie symmetries with experimental data. As a whole this book is a unique collection of contributions from experts in the field...

Combining multiple FDG-PET radiotherapy target segmentation methods to reduce the effect of variable performance of individual segmentation methods

Energy Technology Data Exchange (ETDEWEB)

McGurk, Ross J. [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Bowsher, James; Das, Shiva K. [Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Lee, John A [Molecular Imaging and Experimental Radiotherapy Unit, Universite Catholique de Louvain, 1200 Brussels (Belgium)

2013-04-15

Purpose: Many approaches have been proposed to segment high uptake objects in 18F-fluoro-deoxy-glucose positron emission tomography images but none provides consistent performance across the large variety of imaging situations. This study investigates the use of two methods of combining individual segmentation methods to reduce the impact of inconsistent performance of the individual methods: simple majority voting and probabilistic estimation. Methods: The National Electrical Manufacturers Association image quality phantom containing five glass spheres with diameters 13-37 mm and two irregularly shaped volumes (16 and 32 cc) formed by deforming high-density polyethylene bottles in a hot water bath were filled with 18-fluoro-deoxyglucose and iodine contrast agent. Repeated 5-min positron emission tomography (PET) images were acquired at 4:1 and 8:1 object-to-background contrasts for spherical objects and 4.5:1 and 9:1 for irregular objects. Five individual methods were used to segment each object: 40% thresholding, adaptive thresholding, k-means clustering, seeded region-growing, and a gradient based method. Volumes were combined using a majority vote (MJV) or Simultaneous Truth And Performance Level Estimate (STAPLE) method. Accuracy of segmentations relative to CT ground truth volumes were assessed using the Dice similarity coefficient (DSC) and the symmetric mean absolute surface distances (SMASDs). Results: MJV had median DSC values of 0.886 and 0.875; and SMASD of 0.52 and 0.71 mm for spheres and irregular shapes, respectively. STAPLE provided similar results with median DSC of 0.886 and 0.871; and median SMASD of 0.50 and 0.72 mm for spheres and irregular shapes, respectively. STAPLE had significantly higher DSC and lower SMASD values than MJV for spheres (DSC, p < 0.0001; SMASD, p= 0.0101) but MJV had significantly higher DSC and lower SMASD values compared to STAPLE for irregular shapes (DSC, p < 0.0001; SMASD, p= 0.0027). DSC was not significantly

COMPANY PERFORMANCE MEASUREMENT AND REPORTING METHODS

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Nicu Ioana Elena

2012-12-01

Full Text Available One of the priorities of economic research has been and remains the re-evaluation of the notion of performance and especially exploring and finding some indicators that would reflect as accurately as possible the subtleties of the economic entity. The main purpose of this paper is to highlight the main company performance measurement and reporting methods. Performance is a concept that raises many question marks concerning the most accurate or the best method of reporting the performance at the company level. The research methodology has aimed at studying the Romanian and foreign specialized literature dealing with the analyzed field, studying magazines specialized on company performance measurement. If the financial performance measurement indicators are considered to offer an accurate image of the situation of the company, the modern approach through non-financial indicators offers a new perspective upon performance measurement, which is based on simplicity. In conclusion, after the theoretical study, I have noticed that the methods of performance measurement, reporting and interpretation are various, the opinions regarding the best performance measurement methods are contradictive and the companies prefer resorting to financial indicators that still play a more important role in the consolidation of the company performance measurement than the non-financial indicators do.

Blind deconvolution using the similarity of multiscales regularization for infrared spectrum

International Nuclear Information System (INIS)

Huang, Tao; Liu, Hai; Zhang, Zhaoli; Liu, Sanyan; Liu, Tingting; Shen, Xiaoxuan; Zhang, Jianfeng; Zhang, Tianxu

2015-01-01

Band overlap and random noise exist widely when the spectra are captured using an infrared spectrometer, especially since the aging of instruments has become a serious problem. In this paper, via introducing the similarity of multiscales, a blind spectral deconvolution method is proposed. Considering that there is a similarity between latent spectra at different scales, it is used as prior knowledge to constrain the estimated latent spectrum similar to pre-scale to reduce artifacts which are produced from deconvolution. The experimental results indicate that the proposed method is able to obtain a better performance than state-of-the-art methods, and to obtain satisfying deconvolution results with fewer artifacts. The recovered infrared spectra can easily extract the spectral features and recognize unknown objects. (paper)

The production and perception of emotionally expressive walking sounds: similarities between musical performance and everyday motor activity.

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Bruno L Giordano

Full Text Available Several studies have investigated the encoding and perception of emotional expressivity in music performance. A relevant question concerns how the ability to communicate emotions in music performance is acquired. In accordance with recent theories on the embodiment of emotion, we suggest here that both the expression and recognition of emotion in music might at least in part rely on knowledge about the sounds of expressive body movements. We test this hypothesis by drawing parallels between musical expression of emotions and expression of emotions in sounds associated with a non-musical motor activity: walking. In a combined production-perception design, two experiments were conducted, and expressive acoustical features were compared across modalities. An initial performance experiment tested for similar feature use in walking sounds and music performance, and revealed that strong similarities exist. Features related to sound intensity, tempo and tempo regularity were identified as been used similarly in both domains. Participants in a subsequent perception experiment were able to recognize both non-emotional and emotional properties of the sound-generating walkers. An analysis of the acoustical correlates of behavioral data revealed that variations in sound intensity, tempo, and tempo regularity were likely used to recognize expressed emotions. Taken together, these results lend support the motor origin hypothesis for the musical expression of emotions.

Retrieval evaluation and distance learning from perceived similarity between endomicroscopy videos.

Science.gov (United States)

André, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2011-01-01

Evaluating content-based retrieval (CBR) is challenging because it requires an adequate ground-truth. When the available groundtruth is limited to textual metadata such as pathological classes, retrieval results can only be evaluated indirectly, for example in terms of classification performance. In this study we first present a tool to generate perceived similarity ground-truth that enables direct evaluation of endomicroscopic video retrieval. This tool uses a four-points Likert scale and collects subjective pairwise similarities perceived by multiple expert observers. We then evaluate against the generated ground-truth a previously developed dense bag-of-visual-words method for endomicroscopic video retrieval. Confirming the results of previous indirect evaluation based on classification, our direct evaluation shows that this method significantly outperforms several other state-of-the-art CBR methods. In a second step, we propose to improve the CBR method by learning an adjusted similarity metric from the perceived similarity ground-truth. By minimizing a margin-based cost function that differentiates similar and dissimilar video pairs, we learn a weight vector applied to the visual word signatures of videos. Using cross-validation, we demonstrate that the learned similarity distance is significantly better correlated with the perceived similarity than the original visual-word-based distance.

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 ...

MULTICRITERIA METHODS IN PERFORMING COMPANIES’ RESULTS USING ELECTRONIC RECRUITING, CORPORATE COMMUNICATION AND FINANCIAL RATIOS

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Ivana Bilić

2011-02-01

Full Text Available Human resources represent one of the most important companies’ resources responsible in creation of companies’ competitive advantage. In search for the most valuable resources, companies use different methods. Lately, one of the growing methods is electronic recruiting, not only as a recruitment tool, but also as a mean of external communication. Additionally, in the process of corporate communication, companies nowadays use the electronic corporate communication as the easiest, the cheapest and the simplest form of business communication. The aim of this paper is to investigate relationship between three groups of different criteria; including main characteristics of performed electronic recruiting, corporate communication and selected financial performances. Selected companies were ranked separately by each group of criteria by usage of multicriteria decision making method PROMETHEE II. The main idea is to research whether companies which are the highest performers by certain group of criteria obtain the similar results regarding other group of criteria or performing results.

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

Science.gov (United States)

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

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.

ProCKSI: a decision support system for Protein (Structure Comparison, Knowledge, Similarity and Information

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Błażewicz Jacek

2007-10-01

Full Text Available Abstract Background We introduce the decision support system for Protein (Structure Comparison, Knowledge, Similarity and Information (ProCKSI. ProCKSI integrates various protein similarity measures through an easy to use interface that allows the comparison of multiple proteins simultaneously. It employs the Universal Similarity Metric (USM, the Maximum Contact Map Overlap (MaxCMO of protein structures and other external methods such as the DaliLite and the TM-align methods, the Combinatorial Extension (CE of the optimal path, and the FAST Align and Search Tool (FAST. Additionally, ProCKSI allows the user to upload a user-defined similarity matrix supplementing the methods mentioned, and computes a similarity consensus in order to provide a rich, integrated, multicriteria view of large datasets of protein structures. Results We present ProCKSI's architecture and workflow describing its intuitive user interface, and show its potential on three distinct test-cases. In the first case, ProCKSI is used to evaluate the results of a previous CASP competition, assessing the similarity of proposed models for given targets where the structures could have a large deviation from one another. To perform this type of comparison reliably, we introduce a new consensus method. The second study deals with the verification of a classification scheme for protein kinases, originally derived by sequence comparison by Hanks and Hunter, but here we use a consensus similarity measure based on structures. In the third experiment using the Rost and Sander dataset (RS126, we investigate how a combination of different sets of similarity measures influences the quality and performance of ProCKSI's new consensus measure. ProCKSI performs well with all three datasets, showing its potential for complex, simultaneous multi-method assessment of structural similarity in large protein datasets. Furthermore, combining different similarity measures is usually more robust than

Pulse shape analysis based on similarity and neural network with digital-analog fusion method

International Nuclear Information System (INIS)

Mardiyanto, M.P.; Uritani, A.; Sakai, H.; Kawarabayashi, J.; Iguchi, T.

2000-01-01

Through the measurement of 22 Na γ-rays, it has been demonstrated that the correction process was well done by fusing the similarity values with the pulse heights measured by the analog system, where at least four improvements in the energy spectrum characteristics were recognized, i.e., the increase of the peak-to-valley ratio, the photopeak area, the photopeak sharpness without discarding any events, and the 1,275 keV γ-ray photopeak was seen. The use of a slow digitizer was the main problem for this method. However, it can be solved easily using a faster digitizer. The fusion method was also applied for the beta-gamma mixed spectra separation. Mixed spectra of beta-gamma of the 137 Cs- 90 Sr mixed source could be separated well. We made a comparison between the energy spectrum of 137 Cs as a result of independent measurement with the result of the separation. After being compared, both FWHM agreed quite well. However, there was a slight difference between the two spectra on the peak-to-valley ratio. This separation method is simple and useful so that it can be applied for many other similar applications. (S.Y.)

The Nonlocal Sparse Reconstruction Algorithm by Similarity Measurement with Shearlet Feature Vector

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Wu Qidi

2014-01-01

Full Text Available Due to the limited accuracy of conventional methods with image restoration, the paper supplied a nonlocal sparsity reconstruction algorithm with similarity measurement. To improve the performance of restoration results, we proposed two schemes to dictionary learning and sparse coding, respectively. In the part of the dictionary learning, we measured the similarity between patches from degraded image by constructing the Shearlet feature vector. Besides, we classified the patches into different classes with similarity and trained the cluster dictionary for each class, by cascading which we could gain the universal dictionary. In the part of sparse coding, we proposed a novel optimal objective function with the coding residual item, which can suppress the residual between the estimate coding and true sparse coding. Additionally, we show the derivation of self-adaptive regularization parameter in optimization under the Bayesian framework, which can make the performance better. It can be indicated from the experimental results that by taking full advantage of similar local geometric structure feature existing in the nonlocal patches and the coding residual suppression, the proposed method shows advantage both on visual perception and PSNR compared to the conventional methods.

Determination of subjective similarity for pairs of masses and pairs of clustered microcalcifications on mammograms: Comparison of similarity ranking scores and absolute similarity ratings

International Nuclear Information System (INIS)

Muramatsu, Chisako; Li Qiang; Schmidt, Robert A.; Shiraishi, Junji; Suzuki, Kenji; Newstead, Gillian M.; Doi, Kunio

2007-01-01

The presentation of images that are similar to that of an unknown lesion seen on a mammogram may be helpful for radiologists to correctly diagnose that lesion. For similar images to be useful, they must be quite similar from the radiologists' point of view. We have been trying to quantify the radiologists' impression of similarity for pairs of lesions and to establish a ''gold standard'' for development and evaluation of a computerized scheme for selecting such similar images. However, it is considered difficult to reliably and accurately determine similarity ratings, because they are subjective. In this study, we compared the subjective similarities obtained by two different methods, an absolute rating method and a 2-alternative forced-choice (2AFC) method, to demonstrate that reliable similarity ratings can be determined by the responses of a group of radiologists. The absolute similarity ratings were previously obtained for pairs of masses and pairs of microcalcifications from five and nine radiologists, respectively. In this study, similarity ranking scores for eight pairs of masses and eight pairs of microcalcifications were determined by use of the 2AFC method. In the first session, the eight pairs of masses and eight pairs of microcalcifications were grouped and compared separately for determining the similarity ranking scores. In the second session, another similarity ranking score was determined by use of mixed pairs, i.e., by comparison of the similarity of a mass pair with that of a calcification pair. Four pairs of masses and four pairs of microcalcifications were grouped together to create two sets of eight pairs. The average absolute similarity ratings and the average similarity ranking scores showed very good correlations in the first study (Pearson's correlation coefficients: 0.94 and 0.98 for masses and microcalcifications, respectively). Moreover, in the second study, the correlations between the absolute ratings and the ranking scores were also

Analysis of the similarity factors of the villages in the areas of the nuclear power plants from the premature death-rate performed by fuzzy logic method

International Nuclear Information System (INIS)

Letkovicova, M.; Rehak, R.; Korec, J.; Mihaly, B.; Prikazsky, V.

1998-01-01

Our paper examines the surrounding areas of NPP from the proportion of premature death-rate which is one of the complex indicators of the health situation of the population. Specially, attention is focused on NPP in Bohunice (SE-EBO) which has been in operation for the last 30 years and NPP Mochovce (SE-EMO) which was still under construction when data was collected. WHO considers every death of the individual before 65 years of age a premature death case, except death cases of children younger that 1 year. Because of the diversity of the population, this factor is a standard for the population of Slovak Republic (SR) as well as for the european population. The objective of the work is to prove, that even a long term production of energy in NPP does not evoke health problems for the population living in the surrounding areas, which could be recorded through analysis of premature death cases. Using the fuzzy logic method when searching for similar objects and evaluating the influence of the NPP on its surrounding area seems more natural than classical accumulation method, which separates objects into groups. When using the classical accumulation method, the objects in particular accumulation group are more similar than 2 objects in different accumulation groups. When using the fuzzy logic method the similarity is defined more naturally. Within the observed regions of the NPP, the percentage of directly standardized premature death cases is almost identical with the average for the SR. The most closely observed region of SE-EMO up to 5 kilometers zone even shows the lowest percentage. Also we did not record any areas that would have unfavourable values from the wind streams perspective neither than from the local water streams recipients of SE-EBO Manivier and Dudvah. The region of SE-EMO is also within the SR average, unfavourable coherent areas of premature death case are non existent. Galanta city region comes out of the comparison with the relatively worse

Operation Performance Evaluation of Power Grid Enterprise Using a Hybrid BWM-TOPSIS Method

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Peipei You

2017-12-01

Full Text Available Electricity market reform is in progress in China, and the operational performance of power grid enterprises are vital for its healthy and sustainable development in the current electricity market environment. In this paper, a hybrid multi-criteria decision-making (MCDM framework for operational performance evaluation of a power grid enterprise is proposed from the perspective of sustainability. The latest MCDM method, namely the best-worst method (BWM was employed to determine the weights of all criteria, and the technique for order preference by similarity to an ideal solution (TOPSIS was applied to rank the operation performance of a power grid enterprise. The evaluation index system was built based on the concept of sustainability, which includes three criteria (namely economy, society, and environment and seven sub-criteria. Four power grid enterprises were selected to perform the empirical analysis, and the results indicate that power grid enterprise A1 has the best operation performance. The proposed hybrid BWM-TOPSIS-based framework for operation performance evaluation of a power grid enterprise is effective and practical.

Similar speaker recognition using nonlinear analysis

International Nuclear Information System (INIS)

Seo, J.P.; Kim, M.S.; Baek, I.C.; Kwon, Y.H.; Lee, K.S.; Chang, S.W.; Yang, S.I.

2004-01-01

Speech features of the conventional speaker identification system, are usually obtained by linear methods in spectral space. However, these methods have the drawback that speakers with similar voices cannot be distinguished, because the characteristics of their voices are also similar in spectral space. To overcome the difficulty in linear methods, we propose to use the correlation exponent in the nonlinear space as a new feature vector for speaker identification among persons with similar voices. We show that our proposed method surprisingly reduces the error rate of speaker identification system to speakers with similar voices

The strategic selecting criteria and performance by using the multiple criteria method

Directory of Open Access Journals (Sweden)

Lisa Y. Chen

2008-02-01

Full Text Available As the increasing competitive intensity in the current service market, organizational capabilities have been recognized as the importance of sustaining competitive advantage. The profitable growth for the firms has been fueled a need to systematically assess and renew the organization. The purpose of this study is to analyze the financial performance of the firms to create an effective evaluating structure for the Taiwan's service industry. This study utilized TOPSIS (technique for order preference by similarity to ideal solution method to evaluate the operating performance of 12 companies. TOPSIS is a multiple criteria decision making method to identify solutions from a finite set of alternatives based upon simultaneous minimization of distance from an ideal point and maximization of distance from a nadir point. By using this approach, this study measures the financial performance of firms through two aspects and ten indicators. The result indicated e-life had outstanding performance among the 12 retailers. The findings of this study provided managers to better understand their market position, competition, and profitability for future strategic planning and operational management.

Performance Evaluation of Methods for Estimating Achievable Throughput on Cellular Connections

DEFF Research Database (Denmark)

Mikkelsen, Lars Møller; Højholt, Nikolaj Bove; Madsen, Tatiana Kozlova

2015-01-01

The continuous increase in always connected devices and the advance in capabilities of networks and services offered via the network is evident. The target group of most of these devices and services is users, so how users perceive the network performance is of great importance. Estimating achiev...... AT, due to its much reduced resource consumption. Based on real-life measurements of the two methods we conclude that TOPP is a good candidate to estimate AT, based on similarity in results with BTC....

An adaptive image sparse reconstruction method combined with nonlocal similarity and cosparsity for mixed Gaussian-Poisson noise removal

Science.gov (United States)

Chen, Yong-fei; Gao, Hong-xia; Wu, Zi-ling; Kang, Hui

2018-01-01

Compressed sensing (CS) has achieved great success in single noise removal. However, it cannot restore the images contaminated with mixed noise efficiently. This paper introduces nonlocal similarity and cosparsity inspired by compressed sensing to overcome the difficulties in mixed noise removal, in which nonlocal similarity explores the signal sparsity from similar patches, and cosparsity assumes that the signal is sparse after a possibly redundant transform. Meanwhile, an adaptive scheme is designed to keep the balance between mixed noise removal and detail preservation based on local variance. Finally, IRLSM and RACoSaMP are adopted to solve the objective function. Experimental results demonstrate that the proposed method is superior to conventional CS methods, like K-SVD and state-of-art method nonlocally centralized sparse representation (NCSR), in terms of both visual results and quantitative measures.

Evaluation method for acoustic trapping performance by tracking motion of trapped microparticle

Science.gov (United States)

Lim, Hae Gyun; Ham Kim, Hyung; Yoon, Changhan

2018-05-01

We report a method to evaluate the performances of a single-beam acoustic tweezer using a high-frequency ultrasound transducer. The motion of a microparticle trapped by a 45-MHz single-element transducer was captured and analyzed to deduce the magnitude of trapping force. In the proposed method, the motion of a trapped microparticle was analyzed from a series of microscopy images to compute trapping force; thus, no additional equipment such as microfluidics is required. The method could be used to estimate the effective trapping force in an acoustic tweezer experiment to assess cell membrane deformability by attaching a microbead to the surface of a cell and tracking the motion of the trapped bead, which is similar to a bead-based assay that uses optical tweezers. The results showed that the trapping force increased with increasing acoustic intensity and duty factor, but the force eventually reached a plateau at a higher acoustic intensity. They demonstrated that this method could be used as a simple tool to evaluate the performance and to optimize the operating conditions of acoustic tweezers.

The semantic similarity ensemble

Directory of Open Access Journals (Sweden)

Andrea Ballatore

2013-12-01

Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

Science.gov (United States)

Swartz, R. Andrew

2013-01-01

This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

Directory of Open Access Journals (Sweden)

Wenjia Liu

2013-01-01

Full Text Available This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate.

Distinguishing the Chinese materia medica Tiepishihu from similar Dendrobium species of the same genus using histological and microscopic method.

Science.gov (United States)

Yu, Kun-Zi; Yan, Hua; Tai, Hai-Chuan; Zhang, Nan-Ping; Cheng, Xian-Long; Guo, Zeng-Xi; Ma, Shuang-Cheng; Wei, Feng

2017-07-01

The Chinese Materia Medica, Tiepishihu, used as a tonic for over one thousand years, is a well-known precious medicine in China. According to the Chinese Pharmacopoeia, its source is the species Dendrobium officinale Kimura et Migo, which is distinguished from other species in Dendrobium genus. However, these species from the same genus are similar with Tiepishihu and caused confusion in the market. To find a quick and simple method to distinguish Tiepishihu from other similar species, histologic and microscopic methods were combined together to investigate the transverse section of stem of Tiepishihu and other similar species. Phloroglucinol test solution with hydrochloric acid was used to reveal the lignified tissue by staining the transverse section of Tiepishihu and similar species. Results revealed the unique identification characteristics to distinguish Tiepishihu from similar species, which were difficult to distinguish by other methods. The identification characteristics of Tiepishihu include the cells of vascular bundle sheath were stained red, parenchyma cells were not stained red. What's more, other species can be distinguished from each other with microscopic and histological characteristics. These characteristics proved stable and can be easily observed by normal light microscopic examination. This method is rapid, accurate, stable, and inexpensive. © 2017 Wiley Periodicals, Inc.

Class attendance, peer similarity, and academic performance in a large field study

Science.gov (United States)

Bjerre-Nielsen, Andreas; Mones, Enys; Lehmann, Sune; Lassen, David Dreyer

2017-01-01

Identifying the factors that determine academic performance is an essential part of educational research. Existing research indicates that class attendance is a useful predictor of subsequent course achievements. The majority of the literature is, however, based on surveys and self-reports, methods which have well-known systematic biases that lead to limitations on conclusions and generalizability as well as being costly to implement. Here we propose a novel method for measuring class attendance that overcomes these limitations by using location and bluetooth data collected from smartphone sensors. Based on measured attendance data of nearly 1,000 undergraduate students, we demonstrate that early and consistent class attendance strongly correlates with academic performance. In addition, our novel dataset allows us to determine that attendance among social peers was substantially correlated (>0.5), suggesting either an important peer effect or homophily with respect to attendance. PMID:29117190

Class attendance, peer similarity, and academic performance in a large field study

DEFF Research Database (Denmark)

Kassarnig, Valentin; Bjerre-Nielsen, Andreas; Mones, Enys

2017-01-01

Identifying the factors that determine academic performance is an essential part of educational research. Existing research indicates that class attendance is a useful predictor of subsequent course achievements. The majority of the literature is, however, based on surveys and self-reports, methods....... Based on measured attendance data of nearly 1,000 undergraduate students, we demonstrate that early and consistent class attendance strongly correlates with academic performance. In addition, our novel dataset allows us to determine that attendance among social peers was substantially correlated (>0...

Finding Similarities in Ancient Ceramics by EDXRF and Multivariate Methods

International Nuclear Information System (INIS)

Civici, N.; Stamati, F.

1999-01-01

We have studied 39 samples of fragments from ceramic roof tiles with different stamps(Diamalas and Heraion), dated between 330 to 170 BC and found at the archaeological site of Dimales, some 30 km from the Adriatic coast. The data from these samples were compared with those obtained from 7 samples of similar objects and period with the stamp H eraion , found at the archaeological site of APOLLONIA. The samples were analyzed by energy-dispersive X -ray fluorescence(EDXRF), using of the x-ray lines of the elements to the intensity of the Compton peak. The results have been treated with diverse multivariate methods. The application of hierarchical cluster analysis and factor analysis permitted the identification of two main clusters. The first cluster is composed from the ''Heraion'' samples discovered in Apollonia, while the second comprises all the samples discovered in Dimale independent of their stamp. (authors)

Neutron-Gamma Pulse Shape Discrimination With Ne-213 Liquid Scintillator By Using Digital Signal Processing Combined With Similarity Method

International Nuclear Information System (INIS)

Mardiyanto

2008-01-01

Neutron-Gamma Pulse Shape Discrimination with a NE-213 Liquid Scintillator by Using Digital Signal Processing Combined with Similarity Method. Measurement of mixed neutron-gamma radiation is difficult because a nuclear detector is usually sensitive to both radiations. A new attempt of neutron-gamma pulse shape discrimination for a NE-213 liquid scintillator is presented by using digital signal processing combined with an off-line similarity method. The output pulse shapes are digitized with a high speed digital oscilloscope. The n-γ discrimination is done by calculating the index of each pulse shape, which is determined by the similarity method, and then fusing it with its corresponding pulse height. Preliminary results demonstrate good separation of neutron and gamma-ray signals from a NE-213 scintillator with a simple digital system. The results were better than those with a conventional rise time method. Figure of Merit is used to determine the quality of discrimination. The figure of merit of the discrimination using digital signal processing combined with off-line similarity method are 1.9; 1.7; 1.1; 1.1; and 0.8; on the other hand by using conventional method the rise time are 0.9; 0.9; 0.9; 0.7; and 0.4 for the equivalent electron energy of 800; 278; 139; 69; and 30 keV. (author)

Learning semantic and visual similarity for endomicroscopy video retrieval.

Science.gov (United States)

Andre, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2012-06-01

Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them

Biorthogonal projected energies of a Gutzwiller similarity transformed Hamiltonian.

Science.gov (United States)

Wahlen-Strothman, J M; Scuseria, G E

2016-12-07

We present a method incorporating biorthogonal orbital-optimization, symmetry projection, and double-occupancy screening with a non-unitary similarity transformation generated by the Gutzwiller factor [Formula: see text], and apply it to the Hubbard model. Energies are calculated with mean-field computational scaling with high-quality results comparable to coupled cluster singles and doubles. This builds on previous work performing similarity transformations with more general, two-body Jastrow-style correlators. The theory is tested on 2D lattices ranging from small systems into the thermodynamic limit and is compared to available reference data.

Markov chain-based mass estimation method for loose part monitoring system and its performance

Directory of Open Access Journals (Sweden)

Sung-Hwan Shin

2017-10-01

Full Text Available A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

Neutrosophic Cubic MCGDM Method Based on Similarity Measure

Directory of Open Access Journals (Sweden)

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.

Genetic similarity of soybean genotypes revealed by seed protein

Directory of Open Access Journals (Sweden)

Nikolić Ana

2005-01-01

Full Text Available More accurate and complete descriptions of genotypes could help determinate future breeding strategies and facilitate introgression of new genotypes in current soybean genetic pool. The objective of this study was to characterize 20 soybean genotypes from the Maize Research Institute "Zemun Polje" collection, which have good agronomic performances, high yield, lodging and drought resistance, and low shuttering by seed proteins as biochemical markers. Seed proteins were isolated and separated by PAA electrophoresis. On the basis of the presence/absence of protein fractions coefficients of similarity were calculated as Dice and Roger and Tanamoto coefficient between pairs of genotypes. The similarity matrix was submitted for hierarchical cluster analysis of un weighted pair group using arithmetic average (UPGMA method and necessary computation were performed using NTSYS-pc program. Protein seed analysis confirmed low level of genetic diversity in soybean. The highest genetic similarity was between genotypes P9272 and Kador. According to obtained results, soybean genotypes were assigned in two larger groups and coefficients of similarity showed similar results. Because of the lack of pedigree data for analyzed genotypes, correspondence with marker data could not be determined. In plant with a narrow genetic base in their gene pool, such as soybean, protein markers may not be sufficient for characterization and study of genetic diversity.

Depth compensating calculation method of computer-generated holograms using symmetry and similarity of zone plates

Science.gov (United States)

Wei, Hui; Gong, Guanghong; Li, Ni

2017-10-01

Computer-generated hologram (CGH) is a promising 3D display technology while it is challenged by heavy computation load and vast memory requirement. To solve these problems, a depth compensating CGH calculation method based on symmetry and similarity of zone plates is proposed and implemented on graphics processing unit (GPU). An improved LUT method is put forward to compute the distances between object points and hologram pixels in the XY direction. The concept of depth compensating factor is defined and used for calculating the holograms of points with different depth positions instead of layer-based methods. The proposed method is suitable for arbitrary sampling objects with lower memory usage and higher computational efficiency compared to other CGH methods. The effectiveness of the proposed method is validated by numerical and optical experiments.

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.

Science.gov (United States)

Gong, Kuang; Cheng-Liao, Jinxiu; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2018-04-01

Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.

InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk.

Science.gov (United States)

Cheng, Liang; Jiang, Yue; Ju, Hong; Sun, Jie; Peng, Jiajie; Zhou, Meng; Hu, Yang

2018-01-19

Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human Phenotype Ontology (HPO). Because of the advantage of identifying novel relationships between terms, calculating similarity between ontology terms is one of the major tasks in this research area. Though similarities between terms within each ontology have been studied with in silico methods, term similarities across different ontologies were not investigated as deeply. The latest method took advantage of gene functional interaction network (GFIN) to explore such inter-ontology similarities of terms. However, it only used gene interactions and failed to make full use of the connectivity among gene nodes of the network. In addition, all existent methods are particularly designed for GO and their performances on the extended ontology community remain unknown. We proposed a method InfAcrOnt to infer similarities between terms across ontologies utilizing the entire GFIN. InfAcrOnt builds a term-gene-gene network which comprised ontology annotations and GFIN, and acquires similarities between terms across ontologies through modeling the information flow within the network by random walk. In our benchmark experiments on sub-ontologies of GO, InfAcrOnt achieves a high average area under the receiver operating characteristic curve (AUC) (0.9322 and 0.9309) and low standard deviations (1.8746e-6 and 3.0977e-6) in both human and yeast benchmark datasets exhibiting superior performance. Meanwhile, comparisons of InfAcrOnt results and prior knowledge on pair-wise DO-HPO terms and pair-wise DO-GO terms show high correlations. The experiment results show that InfAcrOnt significantly improves the performance of inferring similarities between terms across ontologies in benchmark set.

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

A new similarity index for nonlinear signal analysis based on local extrema patterns

Science.gov (United States)

Niknazar, Hamid; Motie Nasrabadi, Ali; Shamsollahi, Mohammad Bagher

2018-02-01

Common similarity measures of time domain signals such as cross-correlation and Symbolic Aggregate approximation (SAX) are not appropriate for nonlinear signal analysis. This is because of the high sensitivity of nonlinear systems to initial points. Therefore, a similarity measure for nonlinear signal analysis must be invariant to initial points and quantify the similarity by considering the main dynamics of signals. The statistical behavior of local extrema (SBLE) method was previously proposed to address this problem. The SBLE similarity index uses quantized amplitudes of local extrema to quantify the dynamical similarity of signals by considering patterns of sequential local extrema. By adding time information of local extrema as well as fuzzifying quantized values, this work proposes a new similarity index for nonlinear and long-term signal analysis, which extends the SBLE method. These new features provide more information about signals and reduce noise sensitivity by fuzzifying them. A number of practical tests were performed to demonstrate the ability of the method in nonlinear signal clustering and classification on synthetic data. In addition, epileptic seizure detection based on electroencephalography (EEG) signal processing was done by the proposed similarity to feature the potentials of the method as a real-world application tool.

Similarity indices of meteo-climatic gauging stations: definition and comparison.

Science.gov (United States)

Barca, Emanuele; Bruno, Delia Evelina; Passarella, Giuseppe

2016-07-01

Space-time dependencies among monitoring network stations have been investigated to detect and quantify similarity relationships among gauging stations. In this work, besides the well-known rank correlation index, two new similarity indices have been defined and applied to compute the similarity matrix related to the Apulian meteo-climatic monitoring network. The similarity matrices can be applied to address reliably the issue of missing data in space-time series. In order to establish the effectiveness of the similarity indices, a simulation test was then designed and performed with the aim of estimating missing monthly rainfall rates in a suitably selected gauging station. The results of the simulation allowed us to evaluate the effectiveness of the proposed similarity indices. Finally, the multiple imputation by chained equations method was used as a benchmark to have an absolute yardstick for comparing the outcomes of the test. In conclusion, the new proposed multiplicative similarity index resulted at least as reliable as the selected benchmark.

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.

Similarity measures for face recognition

CERN Document Server

Vezzetti, Enrico

2015-01-01

Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.

Prioritization of candidate disease genes by topological similarity between disease and protein diffusion profiles.

Science.gov (United States)

Zhu, Jie; Qin, Yufang; Liu, Taigang; Wang, Jun; Zheng, Xiaoqi

2013-01-01

Identification of gene-phenotype relationships is a fundamental challenge in human health clinic. Based on the observation that genes causing the same or similar phenotypes tend to correlate with each other in the protein-protein interaction network, a lot of network-based approaches were proposed based on different underlying models. A recent comparative study showed that diffusion-based methods achieve the state-of-the-art predictive performance. In this paper, a new diffusion-based method was proposed to prioritize candidate disease genes. Diffusion profile of a disease was defined as the stationary distribution of candidate genes given a random walk with restart where similarities between phenotypes are incorporated. Then, candidate disease genes are prioritized by comparing their diffusion profiles with that of the disease. Finally, the effectiveness of our method was demonstrated through the leave-one-out cross-validation against control genes from artificial linkage intervals and randomly chosen genes. Comparative study showed that our method achieves improved performance compared to some classical diffusion-based methods. To further illustrate our method, we used our algorithm to predict new causing genes of 16 multifactorial diseases including Prostate cancer and Alzheimer's disease, and the top predictions were in good consistent with literature reports. Our study indicates that integration of multiple information sources, especially the phenotype similarity profile data, and introduction of global similarity measure between disease and gene diffusion profiles are helpful for prioritizing candidate disease genes. Programs and data are available upon request.

Do Tillage Methods Affect Germination and Species Similarity of Soil Weed Seeds Bank?

Directory of Open Access Journals (Sweden)

Shahgholi Hassan

2015-12-01

Full Text Available Cultural practices such as tillage used for crop production influence the composition of the weed seed bank in the soil. In order to investigate the effects of different tillage methods on seed bank properties, species diversity and similarity, two laboratory and greenhouse experiments were carried out as randomized complete block design with four replications in 2011. Treatments included: once tillage per year (T1, twice tillage per year (T2, more than twice tillage (T3 and no tillage (T4. Laboratory results showed that the T3 and T4 treatments had the highest and the lowest observed seeds numbers, respectively. Between the laboratory observed weed seeds, the maximum weed seed numbers were Echinochloa crus-galli and Amaranthus retroflexus in the T3 treatment, while Chenopodium album, Polygonum aviculare and Cuscuta campestris had the highest seed numbers in the T2 treatment. At the greenhouse study, Chenopodium album, Amaranthus retroflexus and Hordeum morinum in the T2 treatment were dominant species. The highest diversity was observed in the T2 treatment, and Chenopodium album and Echinochloa crus-galli were dominant species in the T2 and T3 treatments. Maximum species similarity index was achieved from the T1 and T3 treatments. Thereby this study concluded that increasing of tillage number could affect the similarity index of weed seeds and subsequently alters the weed community composition.

A method for optimizing the performance of buildings

DEFF Research Database (Denmark)

Pedersen, Frank

2007-01-01

needed for solving the optimization problem. Furthermore, the algorithm uses so-called domain constraint functions in order to ensure that the input to the simulation software is feasible. Using this technique avoids performing time-consuming simulations for unrealistic design decisions. The algorithm......This thesis describes a method for optimizing the performance of buildings. Design decisions made in early stages of the building design process have a significant impact on the performance of buildings, for instance, the performance with respect to the energy consumption, economical aspects......, and the indoor environment. The method is intended for supporting design decisions for buildings, by combining methods for calculating the performance of buildings with numerical optimization methods. The method is able to find optimum values of decision variables representing different features of the building...

Similarity Analysis of Cable Insulations by Chemical Test

Energy Technology Data Exchange (ETDEWEB)

Kim, Jong Seog [Central Research Institute of Korea Hydro and Nuclear Power Co., Daejeon (Korea, Republic of)

2013-10-15

As result of this experiment, it was found that FT-IR test for material composition, TGA test for aging trend are applicable for similarity analysis of cable materials. OIT is recommended as option if TGA doesn't show good trend. Qualification of new insulation by EQ report of old insulation should be based on higher activation energy of new insulation than that of old one in the consideration of conservatism. In old nuclear power plant, it is easy to find black cable which has no marking of cable information such as manufacturer, material name and voltage. If a type test is required for qualification of these cables, how could I select representative cable? How could I determine the similarity of these cables? If manufacturer has qualified a cable for nuclear power plant more than a decade ago and composition of cable material is changed with similar one, is it acceptable to use the old EQ report for recently manufactured cable? It is well known to use FT-IR method to determine the similarity of cable materials. Infrared ray is easy tool to compare compositions of each material. But, it is not proper to compare aging trend of these materials. Study for similarity analysis of cable insulation by chemical test is described herein. To study a similarity evaluation method for polymer materials, FT-IR, TGA and OIT tests were performed for two cable insulation(old and new) which were supplied from same manufacturer. FT-IR shows good result to compare material compositions while TGA and OIT show good result to compare aging character of materials.

Similarity Analysis of Cable Insulations by Chemical Test

International Nuclear Information System (INIS)

Kim, Jong Seog

2013-01-01

As result of this experiment, it was found that FT-IR test for material composition, TGA test for aging trend are applicable for similarity analysis of cable materials. OIT is recommended as option if TGA doesn't show good trend. Qualification of new insulation by EQ report of old insulation should be based on higher activation energy of new insulation than that of old one in the consideration of conservatism. In old nuclear power plant, it is easy to find black cable which has no marking of cable information such as manufacturer, material name and voltage. If a type test is required for qualification of these cables, how could I select representative cable? How could I determine the similarity of these cables? If manufacturer has qualified a cable for nuclear power plant more than a decade ago and composition of cable material is changed with similar one, is it acceptable to use the old EQ report for recently manufactured cable? It is well known to use FT-IR method to determine the similarity of cable materials. Infrared ray is easy tool to compare compositions of each material. But, it is not proper to compare aging trend of these materials. Study for similarity analysis of cable insulation by chemical test is described herein. To study a similarity evaluation method for polymer materials, FT-IR, TGA and OIT tests were performed for two cable insulation(old and new) which were supplied from same manufacturer. FT-IR shows good result to compare material compositions while TGA and OIT show good result to compare aging character of materials

Gait Recognition Using Image Self-Similarity

Directory of Open Access Journals (Sweden)

Chiraz BenAbdelkader

2004-04-01

Full Text Available Gait is one of the few biometrics that can be measured at a distance, and is hence useful for passive surveillance as well as biometric applications. Gait recognition research is still at its infancy, however, and we have yet to solve the fundamental issue of finding gait features which at once have sufficient discrimination power and can be extracted robustly and accurately from low-resolution video. This paper describes a novel gait recognition technique based on the image self-similarity of a walking person. We contend that the similarity plot encodes a projection of gait dynamics. It is also correspondence-free, robust to segmentation noise, and works well with low-resolution video. The method is tested on multiple data sets of varying sizes and degrees of difficulty. Performance is best for fronto-parallel viewpoints, whereby a recognition rate of 98% is achieved for a data set of 6 people, and 70% for a data set of 54 people.

Alternative test method to assess the energy performance of frost-free refrigerating appliances

International Nuclear Information System (INIS)

Hermes, Christian J.L.; Melo, Cláudio; Knabben, Fernando T.

2013-01-01

This paper outlines an alternative test method to evaluate the energy consumption of frost-free refrigerators and freezers for residential applications. While the standardized methods require the refrigerating appliance to be kept running according to its onboard control system, which usually drives the refrigerator through an on–off cycling pattern, the proposed approach assesses the refrigerator energy performance in the steady-state regime, being therefore much faster and more reliable. In this procedure, the cooling capacity is matched to the cooling loads by PID-controlled electrical heaters installed within the refrigerated compartments, so that the compartment temperatures are kept at the desired standardized levels. Comparisons between the experimental results obtained using the steady-state energy test and the standardized procedures showed that the former follows closely the trends observed for the latter. - Highlights: ► An alternative test method to assess the energy consumption of refrigerators is proposed. ► PID-controlled electrical heaters were installed within the compartments. ► Steady-state and ISO energy tests were performed and compared. ► Both proposed and standardized test procedures showed similar trends.

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

Directory of Open Access Journals (Sweden)

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.

Efficient similarity-based data clustering by optimal object to cluster reallocation.

Science.gov (United States)

Rossignol, Mathias; Lagrange, Mathieu; Cont, Arshia

2018-01-01

We present an iterative flat hard clustering algorithm designed to operate on arbitrary similarity matrices, with the only constraint that these matrices be symmetrical. Although functionally very close to kernel k-means, our proposal performs a maximization of average intra-class similarity, instead of a squared distance minimization, in order to remain closer to the semantics of similarities. We show that this approach permits the relaxing of some conditions on usable affinity matrices like semi-positiveness, as well as opening possibilities for computational optimization required for large datasets. Systematic evaluation on a variety of data sets shows that compared with kernel k-means and the spectral clustering methods, the proposed approach gives equivalent or better performance, while running much faster. Most notably, it significantly reduces memory access, which makes it a good choice for large data collections. Material enabling the reproducibility of the results is made available online.

The In-Medium Similarity Renormalization Group: A novel ab initio method for nuclei

Energy Technology Data Exchange (ETDEWEB)

Hergert, H., E-mail: hergert@nscl.msu.edu [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States); Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States); Department of Physics, The Ohio State University, Columbus, OH 43210 (United States); Bogner, S.K., E-mail: bogner@nscl.msu.edu [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States); Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States); Morris, T.D., E-mail: morrist@nscl.msu.edu [Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States); National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States); Schwenk, A., E-mail: schwenk@physik.tu-darmstadt.de [Institut für Kernphysik, Technische Universität Darmstadt, 64289 Darmstadt (Germany); ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum für Schwerionenforschung GmbH, 64291 Darmstadt (Germany); Tsukiyama, K., E-mail: tsuki.kr@gmail.com [Center for Nuclear Study, Graduate School of Science, University of Tokyo, Hongo, Tokyo, 113-0033 (Japan)

2016-03-21

We present a comprehensive review of the In-Medium Similarity Renormalization Group (IM-SRG), a novel ab initio method for nuclei. The IM-SRG employs a continuous unitary transformation of the many-body Hamiltonian to decouple the ground state from all excitations, thereby solving the many-body problem. Starting from a pedagogical introduction of the underlying concepts, the IM-SRG flow equations are developed for systems with and without explicit spherical symmetry. We study different IM-SRG generators that achieve the desired decoupling, and how they affect the details of the IM-SRG flow. Based on calculations of closed-shell nuclei, we assess possible truncations for closing the system of flow equations in practical applications, as well as choices of the reference state. We discuss the issue of center-of-mass factorization and demonstrate that the IM-SRG ground-state wave function exhibits an approximate decoupling of intrinsic and center-of-mass degrees of freedom, similar to Coupled Cluster (CC) wave functions. To put the IM-SRG in context with other many-body methods, in particular many-body perturbation theory and non-perturbative approaches like CC, a detailed perturbative analysis of the IM-SRG flow equations is carried out. We conclude with a discussion of ongoing developments, including IM-SRG calculations with three-nucleon forces, the multi-reference IM-SRG for open-shell nuclei, first non-perturbative derivations of shell-model interactions, and the consistent evolution of operators in the IM-SRG. We dedicate this review to the memory of Gerry Brown, one of the pioneers of many-body calculations of nuclei.

The In-Medium Similarity Renormalization Group: A novel ab initio method for nuclei

International Nuclear Information System (INIS)

Hergert, H.; Bogner, S.K.; Morris, T.D.; Schwenk, A.; Tsukiyama, K.

2016-01-01

We present a comprehensive review of the In-Medium Similarity Renormalization Group (IM-SRG), a novel ab initio method for nuclei. The IM-SRG employs a continuous unitary transformation of the many-body Hamiltonian to decouple the ground state from all excitations, thereby solving the many-body problem. Starting from a pedagogical introduction of the underlying concepts, the IM-SRG flow equations are developed for systems with and without explicit spherical symmetry. We study different IM-SRG generators that achieve the desired decoupling, and how they affect the details of the IM-SRG flow. Based on calculations of closed-shell nuclei, we assess possible truncations for closing the system of flow equations in practical applications, as well as choices of the reference state. We discuss the issue of center-of-mass factorization and demonstrate that the IM-SRG ground-state wave function exhibits an approximate decoupling of intrinsic and center-of-mass degrees of freedom, similar to Coupled Cluster (CC) wave functions. To put the IM-SRG in context with other many-body methods, in particular many-body perturbation theory and non-perturbative approaches like CC, a detailed perturbative analysis of the IM-SRG flow equations is carried out. We conclude with a discussion of ongoing developments, including IM-SRG calculations with three-nucleon forces, the multi-reference IM-SRG for open-shell nuclei, first non-perturbative derivations of shell-model interactions, and the consistent evolution of operators in the IM-SRG. We dedicate this review to the memory of Gerry Brown, one of the pioneers of many-body calculations of nuclei.

Optic Disc Detection from Fundus Photography via Best-Buddies Similarity

Directory of Open Access Journals (Sweden)

Kangning Hou

2018-05-01

Full Text Available Robust and effective optic disc (OD detection is a necessary processing step in the research work of the automatic analysis of fundus images. In this paper, we propose a novel and robust method for the automated detection of ODs from fundus photographs. It is essentially carried out by performing template matching using the Best-Buddies Similarity (BBS measure between the hand-marked OD region and the small parts of target images. For well characterizing the local spatial information of fundus images, a gradient constraint term was introduced for computing the BBS measurement. The performance of the proposed method is validated with Digital Retinal Images for Vessel Extraction (DRIVE and Standard Diabetic Retinopathy Database Calibration Level 1 (DIARETDB1 databases, and quantitative results were obtained. Success rates/error distances of 100%/10.4 pixel and of 97.7%/12.9 pixel, respectively, were achieved. The algorithm has been tested and compared with other commonly used methods, and the results show that the proposed method shows superior performance.

Comparison of Various Similarity Measures for Average Image Hash in Mobile Phone Application

Science.gov (United States)

Farisa Chaerul Haviana, Sam; Taufik, Muhammad

2017-04-01

One of the main issue in Content Based Image Retrieval (CIBR) is similarity measures for resulting image hashes. The main key challenge is to find the most benefits distance or similarity measures for calculating the similarity in term of speed and computing costs, specially under limited computing capabilities device like mobile phone. This study we utilize twelve most common and popular distance or similarity measures technique implemented in mobile phone application, to be compared and studied. The results show that all similarity measures implemented in this study was perform equally under mobile phone application. This gives more possibilities for method combinations to be implemented for image retrieval.

Performance Analysis and Application of Three Different Computational Methods for Solar Heating System with Seasonal Water Tank Heat Storage

Directory of Open Access Journals (Sweden)

Dongliang Sun

2013-01-01

Full Text Available We analyze and compare three different computational methods for a solar heating system with seasonal water tank heat storage (SHS-SWTHS. These methods are accurate numerical method, temperature stratification method, and uniform temperature method. The accurate numerical method can accurately predict the performance of the system, but it takes about 4 to 5 weeks, which is too long and hard for the performance analysis of this system. The temperature stratification method obtains relatively accurate computation results and takes a relatively short computation time, which is about 2 to 3 hours. Therefore, this method is most suitable for the performance analysis of this system. The deviation of the computational results of the uniform temperature method is great, and the time consumed is similar to that of the temperature stratification method. Therefore, this method is not recommended herein. Based on the above analyses, the temperature stratification method is applied to analyze the influence of the embedded depth of water tank, the thickness of thermal insulation material, and the collection area on the performance of this system. The results will provide a design basis for the related demonstration projects.

Similar inflammatory responses following sprint interval training performed in hypoxia and normoxia

Directory of Open Access Journals (Sweden)

Alan James Richardson

2016-08-01

Full Text Available Sprint interval training (SIT is an efficient intervention capable of improving aerobic capacity and exercise performance. This experiment aimed to determine differences in training adaptations and the inflammatory responses following 2 weeks of SIT (30s maximal work, 4 min recovery; 4-7 repetitions performed in normoxia or hypoxia. Forty-two untrained participants [(mean ± SD, age 21 ±1 yrs, body mass 72.1 ±11.4 kg and height 173 ±10 cm] were equally and randomly assigned to one of three groups; control (CONT; no training, n = 14, normoxic (NORM; SIT in FiO2: 0.21, n = 14 and normobaric hypoxic (HYP; SIT in FiO2: 0.15, n = 14. Participants completed a V̇O2peak test, a time to exhaustion (TTE trial (power = 80% V̇O2peak and had haematological [haemoglobin (Hb, haematocrit (Hct] and inflammatory markers [interleukin-6 (IL-6, tumor necrosis factor-α (TNFα] measured in a resting state, pre and post SIT. V̇O2peak (mL.kg-1.min-1 improved in HYP (+11.9% and NORM (+9.8%, but not CON (+0.9%. Similarly TTE improved in HYP (+32.2% and NORM (+33.0%, but not CON (+3.4% whilst the power at the anaerobic threshold (AT; W.kg-1 also improved in HYP (+13.3% and NORM (+8.0%, but not CON (-0.3%. AT (mL.kg-1.min-1 improved in HYP (+9.5%, but not NORM (+5% or CON (-0.3%. No between group change occurred in 30 s sprint performance or Hb and Hct. IL-6 increased in HYP (+17.4% and NORM (+20.1%, but not CON (+1.2% respectively. TNF-α increased in HYP (+10.8% NORM (+12.9% and CON (+3.4%.SIT in HYP and NORM increased VO2peak, power at AT and TTE performance in untrained individuals, improvements in AT occurred only when SIT was performed in HYP. Increases in IL-6 and TNFα reflect a training induced inflammatory response to SIT; hypoxic conditions do not exacerbate this.

Validation of the Mnemonic Similarity Task – Context Version

Directory of Open Access Journals (Sweden)

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.

A general method for assessing brain-computer interface performance and its limitations

Science.gov (United States)

Hill, N. Jeremy; Häuser, Ann-Katrin; Schalk, Gerwin

2014-04-01

Objective. When researchers evaluate brain-computer interface (BCI) systems, we want quantitative answers to questions such as: How good is the system’s performance? How good does it need to be? and: Is it capable of reaching the desired level in future? In response to the current lack of objective, quantitative, study-independent approaches, we introduce methods that help to address such questions. We identified three challenges: (I) the need for efficient measurement techniques that adapt rapidly and reliably to capture a wide range of performance levels; (II) the need to express results in a way that allows comparison between similar but non-identical tasks; (III) the need to measure the extent to which certain components of a BCI system (e.g. the signal processing pipeline) not only support BCI performance, but also potentially restrict the maximum level it can reach. Approach. For challenge (I), we developed an automatic staircase method that adjusted task difficulty adaptively along a single abstract axis. For challenge (II), we used the rate of information gain between two Bernoulli distributions: one reflecting the observed success rate, the other reflecting chance performance estimated by a matched random-walk method. This measure includes Wolpaw’s information transfer rate as a special case, but addresses the latter’s limitations including its restriction to item-selection tasks. To validate our approach and address challenge (III), we compared four healthy subjects’ performance using an EEG-based BCI, a ‘Direct Controller’ (a high-performance hardware input device), and a ‘Pseudo-BCI Controller’ (the same input device, but with control signals processed by the BCI signal processing pipeline). Main results. Our results confirm the repeatability and validity of our measures, and indicate that our BCI signal processing pipeline reduced attainable performance by about 33% (21 bits min-1). Significance. Our approach provides a flexible basis

Similarity Structure of Wave-Collapse

DEFF Research Database (Denmark)

Rypdal, Kristoffer; Juul Rasmussen, Jens; Thomsen, Kenneth

1985-01-01

Similarity transformations of the cubic Schrödinger equation (CSE) are investigated. The transformations are used to remove the explicit time variation in the CSE and reduce it to differential equations in the spatial variables only. Two different methods for similarity reduction are employed and...

A comparative analysis of Painleve, Lax pair, and similarity transformation methods in obtaining the integrability conditions of nonlinear Schroedinger equations

International Nuclear Information System (INIS)

Al Khawaja, U.

2010-01-01

We derive the integrability conditions of nonautonomous nonlinear Schroedinger equations using the Lax pair and similarity transformation methods. We present a comparative analysis of these integrability conditions with those of the Painleve method. We show that while the Painleve integrability conditions restrict the dispersion, nonlinearity, and dissipation/gain coefficients to be space independent and the external potential to be only a quadratic function of position, the Lax Pair and the similarity transformation methods allow for space-dependent coefficients and an external potential that is not restricted to the quadratic form. The integrability conditions of the Painleve method are retrieved as a special case of our general integrability conditions. We also derive the integrability conditions of nonautonomous nonlinear Schroedinger equations for two- and three-spacial dimensions.

Mixed Methods and Action Research: similar or different?

OpenAIRE

Wiśniewska, Danuta

2011-01-01

This article attempts to analyse and compare ELT studies grounded solely in mixed methods and ELT action research studies based on a mixed methods approach in order to identify to what degree action research studies combining different methods in a single study comply with the principles of rigorous mixed methods study.

Development of a high performance liquid chromatography method ...

African Journals Online (AJOL)

Development of a high performance liquid chromatography method for simultaneous ... Purpose: To develop and validate a new low-cost high performance liquid chromatography (HPLC) method for ..... Several papers have reported the use of ...

Empirical Performance of Cross-Validation With Oracle Methods in a Genomics Context.

Science.gov (United States)

Martinez, Josue G; Carroll, Raymond J; Müller, Samuel; Sampson, Joshua N; Chatterjee, Nilanjan

2011-11-01

When employing model selection methods with oracle properties such as the smoothly clipped absolute deviation (SCAD) and the Adaptive Lasso, it is typical to estimate the smoothing parameter by m-fold cross-validation, for example, m = 10. In problems where the true regression function is sparse and the signals large, such cross-validation typically works well. However, in regression modeling of genomic studies involving Single Nucleotide Polymorphisms (SNP), the true regression functions, while thought to be sparse, do not have large signals. We demonstrate empirically that in such problems, the number of selected variables using SCAD and the Adaptive Lasso, with 10-fold cross-validation, is a random variable that has considerable and surprising variation. Similar remarks apply to non-oracle methods such as the Lasso. Our study strongly questions the suitability of performing only a single run of m-fold cross-validation with any oracle method, and not just the SCAD and Adaptive Lasso.

Influence of heat treatment on fatigue performances for self-piercing riveting similar and dissimilar titanium, aluminium and copper alloys

OpenAIRE

Zhang, Xianlian; He, Xiaocong; Xing, Baoying; Zhao, Lun; Lu, Yi; Gu, Fengshou; Ball, Andrew

2016-01-01

The fatigue performances of self-piercing riveting (SPR) joints connecting similar and dissimilar sheets of TA1 titanium alloy (TA1), Al5052 aluminium alloy (Al5052) and H62 copper alloy (H62) were studied in this paper. The specimens of similar TA1 sheets treated with stress relief annealing were prepared to investigate the influence of relief annealing on the mechanical properties of SPR joints. Fatigue tests were conducted to characterize the fatigue lives and failure modes of the joints. ...

Enhancement of chemical entity identification in text using semantic similarity validation.

Directory of Open Access Journals (Sweden)

Tiago Grego

Full Text Available With the amount of chemical data being produced and reported in the literature growing at a fast pace, it is increasingly important to efficiently retrieve this information. To tackle this issue text mining tools have been applied, but despite their good performance they still provide many errors that we believe can be filtered by using semantic similarity. Thus, this paper proposes a novel method that receives the results of chemical entity identification systems, such as Whatizit, and exploits the semantic relationships in ChEBI to measure the similarity between the entities found in the text. The method assigns a single validation score to each entity based on its similarities with the other entities also identified in the text. Then, by using a given threshold, the method selects a set of validated entities and a set of outlier entities. We evaluated our method using the results of two state-of-the-art chemical entity identification tools, three semantic similarity measures and two text window sizes. The method was able to increase precision without filtering a significant number of correctly identified entities. This means that the method can effectively discriminate the correctly identified chemical entities, while discarding a significant number of identification errors. For example, selecting a validation set with 75% of all identified entities, we were able to increase the precision by 28% for one of the chemical entity identification tools (Whatizit, maintaining in that subset 97% the correctly identified entities. Our method can be directly used as an add-on by any state-of-the-art entity identification tool that provides mappings to a database, in order to improve their results. The proposed method is included in a freely accessible web tool at www.lasige.di.fc.ul.pt/webtools/ice/.

Using concept similarity in cross ontology for adaptive e-Learning systems

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B. Saleena

2015-01-01

Full Text Available e-Learning is one of the most preferred media of learning by the learners. The learners search the web to gather knowledge about a particular topic from the information in the repositories. Retrieval of relevant materials from a domain can be easily implemented if the information is organized and related in some way. Ontologies are a key concept that helps us to relate information for providing the more relevant lessons to the learner. This paper proposes an adaptive e-Learning system, which generates a user specific e-Learning content by comparing the concepts with more than one system using similarity measures. A cross ontology measure is defined, which consists of fuzzy domain ontology as the primary ontology and the domain expert’s ontology as the secondary ontology, for the comparison process. A personalized document is provided to the user with a user profile, which includes the data obtained from the processing of the proposed method under a User score, which is obtained through the user evaluation. The results of the proposed e-Learning system under the designed cross ontology similarity measure show a significant increase in performance and accuracy under different conditions. The assessment of the comparative analysis, showed the difference in performance of our proposed method over other methods. Based on the assessment results it is proved that the proposed approach is effective over other methods.

Neighborhood Structural Similarity Mapping for the Classification of Masses in Mammograms.

Science.gov (United States)

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree

2018-05-01

In this paper, two novel feature extraction methods, using neighborhood structural similarity (NSS), are proposed for the characterization of mammographic masses as benign or malignant. Since gray-level distribution of pixels is different in benign and malignant masses, more regular and homogeneous patterns are visible in benign masses compared to malignant masses; the proposed method exploits the similarity between neighboring regions of masses by designing two new features, namely, NSS-I and NSS-II, which capture global similarity at different scales. Complementary to these global features, uniform local binary patterns are computed to enhance the classification efficiency by combining with the proposed features. The performance of the features are evaluated using the images from the mini-mammographic image analysis society (mini-MIAS) and digital database for screening mammography (DDSM) databases, where a tenfold cross-validation technique is incorporated with Fisher linear discriminant analysis, after selecting the optimal set of features using stepwise logistic regression method. The best area under the receiver operating characteristic curve of 0.98 with an accuracy of is achieved with the mini-MIAS database, while the same for the DDSM database is 0.93 with accuracy .

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)

Protein structural similarity search by Ramachandran codes

Directory of Open Access Journals (Sweden)

Chang Chih-Hung

2007-08-01

Full Text Available Abstract Background Protein structural data has increased exponentially, such that fast and accurate tools are necessary to access structure similarity search. To improve the search speed, several methods have been designed to reduce three-dimensional protein structures to one-dimensional text strings that are then analyzed by traditional sequence alignment methods; however, the accuracy is usually sacrificed and the speed is still unable to match sequence similarity search tools. Here, we aimed to improve the linear encoding methodology and develop efficient search tools that can rapidly retrieve structural homologs from large protein databases. Results We propose a new linear encoding method, SARST (Structural similarity search Aided by Ramachandran Sequential Transformation. SARST transforms protein structures into text strings through a Ramachandran map organized by nearest-neighbor clustering and uses a regenerative approach to produce substitution matrices. Then, classical sequence similarity search methods can be applied to the structural similarity search. Its accuracy is similar to Combinatorial Extension (CE and works over 243,000 times faster, searching 34,000 proteins in 0.34 sec with a 3.2-GHz CPU. SARST provides statistically meaningful expectation values to assess the retrieved information. It has been implemented into a web service and a stand-alone Java program that is able to run on many different platforms. Conclusion As a database search method, SARST can rapidly distinguish high from low similarities and efficiently retrieve homologous structures. It demonstrates that the easily accessible linear encoding methodology has the potential to serve as a foundation for efficient protein structural similarity search tools. These search tools are supposed applicable to automated and high-throughput functional annotations or predictions for the ever increasing number of published protein structures in this post-genomic era.

Improvement in Performance of ZnO based DSC Prepared by Spraying Method

Directory of Open Access Journals (Sweden)

Rangga Winantyo

2013-09-01

Full Text Available This paper reports the effect of TiCl4 on the performance of ZnO based DSC. ZnO was used due to its stability against photo-corrosion  and  photochemical  properties  similar  to  TiO2.  Thin  films  of  nanocrystalline  ZnO  were  deposited  on transparent conducting oxide glass using spray  method. The ZnO  films  were treated using TiCl4. The cell’s efficiency was found to be 2.5% with TiCl4 post-treatment and 1.9% without TiCl4 post-treatment.

Measuring transferring similarity via local information

Science.gov (United States)

Yin, Likang; Deng, Yong

2018-05-01

Recommender systems have developed along with the web science, and how to measure the similarity between users is crucial for processing collaborative filtering recommendation. Many efficient models have been proposed (i.g., the Pearson coefficient) to measure the direct correlation. However, the direct correlation measures are greatly affected by the sparsity of dataset. In other words, the direct correlation measures would present an inauthentic similarity if two users have a very few commonly selected objects. Transferring similarity overcomes this drawback by considering their common neighbors (i.e., the intermediates). Yet, the transferring similarity also has its drawback since it can only provide the interval of similarity. To break the limitations, we propose the Belief Transferring Similarity (BTS) model. The contributions of BTS model are: (1) BTS model addresses the issue of the sparsity of dataset by considering the high-order similarity. (2) BTS model transforms uncertain interval to a certain state based on fuzzy systems theory. (3) BTS model is able to combine the transferring similarity of different intermediates using information fusion method. Finally, we compare BTS models with nine different link prediction methods in nine different networks, and we also illustrate the convergence property and efficiency of the BTS model.

Similar solutions for viscous hypersonic flow over a slender three-fourths-power body of revolution

Science.gov (United States)

Lin, Chin-Shun

1987-01-01

For hypersonic flow with a shock wave, there is a similar solution consistent throughout the viscous and inviscid layers along a very slender three-fourths-power body of revolution The strong pressure interaction problem can then be treated by the method of similarity. Numerical calculations are performed in the viscous region with the edge pressure distribution known from the inviscid similar solutions. The compressible laminar boundary-layer equations are transformed into a system of ordinary differential equations. The resulting two-point boundary value problem is then solved by the Runge-Kutta method with a modified Newton's method for the corresponding boundary conditions. The effects of wall temperature, mass bleeding, and body transverse curvature are investigated. The induced pressure, displacement thickness, skin friction, and heat transfer due to the previously mentioned parameters are estimated and analyzed.

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.

Trajectory similarity join in spatial networks

KAUST Repository

Shang, Shuo

2017-09-07

The matching of similar pairs of objects, called similarity join, is fundamental functionality in data management. We consider the case of trajectory similarity join (TS-Join), where the objects are trajectories of vehicles moving in road networks. Thus, given two sets of trajectories and a threshold θ, the TS-Join returns all pairs of trajectories from the two sets with similarity above θ. This join targets applications such as trajectory near-duplicate detection, data cleaning, ridesharing recommendation, and traffic congestion prediction. With these applications in mind, we provide a purposeful definition of similarity. To enable efficient TS-Join processing on large sets of trajectories, we develop search space pruning techniques and take into account the parallel processing capabilities of modern processors. Specifically, we present a two-phase divide-and-conquer algorithm. For each trajectory, the algorithm first finds similar trajectories. Then it merges the results to achieve a final result. The algorithm exploits an upper bound on the spatiotemporal similarity and a heuristic scheduling strategy for search space pruning. The algorithm\\'s per-trajectory searches are independent of each other and can be performed in parallel, and the merging has constant cost. An empirical study with real data offers insight in the performance of the algorithm and demonstrates that is capable of outperforming a well-designed baseline algorithm by an order of magnitude.

Load reduction test method of similarity theory and BP neural networks of large cranes

Science.gov (United States)

Yang, Ruigang; Duan, Zhibin; Lu, Yi; Wang, Lei; Xu, Gening

2016-01-01

Static load tests are an important means of supervising and detecting a crane's lift capacity. Due to space restrictions, however, there are difficulties and potential danger when testing large bridge cranes. To solve the loading problems of large-tonnage cranes during testing, an equivalency test is proposed based on the similarity theory and BP neural networks. The maximum stress and displacement of a large bridge crane is tested in small loads, combined with the training neural network of a similar structure crane through stress and displacement data which is collected by a physics simulation progressively loaded to a static load test load within the material scope of work. The maximum stress and displacement of a crane under a static load test load can be predicted through the relationship of stress, displacement, and load. By measuring the stress and displacement of small tonnage weights, the stress and displacement of large loads can be predicted, such as the maximum load capacity, which is 1.25 times the rated capacity. Experimental study shows that the load reduction test method can reflect the lift capacity of large bridge cranes. The load shedding predictive analysis for Sanxia 1200 t bridge crane test data indicates that when the load is 1.25 times the rated lifting capacity, the predicted displacement and actual displacement error is zero. The method solves the problem that lifting capacities are difficult to obtain and testing accidents are easily possible when 1.25 times related weight loads are tested for large tonnage cranes.

Two methods to simulate intrapulpal pressure: effects upon bonding performance of self-etch adhesives.

Science.gov (United States)

Feitosa, V P; Gotti, V B; Grohmann, C V; Abuná, G; Correr-Sobrinho, L; Sinhoreti, M A C; Correr, A B

2014-09-01

To evaluate the effects of two methods to simulate physiological pulpal pressure on the dentine bonding performance of two all-in-one adhesives and a two-step self-etch silorane-based adhesive by means of microtensile bond strength (μTBS) and nanoleakage surveys. The self-etch adhesives [G-Bond Plus (GB), Adper Easy Bond (EB) and silorane adhesive (SIL)] were applied to flat deep dentine surfaces from extracted human molars. The restorations were constructed using resin composites Filtek Silorane or Filtek Z350 (3M ESPE). After 24 h using the two methods of simulated pulpal pressure or no pulpal pressure (control groups), the bonded teeth were cut into specimens and submitted to μTBS and silver uptake examination. Results were analysed with two-way anova and Tukey's test (P adhesives. No difference between control and pulpal pressure groups was found for SIL and GB. EB led significant drop (P = 0.002) in bond strength under pulpal pressure. Silver impregnation was increased after both methods of simulated pulpal pressure for all adhesives, and it was similar between the simulated pulpal pressure methods. The innovative method to simulate pulpal pressure behaved similarly to the classic one and could be used as an alternative. The HEMA-free one-step and the two-step self-etch adhesives had acceptable resistance against pulpal pressure, unlike the HEMA-rich adhesive. © 2013 International Endodontic Journal. Published by John Wiley & Sons Ltd.

A comprehensive comparison of network similarities for link prediction and spurious link elimination

Science.gov (United States)

Zhang, Peng; Qiu, Dan; Zeng, An; Xiao, Jinghua

2018-06-01

Identifying missing interactions in complex networks, known as link prediction, is realized by estimating the likelihood of the existence of a link between two nodes according to the observed links and nodes' attributes. Similar approaches have also been employed to identify and remove spurious links in networks which is crucial for improving the reliability of network data. In network science, the likelihood for two nodes having a connection strongly depends on their structural similarity. The key to address these two problems thus becomes how to objectively measure the similarity between nodes in networks. In the literature, numerous network similarity metrics have been proposed and their accuracy has been discussed independently in previous works. In this paper, we systematically compare the accuracy of 18 similarity metrics in both link prediction and spurious link elimination when the observed networks are very sparse or consist of inaccurate linking information. Interestingly, some methods have high prediction accuracy, they tend to perform low accuracy in identification spurious interaction. We further find that methods can be classified into several cluster according to their behaviors. This work is useful for guiding future use of these similarity metrics for different purposes.

Personalized Mortality Prediction Driven by Electronic Medical Data and a Patient Similarity Metric

Science.gov (United States)

Lee, Joon; Maslove, David M.; Dubin, Joel A.

2015-01-01

Background Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1) to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2) to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made. Methods and Findings We deployed a cosine-similarity-based patient similarity metric (PSM) to an intensive care unit (ICU) database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care. Conclusions The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR) systems, our

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...

Development of an analytical microbial consortia method for enhancing performance monitoring at aerobic wastewater treatment plants.

Science.gov (United States)

Razban, Behrooz; Nelson, Kristina Y; McMartin, Dena W; Cullimore, D Roy; Wall, Michelle; Wang, Dunling

2012-01-01

An analytical method to produce profiles of bacterial biomass fatty acid methyl esters (FAME) was developed employing rapid agitation followed by static incubation (RASI) using selective media of wastewater microbial communities. The results were compiled to produce a unique library for comparison and performance analysis at a Wastewater Treatment Plant (WWTP). A total of 146 samples from the aerated WWTP, comprising 73 samples of each secondary and tertiary effluent, were included analyzed. For comparison purposes, all samples were evaluated via a similarity index (SI) with secondary effluents producing an SI of 0.88 with 2.7% variation and tertiary samples producing an SI 0.86 with 5.0% variation. The results also highlighted significant differences between the fatty acid profiles of the tertiary and secondary effluents indicating considerable shifts in the bacterial community profile between these treatment phases. The WWTP performance results using this method were highly replicable and reproducible indicating that the protocol has potential as a performance-monitoring tool for aerated WWTPs. The results quickly and accurately reflect shifts in dominant bacterial communities that result when processes operations and performance change.

An Experimental Comparison of Similarity Assessment Measures for 3D Models on Constrained Surface Deformation

Science.gov (United States)

Quan, Lulin; Yang, Zhixin

2010-05-01

To address the issues in the area of design customization, this paper expressed the specification and application of the constrained surface deformation, and reported the experimental performance comparison of three prevail effective similarity assessment algorithms on constrained surface deformation domain. Constrained surface deformation becomes a promising method that supports for various downstream applications of customized design. Similarity assessment is regarded as the key technology for inspecting the success of new design via measuring the difference level between the deformed new design and the initial sample model, and indicating whether the difference level is within the limitation. According to our theoretical analysis and pre-experiments, three similarity assessment algorithms are suitable for this domain, including shape histogram based method, skeleton based method, and U system moment based method. We analyze their basic functions and implementation methodologies in detail, and do a series of experiments on various situations to test their accuracy and efficiency using precision-recall diagram. Shoe model is chosen as an industrial example for the experiments. It shows that shape histogram based method gained an optimal performance in comparison. Based on the result, we proposed a novel approach that integrating surface constrains and shape histogram description with adaptive weighting method, which emphasize the role of constrains during the assessment. The limited initial experimental result demonstrated that our algorithm outperforms other three algorithms. A clear direction for future development is also drawn at the end of the paper.

Analysis of pulse thermography using similarities between wave and diffusion propagation

Science.gov (United States)

Gershenson, M.

2017-05-01

Pulse thermography or thermal wave imaging are commonly used as nondestructive evaluation (NDE) method. While the technical aspect has evolve with time, theoretical interpretation is lagging. Interpretation is still using curved fitting on a log log scale. A new approach based directly on the governing differential equation is introduced. By using relationships between wave propagation and the diffusive propagation of thermal excitation, it is shown that one can transform from solutions in one type of propagation to the other. The method is based on the similarities between the Laplace transforms of the diffusion equation and the wave equation. For diffusive propagation we have the Laplace variable s to the first power, while for the wave propagation similar equations occur with s2. For discrete time the transformation between the domains is performed by multiplying the temperature data vector by a matrix. The transform is local. The performance of the techniques is tested on synthetic data. The application of common back projection techniques used in the processing of wave data is also demonstrated. The combined use of the transform and back projection makes it possible to improve both depth and lateral resolution of transient thermography.

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.

Improved Performance of Unsupervised Method by Renovated K-Means

OpenAIRE

Ashok, P.; Nawaz, G. M Kadhar; Elayaraja, E.; Vadivel, V.

2013-01-01

Clustering is a separation of data into groups of similar objects. Every group called cluster consists of objects that are similar to one another and dissimilar to objects of other groups. In this paper, the K-Means algorithm is implemented by three distance functions and to identify the optimal distance function for clustering methods. The proposed K-Means algorithm is compared with K-Means, Static Weighted K-Means (SWK-Means) and Dynamic Weighted K-Means (DWK-Means) algorithm by using Davis...

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

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

Trajectory similarity join in spatial networks

KAUST Repository

Shang, Shuo; Chen, Lisi; Wei, Zhewei; Jensen, Christian S.; Zheng, Kai; Kalnis, Panos

2017-01-01

With these applications in mind, we provide a purposeful definition of similarity. To enable efficient TS-Join processing on large sets of trajectories, we develop search space pruning techniques and take into account the parallel processing capabilities of modern processors. Specifically, we present a two-phase divide-and-conquer algorithm. For each trajectory, the algorithm first finds similar trajectories. Then it merges the results to achieve a final result. The algorithm exploits an upper bound on the spatiotemporal similarity and a heuristic scheduling strategy for search space pruning. The algorithm's per-trajectory searches are independent of each other and can be performed in parallel, and the merging has constant cost. An empirical study with real data offers insight in the performance of the algorithm and demonstrates that is capable of outperforming a well-designed baseline algorithm by an order of magnitude.

Authentication of commercial spices based on the similarities between gas chromatographic fingerprints.

Science.gov (United States)

Matsushita, Takaya; Zhao, Jing Jing; Igura, Noriyuki; Shimoda, Mitsuya

2018-06-01

A simple and solvent-free method was developed for the authentication of commercial spices. The similarities between gas chromatographic fingerprints were measured using similarity indices and multivariate data analyses, as morphological differentiation between dried powders and small spice particles was challenging. The volatile compounds present in 11 spices (i.e. allspice, anise, black pepper, caraway, clove, coriander, cumin, dill, fennel, star anise, and white pepper) were extracted by headspace solid-phase microextraction, and analysed by gas chromatography-mass spectrometry. The largest 10 peaks were selected from each total ion chromatogram, and a total of 65 volatiles were tentatively identified. The similarity indices (i.e. the congruence coefficients) were calculated using the data matrices of the identified compound relative peak areas to differentiate between two sets of fingerprints. Where pairs of similar fingerprints produced high congruence coefficients (>0.80), distinctive volatile markers were employed to distinguish between these samples. In addition, hierarchical cluster analysis and principal component analysis were performed to visualise the similarity among fingerprints, and the analysed spices were grouped and characterised according to their distinctive major components. This method is suitable for screening unknown spices, and can therefore be employed to evaluate the quality and authenticity of various spices. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Application of Shape Similarity in Pose Selection and Virtual Screening in CSARdock2014 Exercise.

Science.gov (United States)

Kumar, Ashutosh; Zhang, Kam Y J

2016-06-27

To evaluate the applicability of shape similarity in docking-based pose selection and virtual screening, we participated in the CSARdock2014 benchmark exercise for identifying the correct docking pose of inhibitors targeting factor XA, spleen tyrosine kinase, and tRNA methyltransferase. This exercise provides a valuable opportunity for researchers to test their docking programs, methods, and protocols in a blind testing environment. In the CSARdock2014 benchmark exercise, we have implemented an approach that uses ligand 3D shape similarity to facilitate docking-based pose selection and virtual screening. We showed here that ligand 3D shape similarity between bound poses could be used to identify the native-like pose from an ensemble of docking-generated poses. Our method correctly identified the native pose as the top-ranking pose for 73% of test cases in a blind testing environment. Moreover, the pose selection results also revealed an excellent correlation between ligand 3D shape similarity scores and RMSD to X-ray crystal structure ligand. In the virtual screening exercise, the average RMSD for our pose prediction was found to be 1.02 Å, and it was one of the top performances achieved in CSARdock2014 benchmark exercise. Furthermore, the inclusion of shape similarity improved virtual screening performance of docking-based scoring and ranking. The coefficient of determination (r(2)) between experimental activities and docking scores for 276 spleen tyrosine kinase inhibitors was found to be 0.365 but reached 0.614 when the ligand 3D shape similarity was included.

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.

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.

A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

Science.gov (United States)

Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

2018-01-01

The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

A method for optimizing the performance of buildings

Energy Technology Data Exchange (ETDEWEB)

Pedersen, Frank

2006-07-01

This thesis describes a method for optimizing the performance of buildings. Design decisions made in early stages of the building design process have a significant impact on the performance of buildings, for instance, the performance with respect to the energy consumption, economical aspects, and the indoor environment. The method is intended for supporting design decisions for buildings, by combining methods for calculating the performance of buildings with numerical optimization methods. The method is able to find optimum values of decision variables representing different features of the building, such as its shape, the amount and type of windows used, and the amount of insulation used in the building envelope. The parties who influence design decisions for buildings, such as building owners, building users, architects, consulting engineers, contractors, etc., often have different and to some extent conflicting requirements to buildings. For instance, the building owner may be more concerned about the cost of constructing the building, rather than the quality of the indoor climate, which is more likely to be a concern of the building user. In order to support the different types of requirements made by decision-makers for buildings, an optimization problem is formulated, intended for representing a wide range of design decision problems for buildings. The problem formulation involves so-called performance measures, which can be calculated with simulation software for buildings. For instance, the annual amount of energy required by the building, the cost of constructing the building, and the annual number of hours where overheating occurs, can be used as performance measures. The optimization problem enables the decision-makers to specify many different requirements to the decision variables, as well as to the performance of the building. Performance measures can for instance be required to assume their minimum or maximum value, they can be subjected to upper or

Large margin classification with indefinite similarities

KAUST Repository

Alabdulmohsin, Ibrahim

2016-01-07

Classification with indefinite similarities has attracted attention in the machine learning community. This is partly due to the fact that many similarity functions that arise in practice are not symmetric positive semidefinite, i.e. the Mercer condition is not satisfied, or the Mercer condition is difficult to verify. Examples of such indefinite similarities in machine learning applications are ample including, for instance, the BLAST similarity score between protein sequences, human-judged similarities between concepts and words, and the tangent distance or the shape matching distance in computer vision. Nevertheless, previous works on classification with indefinite similarities are not fully satisfactory. They have either introduced sources of inconsistency in handling past and future examples using kernel approximation, settled for local-minimum solutions using non-convex optimization, or produced non-sparse solutions by learning in Krein spaces. Despite the large volume of research devoted to this subject lately, we demonstrate in this paper how an old idea, namely the 1-norm support vector machine (SVM) proposed more than 15 years ago, has several advantages over more recent work. In particular, the 1-norm SVM method is conceptually simpler, which makes it easier to implement and maintain. It is competitive, if not superior to, all other methods in terms of predictive accuracy. Moreover, it produces solutions that are often sparser than more recent methods by several orders of magnitude. In addition, we provide various theoretical justifications by relating 1-norm SVM to well-established learning algorithms such as neural networks, SVM, and nearest neighbor classifiers. Finally, we conduct a thorough experimental evaluation, which reveals that the evidence in favor of 1-norm SVM is statistically significant.

Statistical learning methods: Basics, control and performance

Energy Technology Data Exchange (ETDEWEB)

Zimmermann, J. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de

2006-04-01

The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms.

Statistical learning methods: Basics, control and performance

International Nuclear Information System (INIS)

Zimmermann, J.

2006-01-01

The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms

Chromatographic fingerprint similarity analysis for pollutant source identification

International Nuclear Information System (INIS)

Xie, Juan-Ping; Ni, Hong-Gang

2015-01-01

In the present study, a similarity analysis method was proposed to evaluate the source-sink relationships among environmental media for polybrominated diphenyl ethers (PBDEs), which were taken as the representative contaminants. Chromatographic fingerprint analysis has been widely used in the fields of natural products chemistry and forensic chemistry, but its application to environmental science has been limited. We established a library of various sources of media containing contaminants (e.g., plastics), recognizing that the establishment of a more comprehensive library allows for a better understanding of the sources of contamination. We then compared an environmental complex mixture (e.g., sediment, soil) with the profiles in the library. These comparisons could be used as the first step in source tracking. The cosine similarities between plastic and soil or sediment ranged from 0.53 to 0.68, suggesting that plastic in electronic waste is an important source of PBDEs in the environment, but it is not the only source. A similarity analysis between soil and sediment indicated that they have a source-sink relationship. Generally, the similarity analysis method can encompass more relevant information of complex mixtures in the environment than a profile-based approach that only focuses on target pollutants. There is an inherent advantage to creating a data matrix containing all peaks and their relative levels after matching the peaks based on retention times and peak areas. This data matrix can be used for source identification via a similarity analysis without quantitative or qualitative analysis of all chemicals in a sample. - Highlights: • Chromatographic fingerprint analysis can be used as the first step in source tracking. • Similarity analysis method can encompass more relevant information of pollution. • The fingerprints strongly depend on the chromatographic conditions. • A more effective and robust method for identifying similarities is required

Development of similarity theory for control systems

Science.gov (United States)

Myshlyaev, L. P.; Evtushenko, V. F.; Ivushkin, K. A.; Makarov, G. V.

2018-05-01

The area of effective application of the traditional similarity theory and the need necessity of its development for systems are discussed. The main statements underlying the similarity theory of control systems are given. The conditions for the similarity of control systems and the need for similarity control control are formulated. Methods and algorithms for estimating and similarity control of control systems and the results of research of control systems based on their similarity are presented. The similarity control of systems includes the current evaluation of the degree of similarity of control systems and the development of actions controlling similarity, and the corresponding targeted change in the state of any element of control systems.

Gradient High Performance Liquid Chromatography Method ...

African Journals Online (AJOL)

Purpose: To develop a gradient high performance liquid chromatography (HPLC) method for the simultaneous determination of phenylephrine (PHE) and ibuprofen (IBU) in solid ..... nimesulide, phenylephrine. Hydrochloride, chlorpheniramine maleate and caffeine anhydrous in pharmaceutical dosage form. Acta Pol.

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

Directory of Open Access Journals (Sweden)

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.

Improved collaborative filtering recommendation algorithm of similarity measure

Science.gov (United States)

Zhang, Baofu; Yuan, Baoping

2017-05-01

The Collaborative filtering recommendation algorithm is one of the most widely used recommendation algorithm in personalized recommender systems. The key is to find the nearest neighbor set of the active user by using similarity measure. However, the methods of traditional similarity measure mainly focus on the similarity of user common rating items, but ignore the relationship between the user common rating items and all items the user rates. And because rating matrix is very sparse, traditional collaborative filtering recommendation algorithm is not high efficiency. In order to obtain better accuracy, based on the consideration of common preference between users, the difference of rating scale and score of common items, this paper presents an improved similarity measure method, and based on this method, a collaborative filtering recommendation algorithm based on similarity improvement is proposed. Experimental results show that the algorithm can effectively improve the quality of recommendation, thus alleviate the impact of data sparseness.

On different forms of self similarity

International Nuclear Information System (INIS)

Aswathy, R.K.; Mathew, Sunil

2016-01-01

Fractal geometry is mainly based on the idea of self-similar forms. To be self-similar, a shape must able to be divided into parts that are smaller copies, which are more or less similar to the whole. There are different forms of self similarity in nature and mathematics. In this paper, some of the topological properties of super self similar sets are discussed. It is proved that in a complete metric space with two or more elements, the set of all non super self similar sets are dense in the set of all non-empty compact sub sets. It is also proved that the product of self similar sets are super self similar in product metric spaces and that the super self similarity is preserved under isometry. A characterization of super self similar sets using contracting sub self similarity is also presented. Some relevant counterexamples are provided. The concepts of exact super and sub self similarity are introduced and a necessary and sufficient condition for a set to be exact super self similar in terms of condensation iterated function systems (Condensation IFS’s) is obtained. A method to generate exact sub self similar sets using condensation IFS’s and the denseness of exact super self similar sets are also discussed.

Revisiting Inter-Genre Similarity

DEFF Research Database (Denmark)

Sturm, Bob L.; Gouyon, Fabien

2013-01-01

We revisit the idea of ``inter-genre similarity'' (IGS) for machine learning in general, and music genre recognition in particular. We show analytically that the probability of error for IGS is higher than naive Bayes classification with zero-one loss (NB). We show empirically that IGS does...... not perform well, even for data that satisfies all its assumptions....

Abundance estimation of spectrally similar minerals

CSIR Research Space (South Africa)

Debba, Pravesh

2009-07-01

Full Text Available This paper evaluates a spectral unmixing method for estimating the partial abundance of spectrally similar minerals in complex mixtures. The method requires formulation of a linear function of individual spectra of individual minerals. The first...

Validated High Performance Liquid Chromatography Method for ...

African Journals Online (AJOL)

Purpose: To develop a simple, rapid and sensitive high performance liquid chromatography (HPLC) method for the determination of cefadroxil monohydrate in human plasma. Methods: Schimadzu HPLC with LC solution software was used with Waters Spherisorb, C18 (5 μm, 150mm × 4.5mm) column. The mobile phase ...

Improved power performance assessment methods

Energy Technology Data Exchange (ETDEWEB)

Frandsen, S; Antoniou, I; Dahlberg, J A [and others

1999-03-01

The uncertainty of presently-used methods for retrospective assessment of the productive capacity of wind farms is unacceptably large. The possibilities of improving the accuracy have been investigated and are reported. A method is presented that includes an extended power curve and site calibration. In addition, blockage effects with respect to reference wind speed measurements are analysed. It is found that significant accuracy improvements are possible by the introduction of more input variables such as turbulence and wind shear, in addition to mean wind speed and air density. Also, the testing of several or all machines in the wind farm - instead of only one or two - may provide a better estimate of the average performance. (au)

Performance of Firth-and logF-type penalized methods in risk prediction for small or sparse binary data.

Science.gov (United States)

Rahman, M Shafiqur; Sultana, Mahbuba

2017-02-23

When developing risk models for binary data with small or sparse data sets, the standard maximum likelihood estimation (MLE) based logistic regression faces several problems including biased or infinite estimate of the regression coefficient and frequent convergence failure of the likelihood due to separation. The problem of separation occurs commonly even if sample size is large but there is sufficient number of strong predictors. In the presence of separation, even if one develops the model, it produces overfitted model with poor predictive performance. Firth-and logF-type penalized regression methods are popular alternative to MLE, particularly for solving separation-problem. Despite the attractive advantages, their use in risk prediction is very limited. This paper evaluated these methods in risk prediction in comparison with MLE and other commonly used penalized methods such as ridge. The predictive performance of the methods was evaluated through assessing calibration, discrimination and overall predictive performance using an extensive simulation study. Further an illustration of the methods were provided using a real data example with low prevalence of outcome. The MLE showed poor performance in risk prediction in small or sparse data sets. All penalized methods offered some improvements in calibration, discrimination and overall predictive performance. Although the Firth-and logF-type methods showed almost equal amount of improvement, Firth-type penalization produces some bias in the average predicted probability, and the amount of bias is even larger than that produced by MLE. Of the logF(1,1) and logF(2,2) penalization, logF(2,2) provides slight bias in the estimate of regression coefficient of binary predictor and logF(1,1) performed better in all aspects. Similarly, ridge performed well in discrimination and overall predictive performance but it often produces underfitted model and has high rate of convergence failure (even the rate is higher than that

Application of clustering methods: Regularized Markov clustering (R-MCL) for analyzing dengue virus similarity

Science.gov (United States)

Lestari, D.; Raharjo, D.; Bustamam, A.; Abdillah, B.; Widhianto, W.

2017-07-01

Dengue virus consists of 10 different constituent proteins and are classified into 4 major serotypes (DEN 1 - DEN 4). This study was designed to perform clustering against 30 protein sequences of dengue virus taken from Virus Pathogen Database and Analysis Resource (VIPR) using Regularized Markov Clustering (R-MCL) algorithm and then we analyze the result. By using Python program 3.4, R-MCL algorithm produces 8 clusters with more than one centroid in several clusters. The number of centroid shows the density level of interaction. Protein interactions that are connected in a tissue, form a complex protein that serves as a specific biological process unit. The analysis of result shows the R-MCL clustering produces clusters of dengue virus family based on the similarity role of their constituent protein, regardless of serotypes.

Audio Query by Example Using Similarity Measures between Probability Density Functions of Features

Directory of Open Access Journals (Sweden)

Marko Helén

2010-01-01

Full Text Available This paper proposes a query by example system for generic audio. We estimate the similarity of the example signal and the samples in the queried database by calculating the distance between the probability density functions (pdfs of their frame-wise acoustic features. Since the features are continuous valued, we propose to model them using Gaussian mixture models (GMMs or hidden Markov models (HMMs. The models parametrize each sample efficiently and retain sufficient information for similarity measurement. To measure the distance between the models, we apply a novel Euclidean distance, approximations of Kullback-Leibler divergence, and a cross-likelihood ratio test. The performance of the measures was tested in simulations where audio samples are automatically retrieved from a general audio database, based on the estimated similarity to a user-provided example. The simulations show that the distance between probability density functions is an accurate measure for similarity. Measures based on GMMs or HMMs are shown to produce better results than that of the existing methods based on simpler statistics or histograms of the features. A good performance with low computational cost is obtained with the proposed Euclidean distance.

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

Science.gov (United States)

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.

Performance prediction method for a multi-stage Knudsen pump

Science.gov (United States)

Kugimoto, K.; Hirota, Y.; Kizaki, Y.; Yamaguchi, H.; Niimi, T.

2017-12-01

In this study, the novel method to predict the performance of a multi-stage Knudsen pump is proposed. The performance prediction method is carried out in two steps numerically with the assistance of a simple experimental result. In the first step, the performance of a single-stage Knudsen pump was measured experimentally under various pressure conditions, and the relationship of the mass flow rate was obtained with respect to the average pressure between the inlet and outlet of the pump and the pressure difference between them. In the second step, the performance of a multi-stage pump was analyzed by a one-dimensional model derived from the mass conservation law. The performances predicted by the 1D-model of 1-stage, 2-stage, 3-stage, and 4-stage pumps were validated by the experimental results for the corresponding number of stages. It was concluded that the proposed prediction method works properly.

Determining when a fracture occurred: Does the method matter? Analysis of the similarity of three different methods for estimating time since fracture of juvenile long bones.

Science.gov (United States)

Drury, Anne; Cunningham, Craig

2018-01-01

Radiographic fracture date estimation is a critical component of skeletal trauma analysis in the living. Several timetables have been proposed for how the appearance of radiographic features can be interpreted to provide a likely time frame for fracture occurrence. This study compares three such timetables for pediatric fractures, by Islam et al. (2000), Malone et al. (2011), and Prosser et al. (2012), in order to determine whether the fracture date ranges produced by using these methods are in agreement with one another. Fracture date ranges were estimated for 112 long bone fractures in 96 children aged 1-17 years, using the three different timetables. The extent of similarity of the intervals was tested by statistically comparing the overlap between the ranges. Results showed that none of the methods were in perfect agreement with one another. Differences seen included the size of the estimated date range for when a fracture occurred, and the specific dates given for both the upper and lower ends of the fracture date range. There was greater similarity between the ranges produced by Malone et al. (2011) and both the other two studies than there was between Islam et al. (2000) and Prosser et al. (2012). The greatest similarity existed between Malone et al. (2011) and Islam et al. (2000). The extent of differences between methods can vary widely, depending on the fracture analysed. Using one timetable gives an average earliest possible fracture date of less than 2 days before another, but the range was extreme, with one method estimating minimum time since fracture as 25 days before another method for a given fracture. In most cases, one method gave maximum time since fracture as a week less than the other two methods, but range was extreme and some estimates were nearly two months different. The variability in fracture date estimates given by these timetables indicates that caution should be exercised when estimating the timing of a juvenile fracture if relying

Similarity, Not Complexity, Determines Visual Working Memory Performance

Science.gov (United States)

Jackson, Margaret C.; Linden, David E. J.; Roberts, Mark V.; Kriegeskorte, Nikolaus; Haenschel, Corinna

2015-01-01

A number of studies have shown that visual working memory (WM) is poorer for complex versus simple items, traditionally accounted for by higher information load placing greater demands on encoding and storage capacity limits. Other research suggests that it may not be complexity that determines WM performance per se, but rather increased…

Event Shape Sorting: selecting events with similar evolution

Directory of Open Access Journals (Sweden)

Tomášik Boris

2017-01-01

Full Text Available We present novel method for the organisation of events. The method is based on comparing event-by-event histograms of a chosen quantity Q that is measured for each particle in every event. The events are organised in such a way that those with similar shape of the Q-histograms end-up placed close to each other. We apply the method on histograms of azimuthal angle of the produced hadrons in ultrarelativsitic nuclear collisions. By selecting events with similar azimuthal shape of their hadron distribution one chooses events which are likely that they underwent similar evolution from the initial state to the freeze-out. Such events can more easily be compared to theoretical simulations where all conditions can be controlled. We illustrate the method on data simulated by the AMPT model.

Developing and evaluating a target-background similarity metric for camouflage detection.

Directory of Open Access Journals (Sweden)

Chiuhsiang Joe Lin

Full Text Available BACKGROUND: Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. METHODOLOGY: In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. SIGNIFICANCE: The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results.

Developing and evaluating a target-background similarity metric for camouflage detection.

Science.gov (United States)

Lin, Chiuhsiang Joe; Chang, Chi-Chan; Liu, Bor-Shong

2014-01-01

Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results.

On Similarity Invariance of Balancing for Nonlinear Systems

NARCIS (Netherlands)

Scherpen, Jacquelien M.A.

1995-01-01

A previously obtained balancing method for nonlinear systems is investigated on similarity in variance by generalization of the observations on the similarity invariance of the linear balanced realization theory. For linear systems it is well known that the Hankel singular values are similarity

Self-Similarity Superresolution for Resource-Constrained Image Sensor Node in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Yuehai Wang

2014-01-01

Full Text Available Wireless sensor networks, in combination with image sensors, open up a grand sensing application field. It is a challenging problem to recover a high resolution (HR image from its low resolution (LR counterpart, especially for low-cost resource-constrained image sensors with limited resolution. Sparse representation-based techniques have been developed recently and increasingly to solve this ill-posed inverse problem. Most of these solutions are based on an external dictionary learned from huge image gallery, consequently needing tremendous iteration and long time to match. In this paper, we explore the self-similarity inside the image itself, and propose a new combined self-similarity superresolution (SR solution, with low computation cost and high recover performance. In the self-similarity image super resolution model (SSIR, a small size sparse dictionary is learned from the image itself by the methods such as KSVD. The most similar patch is searched and specially combined during the sparse regulation iteration. Detailed information, such as edge sharpness, is preserved more faithfully and clearly. Experiment results confirm the effectiveness and efficiency of this double self-learning method in the image super resolution.

Investigation of Thermal Performance for Atria: a Method Overview

Directory of Open Access Journals (Sweden)

Moosavi Leila

2016-01-01

Full Text Available The importance of low energy design in large buildings has encouraged researchers to implement different methods for predicting a building’s thermal performance. Atria, as energy efficient features, have been implemented to improve the indoor thermal environment in large modern buildings. Though widely implemented, the thorough study of atrium performance is restricted due to its large size, complex thermodynamic behavior and the inaccuracies and limitations of available prediction tools. This study reviews the most common research tools implemented in previous researches on atria thermal performance, to explore the advantages and limitation of different methods for future studies. The methods reviewed are analytical, experimental, computer modelling and a combination of any or all of these methods. The findings showed that CFD (computational fluid dynamic models are the most popular tools of recent due to their higher accuracy, capabilities and user-friendly modification. Although the experimental methods were reliable for predicting atria thermal and ventilation performance, they have mostly been used to provide data for validation of CFD models. Furthermore, coupling CFD with other experimental models could increase the reliability and accuracy of the models and provide a more comprehensive analysis.

Performance of machine learning methods for ligand-based virtual screening.

Science.gov (United States)

Plewczynski, Dariusz; Spieser, Stéphane A H; Koch, Uwe

2009-05-01

Computational screening of compound databases has become increasingly popular in pharmaceutical research. This review focuses on the evaluation of ligand-based virtual screening using active compounds as templates in the context of drug discovery. Ligand-based screening techniques are based on comparative molecular similarity analysis of compounds with known and unknown activity. We provide an overview of publications that have evaluated different machine learning methods, such as support vector machines, decision trees, ensemble methods such as boosting, bagging and random forests, clustering methods, neuronal networks, naïve Bayesian, data fusion methods and others.

Personality, Assessment Methods and Academic Performance

Science.gov (United States)

Furnham, Adrian; Nuygards, Sarah; Chamorro-Premuzic, Tomas

2013-01-01

This study examines the relationship between personality and two different academic performance (AP) assessment methods, namely exams and coursework. It aimed to examine whether the relationship between traits and AP was consistent across self-reported versus documented exam results, two different assessment techniques and across different…

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...

Similarity relations in visual search predict rapid visual categorization

Science.gov (United States)

Mohan, Krithika; Arun, S. P.

2012-01-01

How do we perform rapid visual categorization?It is widely thought that categorization involves evaluating the similarity of an object to other category items, but the underlying features and similarity relations remain unknown. Here, we hypothesized that categorization performance is based on perceived similarity relations between items within and outside the category. To this end, we measured the categorization performance of human subjects on three diverse visual categories (animals, vehicles, and tools) and across three hierarchical levels (superordinate, basic, and subordinate levels among animals). For the same subjects, we measured their perceived pair-wise similarities between objects using a visual search task. Regardless of category and hierarchical level, we found that the time taken to categorize an object could be predicted using its similarity to members within and outside its category. We were able to account for several classic categorization phenomena, such as (a) the longer times required to reject category membership; (b) the longer times to categorize atypical objects; and (c) differences in performance across tasks and across hierarchical levels. These categorization times were also accounted for by a model that extracts coarse structure from an image. The striking agreement observed between categorization and visual search suggests that these two disparate tasks depend on a shared coarse object representation. PMID:23092947

A new method to assess the sustainability performance of events: Application to the 2014 World Orienteering Championship

Energy Technology Data Exchange (ETDEWEB)

Scrucca, Flavio; Severi, Claudio [ECOCONGRESS Scientific Department, Via N. Cristofani 4/a, 06135 Perugia (Italy); Galvan, Nicola [WOC (World Orienteering Championship) Organising Committee 2014, Loc. Parco 3, 38056 Levico Terme (Italy); Brunori, Antonio, E-mail: info@pefc.it [PEFC Italy (Programme for Endorsement of Forest Certification schemes), Strada dei Loggi 22, 06135 Perugia (Italy)

2016-01-15

Nowadays an increasing attention of public and private agencies to the sustainability performance of events is observed, since it is recognized as a key issue in the context of sustainable development. Assessing the sustainability performance of events involves environmental, social and economic aspects; their impacts are complex and a quantitative assessment is often difficult. This paper presents a new quali-quantitative method developed to measure the sustainability of events, taking into account all its potential impacts. The 2014 World Orienteering Championship, held in Italy, was selected to test the proposed evaluation methodology. The total carbon footprint of the event was 165.34 tCO{sub 2}eq and the avoided emissions were estimated as being 46 tCO{sub 2}eq. The adopted quali-quantitative method resulted to be efficient in assessing the sustainability impacts and can be applied for the evaluation of similar events. - Highlights: • A quali-quantitative method to assess events' sustainability is presented. • All the methodological issues related to the method are explained. • The method is used to evaluate the sustainability of an international sports event. • The method resulted to be valid to assess the event's sustainability level. • The carbon footprint of the event has been calculated.

A new method to assess the sustainability performance of events: Application to the 2014 World Orienteering Championship

International Nuclear Information System (INIS)

Scrucca, Flavio; Severi, Claudio; Galvan, Nicola; Brunori, Antonio

2016-01-01

Nowadays an increasing attention of public and private agencies to the sustainability performance of events is observed, since it is recognized as a key issue in the context of sustainable development. Assessing the sustainability performance of events involves environmental, social and economic aspects; their impacts are complex and a quantitative assessment is often difficult. This paper presents a new quali-quantitative method developed to measure the sustainability of events, taking into account all its potential impacts. The 2014 World Orienteering Championship, held in Italy, was selected to test the proposed evaluation methodology. The total carbon footprint of the event was 165.34 tCO_2eq and the avoided emissions were estimated as being 46 tCO_2eq. The adopted quali-quantitative method resulted to be efficient in assessing the sustainability impacts and can be applied for the evaluation of similar events. - Highlights: • A quali-quantitative method to assess events' sustainability is presented. • All the methodological issues related to the method are explained. • The method is used to evaluate the sustainability of an international sports event. • The method resulted to be valid to assess the event's sustainability level. • The carbon footprint of the event has been calculated.

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

Directory of Open Access Journals (Sweden)

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.

Spherical anharmonic oscillator in self-similar approximation

International Nuclear Information System (INIS)

Yukalova, E.P.; Yukalov, V.I.

1992-01-01

The method of self-similar approximation is applied here for calculating the eigenvalues of the three-dimensional spherical anharmonic oscillator. The advantage of this method is in its simplicity and high accuracy. The comparison with other known analytical methods proves that this method is more simple and accurate. 25 refs

Resource Isolation Method for Program’S Performance on CMP

Science.gov (United States)

Guan, Ti; Liu, Chunxiu; Xu, Zheng; Li, Huicong; Ma, Qiang

2017-10-01

Data center and cloud computing are more popular, which make more benefits for customers and the providers. However, in data center or clusters, commonly there is more than one program running on one server, but programs may interference with each other. The interference may take a little effect, however, the interference may cause serious drop down of performance. In order to avoid the performance interference problem, the mechanism of isolate resource for different programs is a better choice. In this paper we propose a light cost resource isolation method to improve program’s performance. This method uses Cgroups to set the dedicated CPU and memory resource for a program, aiming at to guarantee the program’s performance. There are three engines to realize this method: Program Monitor Engine top program’s resource usage of CPU and memory and transfer the information to Resource Assignment Engine; Resource Assignment Engine calculates the size of CPU and memory resource should be applied for the program; Cgroups Control Engine divide resource by Linux tool Cgroups, and drag program in control group for execution. The experiment result show that making use of the resource isolation method proposed by our paper, program’s performance can be improved.

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

A New Trajectory Similarity Measure for GPS Data

KAUST Repository

Ismail, Anas; Vigneron, Antoine E.

2016-01-01

We present a new algorithm for measuring the similarity between trajectories, and in particular between GPS traces. We call this new similarity measure the Merge Distance (MD). Our approach is robust against subsampling and supersampling. We perform experiments to compare this new similarity measure with the two main approaches that have been used so far: Dynamic Time Warping (DTW) and the Euclidean distance. © 2015 ACM.

A New Trajectory Similarity Measure for GPS Data

KAUST Repository

Ismail, Anas

2016-08-08

We present a new algorithm for measuring the similarity between trajectories, and in particular between GPS traces. We call this new similarity measure the Merge Distance (MD). Our approach is robust against subsampling and supersampling. We perform experiments to compare this new similarity measure with the two main approaches that have been used so far: Dynamic Time Warping (DTW) and the Euclidean distance. © 2015 ACM.

Examining Similarity Structure: Multidimensional Scaling and Related Approaches in Neuroimaging

Directory of Open Access Journals (Sweden)

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.

Investigation of psychophysical similarity measures for selection of similar images in the diagnosis of clustered microcalcifications on mammograms

International Nuclear Information System (INIS)

Muramatsu, Chisako; Li Qiang; Schmidt, Robert; Shiraishi, Junji; Doi, Kunio

2008-01-01

The presentation of images with lesions of known pathology that are similar to an unknown lesion may be helpful to radiologists in the diagnosis of challenging cases for improving the diagnostic accuracy and also for reducing variation among different radiologists. The authors have been developing a computerized scheme for automatically selecting similar images with clustered microcalcifications on mammograms from a large database. For similar images to be useful, they must be similar from the point of view of the diagnosing radiologists. In order to select such images, subjective similarity ratings were obtained for a number of pairs of clustered microcalcifications by breast radiologists for establishment of a ''gold standard'' of image similarity, and the gold standard was employed for determination and evaluation of the selection of similar images. The images used in this study were obtained from the Digital Database for Screening Mammography developed by the University of South Florida. The subjective similarity ratings for 300 pairs of images with clustered microcalcifications were determined by ten breast radiologists. The authors determined a number of image features which represent the characteristics of clustered microcalcifications that radiologists would use in their diagnosis. For determination of objective similarity measures, an artificial neural network (ANN) was employed. The ANN was trained with the average subjective similarity ratings as teacher and selected image features as input data. The ANN was trained to learn the relationship between the image features and the radiologists' similarity ratings; therefore, once the training was completed, the ANN was able to determine the similarity, called a psychophysical similarity measure, which was expected to be close to radiologists' impressions, for an unknown pair of clustered microcalcifications. By use of a leave-one-out test method, the best combination of features was selected. The correlation

Investigation of psychophysical similarity measures for selection of similar images in the diagnosis of clustered microcalcifications on mammograms

Energy Technology Data Exchange (ETDEWEB)

Muramatsu, Chisako; Li Qiang; Schmidt, Robert; Shiraishi, Junji; Doi, Kunio [Department of Radiology, University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637 (United States) and Department of Intelligent Image Information, Gifu University, 1-1 Yanagido, Gifu (Japan); Department of Radiology, Duke Advanced Imaging Labs, Duke University, 2424 Erwin Road, Suite 302, Durham, North Carolina 27705 (United States); Department of Radiology, University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637 (United States)

2008-12-15

The presentation of images with lesions of known pathology that are similar to an unknown lesion may be helpful to radiologists in the diagnosis of challenging cases for improving the diagnostic accuracy and also for reducing variation among different radiologists. The authors have been developing a computerized scheme for automatically selecting similar images with clustered microcalcifications on mammograms from a large database. For similar images to be useful, they must be similar from the point of view of the diagnosing radiologists. In order to select such images, subjective similarity ratings were obtained for a number of pairs of clustered microcalcifications by breast radiologists for establishment of a ''gold standard'' of image similarity, and the gold standard was employed for determination and evaluation of the selection of similar images. The images used in this study were obtained from the Digital Database for Screening Mammography developed by the University of South Florida. The subjective similarity ratings for 300 pairs of images with clustered microcalcifications were determined by ten breast radiologists. The authors determined a number of image features which represent the characteristics of clustered microcalcifications that radiologists would use in their diagnosis. For determination of objective similarity measures, an artificial neural network (ANN) was employed. The ANN was trained with the average subjective similarity ratings as teacher and selected image features as input data. The ANN was trained to learn the relationship between the image features and the radiologists' similarity ratings; therefore, once the training was completed, the ANN was able to determine the similarity, called a psychophysical similarity measure, which was expected to be close to radiologists' impressions, for an unknown pair of clustered microcalcifications. By use of a leave-one-out test method, the best combination of features

Similarity-based Polymorphic Shellcode Detection

Directory of Open Access Journals (Sweden)

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.

Semantic relatedness and similarity of biomedical terms: examining the effects of recency, size, and section of biomedical publications on the performance of word2vec.

Science.gov (United States)

Zhu, Yongjun; Yan, Erjia; Wang, Fei

2017-07-03

Understanding semantic relatedness and similarity between biomedical terms has a great impact on a variety of applications such as biomedical information retrieval, information extraction, and recommender systems. The objective of this study is to examine word2vec's ability in deriving semantic relatedness and similarity between biomedical terms from large publication data. Specifically, we focus on the effects of recency, size, and section of biomedical publication data on the performance of word2vec. We download abstracts of 18,777,129 articles from PubMed and 766,326 full-text articles from PubMed Central (PMC). The datasets are preprocessed and grouped into subsets by recency, size, and section. Word2vec models are trained on these subtests. Cosine similarities between biomedical terms obtained from the word2vec models are compared against reference standards. Performance of models trained on different subsets are compared to examine recency, size, and section effects. Models trained on recent datasets did not boost the performance. Models trained on larger datasets identified more pairs of biomedical terms than models trained on smaller datasets in relatedness task (from 368 at the 10% level to 494 at the 100% level) and similarity task (from 374 at the 10% level to 491 at the 100% level). The model trained on abstracts produced results that have higher correlations with the reference standards than the one trained on article bodies (i.e., 0.65 vs. 0.62 in the similarity task and 0.66 vs. 0.59 in the relatedness task). However, the latter identified more pairs of biomedical terms than the former (i.e., 344 vs. 498 in the similarity task and 339 vs. 503 in the relatedness task). Increasing the size of dataset does not always enhance the performance. Increasing the size of datasets can result in the identification of more relations of biomedical terms even though it does not guarantee better precision. As summaries of research articles, compared with article

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.

Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

Science.gov (United States)

Radev, Dimitar; Lokshina, Izabella

2010-11-01

The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.

Measuring user similarity using electric circuit analysis: application to collaborative filtering.

Science.gov (United States)

Yang, Joonhyuk; Kim, Jinwook; Kim, Wonjoon; Kim, Young Hwan

2012-01-01

We propose a new technique of measuring user similarity in collaborative filtering using electric circuit analysis. Electric circuit analysis is used to measure the potential differences between nodes on an electric circuit. In this paper, by applying this method to transaction networks comprising users and items, i.e., user-item matrix, and by using the full information about the relationship structure of users in the perspective of item adoption, we overcome the limitations of one-to-one similarity calculation approach, such as the Pearson correlation, Tanimoto coefficient, and Hamming distance, in collaborative filtering. We found that electric circuit analysis can be successfully incorporated into recommender systems and has the potential to significantly enhance predictability, especially when combined with user-based collaborative filtering. We also propose four types of hybrid algorithms that combine the Pearson correlation method and electric circuit analysis. One of the algorithms exceeds the performance of the traditional collaborative filtering by 37.5% at most. This work opens new opportunities for interdisciplinary research between physics and computer science and the development of new recommendation systems.

Measuring user similarity using electric circuit analysis: application to collaborative filtering.

Directory of Open Access Journals (Sweden)

Joonhyuk Yang

Full Text Available We propose a new technique of measuring user similarity in collaborative filtering using electric circuit analysis. Electric circuit analysis is used to measure the potential differences between nodes on an electric circuit. In this paper, by applying this method to transaction networks comprising users and items, i.e., user-item matrix, and by using the full information about the relationship structure of users in the perspective of item adoption, we overcome the limitations of one-to-one similarity calculation approach, such as the Pearson correlation, Tanimoto coefficient, and Hamming distance, in collaborative filtering. We found that electric circuit analysis can be successfully incorporated into recommender systems and has the potential to significantly enhance predictability, especially when combined with user-based collaborative filtering. We also propose four types of hybrid algorithms that combine the Pearson correlation method and electric circuit analysis. One of the algorithms exceeds the performance of the traditional collaborative filtering by 37.5% at most. This work opens new opportunities for interdisciplinary research between physics and computer science and the development of new recommendation systems.

Buffer-Free High Performance Liquid Chromatography Method for ...

African Journals Online (AJOL)

Purpose: To develop and validate a simple, economical and reproducible high performance liquid chromatographic (HPLC) method for the determination of theophylline in pharmaceutical dosage forms. Method: Caffeine was used as the internal standard and reversed phase C-18 column was used to elute the drug and ...

Parallel trajectory similarity joins in spatial networks

KAUST Repository

Shang, Shuo

2018-04-04

The matching of similar pairs of objects, called similarity join, is fundamental functionality in data management. We consider two cases of trajectory similarity joins (TS-Joins), including a threshold-based join (Tb-TS-Join) and a top-k TS-Join (k-TS-Join), where the objects are trajectories of vehicles moving in road networks. Given two sets of trajectories and a threshold θ, the Tb-TS-Join returns all pairs of trajectories from the two sets with similarity above θ. In contrast, the k-TS-Join does not take a threshold as a parameter, and it returns the top-k most similar trajectory pairs from the two sets. The TS-Joins target diverse applications such as trajectory near-duplicate detection, data cleaning, ridesharing recommendation, and traffic congestion prediction. With these applications in mind, we provide purposeful definitions of similarity. To enable efficient processing of the TS-Joins on large sets of trajectories, we develop search space pruning techniques and enable use of the parallel processing capabilities of modern processors. Specifically, we present a two-phase divide-and-conquer search framework that lays the foundation for the algorithms for the Tb-TS-Join and the k-TS-Join that rely on different pruning techniques to achieve efficiency. For each trajectory, the algorithms first find similar trajectories. Then they merge the results to obtain the final result. The algorithms for the two joins exploit different upper and lower bounds on the spatiotemporal trajectory similarity and different heuristic scheduling strategies for search space pruning. Their per-trajectory searches are independent of each other and can be performed in parallel, and the mergings have constant cost. An empirical study with real data offers insight in the performance of the algorithms and demonstrates that they are capable of outperforming well-designed baseline algorithms by an order of magnitude.

Parallel trajectory similarity joins in spatial networks

KAUST Repository

Shang, Shuo; Chen, Lisi; Wei, Zhewei; Jensen, Christian S.; Zheng, Kai; Kalnis, Panos

2018-01-01

The matching of similar pairs of objects, called similarity join, is fundamental functionality in data management. We consider two cases of trajectory similarity joins (TS-Joins), including a threshold-based join (Tb-TS-Join) and a top-k TS-Join (k-TS-Join), where the objects are trajectories of vehicles moving in road networks. Given two sets of trajectories and a threshold θ, the Tb-TS-Join returns all pairs of trajectories from the two sets with similarity above θ. In contrast, the k-TS-Join does not take a threshold as a parameter, and it returns the top-k most similar trajectory pairs from the two sets. The TS-Joins target diverse applications such as trajectory near-duplicate detection, data cleaning, ridesharing recommendation, and traffic congestion prediction. With these applications in mind, we provide purposeful definitions of similarity. To enable efficient processing of the TS-Joins on large sets of trajectories, we develop search space pruning techniques and enable use of the parallel processing capabilities of modern processors. Specifically, we present a two-phase divide-and-conquer search framework that lays the foundation for the algorithms for the Tb-TS-Join and the k-TS-Join that rely on different pruning techniques to achieve efficiency. For each trajectory, the algorithms first find similar trajectories. Then they merge the results to obtain the final result. The algorithms for the two joins exploit different upper and lower bounds on the spatiotemporal trajectory similarity and different heuristic scheduling strategies for search space pruning. Their per-trajectory searches are independent of each other and can be performed in parallel, and the mergings have constant cost. An empirical study with real data offers insight in the performance of the algorithms and demonstrates that they are capable of outperforming well-designed baseline algorithms by an order of magnitude.

Mining Diagnostic Assessment Data for Concept Similarity

Science.gov (United States)

Madhyastha, Tara; Hunt, Earl

2009-01-01

This paper introduces a method for mining multiple-choice assessment data for similarity of the concepts represented by the multiple choice responses. The resulting similarity matrix can be used to visualize the distance between concepts in a lower-dimensional space. This gives an instructor a visualization of the relative difficulty of concepts…

A method to evaluate process performance by integrating time and resources

Science.gov (United States)

Wang, Yu; Wei, Qingjie; Jin, Shuang

2017-06-01

The purpose of process mining is to improve the existing process of the enterprise, so how to measure the performance of the process is particularly important. However, the current research on the performance evaluation method is still insufficient. The main methods of evaluation are mainly using time or resource. These basic statistics cannot evaluate process performance very well. In this paper, a method of evaluating the performance of the process based on time dimension and resource dimension is proposed. This method can be used to measure the utilization and redundancy of resources in the process. This paper will introduce the design principle and formula of the evaluation algorithm. Then, the design and the implementation of the evaluation method will be introduced. Finally, we will use the evaluating method to analyse the event log from a telephone maintenance process and propose an optimization plan.

Does Avatar Appearance Matter? How Team Visual Similarity and Member–Avatar Similarity Influence Virtual Team Performance

NARCIS (Netherlands)

van der Land, S.F.; Schouten, A.P.; Feldberg, J.F.M.; Huysman, M.H.; van den Hooff, B.J.

2015-01-01

This multimethod study investigated how avatar appearance influences virtual team performance. This study is the first to integrate the framework of social identity model of de-individuation effects (SIDE) and Self-Identification theory, using "morphing" techniques. Results were obtained from a 2

Concept similarity in publications precedes cross-disciplinary collaboration.

Science.gov (United States)

Post, Andrew R; Harrison, James H

2008-11-06

Innovative science frequently occurs as a result of cross-disciplinary collaboration, the importance of which is reflected by recent NIH funding initiatives that promote communication and collaboration. If shared research interests between collaborators are important for the formation of collaborations,methods for identifying these shared interests across scientific domains could potentially reveal new and useful collaboration opportunities. MEDLINE represents a comprehensive database of collaborations and research interests, as reflected by article co-authors and concept content. We analyzed six years of citations using information retrieval based methods to compute articles conceptual similarity, and found that articles by basic and clinical scientists who later collaborated had significantly higher average similarity than articles by similar scientists who did not collaborate.Refinement of these methods and characterization of found conceptual overlaps could allow automated discovery of collaboration opportunities that are currently missed.

Epistemic Similarities between Students' Scientific and Supernatural Beliefs

Science.gov (United States)

Shtulman, Andrew

2013-01-01

The evidential support for scientific claims is quantitatively and qualitatively superior to that for supernatural claims, yet students may not appreciate this difference in light of the fact that both types of claims are learned in similar ways (through testimony rather than firsthand observation) and perform similar functions (explaining…

Cloud4Psi: cloud computing for 3D protein structure similarity searching.

Science.gov (United States)

Mrozek, Dariusz; Małysiak-Mrozek, Bożena; Kłapciński, Artur

2014-10-01

Popular methods for 3D protein structure similarity searching, especially those that generate high-quality alignments such as Combinatorial Extension (CE) and Flexible structure Alignment by Chaining Aligned fragment pairs allowing Twists (FATCAT) are still time consuming. As a consequence, performing similarity searching against large repositories of structural data requires increased computational resources that are not always available. Cloud computing provides huge amounts of computational power that can be provisioned on a pay-as-you-go basis. We have developed the cloud-based system that allows scaling of the similarity searching process vertically and horizontally. Cloud4Psi (Cloud for Protein Similarity) was tested in the Microsoft Azure cloud environment and provided good, almost linearly proportional acceleration when scaled out onto many computational units. Cloud4Psi is available as Software as a Service for testing purposes at: http://cloud4psi.cloudapp.net/. For source code and software availability, please visit the Cloud4Psi project home page at http://zti.polsl.pl/dmrozek/science/cloud4psi.htm. © The Author 2014. Published by Oxford University Press.

A high-performance liquid chromatography method for the serotonin release assay is equivalent to the radioactive method.

Science.gov (United States)

Sono-Koree, N K; Crist, R A; Frank, E L; Rodgers, G M; Smock, K J

2016-02-01

The serotonin release assay (SRA) is considered the gold standard laboratory test for heparin-induced thrombocytopenia (HIT). The historic SRA method uses platelets loaded with radiolabeled serotonin to evaluate platelet activation by HIT immune complexes. However, a nonradioactive method is desirable. We report the performance characteristics of a high-performance liquid chromatography (HPLC) SRA method. We validated the performance characteristics of an HPLC-SRA method, including correlation with a reference laboratory using the radioactive method. Serotonin released from reagent platelets was quantified by HPLC using fluorescent detection. Results were expressed as % release and classified as positive, negative, or indeterminate based on previously published cutoffs. Serum samples from 250 subjects with suspected HIT were tested in the HPLC-SRA and with the radioactive method. Concordant classifications were observed in 230 samples (92%). Sera from 41 healthy individuals tested negative. Between-run imprecision studies showed standard deviation of performance characteristics, equivalent to the historic radioactive method, but avoids the complexities of working with radioactivity. © 2015 John Wiley & Sons Ltd.

Modeling Nanoscale FinFET Performance by a Neural Network Method

Directory of Open Access Journals (Sweden)

Jin He

2017-07-01

Full Text Available This paper presents a neural network method to model nanometer FinFET performance. The principle of this method is firstly introduced and its application in modeling DC and conductance characteristics of nanoscale FinFET transistor is demonstrated in detail. It is shown that this method does not need parameter extraction routine while its prediction of the transistor performance has a small relative error within 1 % compared with measured data, thus this new method is as accurate as the physics based surface potential model.

Determination of optimal samples for robot calibration based on error similarity

Directory of Open Access Journals (Sweden)

Tian Wei

2015-06-01

Full Text Available Industrial robots are used for automatic drilling and riveting. The absolute position accuracy of an industrial robot is one of the key performance indexes in aircraft assembly, and can be improved through error compensation to meet aircraft assembly requirements. The achievable accuracy and the difficulty of accuracy compensation implementation are closely related to the choice of sampling points. Therefore, based on the error similarity error compensation method, a method for choosing sampling points on a uniform grid is proposed. A simulation is conducted to analyze the influence of the sample point locations on error compensation. In addition, the grid steps of the sampling points are optimized using a statistical analysis method. The method is used to generate grids and optimize the grid steps of a Kuka KR-210 robot. The experimental results show that the method for planning sampling data can be used to effectively optimize the sampling grid. After error compensation, the position accuracy of the robot meets the position accuracy requirements.

Identification of robust statistical downscaling methods based on a comprehensive suite of performance metrics for South Korea

Science.gov (United States)

Eum, H. I.; Cannon, A. J.

2015-12-01

Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the

40 CFR 63.344 - Performance test requirements and test methods.

Science.gov (United States)

2010-07-01

... electroplating tanks or chromium anodizing tanks. The sampling time and sample volume for each run of Methods 306... Chromium Anodizing Tanks § 63.344 Performance test requirements and test methods. (a) Performance test... Emissions From Decorative and Hard Chromium Electroplating and Anodizing Operations,” appendix A of this...

46 CFR 57.06-3 - Method of performing production testing.

Science.gov (United States)

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Method of performing production testing. 57.06-3 Section 57.06-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING WELDING AND BRAZING Production Tests § 57.06-3 Method of performing production testing. (a) Except as...

A touch-probe path generation method through similarity analysis between the feature vectors in new and old models

Energy Technology Data Exchange (ETDEWEB)

Jeon, Hye Sung; Lee, Jin Won; Yang, Jeong Sam [Dept. of Industrial Engineering, Ajou University, Suwon (Korea, Republic of)

2016-10-15

The On-machine measurement (OMM), which measures a work piece during or after the machining process in the machining center, has the advantage of measuring the work piece directly within the work space without moving it. However, the path generation procedure used to determine the measuring sequence and variables for the complex features of a target work piece has the limitation of requiring time-consuming tasks to generate the measuring points and mostly relies on the proficiency of the on-site engineer. In this study, we propose a touch-probe path generation method using similarity analysis between the feature vectors of three-dimensional (3-D) shapes for the OMM. For the similarity analysis between a new 3-D model and existing 3-D models, we extracted the feature vectors from models that can describe the characteristics of a geometric shape model; then, we applied those feature vectors to a geometric histogram that displays a probability distribution obtained by the similarity analysis algorithm. In addition, we developed a computer-aided inspection planning system that corrects non-applied measuring points that are caused by minute geometry differences between the two models and generates the final touch-probe path.

Identification of strains with phenotypes similar to those of Staphylococcus aureus isolated from table chicken eggs using MALDI-TOF MS and genotyping methods

Directory of Open Access Journals (Sweden)

Marek Agnieszka

2015-06-01

Full Text Available The aim of the study was to identify the affinity of 10 Staphylococcus strains isolated from table chicken eggs to specific species. Preliminary analysis performed by API ID32 Staph test identified these strains as S. aureus, but they exhibited a negative reaction in the tube coagulase test. Thus, the analysed strains were initially characterised as Staphylococcus aureus-like (SAL. Further characterisation was performed by genotypic methods, using restriction fragment length polymorphism (RFLP of the coagulase gene (coa and sequencing of the gene rpoB. An attempt was also made to identify the isolated Staphylococcus strains by MALDI-TOF mass spectrometry. The results indicated that none of the strains tested belonged to the species S. aureus. The rpoB sequences of five isolates showed the highest sequence similarity to S. haemolyticus, three isolates to S. chromogenes, and one isolate to S. epidermidis. One strain (SAL4 remained unidentified in this analysis. The results obtained using mass spectrometry were comparable to those based on gene sequence analysis. Strain SAL4, which could not be identified by sequencing, was identified by MALDI-TOF as Staphylococcus chromogenes.

Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity.

Science.gov (United States)

Li, Guanghui; Luo, Jiawei; Xiao, Qiu; Liang, Cheng; Ding, Pingjian

2018-05-12

Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases. Copyright © 2018. Published by Elsevier Inc.

Human performance assessment: methods and measures

International Nuclear Information System (INIS)

Andresen, Gisle; Droeivoldsmo, Asgeir

2000-10-01

The Human Error Analysis Project (HEAP) was initiated in 1994. The aim of the project was to acquire insights on how and why cognitive errors occur when operators are engaged in problem solving in advanced integrated control rooms. Since human error had not been studied in the HAlden Man-Machine LABoratory (HAMMLAB) before, it was also necessary to carry out research in methodology. In retrospect, it is clear that much of the methodological work is relevant to human-machine research in general, and not only to research on human error. The purpose of this report is, therefore, to give practitioners and researchers an overview of the methodological parts of HEAP. The scope of the report is limited to methods used throughout the data acquisition process, i.e., data-collection methods, data-refinement methods, and measurement methods. The data-collection methods include various types of verbal protocols, simulator logs, questionnaires, and interviews. Data-refinement methods involve different applications of the Eyecon system, a flexible data-refinement tool, and small computer programs used for rearranging, reformatting, and aggregating raw-data. Measurement methods involve assessment of diagnostic behaviour, erroneous actions, complexity, task/system performance, situation awareness, and workload. The report concludes that the data-collection methods are generally both reliable and efficient. The data-refinement methods, however, should be easier to use in order to facilitate explorative analyses. Although the series of experiments provided an opportunity for measurement validation, there are still uncertainties connected to several measures, due to their reliability still being unknown. (Author). 58 refs.,7 tabs

New similarity of triangular fuzzy number and its application.

Science.gov (United States)

Zhang, Xixiang; Ma, Weimin; Chen, Liping

2014-01-01

The similarity of triangular fuzzy numbers is an important metric for application of it. There exist several approaches to measure similarity of triangular fuzzy numbers. However, some of them are opt to be large. To make the similarity well distributed, a new method SIAM (Shape's Indifferent Area and Midpoint) to measure triangular fuzzy number is put forward, which takes the shape's indifferent area and midpoint of two triangular fuzzy numbers into consideration. Comparison with other similarity measurements shows the effectiveness of the proposed method. Then, it is applied to collaborative filtering recommendation to measure users' similarity. A collaborative filtering case is used to illustrate users' similarity based on cloud model and triangular fuzzy number; the result indicates that users' similarity based on triangular fuzzy number can obtain better discrimination. Finally, a simulated collaborative filtering recommendation system is developed which uses cloud model and triangular fuzzy number to express users' comprehensive evaluation on items, and result shows that the accuracy of collaborative filtering recommendation based on triangular fuzzy number is higher.

Performance of the lot quality assurance sampling method compared to surveillance for identifying inadequately-performing areas in Matlab, Bangladesh.

Science.gov (United States)

Bhuiya, Abbas; Hanifi, S M A; Roy, Nikhil; Streatfield, P Kim

2007-03-01

This paper compared the performance of the lot quality assurance sampling (LQAS) method in identifying inadequately-performing health work-areas with that of using health and demographic surveillance system (HDSS) data and examined the feasibility of applying the method by field-level programme supervisors. The study was carried out in Matlab, the field site of ICDDR,B, where a HDSS has been in place for over 30 years. The LQAS method was applied in 57 work-areas of community health workers in ICDDR,B-served areas in Matlab during July-September 2002. The performance of the LQAS method in identifying work-areas with adequate and inadequate coverage of various health services was compared with those of the HDSS. The health service-coverage indicators included coverage of DPT, measles, BCG vaccination, and contraceptive use. It was observed that the difference in the proportion of work-areas identified to be inadequately performing using the LQAS method with less than 30 respondents, and the HDSS was not statistically significant. The consistency between the LQAS method and the HDSS in identifying work-areas was greater for adequately-performing areas than inadequately-performing areas. It was also observed that the field managers could be trained to apply the LQAS method in monitoring their performance in reaching the target population.

Cold modalities with different thermodynamic properties have similar effects on muscular performance and activation.

Science.gov (United States)

Vieira, A; Oliveira, A B; Costa, J R; Herrera, E; Salvini, T F

2013-10-01

Although tissue cooling is widely used in the treatment of musculoskeletal injuries there is still controversy about its effects on muscular performance. The combination of cooling and exercise justifies the study of this topic. The aim was to compare the effects of ice pack and cold-water immersion on the muscular performance parameters of plantar flexors and muscular activation of the triceps surae. 41 healthy men (mean age: 22.1 years, SD: 2.9) were randomly assigned to cooling with either ice pack (n=20) or cold-water immersion (n=21). Independent variables were cold modality (ice pack or cold-water immersion) and pre- and post-cooling measurement time. Dependent variables were muscular performance (measured during isometric and concentric contractions of plantar flexors) and electromyography parameters of the triceps surae (median frequency and root mean square amplitude). Dependent-samples t-tests were used to compare pre- and post-cooling data and independent-samples t-tests were used to compare the difference (pre- and post-cooling) between groups. Ice pack increased isometric peak torque (mean: 9.00 Nm, P=0.01) and both cold modalities reduced muscular activation in triceps surae (Pimmersion and ice pack reduced peak torque and total work during dynamic isokinetic contraction at both velocities (mean: -11,00 Nm, Pimmersion decrease concentric muscular performance. These results indicate that these cooling methods should be chosen with caution, considering the type of task required during training or rehabilitation. New studies investigating other muscle groups and joints are necessary. © Georg Thieme Verlag KG Stuttgart · New York.

Application of 3D Zernike descriptors to shape-based ligand similarity searching.

Science.gov (United States)

Venkatraman, Vishwesh; Chakravarthy, Padmasini Ramji; Kihara, Daisuke

2009-12-17

The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.

Detecting local ligand-binding site similarity in nonhomologous proteins by surface patch comparison.

Science.gov (United States)

Sael, Lee; Kihara, Daisuke

2012-04-01

Functional elucidation of proteins is one of the essential tasks in biology. Function of a protein, specifically, small ligand molecules that bind to a protein, can be predicted by finding similar local surface regions in binding sites of known proteins. Here, we developed an alignment free local surface comparison method for predicting a ligand molecule which binds to a query protein. The algorithm, named Patch-Surfer, represents a binding pocket as a combination of segmented surface patches, each of which is characterized by its geometrical shape, the electrostatic potential, the hydrophobicity, and the concaveness. Representing a pocket by a set of patches is effective to absorb difference of global pocket shape while capturing local similarity of pockets. The shape and the physicochemical properties of surface patches are represented using the 3D Zernike descriptor, which is a series expansion of mathematical 3D function. Two pockets are compared using a modified weighted bipartite matching algorithm, which matches similar patches from the two pockets. Patch-Surfer was benchmarked on three datasets, which consist in total of 390 proteins that bind to one of 21 ligands. Patch-Surfer showed superior performance to existing methods including a global pocket comparison method, Pocket-Surfer, which we have previously introduced. Particularly, as intended, the accuracy showed large improvement for flexible ligand molecules, which bind to pockets in different conformations. Copyright © 2011 Wiley Periodicals, Inc.

Mitigating component performance variation

Science.gov (United States)

Gara, Alan G.; Sylvester, Steve S.; Eastep, Jonathan M.; Nagappan, Ramkumar; Cantalupo, Christopher M.

2018-01-09

Apparatus and methods may provide for characterizing a plurality of similar components of a distributed computing system based on a maximum safe operation level associated with each component and storing characterization data in a database and allocating non-uniform power to each similar component based at least in part on the characterization data in the database to substantially equalize performance of the components.

Notions of similarity for systems biology models.

Science.gov (United States)

Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knüpfer, Christian; Liebermeister, Wolfram; Waltemath, Dagmar

2018-01-01

Systems biology models are rapidly increasing in complexity, size and numbers. When building large models, researchers rely on software tools for the retrieval, comparison, combination and merging of models, as well as for version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of 'similarity' may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here we survey existing methods for the comparison of models, introduce quantitative measures for model similarity, and discuss potential applications of combined similarity measures. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on a combination of different model aspects. The six aspects that we define as potentially relevant for similarity are underlying encoding, references to biological entities, quantitative behaviour, qualitative behaviour, mathematical equations and parameters and network structure. We argue that future similarity measures will benefit from combining these model aspects in flexible, problem-specific ways to mimic users' intuition about model similarity, and to support complex model searches in databases. © The Author 2016. Published by Oxford University Press.

Performance Poetry as a Method to Understand Disability

Directory of Open Access Journals (Sweden)

Lee-Ann Fenge

2016-03-01

Full Text Available The Seen but Seldom Heard project was a performative social science (PSS project which used performance poetry to illuminate the experiences of young people with physical impairments. Two performance poets, a group of young people with physical impairments, and academics from social science and media/communication backgrounds worked together to explore various aspects of the lived experience of disability exploring issues associated with identity, stereotypes, stigma and representation. In this article, we will present an overview of the project and consider how PSS offers a method to engage seldom heard voices, and illustrate this through two poems which shed light on the lived experience of disability. The article will consider the impact of these poems as PSS, and how this method allows the audience to develop a deeper understanding of the "lived" experience of disability and to reflect upon their own understandings of disability and discrimination. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs1602118

Performance-based parameter tuning method of model-driven PID control systems.

Science.gov (United States)

Zhao, Y M; Xie, W F; Tu, X W

2012-05-01

In this paper, performance-based parameter tuning method of model-driven Two-Degree-of-Freedom PID (MD TDOF PID) control system has been proposed to enhance the control performances of a process. Known for its ability of stabilizing the unstable processes, fast tracking to the change of set points and rejecting disturbance, the MD TDOF PID has gained research interest recently. The tuning methods for the reported MD TDOF PID are based on internal model control (IMC) method instead of optimizing the performance indices. In this paper, an Integral of Time Absolute Error (ITAE) zero-position-error optimal tuning and noise effect minimizing method is proposed for tuning two parameters in MD TDOF PID control system to achieve the desired regulating and disturbance rejection performance. The comparison with Two-Degree-of-Freedom control scheme by modified smith predictor (TDOF CS MSP) and the designed MD TDOF PID tuned by the IMC tuning method demonstrates the effectiveness of the proposed tuning method. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Self-Similar Spin Images for Point Cloud Matching

Science.gov (United States)

Pulido, Daniel

based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.

Contingency and similarity in response selection.

Science.gov (United States)

Prinz, Wolfgang

2018-05-09

This paper explores issues of task representation in choice reaction time tasks. How is it possible, and what does it take, to represent such a task in a way that enables a performer to do the task in line with the prescriptions entailed in the instructions? First, a framework for task representation is outlined which combines the implementation of task sets and their use for performance with different kinds of representational operations (pertaining to feature compounds for event codes and code assemblies for task sets, respectively). Then, in a second step, the framework is itself embedded in the bigger picture of the classical debate on the roles of contingency and similarity for the formation of associations. The final conclusion is that both principles are needed and that the operation of similarity at the level of task sets requires and presupposes the operation of contingency at the level of event codes. Copyright © 2018 The Author. Published by Elsevier Inc. All rights reserved.

Scalable gastroscopic video summarization via similar-inhibition dictionary selection.

Science.gov (United States)

Wang, Shuai; Cong, Yang; Cao, Jun; Yang, Yunsheng; Tang, Yandong; Zhao, Huaici; Yu, Haibin

2016-01-01

This paper aims at developing an automated gastroscopic video summarization algorithm to assist clinicians to more effectively go through the abnormal contents of the video. To select the most representative frames from the original video sequence, we formulate the problem of gastroscopic video summarization as a dictionary selection issue. Different from the traditional dictionary selection methods, which take into account only the number and reconstruction ability of selected key frames, our model introduces the similar-inhibition constraint to reinforce the diversity of selected key frames. We calculate the attention cost by merging both gaze and content change into a prior cue to help select the frames with more high-level semantic information. Moreover, we adopt an image quality evaluation process to eliminate the interference of the poor quality images and a segmentation process to reduce the computational complexity. For experiments, we build a new gastroscopic video dataset captured from 30 volunteers with more than 400k images and compare our method with the state-of-the-arts using the content consistency, index consistency and content-index consistency with the ground truth. Compared with all competitors, our method obtains the best results in 23 of 30 videos evaluated based on content consistency, 24 of 30 videos evaluated based on index consistency and all videos evaluated based on content-index consistency. For gastroscopic video summarization, we propose an automated annotation method via similar-inhibition dictionary selection. Our model can achieve better performance compared with other state-of-the-art models and supplies more suitable key frames for diagnosis. The developed algorithm can be automatically adapted to various real applications, such as the training of young clinicians, computer-aided diagnosis or medical report generation. Copyright © 2015 Elsevier B.V. All rights reserved.

Validated high performance liquid chromatographic (HPLC) method ...

African Journals Online (AJOL)

STORAGESEVER

2010-02-22

Feb 22, 2010 ... specific and accurate high performance liquid chromatographic method for determination of ZER in micro-volumes ... tional medicine as a cure for swelling, sores, loss of appetite and ... Receptor Activator for Nuclear Factor κ B Ligand .... The effect of ... be suitable for preclinical pharmacokinetic studies. The.

Performance of wave function and density functional methods for water hydrogen bond spin-spin coupling constants.

Science.gov (United States)

García de la Vega, J M; Omar, S; San Fabián, J

2017-04-01

Spin-spin coupling constants in water monomer and dimer have been calculated using several wave function and density functional-based methods. CCSD, MCSCF, and SOPPA wave functions methods yield similar results, specially when an additive approach is used with the MCSCF. Several functionals have been used to analyze their performance with the Jacob's ladder and a set of functionals with different HF exchange were tested. Functionals with large HF exchange appropriately predict 1 J O H , 2 J H H and 2h J O O couplings, while 1h J O H is better calculated with functionals that include a reduced fraction of HF exchange. Accurate functionals for 1 J O H and 2 J H H have been tested in a tetramer water model. The hydrogen bond effects on these intramolecular couplings are additive when they are calculated by SOPPA(CCSD) wave function and DFT methods. Graphical Abstract Evaluation of the additive effect of the hydrogen bond on spin-spin coupling constants of water using WF and DFT methods.

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.

High-performance liquid chromatography method for the determination of hydrogen peroxide present or released in teeth bleaching kits and hair cosmetic products.

Science.gov (United States)

Gimeno, Pascal; Bousquet, Claudine; Lassu, Nelly; Maggio, Annie-Françoise; Civade, Corinne; Brenier, Charlotte; Lempereur, Laurent

2015-03-25

This manuscript presents an HPLC/UV method for the determination of hydrogen peroxide present or released in teeth bleaching products and hair products. The method is based on an oxidation of triphenylphosphine into triphenylphosphine oxide by hydrogen peroxide. Triphenylphosphine oxide formed is quantified by HPLC/UV. Validation data were obtained using the ISO 12787 standard approach, particularly adapted when it is not possible to make reconstituted sample matrices. For comparative purpose, hydrogen peroxide was also determined using ceric sulfate titrimetry for both types of products. For hair products, a cross validation of both ceric titrimetric method and HPLC/UV method using the cosmetic 82/434/EEC directive (official iodometric titration method) was performed. Results obtained for 6 commercialized teeth whitening products and 5 hair products point out similar hydrogen peroxide contain using either the HPLC/UV method or ceric sulfate titrimetric method. For hair products, results were similar to the hydrogen peroxide content using the cosmetic 82/434/EEC directive method and for the HPLC/UV method, mean recoveries obtained on spiked samples, using the ISO 12787 standard, ranges from 100% to 110% with a RSDhydrogen peroxide contents higher than the regulated limit. Copyright © 2015 Elsevier B.V. All rights reserved.

Notions of similarity for computational biology models

KAUST Repository

Waltemath, Dagmar

2016-03-21

Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users\\' intuition about model similarity, and to support complex model searches in databases.

Notions of similarity for computational biology models

KAUST Repository

Waltemath, Dagmar; Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knuepfer, Christian; Liebermeister, Wolfram

2016-01-01

Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users' intuition about model similarity, and to support complex model searches in databases.

Similarity-transformed equation-of-motion vibrational coupled-cluster theory

Science.gov (United States)

Faucheaux, Jacob A.; Nooijen, Marcel; Hirata, So

2018-02-01

A similarity-transformed equation-of-motion vibrational coupled-cluster (STEOM-XVCC) method is introduced as a one-mode theory with an effective vibrational Hamiltonian, which is similarity transformed twice so that its lower-order operators are dressed with higher-order anharmonic effects. The first transformation uses an exponential excitation operator, defining the equation-of-motion vibrational coupled-cluster (EOM-XVCC) method, and the second uses an exponential excitation-deexcitation operator. From diagonalization of this doubly similarity-transformed Hamiltonian in the small one-mode excitation space, the method simultaneously computes accurate anharmonic vibrational frequencies of all fundamentals, which have unique significance in vibrational analyses. We establish a diagrammatic method of deriving the working equations of STEOM-XVCC and prove their connectedness and thus size-consistency as well as the exact equality of its frequencies with the corresponding roots of EOM-XVCC. We furthermore elucidate the similarities and differences between electronic and vibrational STEOM methods and between STEOM-XVCC and vibrational many-body Green's function theory based on the Dyson equation, which is also an anharmonic one-mode theory. The latter comparison inspires three approximate STEOM-XVCC methods utilizing the common approximations made in the Dyson equation: the diagonal approximation, a perturbative expansion of the Dyson self-energy, and the frequency-independent approximation. The STEOM-XVCC method including up to the simultaneous four-mode excitation operator in a quartic force field and its three approximate variants are formulated and implemented in computer codes with the aid of computer algebra, and they are applied to small test cases with varied degrees of anharmonicity.

A Method To ModifyCorrect The Performance Of Amplifiers

Directory of Open Access Journals (Sweden)

Rohith Krishnan R

2015-01-01

Full Text Available Abstract The actual response of the amplifier may vary with the replacement of some aged or damaged components and this method is to compensate that problem. Here we use op-amp Fixator as the design tool. The tool helps us to isolate the selected circuit component from rest of the circuit adjust its operating point to correct the performance deviations and to modify the circuit without changing other parts of the circuit. A method to modifycorrect the performance of amplifiers by properly redesign the circuit is presented in this paper.

Estimation of flows cavitation by similarity test: application to the couple water/liquid sodium

International Nuclear Information System (INIS)

Espanet, Laurent

2000-01-01

In many industrial flows, it is necessary to perform a similarity test to assess the cavitation intensity. The similarity laws must take into account the physical properties of the two fluids and especially the surface tension. To obtain such laws, a continuous description of the two-phase flow has been used. The non linear model of Cahn and Hilliard allows to obtain the equations of motion for these fluids, and non-dimensional conditions yield to the similarity laws. This method has been checked experimentally by achieving two different flows through a diaphragm. When respecting the similarity laws, the comparison of these flows allows to validate the transposition laws and to determine their associated tolerance. At last, the number of dusts and particles is an important parameter for cavitation inception threshold since it leads to the number of bubbles. Using the Laplace theory, it is shown that for each value of flow rate, it exists an upper bound value for the bubble density, which allows to establish a similarity law concerning this number of bubbles. (author) [fr

Performance evaluation methods and instrumentation for mine ventilation fans

Institute of Scientific and Technical Information of China (English)

LI Man; WANG Xue-rong

2009-01-01

Ventilation fans are one of the most important pieces of equipment in coal mines. Their performance plays an important role in the safety of staff and production. Given the actual requirements of coal mine production, we instituted a research project on the measurement methods of key performance parameters such as wind pressure, amount of ventilation and power. At the end a virtual instrument for mine ventilation fans performance evaluation was developed using a USB interface. The practical perform-ance and analytical results of our experiments show that it is feasible, reliable and effective to use the proposed instrumentation for mine ventilation performance evaluation.

HYPOTHESIS TESTING WITH THE SIMILARITY INDEX

Science.gov (United States)

Mulltilocus DNA fingerprinting methods have been used extensively to address genetic issues in wildlife populations. Hypotheses concerning population subdivision and differing levels of diversity can be addressed through the use of the similarity index (S), a band-sharing coeffic...

In-depth performance evaluation of PFP and ESG sequence-based function prediction methods in CAFA 2011 experiment

Directory of Open Access Journals (Sweden)

Chitale Meghana

2013-02-01

Full Text Available Abstract Background Many Automatic Function Prediction (AFP methods were developed to cope with an increasing growth of the number of gene sequences that are available from high throughput sequencing experiments. To support the development of AFP methods, it is essential to have community wide experiments for evaluating performance of existing AFP methods. Critical Assessment of Function Annotation (CAFA is one such community experiment. The meeting of CAFA was held as a Special Interest Group (SIG meeting at the Intelligent Systems in Molecular Biology (ISMB conference in 2011. Here, we perform a detailed analysis of two sequence-based function prediction methods, PFP and ESG, which were developed in our lab, using the predictions submitted to CAFA. Results We evaluate PFP and ESG using four different measures in comparison with BLAST, Prior, and GOtcha. In addition to the predictions submitted to CAFA, we further investigate performance of a different scoring function to rank order predictions by PFP as well as PFP/ESG predictions enriched with Priors that simply adds frequently occurring Gene Ontology terms as a part of predictions. Prediction accuracies of each method were also evaluated separately for different functional categories. Successful and unsuccessful predictions by PFP and ESG are also discussed in comparison with BLAST. Conclusion The in-depth analysis discussed here will complement the overall assessment by the CAFA organizers. Since PFP and ESG are based on sequence database search results, our analyses are not only useful for PFP and ESG users but will also shed light on the relationship of the sequence similarity space and functions that can be inferred from the sequences.

Articulation of Phonologically Similar Items Disrupts Free Recall of Nonwords

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Nishiyama, Ryoji; Ukita, Jun

2013-01-01

The present study sought to clarify whether phonological similarity of encoded information impairs free recall performance (the phonological similarity effect: PSE) for nonwords. Five experiments examined the influence of the encoding process on the PSE in a step-by-step fashion, by using lists that consisted of phonologically similar (decoy)…

Similarity indices I: what do they measure

International Nuclear Information System (INIS)

Johnston, J.W.

1976-11-01

A method for estimating the effects of environmental effusions on ecosystems is described. The characteristics of 25 similarity indices used in studies of ecological communities were investigated. The type of data structure, to which these indices are frequently applied, was described as consisting of vectors of measurements on attributes (species) observed in a set of samples. A general similarity index was characterized as the result of a two-step process defined on a pair of vectors. In the first step an attribute similarity score is obtained for each attribute by comparing the attribute values observed in the pair of vectors. The result is a vector of attribute similarity scores. These are combined in the second step to arrive at the similarity index. The operation in the first step was characterized as a function, g, defined on pairs of attribute values. The second operation was characterized as a function, F, defined on the vector of attribute similarity scores from the first step. Usually, F was a simple sum or weighted sum of the attribute similarity scores. It is concluded that similarity indices should not be used as the test statistic to discriminate between two ecological communities

Similarity indices I: what do they measure.

Energy Technology Data Exchange (ETDEWEB)

Johnston, J.W.

1976-11-01

A method for estimating the effects of environmental effusions on ecosystems is described. The characteristics of 25 similarity indices used in studies of ecological communities were investigated. The type of data structure, to which these indices are frequently applied, was described as consisting of vectors of measurements on attributes (species) observed in a set of samples. A general similarity index was characterized as the result of a two-step process defined on a pair of vectors. In the first step an attribute similarity score is obtained for each attribute by comparing the attribute values observed in the pair of vectors. The result is a vector of attribute similarity scores. These are combined in the second step to arrive at the similarity index. The operation in the first step was characterized as a function, g, defined on pairs of attribute values. The second operation was characterized as a function, F, defined on the vector of attribute similarity scores from the first step. Usually, F was a simple sum or weighted sum of the attribute similarity scores. It is concluded that similarity indices should not be used as the test statistic to discriminate between two ecological communities.

Hybrid recommendation methods in complex networks.

Science.gov (United States)

Fiasconaro, A; Tumminello, M; Nicosia, V; Latora, V; Mantegna, R N

2015-07-01

We propose two recommendation methods, based on the appropriate normalization of already existing similarity measures, and on the convex combination of the recommendation scores derived from similarity between users and between objects. We validate the proposed measures on three data sets, and we compare the performance of our methods to other recommendation systems recently proposed in the literature. We show that the proposed similarity measures allow us to attain an improvement of performances of up to 20% with respect to existing nonparametric methods, and that the accuracy of a recommendation can vary widely from one specific bipartite network to another, which suggests that a careful choice of the most suitable method is highly relevant for an effective recommendation on a given system. Finally, we study how an increasing presence of random links in the network affects the recommendation scores, finding that one of the two recommendation algorithms introduced here can systematically outperform the others in noisy data sets.

Multicriteria Similarity-Based Anomaly Detection Using Pareto Depth Analysis.

Science.gov (United States)

Hsiao, Ko-Jen; Xu, Kevin S; Calder, Jeff; Hero, Alfred O

2016-06-01

We consider the problem of identifying patterns in a data set that exhibits anomalous behavior, often referred to as anomaly detection. Similarity-based anomaly detection algorithms detect abnormally large amounts of similarity or dissimilarity, e.g., as measured by the nearest neighbor Euclidean distances between a test sample and the training samples. In many application domains, there may not exist a single dissimilarity measure that captures all possible anomalous patterns. In such cases, multiple dissimilarity measures can be defined, including nonmetric measures, and one can test for anomalies by scalarizing using a nonnegative linear combination of them. If the relative importance of the different dissimilarity measures are not known in advance, as in many anomaly detection applications, the anomaly detection algorithm may need to be executed multiple times with different choices of weights in the linear combination. In this paper, we propose a method for similarity-based anomaly detection using a novel multicriteria dissimilarity measure, the Pareto depth. The proposed Pareto depth analysis (PDA) anomaly detection algorithm uses the concept of Pareto optimality to detect anomalies under multiple criteria without having to run an algorithm multiple times with different choices of weights. The proposed PDA approach is provably better than using linear combinations of the criteria, and shows superior performance on experiments with synthetic and real data sets.

A Mixed-Method Approach on Digital Educational Games for K12: Gender, Attitudes and Performance

Science.gov (United States)

Law, Effie Lai-Chong; Gamble, Tim; Schwarz, Daniel; Kickmeier-Rust, Michael D.; Holzinger, Andreas

Research on the influence of gender on attitudes towards and performance in digital educational games (DEGs) has quite a long history. Generally, males tend to play such games more engagingly than females, consequently attitude and performance of males using DEGs should be presumably higher than that of females. This paper reports an investigation of a DEG, which was developed to enhance the acquisition of geographical knowledge, carried out on British, German and Austrian K12 students aged between 11 and 14. Methods include a survey on initial design concepts, user tests on the system and two single-gender focus groups. Gender and cultural differences in gameplay habit, game type preferences and game character perceptions were observed. The results showed that both genders similarly improved their geographical knowledge, although boys tended to have a higher level of positive user experience than the girls. The qualitative data from the focus groups illustrated some interesting gender differences in perceiving various aspects of the game.

A service based estimation method for MPSoC performance modelling

DEFF Research Database (Denmark)

Tranberg-Hansen, Anders Sejer; Madsen, Jan; Jensen, Bjørn Sand

2008-01-01

This paper presents an abstract service based estimation method for MPSoC performance modelling which allows fast, cycle accurate design space exploration of complex architectures including multi processor configurations at a very early stage in the design phase. The modelling method uses a service...... oriented model of computation based on Hierarchical Colored Petri Nets and allows the modelling of both software and hardware in one unified model. To illustrate the potential of the method, a small MPSoC system, developed at Bang & Olufsen ICEpower a/s, is modelled and performance estimates are produced...

Influence of discretization method on the digital control system performance

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Futás József

2003-12-01

Full Text Available The design of control system can be divided into two steps. First the process or plant have to be convert into mathematical model form, so that its behavior can be analyzed. Then an appropriate controller have to be design in order to get the desired response of the controlled system. In the continuous time domain the system is represented by differential equations. Replacing a continuous system into discrete time form is always an approximation of the continuous system. The different discretization methods give different digital controller performance. The methods presented on the paper are Step Invariant or Zero Order Hold (ZOH Method, Matched Pole-Zero Method, Backward difference Method and Bilinear transformation. The above mentioned discretization methods are used in developing PI position controller of a dc motor. The motor model was converted by the ZOH method. The performances of the different methods are compared and the results are presented.

Efficient estimation for high similarities using odd sketches

DEFF Research Database (Denmark)

Mitzenmacher, Michael; Pagh, Rasmus; Pham, Ninh Dang

2014-01-01

. This means that Odd Sketches provide a highly space-efficient estimator for sets of high similarity, which is relevant in applications such as web duplicate detection, collaborative filtering, and association rule learning. The method extends to weighted Jaccard similarity, relevant e.g. for TF-IDF vector...... and web duplicate detection tasks....

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.

Modeling Timbre Similarity of Short Music Clips.

Science.gov (United States)

Siedenburg, Kai; Müllensiefen, Daniel

2017-01-01

There is evidence from a number of recent studies that most listeners are able to extract information related to song identity, emotion, or genre from music excerpts with durations in the range of tenths of seconds. Because of these very short durations, timbre as a multifaceted auditory attribute appears as a plausible candidate for the type of features that listeners make use of when processing short music excerpts. However, the importance of timbre in listening tasks that involve short excerpts has not yet been demonstrated empirically. Hence, the goal of this study was to develop a method that allows to explore to what degree similarity judgments of short music clips can be modeled with low-level acoustic features related to timbre. We utilized the similarity data from two large samples of participants: Sample I was obtained via an online survey, used 16 clips of 400 ms length, and contained responses of 137,339 participants. Sample II was collected in a lab environment, used 16 clips of 800 ms length, and contained responses from 648 participants. Our model used two sets of audio features which included commonly used timbre descriptors and the well-known Mel-frequency cepstral coefficients as well as their temporal derivates. In order to predict pairwise similarities, the resulting distances between clips in terms of their audio features were used as predictor variables with partial least-squares regression. We found that a sparse selection of three to seven features from both descriptor sets-mainly encoding the coarse shape of the spectrum as well as spectrotemporal variability-best predicted similarities across the two sets of sounds. Notably, the inclusion of non-acoustic predictors of musical genre and record release date allowed much better generalization performance and explained up to 50% of shared variance ( R 2 ) between observations and model predictions. Overall, the results of this study empirically demonstrate that both acoustic features related

Performance analysis, quality function deployment and structured methods

Science.gov (United States)

Maier, M. W.

Quality function deployment, (QFD), an approach to synthesizing several elements of system modeling and design into a single unit, is presented. Behavioral, physical, and performance modeling are usually considered as separate aspects of system design without explicit linkages. Structured methodologies have developed linkages between behavioral and physical models before, but have not considered the integration of performance models. QFD integrates performance models with traditional structured models. In this method, performance requirements such as cost, weight, and detection range are partitioned into matrices. Partitioning is done by developing a performance model, preferably quantitative, for each requirement. The parameters of the model become the engineering objectives in a QFD analysis and the models are embedded in a spreadsheet version of the traditional QFD matrices. The performance model and its parameters are used to derive part of the functional model by recognizing that a given performance model implies some structure to the functionality of the system.

The predictive model on the user reaction time using the information similarity

International Nuclear Information System (INIS)

Lee, Sung Jin; Heo, Gyun Young; Chang, Soon Heung

2005-01-01

Human performance is frequently degraded because people forget. Memory is one of brain processes that are important when trying to understand how people process information. Although a large number of studies have been made on the human performance, little is known about the similarity effect in human performance. The purpose of this paper is to propose and validate the quantitative and predictive model on the human response time in the user interface with the concept of similarity. However, it is not easy to explain the human performance with only similarity or information amount. We are confronted by two difficulties: making the quantitative model on the human response time with the similarity and validating the proposed model by experimental work. We made the quantitative model based on the Hick's law and the law of practice. In addition, we validated the model with various experimental conditions by measuring participants' response time in the environment of computer-based display. Experimental results reveal that the human performance is improved by the user interface's similarity. We think that the proposed model is useful for the user interface design and evaluation phases

Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods

Directory of Open Access Journals (Sweden)

Huiru Zhao

2016-01-01

Full Text Available As an efficient way to deal with the global climate change and energy shortage problems, a strong, self-healing, compatible, economic and integrative smart gird is under construction in China, which is supported by large amounts of investments and advanced technologies. To promote the construction, operation and sustainable development of Strong Smart Grid (SSG, a novel hybrid framework for evaluating the performance of SSG is proposed from the perspective of sustainability. Based on a literature review, experts’ opinions and the technical characteristics of SSG, the evaluation model involves four sustainability criteria defined as economy, society, environment and technology aspects associated with 12 sub-criteria. Considering the ambiguity and vagueness of the subjective judgments on sub-criteria, fuzzy TOPSIS method is employed to evaluate the performance of SSG. In addition, different from previous research, this paper adopts the stochastic Analytical Hierarchy Process (AHP method to upgrade the traditional Technique for Order Preference by Similarity to Ideal Solution (TOPSIS by addressing the fuzzy and stochastic factors within weights calculation. Finally, four regional smart grids in China are ranked by employing the proposed framework. The results show that the sub-criteria affiliated with environment obtain much more attention than that of economy from experts group. Moreover, the sensitivity analysis indicates the ranking list remains stable no matter how sub-criteria weights are changed, which verifies the robustness and effectiveness of the proposed model and evaluation results. This study provides a comprehensive and effective method for performance evaluation of SSG and also innovates the weights calculation for traditional TOPSIS.

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.

Technology-based vs. traditional instruction. A comparison of two methods for teaching the skill of performing a 12-lead ECG.

Science.gov (United States)

Jeffries, Pamela R; Woolf, Shirley; Linde, Beverly

2003-01-01

The purpose of this study was to compare the effectiveness of an interactive, multimedia CD-ROM with traditional methods of teaching the skill of performing a 12-lead ECG. A randomized pre/posttest experimental design was used. Seventy-seven baccalaureate nursing students in a required, senior-level critical-care course at a large midwestern university were recruited for the study. Two teaching methods were compared. The traditional method included a self-study module, a brief lecture and demonstration by an instructor, and hands-on experience using a plastic manikin and a real 12-lead ECG machine in the learning laboratory. The second method covered the same content using an interactive, multimedia CD-ROM embedded with virtual reality and supplemented with a self-study module. There were no significant (p method, or perception of self-efficacy in performing the skill. Overall results indicated that both groups were satisfied with their instructional method and were similar in their ability to demonstrate the skill correctly on a live, simulated patient. This evaluation study is a beginning step to assess new and potentially more cost-effective teaching methods and their effects on student learning outcomes and behaviors, including the transfer of skill acquisition via a computer simulation to a real patient.

a Two-Step Classification Approach to Distinguishing Similar Objects in Mobile LIDAR Point Clouds

Science.gov (United States)

He, H.; Khoshelham, K.; Fraser, C.

2017-09-01

Nowadays, lidar is widely used in cultural heritage documentation, urban modeling, and driverless car technology for its fast and accurate 3D scanning ability. However, full exploitation of the potential of point cloud data for efficient and automatic object recognition remains elusive. Recently, feature-based methods have become very popular in object recognition on account of their good performance in capturing object details. Compared with global features describing the whole shape of the object, local features recording the fractional details are more discriminative and are applicable for object classes with considerable similarity. In this paper, we propose a two-step classification approach based on point feature histograms and the bag-of-features method for automatic recognition of similar objects in mobile lidar point clouds. Lamp post, street light and traffic sign are grouped as one category in the first-step classification for their inter similarity compared with tree and vehicle. A finer classification of the lamp post, street light and traffic sign based on the result of the first-step classification is implemented in the second step. The proposed two-step classification approach is shown to yield a considerable improvement over the conventional one-step classification approach.

Application of discrete Fourier inter-coefficient difference for assessing genetic sequence similarity.

Science.gov (United States)

King, Brian R; Aburdene, Maurice; Thompson, Alex; Warres, Zach

2014-01-01

Digital signal processing (DSP) techniques for biological sequence analysis continue to grow in popularity due to the inherent digital nature of these sequences. DSP methods have demonstrated early success for detection of coding regions in a gene. Recently, these methods are being used to establish DNA gene similarity. We present the inter-coefficient difference (ICD) transformation, a novel extension of the discrete Fourier transformation, which can be applied to any DNA sequence. The ICD method is a mathematical, alignment-free DNA comparison method that generates a genetic signature for any DNA sequence that is used to generate relative measures of similarity among DNA sequences. We demonstrate our method on a set of insulin genes obtained from an evolutionarily wide range of species, and on a set of avian influenza viral sequences, which represents a set of highly similar sequences. We compare phylogenetic trees generated using our technique against trees generated using traditional alignment techniques for similarity and demonstrate that the ICD method produces a highly accurate tree without requiring an alignment prior to establishing sequence similarity.

Application of 3D Zernike descriptors to shape-based ligand similarity searching

Directory of Open Access Journals (Sweden)

Venkatraman Vishwesh

2009-12-01

Full Text Available Abstract Background The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. Conclusion The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.

Understanding similarity of groundwater systems with empirical copulas

Science.gov (United States)

Haaf, Ezra; Kumar, Rohini; Samaniego, Luis; Barthel, Roland

2016-04-01

Within the classification framework for groundwater systems that aims for identifying similarity of hydrogeological systems and transferring information from a well-observed to an ungauged system (Haaf and Barthel, 2015; Haaf and Barthel, 2016), we propose a copula-based method for describing groundwater-systems similarity. Copulas are an emerging method in hydrological sciences that make it possible to model the dependence structure of two groundwater level time series, independently of the effects of their marginal distributions. This study is based on Samaniego et al. (2010), which described an approach calculating dissimilarity measures from bivariate empirical copula densities of streamflow time series. Subsequently, streamflow is predicted in ungauged basins by transferring properties from similar catchments. The proposed approach is innovative because copula-based similarity has not yet been applied to groundwater systems. Here we estimate the pairwise dependence structure of 600 wells in Southern Germany using 10 years of weekly groundwater level observations. Based on these empirical copulas, dissimilarity measures are estimated, such as the copula's lower- and upper corner cumulated probability, copula-based Spearman's rank correlation - as proposed by Samaniego et al. (2010). For the characterization of groundwater systems, copula-based metrics are compared with dissimilarities obtained from precipitation signals corresponding to the presumed area of influence of each groundwater well. This promising approach provides a new tool for advancing similarity-based classification of groundwater system dynamics. Haaf, E., Barthel, R., 2015. Methods for assessing hydrogeological similarity and for classification of groundwater systems on the regional scale, EGU General Assembly 2015, Vienna, Austria. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs EGU General Assembly

Assessing the stability of free-energy perturbation calculations by performing variations in the method

Science.gov (United States)

Manzoni, Francesco; Ryde, Ulf

2018-03-01

We have calculated relative binding affinities for eight tetrafluorophenyl-triazole-thiogalactoside inhibitors of galectin-3 with the alchemical free-energy perturbation approach. We obtain a mean absolute deviation from experimental estimates of only 2-3 kJ/mol and a correlation coefficient (R 2) of 0.5-0.8 for seven relative affinities spanning a range of up to 11 kJ/mol. We also studied the effect of using different methods to calculate the charges of the inhibitor and different sizes of the perturbed group (the atoms that are described by soft-core potentials and are allowed to have differing coordinates). However, the various approaches gave rather similar results and it is not possible to point out one approach as consistently and significantly better than the others. Instead, we suggest that such small and reasonable variations in the computational method can be used to check how stable the calculated results are and to obtain a more accurate estimate of the uncertainty than if performing only one calculation with a single computational setup.

Presumed cultural similarity paradox : Expatriate adjustment and performance across the border or over the globe

NARCIS (Netherlands)

Vromans, P.; van Engen, M.L.; Mol, S.

2013-01-01

Purpose To introduce the presumed cultural similarity paradox as a possible explanation for the findings that adjusting to a culturally similar country is just as difficult as adjusting to a culturally dissimilar country. We provide a conceptual framework, enabling further understanding and research

Presumed cultural similarity paradox: expatriate adjustment and performance across the border or over the globe

NARCIS (Netherlands)

Vromans, P.; van Engen, M.; Mol, S.

2013-01-01

Purpose - To introduce the presumed cultural similarity paradox as a possible explanation for the findings that adjusting to a culturally similar country is just as difficult as adjusting to a culturally dissimilar country. We provide a conceptual framework, enabling further understanding and

A Similarity Search Using Molecular Topological Graphs

Directory of Open Access Journals (Sweden)

Yoshifumi Fukunishi

2009-01-01

Full Text Available A molecular similarity measure has been developed using molecular topological graphs and atomic partial charges. Two kinds of topological graphs were used. One is the ordinary adjacency matrix and the other is a matrix which represents the minimum path length between two atoms of the molecule. The ordinary adjacency matrix is suitable to compare the local structures of molecules such as functional groups, and the other matrix is suitable to compare the global structures of molecules. The combination of these two matrices gave a similarity measure. This method was applied to in silico drug screening, and the results showed that it was effective as a similarity measure.

Detecting Local Ligand-Binding Site Similarity in Non-Homologous Proteins by Surface Patch Comparison

Science.gov (United States)

Sael, Lee; Kihara, Daisuke

2012-01-01

Functional elucidation of proteins is one of the essential tasks in biology. Function of a protein, specifically, small ligand molecules that bind to a protein, can be predicted by finding similar local surface regions in binding sites of known proteins. Here, we developed an alignment free local surface comparison method for predicting a ligand molecule which binds to a query protein. The algorithm, named Patch-Surfer, represents a binding pocket as a combination of segmented surface patches, each of which is characterized by its geometrical shape, the electrostatic potential, the hydrophobicity, and the concaveness. Representing a pocket by a set of patches is effective to absorb difference of global pocket shape while capturing local similarity of pockets. The shape and the physicochemical properties of surface patches are represented using the 3D Zernike descriptor, which is a series expansion of mathematical 3D function. Two pockets are compared using a modified weighted bipartite matching algorithm, which matches similar patches from the two pockets. Patch-Surfer was benchmarked on three datasets, which consist in total of 390 proteins that bind to one of 21 ligands. Patch-Surfer showed superior performance to existing methods including a global pocket comparison method, Pocket-Surfer, which we have previously introduced. Particularly, as intended, the accuracy showed large improvement for flexible ligand molecules, which bind to pockets in different conformations. PMID:22275074

Toward an enhanced Arabic text classification using cosine similarity and Latent Semantic

Directory of Open Access Journals (Sweden)

Fawaz S. Al-Anzi

2017-04-01

Full Text Available Cosine similarity is one of the most popular distance measures in text classification problems. In this paper, we used this important measure to investigate the performance of Arabic language text classification. For textual features, vector space model (VSM is generally used as a model to represent textual information as numerical vectors. However, Latent Semantic Indexing (LSI is a better textual representation technique as it maintains semantic information between the words. Hence, we used the singular value decomposition (SVD method to extract textual features based on LSI. In our experiments, we conducted comparison between some of the well-known classification methods such as Naïve Bayes, k-Nearest Neighbors, Neural Network, Random Forest, Support Vector Machine, and classification tree. We used a corpus that contains 4,000 documents of ten topics (400 document for each topic. The corpus contains 2,127,197 words with about 139,168 unique words. The testing set contains 400 documents, 40 documents for each topics. As a weighing scheme, we used Term Frequency.Inverse Document Frequency (TF.IDF. This study reveals that the classification methods that use LSI features significantly outperform the TF.IDF-based methods. It also reveals that k-Nearest Neighbors (based on cosine measure and support vector machine are the best performing classifiers.

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.

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.

Total System Performance Assessment-License Application Methods and Approach

Energy Technology Data Exchange (ETDEWEB)

J. McNeish

2002-09-13

''Total System Performance Assessment-License Application (TSPA-LA) Methods and Approach'' provides the top-level method and approach for conducting the TSPA-LA model development and analyses. The method and approach is responsive to the criteria set forth in Total System Performance Assessment Integration (TSPAI) Key Technical Issue (KTI) agreements, the ''Yucca Mountain Review Plan'' (CNWRA 2002 [158449]), and 10 CFR Part 63. This introductory section provides an overview of the TSPA-LA, the projected TSPA-LA documentation structure, and the goals of the document. It also provides a brief discussion of the regulatory framework, the approach to risk management of the development and analysis of the model, and the overall organization of the document. The section closes with some important conventions that are utilized in this document.

Computer Facilitated Mathematical Methods in Chemical Engineering--Similarity Solution

Science.gov (United States)

Subramanian, Venkat R.

2006-01-01

High-performance computers coupled with highly efficient numerical schemes and user-friendly software packages have helped instructors to teach numerical solutions and analysis of various nonlinear models more efficiently in the classroom. One of the main objectives of a model is to provide insight about the system of interest. Analytical…

Investigation on multi-objective performance optimization algorithm application of fan based on response surface method and entropy method

Science.gov (United States)

Zhang, Li; Wu, Kexin; Liu, Yang

2017-12-01

A multi-objective performance optimization method is proposed, and the problem that single structural parameters of small fan balance the optimization between the static characteristics and the aerodynamic noise is solved. In this method, three structural parameters are selected as the optimization variables. Besides, the static pressure efficiency and the aerodynamic noise of the fan are regarded as the multi-objective performance. Furthermore, the response surface method and the entropy method are used to establish the optimization function between the optimization variables and the multi-objective performances. Finally, the optimized model is found when the optimization function reaches its maximum value. Experimental data shows that the optimized model not only enhances the static characteristics of the fan but also obviously reduces the noise. The results of the study will provide some reference for the optimization of multi-objective performance of other types of rotating machinery.

Performance Analyses of Counter-Flow Closed Wet Cooling Towers Based on a Simplified Calculation Method

Directory of Open Access Journals (Sweden)

Xiaoqing Wei

2017-02-01

Full Text Available As one of the most widely used units in water cooling systems, the closed wet cooling towers (CWCTs have two typical counter-flow constructions, in which the spray water flows from the top to the bottom, and the moist air and cooling water flow in the opposite direction vertically (parallel or horizontally (cross, respectively. This study aims to present a simplified calculation method for conveniently and accurately analyzing the thermal performance of the two types of counter-flow CWCTs, viz. the parallel counter-flow CWCT (PCFCWCT and the cross counter-flow CWCT (CCFCWCT. A simplified cooling capacity model that just includes two characteristic parameters is developed. The Levenberg–Marquardt method is employed to determine the model parameters by curve fitting of experimental data. Based on the proposed model, the predicted outlet temperatures of the process water are compared with the measurements of a PCFCWCT and a CCFCWCT, respectively, reported in the literature. The results indicate that the predicted values agree well with the experimental data in previous studies. The maximum absolute errors in predicting the process water outlet temperatures are 0.20 and 0.24 °C for the PCFCWCT and CCFCWCT, respectively. These results indicate that the simplified method is reliable for performance prediction of counter-flow CWCTs. Although the flow patterns of the two towers are different, the variation trends of thermal performance are similar to each other under various operating conditions. The inlet air wet-bulb temperature, inlet cooling water temperature, air flow rate, and cooling water flow rate are crucial for determining the cooling capacity of a counter-flow CWCT, while the cooling tower effectiveness is mainly determined by the flow rates of air and cooling water. Compared with the CCFCWCT, the PCFCWCT is much more applicable in a large-scale cooling water system, and the superiority would be amplified when the scale of water

Evaluating firms' R&D performance using best worst method.

Science.gov (United States)

Salimi, Negin; Rezaei, Jafar

2018-02-01

Since research and development (R&D) is the most critical determinant of the productivity, growth and competitive advantage of firms, measuring R&D performance has become the core of attention of R&D managers, and an extensive body of literature has examined and identified different R&D measurements and determinants of R&D performance. However, measuring R&D performance and assigning the same level of importance to different R&D measures, which is the common approach in existing studies, can oversimplify the R&D measuring process, which may result in misinterpretation of the performance and consequently fallacy R&D strategies. The aim of this study is to measure R&D performance taking into account the different levels of importance of R&D measures, using a multi-criteria decision-making method called Best Worst Method (BWM) to identify the weights (importance) of R&D measures and measure the R&D performance of 50 high-tech SMEs in the Netherlands using the data gathered in a survey among SMEs and from R&D experts. The results show how assigning different weights to different R&D measures (in contrast to simple mean) results in a different ranking of the firms and allow R&D managers to formulate more effective strategies to improve their firm's R&D performance by applying knowledge regarding the importance of different R&D measures. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Application of Numerical Optimization Methods to Perform Molecular Docking on Graphics Processing Units

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M. A. Farkov

2014-01-01

Full Text Available An analysis of numerical optimization methods for solving a problem of molecular docking has been performed. Some additional requirements for optimization methods according to GPU architecture features were specified. A promising method for implementation on GPU was selected. Its implementation was described and performance and accuracy tests were performed.

Numerical investigations on coupled heat transfer and synthetical performance of a pressurized volumetric receiver with MCRT–FVM method

International Nuclear Information System (INIS)

Cheng, Z.D.; He, Y.L.; Cui, F.Q.

2013-01-01

This paper presents an axisymmetric steady-state computational fluid dynamics model and further studies on the complex coupled heat transfer combined radiation–convection–conduction in the pressurized volumetric receiver (PVR), by combining the Finite Volume Method (FVM) and the Monte Carlo Ray-Trace (MCRT) method. Based on this, effects of geometric parameters of the compound parabolic concentrator (CPC) and properties of the porous absorber on synthetical characteristics and performance of the photo-thermal conversion process in the PVR are further analyzed and discussed detailedly. It is found that the solar flux density distributions are always very heterogeneous with large nonuniformities, and the variation trends of the corresponding temperature distributions are very similar to these but with much lower order of magnitude. The CPC shape determined by the CPC exit aperture has much larger effects on synthetical characteristics and performance of the PVR than that of the CPC entry aperture with a constant acceptance angle. And a suitable or optimal thickness of the porous absorber could be determined by examining where the drastic decreasing trends occur at the curves of variations of synthetical characteristics and performance with the porosity. - Highlights: ► An axisymmetric steady-state CFD model of PVR is presented with MCRT–FVM method. ► The complex coupled heat transfer and synthetical performance of the PVR are studied. ► The effects of geometric parameters and porous properties are analyzed and discussed. ► Solar flux and temperature in PVR are very heterogeneous with large nonuniformities. ► An optimal absorber thickness can be determined by examining the effects of porosity.

Effective Summation and Interpolation of Series by Self-Similar Root Approximants

Directory of Open Access Journals (Sweden)

Simon Gluzman

2015-06-01

Full Text Available We describe a simple analytical method for effective summation of series, including divergent series. The method is based on self-similar approximation theory resulting in self-similar root approximants. The method is shown to be general and applicable to different problems, as is illustrated by a number of examples. The accuracy of the method is not worse, and in many cases better, than that of Padé approximants, when the latter can be defined.

Comparative performance evaluation of automated segmentation methods of hippocampus from magnetic resonance images of temporal lobe epilepsy patients.

Science.gov (United States)

Hosseini, Mohammad-Parsa; Nazem-Zadeh, Mohammad-Reza; Pompili, Dario; Jafari-Khouzani, Kourosh; Elisevich, Kost; Soltanian-Zadeh, Hamid

2016-01-01

Segmentation of the hippocampus from magnetic resonance (MR) images is a key task in the evaluation of mesial temporal lobe epilepsy (mTLE) patients. Several automated algorithms have been proposed although manual segmentation remains the benchmark. Choosing a reliable algorithm is problematic since structural definition pertaining to multiple edges, missing and fuzzy boundaries, and shape changes varies among mTLE subjects. Lack of statistical references and guidance for quantifying the reliability and reproducibility of automated techniques has further detracted from automated approaches. The purpose of this study was to develop a systematic and statistical approach using a large dataset for the evaluation of automated methods and establish a method that would achieve results better approximating those attained by manual tracing in the epileptogenic hippocampus. A template database of 195 (81 males, 114 females; age range 32-67 yr, mean 49.16 yr) MR images of mTLE patients was used in this study. Hippocampal segmentation was accomplished manually and by two well-known tools (FreeSurfer and hammer) and two previously published methods developed at their institution [Automatic brain structure segmentation (ABSS) and LocalInfo]. To establish which method was better performing for mTLE cases, several voxel-based, distance-based, and volume-based performance metrics were considered. Statistical validations of the results using automated techniques were compared with the results of benchmark manual segmentation. Extracted metrics were analyzed to find the method that provided a more similar result relative to the benchmark. Among the four automated methods, ABSS generated the most accurate results. For this method, the Dice coefficient was 5.13%, 14.10%, and 16.67% higher, Hausdorff was 22.65%, 86.73%, and 69.58% lower, precision was 4.94%, -4.94%, and 12.35% higher, and the root mean square (RMS) was 19.05%, 61.90%, and 65.08% lower than LocalInfo, FreeSurfer, and

Protein structure similarity from principle component correlation analysis

Directory of Open Access Journals (Sweden)

Chou James

2006-01-01

Full Text Available Abstract Background Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. Results We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. Conclusion The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum

Why Did the Bear Cross the Road? Comparing the Performance of Multiple Resistance Surfaces and Connectivity Modeling Methods

Directory of Open Access Journals (Sweden)

Samuel A. Cushman

2014-12-01

Full Text Available There have been few assessments of the performance of alternative resistance surfaces, and little is known about how connectivity modeling approaches differ in their ability to predict organism movements. In this paper, we evaluate the performance of four connectivity modeling approaches applied to two resistance surfaces in predicting the locations of highway crossings by American black bears in the northern Rocky Mountains, USA. We found that a resistance surface derived directly from movement data greatly outperformed a resistance surface produced from analysis of genetic differentiation, despite their heuristic similarities. Our analysis also suggested differences in the performance of different connectivity modeling approaches. Factorial least cost paths appeared to slightly outperform other methods on the movement-derived resistance surface, but had very poor performance on the resistance surface obtained from multi-model landscape genetic analysis. Cumulative resistant kernels appeared to offer the best combination of high predictive performance and sensitivity to differences in resistance surface parameterization. Our analysis highlights that even when two resistance surfaces include the same variables and have a high spatial correlation of resistance values, they may perform very differently in predicting animal movement and population connectivity.

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....

Total System Performance Assessment - License Application Methods and Approach

International Nuclear Information System (INIS)

McNeish, J.

2003-01-01

''Total System Performance Assessment-License Application (TSPA-LA) Methods and Approach'' provides the top-level method and approach for conducting the TSPA-LA model development and analyses. The method and approach is responsive to the criteria set forth in Total System Performance Assessment Integration (TSPAI) Key Technical Issues (KTIs) identified in agreements with the U.S. Nuclear Regulatory Commission, the ''Yucca Mountain Review Plan'' (YMRP), ''Final Report'' (NRC 2003 [163274]), and the NRC final rule 10 CFR Part 63 (NRC 2002 [156605]). This introductory section provides an overview of the TSPA-LA, the projected TSPA-LA documentation structure, and the goals of the document. It also provides a brief discussion of the regulatory framework, the approach to risk management of the development and analysis of the model, and the overall organization of the document. The section closes with some important conventions that are used in this document

The performances of R GPU implementations of the GMRES method

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Bogdan Oancea

2018-03-01

Full Text Available Although the performance of commodity computers has improved drastically with the introduction of multicore processors and GPU computing, the standard R distribution is still based on single-threaded model of computation, using only a small fraction of the computational power available now for most desktops and laptops. Modern statistical software packages rely on high performance implementations of the linear algebra routines there are at the core of several important leading edge statistical methods. In this paper we present a GPU implementation of the GMRES iterative method for solving linear systems. We compare the performance of this implementation with a pure single threaded version of the CPU. We also investigate the performance of our implementation using different GPU packages available now for R such as gmatrix, gputools or gpuR which are based on CUDA or OpenCL frameworks.

Exploring the relationship between sequence similarity and accurate phylogenetic trees.

Science.gov (United States)

Cantarel, Brandi L; Morrison, Hilary G; Pearson, William

2006-11-01

We have characterized the relationship between accurate phylogenetic reconstruction and sequence similarity, testing whether high levels of sequence similarity can consistently produce accurate evolutionary trees. We generated protein families with known phylogenies using a modified version of the PAML/EVOLVER program that produces insertions and deletions as well as substitutions. Protein families were evolved over a range of 100-400 point accepted mutations; at these distances 63% of the families shared significant sequence similarity. Protein families were evolved using balanced and unbalanced trees, with ancient or recent radiations. In families sharing statistically significant similarity, about 60% of multiple sequence alignments were 95% identical to true alignments. To compare recovered topologies with true topologies, we used a score that reflects the fraction of clades that were correctly clustered. As expected, the accuracy of the phylogenies was greatest in the least divergent families. About 88% of phylogenies clustered over 80% of clades in families that shared significant sequence similarity, using Bayesian, parsimony, distance, and maximum likelihood methods. However, for protein families with short ancient branches (ancient radiation), only 30% of the most divergent (but statistically significant) families produced accurate phylogenies, and only about 70% of the second most highly conserved families, with median expectation values better than 10(-60), produced accurate trees. These values represent upper bounds on expected tree accuracy for sequences with a simple divergence history; proteins from 700 Giardia families, with a similar range of sequence similarities but considerably more gaps, produced much less accurate trees. For our simulated insertions and deletions, correct multiple sequence alignments did not perform much better than those produced by T-COFFEE, and including sequences with expressed sequence tag-like sequencing errors did not

System and Method for Monitoring Piezoelectric Material Performance

Science.gov (United States)

Moses, Robert W. (Inventor); Fox, Christopher L. (Inventor); Fox, Melanie L. (Inventor); Chattin, Richard L. (Inventor); Shams, Qamar A. (Inventor); Fox, Robert L. (Inventor)

2007-01-01

A system and method are provided for monitoring performance capacity of a piezoelectric material that may form part of an actuator or sensor device. A switch is used to selectively electrically couple an inductor to the piezoelectric material to form an inductor-capacitor circuit. Resonance is induced in the inductor-capacitor circuit when the switch is operated to create the circuit. The resonance of the inductor-capacitor circuit is monitored with the frequency of the resonance being indicative of performance capacity of the device's piezoelectric material.

Prediction of Associations between OMIM Diseases and MicroRNAs by Random Walk on OMIM Disease Similarity Network

Directory of Open Access Journals (Sweden)

Hailin Chen

2013-01-01

Full Text Available Increasing evidence has revealed that microRNAs (miRNAs play important roles in the development and progression of human diseases. However, efforts made to uncover OMIM disease-miRNA associations are lacking and the majority of diseases in the OMIM database are not associated with any miRNA. Therefore, there is a strong incentive to develop computational methods to detect potential OMIM disease-miRNA associations. In this paper, random walk on OMIM disease similarity network is applied to predict potential OMIM disease-miRNA associations under the assumption that functionally related miRNAs are often associated with phenotypically similar diseases. Our method makes full use of global disease similarity values. We tested our method on 1226 known OMIM disease-miRNA associations in the framework of leave-one-out cross-validation and achieved an area under the ROC curve of 71.42%. Excellent performance enables us to predict a number of new potential OMIM disease-miRNA associations and the newly predicted associations are publicly released to facilitate future studies. Some predicted associations with high ranks were manually checked and were confirmed from the publicly available databases, which was a strong evidence for the practical relevance of our method.

Clustering and visualizing similarity networks of membrane proteins.

Science.gov (United States)

Hu, Geng-Ming; Mai, Te-Lun; Chen, Chi-Ming

2015-08-01

We proposed a fast and unsupervised clustering method, minimum span clustering (MSC), for analyzing the sequence-structure-function relationship of biological networks, and demonstrated its validity in clustering the sequence/structure similarity networks (SSN) of 682 membrane protein (MP) chains. The MSC clustering of MPs based on their sequence information was found to be consistent with their tertiary structures and functions. For the largest seven clusters predicted by MSC, the consistency in chain function within the same cluster is found to be 100%. From analyzing the edge distribution of SSN for MPs, we found a characteristic threshold distance for the boundary between clusters, over which SSN of MPs could be properly clustered by an unsupervised sparsification of the network distance matrix. The clustering results of MPs from both MSC and the unsupervised sparsification methods are consistent with each other, and have high intracluster similarity and low intercluster similarity in sequence, structure, and function. Our study showed a strong sequence-structure-function relationship of MPs. We discussed evidence of convergent evolution of MPs and suggested applications in finding structural similarities and predicting biological functions of MP chains based on their sequence information. © 2015 Wiley Periodicals, Inc.

Similarity estimation for reference image retrieval in mammograms using convolutional neural network

Science.gov (United States)

Muramatsu, Chisako; Higuchi, Shunichi; Morita, Takako; Oiwa, Mikinao; Fujita, Hiroshi

2018-02-01

Periodic breast cancer screening with mammography is considered effective in decreasing breast cancer mortality. For screening programs to be successful, an intelligent image analytic system may support radiologists' efficient image interpretation. In our previous studies, we have investigated image retrieval schemes for diagnostic references of breast lesions on mammograms and ultrasound images. Using a machine learning method, reliable similarity measures that agree with radiologists' similarity were determined and relevant images could be retrieved. However, our previous method includes a feature extraction step, in which hand crafted features were determined based on manual outlines of the masses. Obtaining the manual outlines of masses is not practical in clinical practice and such data would be operator-dependent. In this study, we investigated a similarity estimation scheme using a convolutional neural network (CNN) to skip such procedure and to determine data-driven similarity scores. By using CNN as feature extractor, in which extracted features were employed in determination of similarity measures with a conventional 3-layered neural network, the determined similarity measures were correlated well with the subjective ratings and the precision of retrieving diagnostically relevant images was comparable with that of the conventional method using handcrafted features. By using CNN for determination of similarity measure directly, the result was also comparable. By optimizing the network parameters, results may be further improved. The proposed method has a potential usefulness in determination of similarity measure without precise lesion outlines for retrieval of similar mass images on mammograms.

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

Benchmarking and Performance Measurement.

Science.gov (United States)

Town, J. Stephen

This paper defines benchmarking and its relationship to quality management, describes a project which applied the technique in a library context, and explores the relationship between performance measurement and benchmarking. Numerous benchmarking methods contain similar elements: deciding what to benchmark; identifying partners; gathering…

Optimization of cooling tower performance analysis using Taguchi method

Directory of Open Access Journals (Sweden)

Ramkumar Ramakrishnan

2013-01-01

Full Text Available This study discuss the application of Taguchi method in assessing maximum cooling tower effectiveness for the counter flow cooling tower using expanded wire mesh packing. The experiments were planned based on Taguchi’s L27 orthogonal array .The trail was performed under different inlet conditions of flow rate of water, air and water temperature. Signal-to-noise ratio (S/N analysis, analysis of variance (ANOVA and regression were carried out in order to determine the effects of process parameters on cooling tower effectiveness and to identity optimal factor settings. Finally confirmation tests verified this reliability of Taguchi method for optimization of counter flow cooling tower performance with sufficient accuracy.

Lyme Disease Diagnosed by Alternative Methods: A Phenotype Similar to That of Chronic Fatigue Syndrome.

Science.gov (United States)

Patrick, David M; Miller, Ruth R; Gardy, Jennifer L; Parker, Shoshana M; Morshed, Muhammad G; Steiner, Theodore S; Singer, Joel; Shojania, Kam; Tang, Patrick

2015-10-01

A subset of patients reporting a diagnosis of Lyme disease can be described as having alternatively diagnosed chronic Lyme syndrome (ADCLS), in which diagnosis is based on laboratory results from a nonreference Lyme specialty laboratory using in-house criteria. Patients with ADCLS report symptoms similar to those reported by patients with chronic fatigue syndrome (CFS). We performed a case-control study comparing patients with ADCLS and CFS to each other and to both healthy controls and controls with systemic lupus erythematosus (SLE). Subjects completed a history, physical exam, screening laboratory tests, 7 functional scales, reference serology for Lyme disease using Centers for Disease Control and Prevention criteria, reference serology for other tick-associated pathogens, and cytokine expression studies. The study enrolled 13 patients with ADCLS (12 of whom were diagnosed by 1 alternative US laboratory), 25 patients with CFS, 25 matched healthy controls, and 11 SLE controls. Baseline clinical data and functional scales indicate significant disability among ADCLS and CFS patients and many important differences between these groups and controls, but no significant differences between each other. No ADCLS patient was confirmed as having positive Lyme serology by reference laboratory testing, and there was no difference in distribution of positive serology for other tick-transmitted pathogens or cytokine expression across the groups. In British Columbia, a setting with low Lyme disease incidence, ADCLS patients have a similar phenotype to that of CFS patients. Disagreement between alternative and reference laboratory Lyme testing results in this setting is most likely explained by false-positive results from the alternative laboratory. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Quality Evaluation of Potentilla fruticosa L. by High Performance Liquid Chromatography Fingerprinting Associated with Chemometric Methods.

Science.gov (United States)

Liu, Wei; Wang, Dongmei; Liu, Jianjun; Li, Dengwu; Yin, Dongxue

2016-01-01

The present study was performed to assess the quality of Potentilla fruticosa L. sampled from distinct regions of China using high performance liquid chromatography (HPLC) fingerprinting coupled with a suite of chemometric methods. For this quantitative analysis, the main active phytochemical compositions and the antioxidant activity in P. fruticosa were also investigated. Considering the high percentages and antioxidant activities of phytochemicals, P. fruticosa samples from Kangding, Sichuan were selected as the most valuable raw materials. Similarity analysis (SA) of HPLC fingerprints, hierarchical cluster analysis (HCA), principle component analysis (PCA), and discriminant analysis (DA) were further employed to provide accurate classification and quality estimates of P. fruticosa. Two principal components (PCs) were collected by PCA. PC1 separated samples from Kangding, Sichuan, capturing 57.64% of the variance, whereas PC2 contributed to further separation, capturing 18.97% of the variance. Two kinds of discriminant functions with a 100% discrimination ratio were constructed. The results strongly supported the conclusion that the eight samples from different regions were clustered into three major groups, corresponding with their morphological classification, for which HPLC analysis confirmed the considerable variation in phytochemical compositions and that P. fruticosa samples from Kangding, Sichuan were of high quality. The results of SA, HCA, PCA, and DA were in agreement and performed well for the quality assessment of P. fruticosa. Consequently, HPLC fingerprinting coupled with chemometric techniques provides a highly flexible and reliable method for the quality evaluation of traditional Chinese medicines.

Quality Evaluation of Potentilla fruticosa L. by High Performance Liquid Chromatography Fingerprinting Associated with Chemometric Methods

Science.gov (United States)

Liu, Wei; Wang, Dongmei; Liu, Jianjun; Li, Dengwu; Yin, Dongxue

2016-01-01

The present study was performed to assess the quality of Potentilla fruticosa L. sampled from distinct regions of China using high performance liquid chromatography (HPLC) fingerprinting coupled with a suite of chemometric methods. For this quantitative analysis, the main active phytochemical compositions and the antioxidant activity in P. fruticosa were also investigated. Considering the high percentages and antioxidant activities of phytochemicals, P. fruticosa samples from Kangding, Sichuan were selected as the most valuable raw materials. Similarity analysis (SA) of HPLC fingerprints, hierarchical cluster analysis (HCA), principle component analysis (PCA), and discriminant analysis (DA) were further employed to provide accurate classification and quality estimates of P. fruticosa. Two principal components (PCs) were collected by PCA. PC1 separated samples from Kangding, Sichuan, capturing 57.64% of the variance, whereas PC2 contributed to further separation, capturing 18.97% of the variance. Two kinds of discriminant functions with a 100% discrimination ratio were constructed. The results strongly supported the conclusion that the eight samples from different regions were clustered into three major groups, corresponding with their morphological classification, for which HPLC analysis confirmed the considerable variation in phytochemical compositions and that P. fruticosa samples from Kangding, Sichuan were of high quality. The results of SA, HCA, PCA, and DA were in agreement and performed well for the quality assessment of P. fruticosa. Consequently, HPLC fingerprinting coupled with chemometric techniques provides a highly flexible and reliable method for the quality evaluation of traditional Chinese medicines. PMID:26890416

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.

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure

Directory of Open Access Journals (Sweden)

Wen Zhang

2016-01-01

Full Text Available Recently, LSI (Latent Semantic Indexing based on SVD (Singular Value Decomposition is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods.

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.

Stego Keys Performance on Feature Based Coding Method in Text Domain

Directory of Open Access Journals (Sweden)

Din Roshidi

2017-01-01

Full Text Available A main critical factor on embedding process in any text steganography method is a key used known as stego key. This factor will be influenced the success of the embedding process of text steganography method to hide a message from third party or any adversary. One of the important aspects on embedding process in text steganography method is the fitness performance of the stego key. Three parameters of the fitness performance of the stego key have been identified such as capacity ratio, embedded fitness ratio and saving space ratio. It is because a better as capacity ratio, embedded fitness ratio and saving space ratio offers of any stego key; a more message can be hidden. Therefore, main objective of this paper is to analyze three features coding based namely CALP, VERT and QUAD of stego keys in text steganography on their capacity ratio, embedded fitness ratio and saving space ratio. It is found that CALP method give a good effort performance compared to VERT and QUAD methods.

A TWO-STEP CLASSIFICATION APPROACH TO DISTINGUISHING SIMILAR OBJECTS IN MOBILE LIDAR POINT CLOUDS

Directory of Open Access Journals (Sweden)

H. He

2017-09-01

Full Text Available Nowadays, lidar is widely used in cultural heritage documentation, urban modeling, and driverless car technology for its fast and accurate 3D scanning ability. However, full exploitation of the potential of point cloud data for efficient and automatic object recognition remains elusive. Recently, feature-based methods have become very popular in object recognition on account of their good performance in capturing object details. Compared with global features describing the whole shape of the object, local features recording the fractional details are more discriminative and are applicable for object classes with considerable similarity. In this paper, we propose a two-step classification approach based on point feature histograms and the bag-of-features method for automatic recognition of similar objects in mobile lidar point clouds. Lamp post, street light and traffic sign are grouped as one category in the first-step classification for their inter similarity compared with tree and vehicle. A finer classification of the lamp post, street light and traffic sign based on the result of the first-step classification is implemented in the second step. The proposed two-step classification approach is shown to yield a considerable improvement over the conventional one-step classification approach.

Total System Performance Assessment - License Application Methods and Approach

Energy Technology Data Exchange (ETDEWEB)

J. McNeish

2003-12-08

''Total System Performance Assessment-License Application (TSPA-LA) Methods and Approach'' provides the top-level method and approach for conducting the TSPA-LA model development and analyses. The method and approach is responsive to the criteria set forth in Total System Performance Assessment Integration (TSPAI) Key Technical Issues (KTIs) identified in agreements with the U.S. Nuclear Regulatory Commission, the ''Yucca Mountain Review Plan'' (YMRP), ''Final Report'' (NRC 2003 [163274]), and the NRC final rule 10 CFR Part 63 (NRC 2002 [156605]). This introductory section provides an overview of the TSPA-LA, the projected TSPA-LA documentation structure, and the goals of the document. It also provides a brief discussion of the regulatory framework, the approach to risk management of the development and analysis of the model, and the overall organization of the document. The section closes with some important conventions that are used in this document.

Visual art teachers and performance assessment methods in ...

African Journals Online (AJOL)

This paper examines the competencies of visual arts teachers in using performance assessment methods, and to ascertain the extent to which the knowledge, skills and experiences of teachers affect their competence in using assessment strategies in their classroom. The study employs a qualitative research design; ...

Sensitive high performance liquid chromatographic method for the ...

African Journals Online (AJOL)

A new simple, sensitive, cost-effective and reproducible high performance liquid chromatographic (HPLC) method for the determination of proguanil (PG) and its metabolites, cycloguanil (CG) and 4-chlorophenylbiguanide (4-CPB) in urine and plasma is described. The extraction procedure is a simple three-step process ...

Comparison of two methods to determine fan performance curves using computational fluid dynamics

Science.gov (United States)

Onma, Patinya; Chantrasmi, Tonkid

2018-01-01

This work investigates a systematic numerical approach that employs Computational Fluid Dynamics (CFD) to obtain performance curves of a backward-curved centrifugal fan. Generating the performance curves requires a number of three-dimensional simulations with varying system loads at a fixed rotational speed. Two methods were used and their results compared to experimental data. The first method incrementally changes the mass flow late through the inlet boundary condition while the second method utilizes a series of meshes representing the physical damper blade at various angles. The generated performance curves from both methods are compared with an experiment setup in accordance with the AMCA fan performance testing standard.

Comparing performance of standard and iterative linear unmixing methods for hyperspectral signatures

Science.gov (United States)

Gault, Travis R.; Jansen, Melissa E.; DeCoster, Mallory E.; Jansing, E. David; Rodriguez, Benjamin M.

2016-05-01

Linear unmixing is a method of decomposing a mixed signature to determine the component materials that are present in sensor's field of view, along with the abundances at which they occur. Linear unmixing assumes that energy from the materials in the field of view is mixed in a linear fashion across the spectrum of interest. Traditional unmixing methods can take advantage of adjacent pixels in the decomposition algorithm, but is not the case for point sensors. This paper explores several iterative and non-iterative methods for linear unmixing, and examines their effectiveness at identifying the individual signatures that make up simulated single pixel mixed signatures, along with their corresponding abundances. The major hurdle addressed in the proposed method is that no neighboring pixel information is available for the spectral signature of interest. Testing is performed using two collections of spectral signatures from the Johns Hopkins University Applied Physics Laboratory's Signatures Database software (SigDB): a hand-selected small dataset of 25 distinct signatures from a larger dataset of approximately 1600 pure visible/near-infrared/short-wave-infrared (VIS/NIR/SWIR) spectra. Simulated spectra are created with three and four material mixtures randomly drawn from a dataset originating from SigDB, where the abundance of one material is swept in 10% increments from 10% to 90%with the abundances of the other materials equally divided amongst the remainder. For the smaller dataset of 25 signatures, all combinations of three or four materials are used to create simulated spectra, from which the accuracy of materials returned, as well as the correctness of the abundances, is compared to the inputs. The experiment is expanded to include the signatures from the larger dataset of almost 1600 signatures evaluated using a Monte Carlo scheme with 5000 draws of three or four materials to create the simulated mixed signatures. The spectral similarity of the inputs to the

Evaluation Method for Low-Temperature Performance of Lithium Battery

Science.gov (United States)

Wang, H. W.; Ma, Q.; Fu, Y. L.; Tao, Z. Q.; Xiao, H. Q.; Bai, H.; Bai, H.

2018-05-01

In this paper, the evaluation method for low temperature performance of lithium battery is established. The low temperature performance level was set up to determine the best operating temperature range of the lithium battery using different cathode materials. Results are shared with the consumers for the proper use of lithium battery to make it have a longer service life and avoid the occurrence of early rejection.

Roles and methods of performance evaluation of hospital academic leadership.

Science.gov (United States)

Zhou, Ying; Yuan, Huikang; Li, Yang; Zhao, Xia; Yi, Lihua

2016-01-01

The rapidly advancing implementation of public hospital reform urgently requires the identification and classification of a pool of exceptional medical specialists, corresponding with incentives to attract and retain them, providing a nucleus of distinguished expertise to ensure public hospital preeminence. This paper examines the significance of academic leadership, from a strategic management perspective, including various tools, methods and mechanisms used in the theory and practice of performance evaluation, and employed in the selection, training and appointment of academic leaders. Objective methods of assessing leadership performance are also provided for reference.

DNA barcoding of recently diverged species: relative performance of matching methods.

Directory of Open Access Journals (Sweden)

Robin van Velzen

Full Text Available Recently diverged species are challenging for identification, yet they are frequently of special interest scientifically as well as from a regulatory perspective. DNA barcoding has proven instrumental in species identification, especially in insects and vertebrates, but for the identification of recently diverged species it has been reported to be problematic in some cases. Problems are mostly due to incomplete lineage sorting or simply lack of a 'barcode gap' and probably related to large effective population size and/or low mutation rate. Our objective was to compare six methods in their ability to correctly identify recently diverged species with DNA barcodes: neighbor joining and parsimony (both tree-based, nearest neighbor and BLAST (similarity-based, and the diagnostic methods DNA-BAR, and BLOG. We analyzed simulated data assuming three different effective population sizes as well as three selected empirical data sets from published studies. Results show, as expected, that success rates are significantly lower for recently diverged species (∼75% than for older species (∼97% (P<0.00001. Similarity-based and diagnostic methods significantly outperform tree-based methods, when applied to simulated DNA barcode data (P<0.00001. The diagnostic method BLOG had highest correct query identification rate based on simulated (86.2% as well as empirical data (93.1%, indicating that it is a consistently better method overall. Another advantage of BLOG is that it offers species-level information that can be used outside the realm of DNA barcoding, for instance in species description or molecular detection assays. Even though we can confirm that identification success based on DNA barcoding is generally high in our data, recently diverged species remain difficult to identify. Nevertheless, our results contribute to improved solutions for their accurate identification.

Prediction of the human response time with the similarity and quantity of information

International Nuclear Information System (INIS)

Lee, Sungjin; Heo, Gyunyoung; Chang, Soon Heung

2006-01-01

Memory is one of brain processes that are important when trying to understand how people process information. Although a large number of studies have been made on the human performance, little is known about the similarity effect in human performance. The purpose of this paper is to propose and validate the quantitative and predictive model on the human response time in the user interface with the concept of similarity. However, it is not easy to explain the human performance with only similarity or information amount. We are confronted by two difficulties: making the quantitative model on the human response time with the similarity and validating the proposed model by experimental work. We made the quantitative model based on the Hick's law and the law of practice. In addition, we validated the model with various experimental conditions by measuring participants' response time in the environment of computer-based display. Experimental results reveal that the human performance is improved by the user interface's similarity. We think that the proposed model is useful for the user interface design and evaluation phases

An improved high-performance liquid chromatography-tandem mass spectrometric method to measure atrazine and its metabolites in human urine.

Science.gov (United States)

Panuwet, Parinya; Restrepo, Paula A; Magsumbol, Melina; Jung, Kyung Y; Montesano, M Angela; Needham, Larry L; Barr, Dana Boyd

2010-04-15

We report an improved solid-phase extraction-high-performance liquid chromatography-tandem mass spectrometry method with isotope dilution quantification to measure seven atrazine metabolites in urine. The metabolites measured were hydroxyatrazine (HA), diaminochloroatrazine (DACT), desisopropylatrazine (DIA), desethylatrazine (DEA), desethylatrazine mercapturate (DEAM), atrazine mercapturate (ATZM), and atrazine (ATZ). Using offline mixed-mode reversed-phase/cation-exchange solid-phase extraction dramatically increased recovery and sensitivity by reducing the influence of matrix components during separation and analysis. DACT extraction recovery improved to greater than 80% while the other analytes had similar extraction efficiencies as previously observed. Limits of detection were lower than our previous method (0.05-0.19 ng/mL) with relative standard deviations less than 10%. The total runtime was shorter (18 min) than the previous on-line method, thus it is suitable for large-scale sample analyses. We increased the throughput of our method twofold by using the newer extraction technique. Published by Elsevier B.V.

Evaluation method for the drying performance of enzyme containing formulations

DEFF Research Database (Denmark)

Sloth, Jakob; Bach, P.; Jensen, Anker Degn

2008-01-01

A method is presented for fast and cheap evaluation of the performance of enzyme containing formulations in terms of preserving the highest enzyme activity during spray drying. The method is based on modeling the kinetics of the thermal inactivation reaction which occurs during the drying process....... Relevant kinetic parameters are determined from differential scanning calorimeter (DSC) experiments and the model is used to simulate the severity of the inactivation reaction for temperatures and moisture levels relevant for spray drying. After conducting experiments and subsequent simulations...... for a number of different formulations it may be deduced which formulation performs best. This is illustrated by a formulation design study where 4 different enzyme containing formulations are evaluated. The method is validated by comparison to pilot scale spray dryer experiments....

Performance of particle in cell methods on highly concurrent computational architectures

International Nuclear Information System (INIS)

Adams, M.F.; Ethier, S.; Wichmann, N.

2009-01-01

Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson's equation or more generally Maxwell's equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores.

Performance of particle in cell methods on highly concurrent computational architectures

International Nuclear Information System (INIS)

Adams, M F; Ethier, S; Wichmann, N

2007-01-01

Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson's equation or more generally Maxwell's equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores

Methods of evaluating performance in controlling marketing,activities

OpenAIRE

Codruţa Dura

2002-01-01

There are specific methods for assessing and improving the effectiveness of a marketing strategy. A marketer should state in the marketing plan what a marketing strategy is supposed to accomplish. These statements should set forth performance standards, which usually are stated in terms of profits, sales, or costs

Phonological Similarity in Serial Recall: Constraints on Theories of Memory

Science.gov (United States)

Lewandowsky, Stephan; Farrell, Simon

2008-01-01

In short-term serial recall, similar-sounding items are remembered more poorly than items that do not sound alike. When lists mix similar and dissimilar items, performance on the dissimilar items is of considerable theoretical interest. Farrell and Lewandowsky [Farrell, S., & Lewandowsky, S. (2003). Dissimilar items benefit from phonological…

How similar are nut-cracking and stone-flaking? A functional approach to percussive technology.

Science.gov (United States)

Bril, Blandine; Parry, Ross; Dietrich, Gilles

2015-11-19

Various authors have suggested similarities between tool use in early hominins and chimpanzees. This has been particularly evident in studies of nut-cracking which is considered to be the most complex skill exhibited by wild apes, and has also been interpreted as a precursor of more complex stone-flaking abilities. It has been argued that there is no major qualitative difference between what the chimpanzee does when he cracks a nut and what early hominins did when they detached a flake from a core. In this paper, similarities and differences between skills involved in stone-flaking and nut-cracking are explored through an experimental protocol with human subjects performing both tasks. We suggest that a 'functional' approach to percussive action, based on the distinction between functional parameters that characterize each task and parameters that characterize the agent's actions and movements, is a fruitful method for understanding those constraints which need to be mastered to perform each task successfully, and subsequently, the nature of skill involved in both tasks. © 2015 The Author(s).

Meta-Analysis of Quantification Methods Shows that Archaea and Bacteria Have Similar Abundances in the Subseafloor

Science.gov (United States)

May, Megan K.; Kevorkian, Richard T.; Steen, Andrew D.

2013-01-01

There is no universally accepted method to quantify bacteria and archaea in seawater and marine sediments, and different methods have produced conflicting results with the same samples. To identify best practices, we compiled data from 65 studies, plus our own measurements, in which bacteria and archaea were quantified with fluorescent in situ hybridization (FISH), catalyzed reporter deposition FISH (CARD-FISH), polyribonucleotide FISH, or quantitative PCR (qPCR). To estimate efficiency, we defined “yield” to be the sum of bacteria and archaea counted by these techniques divided by the total number of cells. In seawater, the yield was high (median, 71%) and was similar for FISH, CARD-FISH, and polyribonucleotide FISH. In sediments, only measurements by CARD-FISH in which archaeal cells were permeabilized with proteinase K showed high yields (median, 84%). Therefore, the majority of cells in both environments appear to be alive, since they contain intact ribosomes. In sediments, the sum of bacterial and archaeal 16S rRNA gene qPCR counts was not closely related to cell counts, even after accounting for variations in copy numbers per genome. However, qPCR measurements were precise relative to other qPCR measurements made on the same samples. qPCR is therefore a reliable relative quantification method. Inconsistent results for the relative abundance of bacteria versus archaea in deep subsurface sediments were resolved by the removal of CARD-FISH measurements in which lysozyme was used to permeabilize archaeal cells and qPCR measurements which used ARCH516 as an archaeal primer or TaqMan probe. Data from best-practice methods showed that archaea and bacteria decreased as the depth in seawater and marine sediments increased, although archaea decreased more slowly. PMID:24096423

Box-counting dimension revisited: presenting an efficient method of minimising quantisation error and an assessment of the self-similarity of structural root systems

Directory of Open Access Journals (Sweden)

Martin eBouda

2016-02-01

Full Text Available Fractal dimension (FD, estimated by box-counting, is a metric used to characterise plant anatomical complexity or space-filling characteristic for a variety of purposes. The vast majority of published studies fail to evaluate the assumption of statistical self-similarity, which underpins the validity of the procedure. The box-counting procedure is also subject to error arising from arbitrary grid placement, known as quantisation error (QE, which is strictly positive and varies as a function of scale, making it problematic for the procedure's slope estimation step. Previous studies either ignore QE or employ inefficient brute-force grid translations to reduce it. The goals of this study were to characterise the effect of QE due to translation and rotation on FD estimates, to provide an efficient method of reducing QE, and to evaluate the assumption of statistical self-similarity of coarse root datasets typical of those used in recent trait studies. Coarse root systems of 36 shrubs were digitised in 3D and subjected to box-counts. A pattern search algorithm was used to minimise QE by optimising grid placement and its efficiency was compared to the brute force method. The degree of statistical self-similarity was evaluated using linear regression residuals and local slope estimates.QE due to both grid position and orientation was a significant source of error in FD estimates, but pattern search provided an efficient means of minimising it. Pattern search had higher initial computational cost but converged on lower error values more efficiently than the commonly employed brute force method. Our representations of coarse root system digitisations did not exhibit details over a sufficient range of scales to be considered statistically self-similar and informatively approximated as fractals, suggesting a lack of sufficient ramification of the coarse root systems for reiteration to be thought of as a dominant force in their development. FD estimates did

Inter Genre Similarity Modelling For Automatic Music Genre Classification

OpenAIRE

Bagci, Ulas; Erzin, Engin

2009-01-01

Music genre classification is an essential tool for music information retrieval systems and it has been finding critical applications in various media platforms. Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modelling (IGS) to improve the performance of automatic music genre classification. Inter-genre similarity information is extracted over the mis-classified feature population....

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

Energy Technology Data Exchange (ETDEWEB)

Harms, Joseph; Wang, Tonghe; Petrongolo, Michael; Zhu, Lei, E-mail: leizhu@gatech.edu [Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States); Niu, Tianye [Sir Run Run Shaw Hospital, Zhejiang University School of Medicine (China); Institute of Translational Medicine, Zhejiang University, Hangzhou, Zhejiang, 310016 (China)

2016-05-15

Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is based on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan{sup ©}600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise

Development of methods of key performance indicators formation for corporate planning

International Nuclear Information System (INIS)

Chebotarev, A.N.

2011-01-01

A theoretical proposition, a model of enterprise performance management and a concept of balanced key performance indicators as a method to control the enterprise strategy have been systematized and presented. An algorithm that increases the efficiency of action plans' formation has been developed and implemented. In particular, a set of criteria for the selection of events and parameters necessary for the formation of an action plan has been created. A method of control of the business processes, allowing the experts to establish the relationship between the business processes performance indicators and the enterprise's key indicators has been developed [ru

Equal Work, Unequal Pay: Gender Discrimination within Work-Similar Occupations.

Science.gov (United States)

Kemp, Alice Abel; Beck, E. M.

1986-01-01

Describes an empirical method to identify work-similar occupations using selected measures from the Dictionary of Occupational Titles. Examines male-female earnings differences within a group of work-similar occupations and finds that discrimination against females is extensive. (Author/CH)

Clustering biomolecular complexes by residue contacts similarity

NARCIS (Netherlands)

Garcia Lopes Maia Rodrigues, João; Trellet, Mikaël; Schmitz, Christophe; Kastritis, Panagiotis; Karaca, Ezgi; Melquiond, Adrien S J; Bonvin, Alexandre M J J; Garcia Lopes Maia Rodrigues, João

Inaccuracies in computational molecular modeling methods are often counterweighed by brute-force generation of a plethora of putative solutions. These are then typically sieved via structural clustering based on similarity measures such as the root mean square deviation (RMSD) of atomic positions.

Personalized mortality prediction driven by electronic medical data and a patient similarity metric.

Science.gov (United States)

Lee, Joon; Maslove, David M; Dubin, Joel A

2015-01-01

Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1) to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2) to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made. We deployed a cosine-similarity-based patient similarity metric (PSM) to an intensive care unit (ICU) database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care. The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR) systems, our novel medical data analytics contributes to

Personalized mortality prediction driven by electronic medical data and a patient similarity metric.

Directory of Open Access Journals (Sweden)

Joon Lee

Full Text Available Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1 to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2 to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made.We deployed a cosine-similarity-based patient similarity metric (PSM to an intensive care unit (ICU database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care.The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR systems, our novel medical data analytics

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.

A new ART iterative method and a comparison of performance among various ART methods

International Nuclear Information System (INIS)

Tan, Yufeng; Sato, Shunsuke

1993-01-01

Many algebraic reconstruction techniques (ART) image reconstruction algorithms, for instance, simultaneous iterative reconstruction technique (SIRT), the relaxation method and multiplicative ART (MART), have been proposed and their convergent properties have been studied. SIRT and the underrelaxed relaxation method converge to the least-squares solution, but the convergent speeds are very slow. The Kaczmarz method converges very quickly, but the reconstructed images contain a lot of noise. The comparative studies between these algorithms have been done by Gilbert and others, but are not adequate. In this paper, we (1) propose a new method which is a modified Kaczmarz method and prove its convergence property, (2) study performance of 7 algorithms including the one proposed here by computer simulation for 3 kinds of typical phantoms. The method proposed here does not give the least-square solution, but the root mean square errors of its reconstructed images decrease very quickly after few interations. The result shows that the method proposed here gives a better reconstructed image. (author)

Financial Performance of Pension Companies Operating in Turkey with Topsis Analysis Method

OpenAIRE

Gulsun Isseveroglu; Ozan Sezer

2015-01-01

In this study, financial performances of the companies were analyzed by TOPSIS method via using financial tables of the sixteen pension and life-pension companies. Firstly, financial ratios which are one of the important indicators for the financial power of companies were determined and calculated for each company separately. Calculated ratios converted to demonstrate of company performance unique point by using TOPSIS method. Companies have sorted according to their calculated performance s...

ESIM: Edge Similarity for Screen Content Image Quality Assessment.

Science.gov (United States)

Ni, Zhangkai; Ma, Lin; Zeng, Huanqiang; Chen, Jing; Cai, Canhui; Ma, Kai-Kuang

2017-10-01

In this paper, an accurate full-reference image quality assessment (IQA) model developed for assessing screen content images (SCIs), called the edge similarity (ESIM), is proposed. It is inspired by the fact that the human visual system (HVS) is highly sensitive to edges that are often encountered in SCIs; therefore, essential edge features are extracted and exploited for conducting IQA for the SCIs. The key novelty of the proposed ESIM lies in the extraction and use of three salient edge features-i.e., edge contrast, edge width, and edge direction. The first two attributes are simultaneously generated from the input SCI based on a parametric edge model, while the last one is derived directly from the input SCI. The extraction of these three features will be performed for the reference SCI and the distorted SCI, individually. The degree of similarity measured for each above-mentioned edge attribute is then computed independently, followed by combining them together using our proposed edge-width pooling strategy to generate the final ESIM score. To conduct the performance evaluation of our proposed ESIM model, a new and the largest SCI database (denoted as SCID) is established in our work and made to the public for download. Our database contains 1800 distorted SCIs that are generated from 40 reference SCIs. For each SCI, nine distortion types are investigated, and five degradation levels are produced for each distortion type. Extensive simulation results have clearly shown that the proposed ESIM model is more consistent with the perception of the HVS on the evaluation of distorted SCIs than the multiple state-of-the-art IQA methods.

A Comparative Study of Potential Evapotranspiration Estimation by Eight Methods with FAO Penman–Monteith Method in Southwestern China

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Dengxiao Lang

2017-09-01

Full Text Available Potential evapotranspiration (PET is crucial for water resources assessment. In this regard, the FAO (Food and Agriculture Organization–Penman–Monteith method (PM is commonly recognized as a standard method for PET estimation. However, due to requirement of detailed meteorological data, the application of PM is often constrained in many regions. Under such circumstances, an alternative method with similar efficiency to that of PM needs to be identified. In this study, three radiation-based methods, Makkink (Mak, Abtew (Abt, and Priestley–Taylor (PT, and five temperature-based methods, Hargreaves–Samani (HS, Thornthwaite (Tho, Hamon (Ham, Linacre (Lin, and Blaney–Criddle (BC, were compared with PM at yearly and seasonal scale, using long-term (50 years data from 90 meteorology stations in southwest China. Indicators, viz. (videlicet Nash–Sutcliffe efficiency (NSE, relative error (Re, normalized root mean squared error (NRMSE, and coefficient of determination (R2 were used to evaluate the performance of PET estimations by the above-mentioned eight methods. The results showed that the performance of the methods in PET estimation varied among regions; HS, PT, and Abt overestimated PET, while others underestimated. In Sichuan basin, Mak, Abt and HS yielded similar estimations to that of PM, while, in Yun-Gui plateau, Abt, Mak, HS, and PT showed better performances. Mak performed the best in the east Tibetan Plateau at yearly and seasonal scale, while HS showed a good performance in summer and autumn. In the arid river valley, HS, Mak, and Abt performed better than the others. On the other hand, Tho, Ham, Lin, and BC could not be used to estimate PET in some regions. In general, radiation-based methods for PET estimation performed better than temperature-based methods among the selected methods in the study area. Among the radiation-based methods, Mak performed the best, while HS showed the best performance among the temperature

HUMAN ERROR QUANTIFICATION USING PERFORMANCE SHAPING FACTORS IN THE SPAR-H METHOD

Energy Technology Data Exchange (ETDEWEB)

Harold S. Blackman; David I. Gertman; Ronald L. Boring

2008-09-01

This paper describes a cognitively based human reliability analysis (HRA) quantification technique for estimating the human error probabilities (HEPs) associated with operator and crew actions at nuclear power plants. The method described here, Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method, was developed to aid in characterizing and quantifying human performance at nuclear power plants. The intent was to develop a defensible method that would consider all factors that may influence performance. In the SPAR-H approach, calculation of HEP rates is especially straightforward, starting with pre-defined nominal error rates for cognitive vs. action-oriented tasks, and incorporating performance shaping factor multipliers upon those nominal error rates.

Proposal for an Evaluation Method for the Performance of Work Procedures.

Science.gov (United States)

Mohammed, Mouda; Mébarek, Djebabra; Wafa, Boulagouas; Makhlouf, Chati

2016-12-01

Noncompliance of operators with work procedures is a recurrent problem. This human behavior has been said to be situational and studied by many different approaches (ergonomic and others), which consider the noncompliance with work procedures to be obvious and seek to analyze its causes as well as consequences. The object of the proposed method is to solve this problem by focusing on the performance of work procedures and ensuring improved performance on a continuous basis. This study has multiple results: (1) assessment of the work procedures' performance by a multicriteria approach; (2) the use of a continuous improvement approach as a framework for the sustainability of the assessment method of work procedures' performance; and (3) adaptation of the Stop-Card as a facilitator support for continuous improvement of work procedures. The proposed method emphasizes to put in value the inputs of continuous improvement of the work procedures in relation with the conventional approaches which adopt the obvious evidence of the noncompliance to the working procedures and seek to analyze the cause-effect relationships related to this unacceptable phenomenon, especially in strategic industry.

Performance Analysis of Video Transmission Using Sequential Distortion Minimization Method for Digital Video Broadcasting Terrestrial

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Novita Astin

2016-12-01

Full Text Available This paper presents about the transmission of Digital Video Broadcasting system with streaming video resolution 640x480 on different IQ rate and modulation. In the video transmission, distortion often occurs, so the received video has bad quality. Key frames selection algorithm is flexibel on a change of video, but on these methods, the temporal information of a video sequence is omitted. To minimize distortion between the original video and received video, we aimed at adding methodology using sequential distortion minimization algorithm. Its aim was to create a new video, better than original video without significant loss of content between the original video and received video, fixed sequentially. The reliability of video transmission was observed based on a constellation diagram, with the best result on IQ rate 2 Mhz and modulation 8 QAM. The best video transmission was also investigated using SEDIM (Sequential Distortion Minimization Method and without SEDIM. The experimental result showed that the PSNR (Peak Signal to Noise Ratio average of video transmission using SEDIM was an increase from 19,855 dB to 48,386 dB and SSIM (Structural Similarity average increase 10,49%. The experimental results and comparison of proposed method obtained a good performance. USRP board was used as RF front-end on 2,2 GHz.

A Control Variate Method for Probabilistic Performance Assessment. Improved Estimates for Mean Performance Quantities of Interest

Energy Technology Data Exchange (ETDEWEB)

MacKinnon, Robert J.; Kuhlman, Kristopher L

2016-05-01

We present a method of control variates for calculating improved estimates for mean performance quantities of interest, E(PQI) , computed from Monte Carlo probabilistic simulations. An example of a PQI is the concentration of a contaminant at a particular location in a problem domain computed from simulations of transport in porous media. To simplify the presentation, the method is described in the setting of a one- dimensional elliptical model problem involving a single uncertain parameter represented by a probability distribution. The approach can be easily implemented for more complex problems involving multiple uncertain parameters and in particular for application to probabilistic performance assessment of deep geologic nuclear waste repository systems. Numerical results indicate the method can produce estimates of E(PQI)having superior accuracy on coarser meshes and reduce the required number of simulations needed to achieve an acceptable estimate.

A little similarity goes a long way: the effects of peripheral but self-revealing similarities on improving and sustaining interracial relationships.

Science.gov (United States)

West, Tessa V; Magee, Joe C; Gordon, Sarah H; Gullett, Lindy

2014-07-01

Integrating theory on close relationships and intergroup relations, we construct a manipulation of similarity that we demonstrate can improve interracial interactions across different settings. We find that manipulating perceptions of similarity on self-revealing attributes that are peripheral to the interaction improves interactions in cross-race dyads and racially diverse task groups. In a getting-acquainted context, we demonstrate that the belief that one's different-race partner is similar to oneself on self-revealing, peripheral attributes leads to less anticipatory anxiety than the belief that one's partner is similar on peripheral, nonself-revealing attributes. In another dyadic context, we explore the range of benefits that perceptions of peripheral, self-revealing similarity can bring to different-race interaction partners and find (a) less anxiety during interaction, (b) greater interest in sustained contact with one's partner, and (c) stronger accuracy in perceptions of one's partners' relationship intentions. By contrast, participants in same-race interactions were largely unaffected by these manipulations of perceived similarity. Our final experiment shows that among small task groups composed of racially diverse individuals, those whose members perceive peripheral, self-revealing similarity perform superior to those who perceive dissimilarity. Implications for using this approach to improve interracial interactions across different goal-driven contexts are discussed.

Molecular similarity measures.

Science.gov (United States)

Maggiora, Gerald M; Shanmugasundaram, Veerabahu

2011-01-01

Molecular similarity is a pervasive concept in chemistry. It is essential to many aspects of chemical reasoning and analysis and is perhaps the fundamental assumption underlying medicinal chemistry. Dissimilarity, the complement of similarity, also plays a major role in a growing number of applications of molecular diversity in combinatorial chemistry, high-throughput screening, and related fields. How molecular information is represented, called the representation problem, is important to the type of molecular similarity analysis (MSA) that can be carried out in any given situation. In this work, four types of mathematical structure are used to represent molecular information: sets, graphs, vectors, and functions. Molecular similarity is a pairwise relationship that induces structure into sets of molecules, giving rise to the concept of chemical space. Although all three concepts - molecular similarity, molecular representation, and chemical space - are treated in this chapter, the emphasis is on molecular similarity measures. Similarity measures, also called similarity coefficients or indices, are functions that map pairs of compatible molecular representations that are of the same mathematical form into real numbers usually, but not always, lying on the unit interval. This chapter presents a somewhat pedagogical discussion of many types of molecular similarity measures, their strengths and limitations, and their relationship to one another. An expanded account of the material on chemical spaces presented in the first edition of this book is also provided. It includes a discussion of the topography of activity landscapes and the role that activity cliffs in these landscapes play in structure-activity studies.

Study on behaviors and performances of universal N-glycopeptide enrichment methods.

Science.gov (United States)

Xue, Yu; Xie, Juanjuan; Fang, Pan; Yao, Jun; Yan, Guoquan; Shen, Huali; Yang, Pengyuan

2018-04-16

Glycosylation is a crucial process in protein biosynthesis. However, the analysis of glycopeptides through MS remains challenging due to the microheterogeneity and macroheterogeneity of the glycoprotein. Selective enrichment of glycopeptides from complex samples prior to MS analysis is essential for successful glycoproteome research. In this work, we systematically investigated the behaviors and performances of boronic acid chemistry, ZIC-HILIC, and PGC of glycopeptide enrichment to promote understanding of these methods. We also optimized boronic acid chemistry and ZIC-HILIC enrichment methods and applied them to enrich glycopeptides from mouse liver. The intact N-glycopeptides were interpreted using the in-house analysis software pGlyco 2.0. We found that boronic acid chemistry in this study preferred to capture glycopeptides with high mannose glycans, ZIC-HILIC enriched most N-glycopeptides and did not show significant preference during enrichment and PGC was not suitable for separating glycopeptides with a long amino acid sequence. We performed a detailed study on the behaviors and performances of boronic acid chemistry, ZIC-HILIC, and PGC enrichment methods and provide a better understanding of enrichment methods for further glycoproteomics research.

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.

What Math Matters? Types of Mathematics Knowledge and Relationships to Methods Course Performance

Science.gov (United States)

Kajander, Ann; Holm, Jennifer

2016-01-01

This study investigated the effect of a departmental focus on enhanced mathematics knowledge for teaching on overall performance in upper elementary mathematics methods courses. The study examined the effect of performance on a new course in mathematics for teaching on performance at the methods course level. In addition, the effect of performance…

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

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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.

Detecting and classifying method based on similarity matching of Android malware behavior with profile.

Science.gov (United States)

Jang, Jae-Wook; Yun, Jaesung; Mohaisen, Aziz; Woo, Jiyoung; Kim, Huy Kang

2016-01-01

Mass-market mobile security threats have increased recently due to the growth of mobile technologies and the popularity of mobile devices. Accordingly, techniques have been introduced for identifying, classifying, and defending against mobile threats utilizing static, dynamic, on-device, and off-device techniques. Static techniques are easy to evade, while dynamic techniques are expensive. On-device techniques are evasion, while off-device techniques need being always online. To address some of those shortcomings, we introduce Andro-profiler, a hybrid behavior based analysis and classification system for mobile malware. Andro-profiler main goals are efficiency, scalability, and accuracy. For that, Andro-profiler classifies malware by exploiting the behavior profiling extracted from the integrated system logs including system calls. Andro-profiler executes a malicious application on an emulator in order to generate the integrated system logs, and creates human-readable behavior profiles by analyzing the integrated system logs. By comparing the behavior profile of malicious application with representative behavior profile for each malware family using a weighted similarity matching technique, Andro-profiler detects and classifies it into malware families. The experiment results demonstrate that Andro-profiler is scalable, performs well in detecting and classifying malware with accuracy greater than 98 %, outperforms the existing state-of-the-art work, and is capable of identifying 0-day mobile malware samples.

Semantic similarity from natural language and ontology analysis

CERN Document Server

Harispe, Sébastien; Janaqi, Stefan

2015-01-01

Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli.In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances def

Description of JNC's analytical method and its performance for FBR cores

International Nuclear Information System (INIS)

Ishikawa, M.

2000-01-01

The description of JNC's analytical method and its performance for FBR cores includes: an outline of JNC's Analytical System Compared with ERANOS; a standard data base for FBR Nuclear Design in JNC; JUPITER Critical Experiment; details of Analytical Method and Its Effects on JUPITER; performance of JNC Analytical System (effective multiplication factor k eff , control rod worth, and sodium void reactivity); design accuracy of a 600 MWe-class FBR Core. JNC developed a consistent analytical system for FBR core evaluation, based on JENDL library, f-table method, and three dimensional diffusion/transport theory, which includes comprehensive sensitivity tools to improve the prediction accuracy of core parameters. JNC system was verified by analysis of JUPITER critical experiment, and other facilities. Its performance can be judged quite satisfactory for FBR-core design work, though there is room for further improvement, such as more detailed treatment of cross-section resonance regions

On the use of the fictitious wave steepness and related surf-similarity parameters in methods that describe the hydraulic and structural response to waves

NARCIS (Netherlands)

Heineke, D.; Verhagen, H.J.

2007-01-01

To assess the hydraulic performance of coastal structures - viz. wave run-up, overtopping and reflection - and to evaluate the stability of the armour layers, use is made of the dimensionless surf similarity parameter, as introduced by Battjes (1974). The front side slope of the structure and the

An exploratory survey of methods used to develop measures of performance

Science.gov (United States)

Hamner, Kenneth L.; Lafleur, Charles A.

1993-09-01

Nonmanufacturing organizations are being challenged to provide high-quality products and services to their customers, with an emphasis on continuous process improvement. Measures of performance, referred to as metrics, can be used to foster process improvement. The application of performance measurement to nonmanufacturing processes can be very difficult. This research explored methods used to develop metrics in nonmanufacturing organizations. Several methods were formally defined in the literature, and the researchers used a two-step screening process to determine the OMB Generic Method was most likely to produce high-quality metrics. The OMB Generic Method was then used to develop metrics. A few other metric development methods were found in use at nonmanufacturing organizations. The researchers interviewed participants in metric development efforts to determine their satisfaction and to have them identify the strengths and weaknesses of, and recommended improvements to, the metric development methods used. Analysis of participants' responses allowed the researchers to identify the key components of a sound metrics development method. Those components were incorporated into a proposed metric development method that was based on the OMB Generic Method, and should be more likely to produce high-quality metrics that will result in continuous process improvement.

Performance of the Lot Quality Assurance Sampling Method Compared to Surveillance for Identifying Inadequately-performing Areas in Matlab, Bangladesh

OpenAIRE

Bhuiya, Abbas; Hanifi, S.M.A.; Roy, Nikhil; Streatfield, P. Kim

2007-01-01

This paper compared the performance of the lot quality assurance sampling (LQAS) method in identifying inadequately-performing health work-areas with that of using health and demographic surveillance system (HDSS) data and examined the feasibility of applying the method by field-level programme supervisors. The study was carried out in Matlab, the field site of ICDDR,B, where a HDSS has been in place for over 30 years. The LQAS method was applied in 57 work-areas of community health workers i...

Determining the semantic similarities among Gene Ontology terms.

Science.gov (United States)

Taha, Kamal

2013-05-01

We present in this paper novel techniques that determine the semantic relationships among GeneOntology (GO) terms. We implemented these techniques in a prototype system called GoSE, which resides between user application and GO database. Given a set S of GO terms, GoSE would return another set S' of GO terms, where each term in S' is semantically related to each term in S. Most current research is focused on determining the semantic similarities among GO ontology terms based solely on their IDs and proximity to one another in the GO graph structure, while overlooking the contexts of the terms, which may lead to erroneous results. The context of a GO term T is the set of other terms, whose existence in the GO graph structure is dependent on T. We propose novel techniques that determine the contexts of terms based on the concept of existence dependency. We present a stack-based sort-merge algorithm employing these techniques for determining the semantic similarities among GO terms.We evaluated GoSE experimentally and compared it with three existing methods. The results of measuring the semantic similarities among genes in KEGG and Pfam pathways retrieved from the DBGET and Sanger Pfam databases, respectively, have shown that our method outperforms the other three methods in recall and precision.

Total error components - isolation of laboratory variation from method performance

International Nuclear Information System (INIS)

Bottrell, D.; Bleyler, R.; Fisk, J.; Hiatt, M.

1992-01-01

The consideration of total error across sampling and analytical components of environmental measurements is relatively recent. The U.S. Environmental Protection Agency (EPA), through the Contract Laboratory Program (CLP), provides complete analyses and documented reports on approximately 70,000 samples per year. The quality assurance (QA) functions of the CLP procedures provide an ideal data base-CLP Automated Results Data Base (CARD)-to evaluate program performance relative to quality control (QC) criteria and to evaluate the analysis of blind samples. Repetitive analyses of blind samples within each participating laboratory provide a mechanism to separate laboratory and method performance. Isolation of error sources is necessary to identify effective options to establish performance expectations, and to improve procedures. In addition, optimized method performance is necessary to identify significant effects that result from the selection among alternative procedures in the data collection process (e.g., sampling device, storage container, mode of sample transit, etc.). This information is necessary to evaluate data quality; to understand overall quality; and to provide appropriate, cost-effective information required to support a specific decision

Intelligent method of plant dynamics behavior estimation by effectively applying similar cases

International Nuclear Information System (INIS)

Gofuku, Akio; Numoto, Atsushi; Yoshikawa, Hidekazu

1994-01-01

In order to accomplish efficient execution of a dynamic simulation of engineering systems, it is important to construct suitable mathematical models for the simulation. In the construction of the mathematical models, it is necessary to estimate the system's behavior to suppose the phenomena which are needed to be modeled. The case-based reasoning is considered to be a powerful tool to estimate the outline of system's behavior because we often estimate it from the similar cases which are stored as our experience or in literature. In this study, the technique based on similar cases is investigated to estimate the outline of time-responses of several important variables of pressurized water reactor (PWR) plants at a small break loss of coolant accident (SBLOCA). The registered cases in case base are gathered from various reports and the authors' numerical simulations related with SBLOCA of PWR plants. The functions to use in the case retrieval are formed from the characteristic features of SBLOCA of PWR plants. On the other hand, the rules to use in the case refinement are obtained from the qualitative and quantitative consideration of plants' behaviors of the cases in the case base. The applicability of the technique is discussed by two simple estimation trials of plant behavior. (author)

An alignment-free method to find similarity among protein sequences via the general form of Chou's pseudo amino acid composition.

Science.gov (United States)

Gupta, M K; Niyogi, R; Misra, M

2013-01-01

In this paper, we propose a method to create the 60-dimensional feature vector for protein sequences via the general form of pseudo amino acid composition. The construction of the feature vector is based on the contents of amino acids, total distance of each amino acid from the first amino acid in the protein sequence and the distribution of 20 amino acids. The obtained cosine distance metric (also called the similarity matrix) is used to construct the phylogenetic tree by the neighbour joining method. In order to show the applicability of our approach, we tested it on three proteins: 1) ND5 protein sequences from nine species, 2) ND6 protein sequences from eight species, and 3) 50 coronavirus spike proteins. The results are in agreement with known history and the output from the multiple sequence alignment program ClustalW, which is widely used. We have also compared our phylogenetic results with six other recently proposed alignment-free methods. These comparisons show that our proposed method gives a more consistent biological relationship than the others. In addition, the time complexity is linear and space required is less as compared with other alignment-free methods that use graphical representation. It should be noted that the multiple sequence alignment method has exponential time complexity.

Algorithmic prediction of inter-song similarity in Western popular music

NARCIS (Netherlands)

Novello, A.; Par, van de S.L.J.D.E.; McKinney, M.F.; Kohlrausch, A.G.

2013-01-01

We investigate a method for automatic extraction of inter-song similarity for songs selected from several genres of Western popular music. The specific purpose of this approach is to evaluate the predictive power of different feature extraction sets based on human perception of music similarity and

Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

Science.gov (United States)

Ferragina, Paolo; Giancarlo, Raffaele; Greco, Valentina; Manzini, Giovanni; Valiente, Gabriel

2007-07-13

Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rather than a formula quantifying the similarity of two strings. Three approximations of USM are available, namely UCD (Universal Compression Dissimilarity), NCD (Normalized Compression Dissimilarity) and CD (Compression Dissimilarity). Their applicability and robustness is tested on various data sets yielding a first massive quantitative estimate that the USM methodology and its approximations are of value. Despite the rich theory developed around USM, its experimental assessment has limitations: only a few data compressors have been tested in conjunction with USM and mostly at a qualitative level, no comparison among UCD, NCD and CD is available and no comparison of USM with existing methods, both based on alignments and not, seems to be available. We experimentally test the USM methodology by using 25 compressors, all three of its known approximations and six data sets of relevance to Molecular Biology. This offers the first systematic and quantitative experimental assessment of this methodology, that naturally complements the many theoretical and the preliminary experimental results available. Moreover, we compare the USM methodology both with methods based on alignments and not. We may group our experiments into two sets. The first one, performed via ROC (Receiver Operating Curve) analysis, aims at

Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment

Directory of Open Access Journals (Sweden)

Manzini Giovanni

2007-07-01

Full Text Available Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rather than a formula quantifying the similarity of two strings. Three approximations of USM are available, namely UCD (Universal Compression Dissimilarity, NCD (Normalized Compression Dissimilarity and CD (Compression Dissimilarity. Their applicability and robustness is tested on various data sets yielding a first massive quantitative estimate that the USM methodology and its approximations are of value. Despite the rich theory developed around USM, its experimental assessment has limitations: only a few data compressors have been tested in conjunction with USM and mostly at a qualitative level, no comparison among UCD, NCD and CD is available and no comparison of USM with existing methods, both based on alignments and not, seems to be available. Results We experimentally test the USM methodology by using 25 compressors, all three of its known approximations and six data sets of relevance to Molecular Biology. This offers the first systematic and quantitative experimental assessment of this methodology, that naturally complements the many theoretical and the preliminary experimental results available. Moreover, we compare the USM methodology both with methods based on alignments and not. We may group our experiments into two sets. The first one, performed via ROC

Anomalous Traffic Detection and Self-Similarity Analysis in the Environment of ATMSim

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Hae-Duck J. Jeong

2017-12-01

Full Text Available Internet utilisation has steadily increased, predominantly due to the rapid recent development of information and communication networks and the widespread distribution of smartphones. As a result of this increase in Internet consumption, various types of services, including web services, social networking services (SNS, Internet banking, and remote processing systems have been created. These services have significantly enhanced global quality of life. However, as a negative side-effect of this rapid development, serious information security problems have also surfaced, which has led to serious to Internet privacy invasions and network attacks. In an attempt to contribute to the process of addressing these problems, this paper proposes a process to detect anomalous traffic using self-similarity analysis in the Anomaly Teletraffic detection Measurement analysis Simulator (ATMSim environment as a research method. Simulations were performed to measure normal and anomalous traffic. First, normal traffic for each attack, including the Address Resolution Protocol (ARP and distributed denial-of-service (DDoS was measured for 48 h over 10 iterations. Hadoop was used to facilitate processing of the large amount of collected data, after which MapReduce was utilised after storing the data in the Hadoop Distributed File System (HDFS. A new platform on Hadoop, the detection system ATMSim, was used to identify anomalous traffic after which a comparative analysis of the normal and anomalous traffic was performed through a self-similarity analysis. There were four categories of collected traffic that were divided according to the attack methods used: normal local area network (LAN traffic, DDoS attack, and ARP spoofing, as well as DDoS and ARP attack. ATMSim, the anomaly traffic detection system, was used to determine if real attacks could be identified effectively. To achieve this, the ATMSim was used in simulations for each scenario to test its ability to

Performance of different methods for reference evapotranspiration estimation in Jaíba, Brazil

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Gustavo H. da Silva

Full Text Available ABSTRACT FAO Penman-Monteith (FO-PM is considered the standard method for the estimation of reference evapotranspiration (ET0 but requires various meteorological data, which are often not available. The objective of this work was to evaluate the performance of the FAO-PM method with limited meteorological data and other methods as alternatives to estimate ET0 in Jaíba-MG. The study used daily meteorological data from 2007 to 2016 of the National Institute of Meteorology’s station. Daily ET0 values were randomized, and 70% of these were used to determine the calibration parameters of the ET0 for the equations of each method under study. The remaining data were used to test the calibration against the standard method. Performance evaluation was based on Willmott’s index of agreement, confidence coefficient and root-mean-square error. When one meteorological variable was missing, either solar radiation, relative air humidity or wind speed, or in the simultaneous absence of wind speed and relative air humidity, the FAO-PM method showed the best performances and, therefore, was recommended for Jaíba. The FAO-PM method with two missing variables, one of them being solar radiation, showed intermediate performance. Methods that used only air temperature data are not recommended for the region.

Semantic similarity between ontologies at different scales

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Zhang, Qingpeng; Haglin, David J.

2016-04-01

In the past decade, existing and new knowledge and datasets has been encoded in different ontologies for semantic web and biomedical research. The size of ontologies is often very large in terms of number of concepts and relationships, which makes the analysis of ontologies and the represented knowledge graph computational and time consuming. As the ontologies of various semantic web and biomedical applications usually show explicit hierarchical structures, it is interesting to explore the trade-offs between ontological scales and preservation/precision of results when we analyze ontologies. This paper presents the first effort of examining the capability of this idea via studying the relationship between scaling biomedical ontologies at different levels and the semantic similarity values. We evaluate the semantic similarity between three Gene Ontology slims (Plant, Yeast, and Candida, among which the latter two belong to the same kingdom—Fungi) using four popular measures commonly applied to biomedical ontologies (Resnik, Lin, Jiang-Conrath, and SimRel). The results of this study demonstrate that with proper selection of scaling levels and similarity measures, we can significantly reduce the size of ontologies without losing substantial detail. In particular, the performance of Jiang-Conrath and Lin are more reliable and stable than that of the other two in this experiment, as proven by (a) consistently showing that Yeast and Candida are more similar (as compared to Plant) at different scales, and (b) small deviations of the similarity values after excluding a majority of nodes from several lower scales. This study provides a deeper understanding of the application of semantic similarity to biomedical ontologies, and shed light on how to choose appropriate semantic similarity measures for biomedical engineering.