Biclustering of gene expression data using reactive greedy randomized adaptive search procedure.

PubMed

Dharan, Smitha; Nair, Achuthsankar S

2009-01-30

Biclustering algorithms belong to a distinct class of clustering algorithms that perform simultaneous clustering of both rows and columns of the gene expression matrix and can be a very useful analysis tool when some genes have multiple functions and experimental conditions are diverse. Cheng and Church have introduced a measure called mean squared residue score to evaluate the quality of a bicluster and has become one of the most popular measures to search for biclusters. In this paper, we review basic concepts of the metaheuristics Greedy Randomized Adaptive Search Procedure (GRASP)-construction and local search phases and propose a new method which is a variant of GRASP called Reactive Greedy Randomized Adaptive Search Procedure (Reactive GRASP) to detect significant biclusters from large microarray datasets. The method has two major steps. First, high quality bicluster seeds are generated by means of k-means clustering. In the second step, these seeds are grown using the Reactive GRASP, in which the basic parameter that defines the restrictiveness of the candidate list is self-adjusted, depending on the quality of the solutions found previously. We performed statistical and biological validations of the biclusters obtained and evaluated the method against the results of basic GRASP and as well as with the classic work of Cheng and Church. The experimental results indicate that the Reactive GRASP approach outperforms the basic GRASP algorithm and Cheng and Church approach. The Reactive GRASP approach for the detection of significant biclusters is robust and does not require calibration efforts.

Improving performances of suboptimal greedy iterative biclustering heuristics via localization.

PubMed

Erten, Cesim; Sözdinler, Melih

2010-10-15

Biclustering gene expression data is the problem of extracting submatrices of genes and conditions exhibiting significant correlation across both the rows and the columns of a data matrix of expression values. Even the simplest versions of the problem are computationally hard. Most of the proposed solutions therefore employ greedy iterative heuristics that locally optimize a suitably assigned scoring function. We provide a fast and simple pre-processing algorithm called localization that reorders the rows and columns of the input data matrix in such a way as to group correlated entries in small local neighborhoods within the matrix. The proposed localization algorithm takes its roots from effective use of graph-theoretical methods applied to problems exhibiting a similar structure to that of biclustering. In order to evaluate the effectivenesss of the localization pre-processing algorithm, we focus on three representative greedy iterative heuristic methods. We show how the localization pre-processing can be incorporated into each representative algorithm to improve biclustering performance. Furthermore, we propose a simple biclustering algorithm, Random Extraction After Localization (REAL) that randomly extracts submatrices from the localization pre-processed data matrix, eliminates those with low similarity scores, and provides the rest as correlated structures representing biclusters. We compare the proposed localization pre-processing with another pre-processing alternative, non-negative matrix factorization. We show that our fast and simple localization procedure provides similar or even better results than the computationally heavy matrix factorization pre-processing with regards to H-value tests. We next demonstrate that the performances of the three representative greedy iterative heuristic methods improve with localization pre-processing when biological correlations in the form of functional enrichment and PPI verification constitute the main performance

Rectified factor networks for biclustering of omics data.

PubMed

Clevert, Djork-Arné; Unterthiner, Thomas; Povysil, Gundula; Hochreiter, Sepp

2017-07-15

Biclustering has become a major tool for analyzing large datasets given as matrix of samples times features and has been successfully applied in life sciences and e-commerce for drug design and recommender systems, respectively. actor nalysis for cluster cquisition (FABIA), one of the most successful biclustering methods, is a generative model that represents each bicluster by two sparse membership vectors: one for the samples and one for the features. However, FABIA is restricted to about 20 code units because of the high computational complexity of computing the posterior. Furthermore, code units are sometimes insufficiently decorrelated and sample membership is difficult to determine. We propose to use the recently introduced unsupervised Deep Learning approach Rectified Factor Networks (RFNs) to overcome the drawbacks of existing biclustering methods. RFNs efficiently construct very sparse, non-linear, high-dimensional representations of the input via their posterior means. RFN learning is a generalized alternating minimization algorithm based on the posterior regularization method which enforces non-negative and normalized posterior means. Each code unit represents a bicluster, where samples for which the code unit is active belong to the bicluster and features that have activating weights to the code unit belong to the bicluster. On 400 benchmark datasets and on three gene expression datasets with known clusters, RFN outperformed 13 other biclustering methods including FABIA. On data of the 1000 Genomes Project, RFN could identify DNA segments which indicate, that interbreeding with other hominins starting already before ancestors of modern humans left Africa. https://github.com/bioinf-jku/librfn. djork-arne.clevert@bayer.com or hochreit@bioinf.jku.at. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Query-based biclustering of gene expression data using Probabilistic Relational Models.

PubMed

Zhao, Hui; Cloots, Lore; Van den Bulcke, Tim; Wu, Yan; De Smet, Riet; Storms, Valerie; Meysman, Pieter; Engelen, Kristof; Marchal, Kathleen

2011-02-15

With the availability of large scale expression compendia it is now possible to view own findings in the light of what is already available and retrieve genes with an expression profile similar to a set of genes of interest (i.e., a query or seed set) for a subset of conditions. To that end, a query-based strategy is needed that maximally exploits the coexpression behaviour of the seed genes to guide the biclustering, but that at the same time is robust against the presence of noisy genes in the seed set as seed genes are often assumed, but not guaranteed to be coexpressed in the queried compendium. Therefore, we developed ProBic, a query-based biclustering strategy based on Probabilistic Relational Models (PRMs) that exploits the use of prior distributions to extract the information contained within the seed set. We applied ProBic on a large scale Escherichia coli compendium to extend partially described regulons with potentially novel members. We compared ProBic's performance with previously published query-based biclustering algorithms, namely ISA and QDB, from the perspective of bicluster expression quality, robustness of the outcome against noisy seed sets and biological relevance.This comparison learns that ProBic is able to retrieve biologically relevant, high quality biclusters that retain their seed genes and that it is particularly strong in handling noisy seeds. ProBic is a query-based biclustering algorithm developed in a flexible framework, designed to detect biologically relevant, high quality biclusters that retain relevant seed genes even in the presence of noise or when dealing with low quality seed sets.

Querying Co-regulated Genes on Diverse Gene Expression Datasets Via Biclustering.

PubMed

Deveci, Mehmet; Küçüktunç, Onur; Eren, Kemal; Bozdağ, Doruk; Kaya, Kamer; Çatalyürek, Ümit V

2016-01-01

Rapid development and increasing popularity of gene expression microarrays have resulted in a number of studies on the discovery of co-regulated genes. One important way of discovering such co-regulations is the query-based search since gene co-expressions may indicate a shared role in a biological process. Although there exist promising query-driven search methods adapting clustering, they fail to capture many genes that function in the same biological pathway because microarray datasets are fraught with spurious samples or samples of diverse origin, or the pathways might be regulated under only a subset of samples. On the other hand, a class of clustering algorithms known as biclustering algorithms which simultaneously cluster both the items and their features are useful while analyzing gene expression data, or any data in which items are related in only a subset of their samples. This means that genes need not be related in all samples to be clustered together. Because many genes only interact under specific circumstances, biclustering may recover the relationships that traditional clustering algorithms can easily miss. In this chapter, we briefly summarize the literature using biclustering for querying co-regulated genes. Then we present a novel biclustering approach and evaluate its performance by a thorough experimental analysis.

A new measure for gene expression biclustering based on non-parametric correlation.

PubMed

Flores, Jose L; Inza, Iñaki; Larrañaga, Pedro; Calvo, Borja

2013-12-01

One of the emerging techniques for performing the analysis of the DNA microarray data known as biclustering is the search of subsets of genes and conditions which are coherently expressed. These subgroups provide clues about the main biological processes. Until now, different approaches to this problem have been proposed. Most of them use the mean squared residue as quality measure but relevant and interesting patterns can not be detected such as shifting, or scaling patterns. Furthermore, recent papers show that there exist new coherence patterns involved in different kinds of cancer and tumors such as inverse relationships between genes which can not be captured. The proposed measure is called Spearman's biclustering measure (SBM) which performs an estimation of the quality of a bicluster based on the non-linear correlation among genes and conditions simultaneously. The search of biclusters is performed by using a evolutionary technique called estimation of distribution algorithms which uses the SBM measure as fitness function. This approach has been examined from different points of view by using artificial and real microarrays. The assessment process has involved the use of quality indexes, a set of bicluster patterns of reference including new patterns and a set of statistical tests. It has been also examined the performance using real microarrays and comparing to different algorithmic approaches such as Bimax, CC, OPSM, Plaid and xMotifs. SBM shows several advantages such as the ability to recognize more complex coherence patterns such as shifting, scaling and inversion and the capability to selectively marginalize genes and conditions depending on the statistical significance. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Implementation of plaid model biclustering method on microarray of carcinoma and adenoma tumor gene expression data

NASA Astrophysics Data System (ADS)

Ardaneswari, Gianinna; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

A Tumor is an abnormal growth of cells that serves no purpose. Carcinoma is a tumor that grows from the top of the cell membrane and the organ adenoma is a benign tumor of the gland-like cells or epithelial tissue. In the field of molecular biology, the development of microarray technology is used in the data store of disease genetic expression. For each of microarray gene, an amount of information is stored for each trait or condition. In gene expression data clustering can be done with a bicluster algorithm, thats clustering method which not only the objects to be clustered, but also the properties or condition of the object. This research proposed Plaid Model Biclustering as one of biclustering method. In this study, we discuss the implementation of Plaid Model Biclustering Method on microarray of Carcinoma and Adenoma tumor gene expression data. From the experimental results, we found three biclusters are formed by Carcinoma gene expression data and four biclusters are formed by Adenoma gene expression data.

BiGGEsTS: integrated environment for biclustering analysis of time series gene expression data

PubMed Central

Gonçalves, Joana P; Madeira, Sara C; Oliveira, Arlindo L

2009-01-01

Background The ability to monitor changes in expression patterns over time, and to observe the emergence of coherent temporal responses using expression time series, is critical to advance our understanding of complex biological processes. Biclustering has been recognized as an effective method for discovering local temporal expression patterns and unraveling potential regulatory mechanisms. The general biclustering problem is NP-hard. In the case of time series this problem is tractable, and efficient algorithms can be used. However, there is still a need for specialized applications able to take advantage of the temporal properties inherent to expression time series, both from a computational and a biological perspective. Findings BiGGEsTS makes available state-of-the-art biclustering algorithms for analyzing expression time series. Gene Ontology (GO) annotations are used to assess the biological relevance of the biclusters. Methods for preprocessing expression time series and post-processing results are also included. The analysis is additionally supported by a visualization module capable of displaying informative representations of the data, including heatmaps, dendrograms, expression charts and graphs of enriched GO terms. Conclusion BiGGEsTS is a free open source graphical software tool for revealing local coexpression of genes in specific intervals of time, while integrating meaningful information on gene annotations. It is freely available at: . We present a case study on the discovery of transcriptional regulatory modules in the response of Saccharomyces cerevisiae to heat stress. PMID:19583847

Bit-Table Based Biclustering and Frequent Closed Itemset Mining in High-Dimensional Binary Data

PubMed Central

Király, András; Abonyi, János

2014-01-01

During the last decade various algorithms have been developed and proposed for discovering overlapping clusters in high-dimensional data. The two most prominent application fields in this research, proposed independently, are frequent itemset mining (developed for market basket data) and biclustering (applied to gene expression data analysis). The common limitation of both methodologies is the limited applicability for very large binary data sets. In this paper we propose a novel and efficient method to find both frequent closed itemsets and biclusters in high-dimensional binary data. The method is based on simple but very powerful matrix and vector multiplication approaches that ensure that all patterns can be discovered in a fast manner. The proposed algorithm has been implemented in the commonly used MATLAB environment and freely available for researchers. PMID:24616651

Biclustering as a method for RNA local multiple sequence alignment.

PubMed

Wang, Shu; Gutell, Robin R; Miranker, Daniel P

2007-12-15

Biclustering is a clustering method that simultaneously clusters both the domain and range of a relation. A challenge in multiple sequence alignment (MSA) is that the alignment of sequences is often intended to reveal groups of conserved functional subsequences. Simultaneously, the grouping of the sequences can impact the alignment; precisely the kind of dual situation biclustering is intended to address. We define a representation of the MSA problem enabling the application of biclustering algorithms. We develop a computer program for local MSA, BlockMSA, that combines biclustering with divide-and-conquer. BlockMSA simultaneously finds groups of similar sequences and locally aligns subsequences within them. Further alignment is accomplished by dividing both the set of sequences and their contents. The net result is both a multiple sequence alignment and a hierarchical clustering of the sequences. BlockMSA was tested on the subsets of the BRAliBase 2.1 benchmark suite that display high variability and on an extension to that suite to larger problem sizes. Also, alignments were evaluated of two large datasets of current biological interest, T box sequences and Group IC1 Introns. The results were compared with alignments computed by ClustalW, MAFFT, MUCLE and PROBCONS alignment programs using Sum of Pairs (SPS) and Consensus Count. Results for the benchmark suite are sensitive to problem size. On problems of 15 or greater sequences, BlockMSA is consistently the best. On none of the problems in the test suite are there appreciable differences in scores among BlockMSA, MAFFT and PROBCONS. On the T box sequences, BlockMSA does the most faithful job of reproducing known annotations. MAFFT and PROBCONS do not. On the Intron sequences, BlockMSA, MAFFT and MUSCLE are comparable at identifying conserved regions. BlockMSA is implemented in Java. Source code and supplementary datasets are available at http://aug.csres.utexas.edu/msa/

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-07-17

The explosion of biological data has largely influenced the focus of today’s biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-06-01

The explosion of biological data has largely influenced the focus of today's biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

BiSet: Semantic Edge Bundling with Biclusters for Sensemaking.

PubMed

Sun, Maoyuan; Mi, Peng; North, Chris; Ramakrishnan, Naren

2016-01-01

Identifying coordinated relationships is an important task in data analytics. For example, an intelligence analyst might want to discover three suspicious people who all visited the same four cities. Existing techniques that display individual relationships, such as between lists of entities, require repetitious manual selection and significant mental aggregation in cluttered visualizations to find coordinated relationships. In this paper, we present BiSet, a visual analytics technique to support interactive exploration of coordinated relationships. In BiSet, we model coordinated relationships as biclusters and algorithmically mine them from a dataset. Then, we visualize the biclusters in context as bundled edges between sets of related entities. Thus, bundles enable analysts to infer task-oriented semantic insights about potentially coordinated activities. We make bundles as first class objects and add a new layer, "in-between", to contain these bundle objects. Based on this, bundles serve to organize entities represented in lists and visually reveal their membership. Users can interact with edge bundles to organize related entities, and vice versa, for sensemaking purposes. With a usage scenario, we demonstrate how BiSet supports the exploration of coordinated relationships in text analytics.

A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data.

PubMed

Rangan, Aaditya V; McGrouther, Caroline C; Kelsoe, John; Schork, Nicholas; Stahl, Eli; Zhu, Qian; Krishnan, Arjun; Yao, Vicky; Troyanskaya, Olga; Bilaloglu, Seda; Raghavan, Preeti; Bergen, Sarah; Jureus, Anders; Landen, Mikael

2018-05-14

A common goal in data-analysis is to sift through a large data-matrix and detect any significant submatrices (i.e., biclusters) that have a low numerical rank. We present a simple algorithm for tackling this biclustering problem. Our algorithm accumulates information about 2-by-2 submatrices (i.e., 'loops') within the data-matrix, and focuses on rows and columns of the data-matrix that participate in an abundance of low-rank loops. We demonstrate, through analysis and numerical-experiments, that this loop-counting method performs well in a variety of scenarios, outperforming simple spectral methods in many situations of interest. Another important feature of our method is that it can easily be modified to account for aspects of experimental design which commonly arise in practice. For example, our algorithm can be modified to correct for controls, categorical- and continuous-covariates, as well as sparsity within the data. We demonstrate these practical features with two examples; the first drawn from gene-expression analysis and the second drawn from a much larger genome-wide-association-study (GWAS).

SiBIC: a web server for generating gene set networks based on biclusters obtained by maximal frequent itemset mining.

PubMed

Takahashi, Kei-ichiro; Takigawa, Ichigaku; Mamitsuka, Hiroshi

2013-01-01

Detecting biclusters from expression data is useful, since biclusters are coexpressed genes under only part of all given experimental conditions. We present a software called SiBIC, which from a given expression dataset, first exhaustively enumerates biclusters, which are then merged into rather independent biclusters, which finally are used to generate gene set networks, in which a gene set assigned to one node has coexpressed genes. We evaluated each step of this procedure: 1) significance of the generated biclusters biologically and statistically, 2) biological quality of merged biclusters, and 3) biological significance of gene set networks. We emphasize that gene set networks, in which nodes are not genes but gene sets, can be more compact than usual gene networks, meaning that gene set networks are more comprehensible. SiBIC is available at http://utrecht.kuicr.kyoto-u.ac.jp:8080/miami/faces/index.jsp.

Analyzing Large Gene Expression and Methylation Data Profiles Using StatBicRM: Statistical Biclustering-Based Rule Mining

PubMed Central

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data

Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

PubMed

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data

Spectral biclustering of microarray data: coclustering genes and conditions.

PubMed

Kluger, Yuval; Basri, Ronen; Chang, Joseph T; Gerstein, Mark

2003-04-01

Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, and one wants to find "marker genes" that are differentially expressed in particular sets of "conditions." We have developed a method that simultaneously clusters genes and conditions, finding distinctive "checkerboard" patterns in matrices of gene expression data, if they exist. In a cancer context, these checkerboards correspond to genes that are markedly up- or downregulated in patients with particular types of tumors. Our method, spectral biclustering, is based on the observation that checkerboard structures in matrices of expression data can be found in eigenvectors corresponding to characteristic expression patterns across genes or conditions. In addition, these eigenvectors can be readily identified by commonly used linear algebra approaches, in particular the singular value decomposition (SVD), coupled with closely integrated normalization steps. We present a number of variants of the approach, depending on whether the normalization over genes and conditions is done independently or in a coupled fashion. We then apply spectral biclustering to a selection of publicly available cancer expression data sets, and examine the degree to which the approach is able to identify checkerboard structures. Furthermore, we compare the performance of our biclustering methods against a number of reasonable benchmarks (e.g., direct application of SVD or normalized cuts to raw data).

Spectral Biclustering of Microarray Data: Coclustering Genes and Conditions

PubMed Central

Kluger, Yuval; Basri, Ronen; Chang, Joseph T.; Gerstein, Mark

2003-01-01

Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, and one wants to find “marker genes” that are differentially expressed in particular sets of “conditions.” We have developed a method that simultaneously clusters genes and conditions, finding distinctive “checkerboard” patterns in matrices of gene expression data, if they exist. In a cancer context, these checkerboards correspond to genes that are markedly up- or downregulated in patients with particular types of tumors. Our method, spectral biclustering, is based on the observation that checkerboard structures in matrices of expression data can be found in eigenvectors corresponding to characteristic expression patterns across genes or conditions. In addition, these eigenvectors can be readily identified by commonly used linear algebra approaches, in particular the singular value decomposition (SVD), coupled with closely integrated normalization steps. We present a number of variants of the approach, depending on whether the normalization over genes and conditions is done independently or in a coupled fashion. We then apply spectral biclustering to a selection of publicly available cancer expression data sets, and examine the degree to which the approach is able to identify checkerboard structures. Furthermore, we compare the performance of our biclustering methods against a number of reasonable benchmarks (e.g., direct application of SVD or normalized cuts to raw data). PMID:12671006

Extending bicluster analysis to annotate unclassified ORFs and predict novel functional modules using expression data

PubMed Central

Bryan, Kenneth; Cunningham, Pádraig

2008-01-01

Background Microarrays have the capacity to measure the expressions of thousands of genes in parallel over many experimental samples. The unsupervised classification technique of bicluster analysis has been employed previously to uncover gene expression correlations over subsets of samples with the aim of providing a more accurate model of the natural gene functional classes. This approach also has the potential to aid functional annotation of unclassified open reading frames (ORFs). Until now this aspect of biclustering has been under-explored. In this work we illustrate how bicluster analysis may be extended into a 'semi-supervised' ORF annotation approach referred to as BALBOA. Results The efficacy of the BALBOA ORF classification technique is first assessed via cross validation and compared to a multi-class k-Nearest Neighbour (kNN) benchmark across three independent gene expression datasets. BALBOA is then used to assign putative functional annotations to unclassified yeast ORFs. These predictions are evaluated using existing experimental and protein sequence information. Lastly, we employ a related semi-supervised method to predict the presence of novel functional modules within yeast. Conclusion In this paper we demonstrate how unsupervised classification methods, such as bicluster analysis, may be extended using of available annotations to form semi-supervised approaches within the gene expression analysis domain. We show that such methods have the potential to improve upon supervised approaches and shed new light on the functions of unclassified ORFs and their co-regulation. PMID:18831786

ParBiBit: Parallel tool for binary biclustering on modern distributed-memory systems

PubMed Central

Expósito, Roberto R.

2018-01-01

Biclustering techniques are gaining attention in the analysis of large-scale datasets as they identify two-dimensional submatrices where both rows and columns are correlated. In this work we present ParBiBit, a parallel tool to accelerate the search of interesting biclusters on binary datasets, which are very popular on different fields such as genetics, marketing or text mining. It is based on the state-of-the-art sequential Java tool BiBit, which has been proved accurate by several studies, especially on scenarios that result on many large biclusters. ParBiBit uses the same methodology as BiBit (grouping the binary information into patterns) and provides the same results. Nevertheless, our tool significantly improves performance thanks to an efficient implementation based on C++11 that includes support for threads and MPI processes in order to exploit the compute capabilities of modern distributed-memory systems, which provide several multicore CPU nodes interconnected through a network. Our performance evaluation with 18 representative input datasets on two different eight-node systems shows that our tool is significantly faster than the original BiBit. Source code in C++ and MPI running on Linux systems as well as a reference manual are available at https://sourceforge.net/projects/parbibit/. PMID:29608567

ParBiBit: Parallel tool for binary biclustering on modern distributed-memory systems.

PubMed

González-Domínguez, Jorge; Expósito, Roberto R

2018-01-01

Biclustering techniques are gaining attention in the analysis of large-scale datasets as they identify two-dimensional submatrices where both rows and columns are correlated. In this work we present ParBiBit, a parallel tool to accelerate the search of interesting biclusters on binary datasets, which are very popular on different fields such as genetics, marketing or text mining. It is based on the state-of-the-art sequential Java tool BiBit, which has been proved accurate by several studies, especially on scenarios that result on many large biclusters. ParBiBit uses the same methodology as BiBit (grouping the binary information into patterns) and provides the same results. Nevertheless, our tool significantly improves performance thanks to an efficient implementation based on C++11 that includes support for threads and MPI processes in order to exploit the compute capabilities of modern distributed-memory systems, which provide several multicore CPU nodes interconnected through a network. Our performance evaluation with 18 representative input datasets on two different eight-node systems shows that our tool is significantly faster than the original BiBit. Source code in C++ and MPI running on Linux systems as well as a reference manual are available at https://sourceforge.net/projects/parbibit/.

Comparative Microbial Modules Resource: Generation and Visualization of Multi-species Biclusters

PubMed Central

Bate, Ashley; Eichenberger, Patrick; Bonneau, Richard

2011-01-01

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures – results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation. PMID:22144874

Comparative microbial modules resource: generation and visualization of multi-species biclusters.

PubMed

Kacmarczyk, Thadeous; Waltman, Peter; Bate, Ashley; Eichenberger, Patrick; Bonneau, Richard

2011-12-01

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures - results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation. © 2011 Kacmarczyk et al.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data.

PubMed

Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

2015-01-01

It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

PubMed Central

2015-01-01

Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

Fine-grained parallelization of fitness functions in bioinformatics optimization problems: gene selection for cancer classification and biclustering of gene expression data.

PubMed

Gomez-Pulido, Juan A; Cerrada-Barrios, Jose L; Trinidad-Amado, Sebastian; Lanza-Gutierrez, Jose M; Fernandez-Diaz, Ramon A; Crawford, Broderick; Soto, Ricardo

2016-08-31

Metaheuristics are widely used to solve large combinatorial optimization problems in bioinformatics because of the huge set of possible solutions. Two representative problems are gene selection for cancer classification and biclustering of gene expression data. In most cases, these metaheuristics, as well as other non-linear techniques, apply a fitness function to each possible solution with a size-limited population, and that step involves higher latencies than other parts of the algorithms, which is the reason why the execution time of the applications will mainly depend on the execution time of the fitness function. In addition, it is usual to find floating-point arithmetic formulations for the fitness functions. This way, a careful parallelization of these functions using the reconfigurable hardware technology will accelerate the computation, specially if they are applied in parallel to several solutions of the population. A fine-grained parallelization of two floating-point fitness functions of different complexities and features involved in biclustering of gene expression data and gene selection for cancer classification allowed for obtaining higher speedups and power-reduced computation with regard to usual microprocessors. The results show better performances using reconfigurable hardware technology instead of usual microprocessors, in computing time and power consumption terms, not only because of the parallelization of the arithmetic operations, but also thanks to the concurrent fitness evaluation for several individuals of the population in the metaheuristic. This is a good basis for building accelerated and low-energy solutions for intensive computing scenarios.

BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.

PubMed

Khakabimamaghani, Sahand; Ester, Martin

2016-01-01

The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data.

A cross-species bi-clustering approach to identifying conserved co-regulated genes.

PubMed

Sun, Jiangwen; Jiang, Zongliang; Tian, Xiuchun; Bi, Jinbo

2016-06-15

A growing number of studies have explored the process of pre-implantation embryonic development of multiple mammalian species. However, the conservation and variation among different species in their developmental programming are poorly defined due to the lack of effective computational methods for detecting co-regularized genes that are conserved across species. The most sophisticated method to date for identifying conserved co-regulated genes is a two-step approach. This approach first identifies gene clusters for each species by a cluster analysis of gene expression data, and subsequently computes the overlaps of clusters identified from different species to reveal common subgroups. This approach is ineffective to deal with the noise in the expression data introduced by the complicated procedures in quantifying gene expression. Furthermore, due to the sequential nature of the approach, the gene clusters identified in the first step may have little overlap among different species in the second step, thus difficult to detect conserved co-regulated genes. We propose a cross-species bi-clustering approach which first denoises the gene expression data of each species into a data matrix. The rows of the data matrices of different species represent the same set of genes that are characterized by their expression patterns over the developmental stages of each species as columns. A novel bi-clustering method is then developed to cluster genes into subgroups by a joint sparse rank-one factorization of all the data matrices. This method decomposes a data matrix into a product of a column vector and a row vector where the column vector is a consistent indicator across the matrices (species) to identify the same gene cluster and the row vector specifies for each species the developmental stages that the clustered genes co-regulate. Efficient optimization algorithm has been developed with convergence analysis. This approach was first validated on synthetic data and compared

Two-way learning with one-way supervision for gene expression data.

PubMed

Wong, Monica H T; Mutch, David M; McNicholas, Paul D

2017-03-04

A family of parsimonious Gaussian mixture models for the biclustering of gene expression data is introduced. Biclustering is accommodated by adopting a mixture of factor analyzers model with a binary, row-stochastic factor loadings matrix. This particular form of factor loadings matrix results in a block-diagonal covariance matrix, which is a useful property in gene expression analyses, specifically in biomarker discovery scenarios where blood can potentially act as a surrogate tissue for other less accessible tissues. Prior knowledge of the factor loadings matrix is useful in this application and is reflected in the one-way supervised nature of the algorithm. Additionally, the factor loadings matrix can be assumed to be constant across all components because of the relationship desired between the various types of tissue samples. Parameter estimates are obtained through a variant of the expectation-maximization algorithm and the best-fitting model is selected using the Bayesian information criterion. The family of models is demonstrated using simulated data and two real microarray data sets. The first real data set is from a rat study that investigated the influence of diabetes on gene expression in different tissues. The second real data set is from a human transcriptomics study that focused on blood and immune tissues. The microarray data sets illustrate the biclustering family's performance in biomarker discovery involving peripheral blood as surrogate biopsy material. The simulation studies indicate that the algorithm identifies the correct biclusters, most optimally when the number of observation clusters is known. Moreover, the biclustering algorithm identified biclusters comprised of biologically meaningful data related to insulin resistance and immune function in the rat and human real data sets, respectively. Initial results using real data show that this biclustering technique provides a novel approach for biomarker discovery by enabling blood to be used

Using qualitative research to inform development of a diagnostic algorithm for UTI in children.

PubMed

de Salis, Isabel; Whiting, Penny; Sterne, Jonathan A C; Hay, Alastair D

2013-06-01

Diagnostic and prognostic algorithms can help reduce clinical uncertainty. The selection of candidate symptoms and signs to be measured in case report forms (CRFs) for potential inclusion in diagnostic algorithms needs to be comprehensive, clearly formulated and relevant for end users. To investigate whether qualitative methods could assist in designing CRFs in research developing diagnostic algorithms. Specifically, the study sought to establish whether qualitative methods could have assisted in designing the CRF for the Health Technology Association funded Diagnosis of Urinary Tract infection in Young children (DUTY) study, which will develop a diagnostic algorithm to improve recognition of urinary tract infection (UTI) in children aged <5 years presenting acutely unwell to primary care. Qualitative methods were applied using semi-structured interviews of 30 UK doctors and nurses working with young children in primary care and a Children's Emergency Department. We elicited features that clinicians believed useful in diagnosing UTI and compared these for presence or absence and terminology with the DUTY CRF. Despite much agreement between clinicians' accounts and the DUTY CRFs, we identified a small number of potentially important symptoms and signs not included in the CRF and some included items that could have been reworded to improve understanding and final data analysis. This study uniquely demonstrates the role of qualitative methods in the design and content of CRFs used for developing diagnostic (and prognostic) algorithms. Research groups developing such algorithms should consider using qualitative methods to inform the selection and wording of candidate symptoms and signs.

Bicluster Pattern of Codon Context Usages between Flavivirus and Vector Mosquito Aedes aegypti: Relevance to Infection and Transcriptional Response of Mosquito Genes

PubMed Central

Behura, Susanta K.; Severson, David W.

2014-01-01

The mosquito Aedes aegypti is the primary vector of dengue virus (DENV) infection in most of the subtropical and tropical countries. Besides DENV, yellow fever virus (YFV) is also transmitted by A. aegypti. Susceptibility of A. aegypti to West Nile virus (WNV) has also been confirmed. Although studies have indicated correlation of codon bias between flaviviridae and their animal/insect hosts, it is not clear if codon sequences have any relation to susceptibility of A. aegypti to DENV, YFV and WNV. In the current study, usages of codon context sequences (codon pairs for neighboring amino acids) of the vector (A. aegypti) genome as well as the flaviviral genomes are investigated. We used bioinformatics methods to quantify codon context bias in a genome-wide manner of A. aegypti as well as DENV, WNV and YFV sequences. Mutual information statistics was applied to perform bicluster analysis of codon context bias between vector and flaviviral sequences. Functional relevance of the bicluster pattern was inferred from published microarray data. Our study shows that codon context bias of DENV, WNV and YFV sequences varies in a bicluster manner with that of specific sets of genes of A. aegypti. Many of these mosquito genes are known to be differentially expressed in response to flaviviral infection suggesting that codon context sequences of A. aegypti and the flaviviruses may play a role in the susceptible interaction between flaviviruses and this mosquito. The bias inusages of codon context sequences likely has a functional association with susceptibility of A. aegypti to flaviviral infection. The results from this study will allow us to conduct hypothesis driven tests to examine the role of codon contexts bias in evolution of vector-virus interactions at the molecular level. PMID:24838953

ChromBiSim: Interactive chromatin biclustering using a simple approach.

PubMed

Noureen, Nighat; Zohaib, Hafiz Muhammad; Qadir, Muhammad Abdul; Fazal, Sahar

2017-10-01

Combinatorial patterns of histone modifications sketch the epigenomic locale. Specific positions of these modifications in the genome are marked by the presence of such signals. Various methods highlight such patterns on global scale hence missing the local patterns which are the actual hidden combinatorics. We present ChromBiSim, an interactive tool for mining subsets of modifications from epigenomic profiles. ChromBiSim efficiently extracts biclusters with their genomic locations. It is the very first user interface based and multiple cell type handling tool for decoding the interplay of subsets of histone modifications combinations along their genomic locations. It displays the results in the forms of charts and heat maps in accordance with saving them in files which could be used for post analysis. ChromBiSim tested on multiple cell types produced in total 803 combinatorial patterns. It could be used to highlight variations among diseased versus normal cell types of any species. ChromBiSim is available at (http://sourceforge.net/projects/chrombisim) in C-sharp and python languages. Copyright © 2017 Elsevier Inc. All rights reserved.

Propagating Qualitative Values Through Quantitative Equations

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak

1992-01-01

In most practical problems where traditional numeric simulation is not adequate, one need to reason about a system with both qualitative and quantitative equations. In this paper, we address the problem of propagating qualitative values represented as interval values through quantitative equations. Previous research has produced exponential-time algorithms for approximate solution of the problem. These may not meet the stringent requirements of many real time applications. This paper advances the state of art by producing a linear-time algorithm that can propagate a qualitative value through a class of complex quantitative equations exactly and through arbitrary algebraic expressions approximately. The algorithm was found applicable to Space Shuttle Reaction Control System model.

Cloud Model Bat Algorithm

PubMed Central

Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi

2014-01-01

Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: “bats approach their prey.” Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425

Planning Robot-Control Parameters With Qualitative Reasoning

NASA Technical Reports Server (NTRS)

Peters, Stephen F.

1993-01-01

Qualitative-reasoning planning algorithm helps to determine quantitative parameters controlling motion of robot. Algorithm regarded as performing search in multidimensional space of control parameters from starting point to goal region in which desired result of robotic manipulation achieved. Makes use of directed graph representing qualitative physical equations describing task, and interacts, at each sampling period, with history of quantitative control parameters and sensory data, to narrow search for reliable values of quantitative control parameters.

Importance of correlation between gene expression levels: application to the type I interferon signature in rheumatoid arthritis.

PubMed

Reynier, Frédéric; Petit, Fabien; Paye, Malick; Turrel-Davin, Fanny; Imbert, Pierre-Emmanuel; Hot, Arnaud; Mougin, Bruno; Miossec, Pierre

2011-01-01

The analysis of gene expression data shows that many genes display similarity in their expression profiles suggesting some co-regulation. Here, we investigated the co-expression patterns in gene expression data and proposed a correlation-based research method to stratify individuals. Using blood from rheumatoid arthritis (RA) patients, we investigated the gene expression profiles from whole blood using Affymetrix microarray technology. Co-expressed genes were analyzed by a biclustering method, followed by gene ontology analysis of the relevant biclusters. Taking the type I interferon (IFN) pathway as an example, a classification algorithm was developed from the 102 RA patients and extended to 10 systemic lupus erythematosus (SLE) patients and 100 healthy volunteers to further characterize individuals. We developed a correlation-based algorithm referred to as Classification Algorithm Based on a Biological Signature (CABS), an alternative to other approaches focused specifically on the expression levels. This algorithm applied to the expression of 35 IFN-related genes showed that the IFN signature presented a heterogeneous expression between RA, SLE and healthy controls which could reflect the level of global IFN signature activation. Moreover, the monitoring of the IFN-related genes during the anti-TNF treatment identified changes in type I IFN gene activity induced in RA patients. In conclusion, we have proposed an original method to analyze genes sharing an expression pattern and a biological function showing that the activation levels of a biological signature could be characterized by its overall state of correlation.

Interactive knowledge discovery and data mining on genomic expression data with numeric formal concept analysis.

PubMed

González-Calabozo, Jose M; Valverde-Albacete, Francisco J; Peláez-Moreno, Carmen

2016-09-15

Gene Expression Data (GED) analysis poses a great challenge to the scientific community that can be framed into the Knowledge Discovery in Databases (KDD) and Data Mining (DM) paradigm. Biclustering has emerged as the machine learning method of choice to solve this task, but its unsupervised nature makes result assessment problematic. This is often addressed by means of Gene Set Enrichment Analysis (GSEA). We put forward a framework in which GED analysis is understood as an Exploratory Data Analysis (EDA) process where we provide support for continuous human interaction with data aiming at improving the step of hypothesis abduction and assessment. We focus on the adaptation to human cognition of data interpretation and visualization of the output of EDA. First, we give a proper theoretical background to bi-clustering using Lattice Theory and provide a set of analysis tools revolving around [Formula: see text]-Formal Concept Analysis ([Formula: see text]-FCA), a lattice-theoretic unsupervised learning technique for real-valued matrices. By using different kinds of cost structures to quantify expression we obtain different sequences of hierarchical bi-clusterings for gene under- and over-expression using thresholds. Consequently, we provide a method with interleaved analysis steps and visualization devices so that the sequences of lattices for a particular experiment summarize the researcher's vision of the data. This also allows us to define measures of persistence and robustness of biclusters to assess them. Second, the resulting biclusters are used to index external omics databases-for instance, Gene Ontology (GO)-thus offering a new way of accessing publicly available resources. This provides different flavors of gene set enrichment against which to assess the biclusters, by obtaining their p-values according to the terminology of those resources. We illustrate the exploration procedure on a real data example confirming results previously published. The GED

A Novel Biclustering Approach to Association Rule Mining for Predicting HIV-1–Human Protein Interactions

PubMed Central

Mukhopadhyay, Anirban; Maulik, Ujjwal; Bandyopadhyay, Sanghamitra

2012-01-01

Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1–human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1–human interaction network. Novel HIV-1–human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed. PMID:22539940

Qualitative and quantitative evaluation of six algorithms for correcting intensity nonuniformity effects.

PubMed

Arnold, J B; Liow, J S; Schaper, K A; Stern, J J; Sled, J G; Shattuck, D W; Worth, A J; Cohen, M S; Leahy, R M; Mazziotta, J C; Rottenberg, D A

2001-05-01

The desire to correct intensity nonuniformity in magnetic resonance images has led to the proliferation of nonuniformity-correction (NUC) algorithms with different theoretical underpinnings. In order to provide end users with a rational basis for selecting a given algorithm for a specific neuroscientific application, we evaluated the performance of six NUC algorithms. We used simulated and real MRI data volumes, including six repeat scans of the same subject, in order to rank the accuracy, precision, and stability of the nonuniformity corrections. We also compared algorithms using data volumes from different subjects and different (1.5T and 3.0T) MRI scanners in order to relate differences in algorithmic performance to intersubject variability and/or differences in scanner performance. In phantom studies, the correlation of the extracted with the applied nonuniformity was highest in the transaxial (left-to-right) direction and lowest in the axial (top-to-bottom) direction. Two of the six algorithms demonstrated a high degree of stability, as measured by the iterative application of the algorithm to its corrected output. While none of the algorithms performed ideally under all circumstances, locally adaptive methods generally outperformed nonadaptive methods. Copyright 2001 Academic Press.

Analysis of the Command and Control Segment (CCS) attitude estimation algorithm

NASA Technical Reports Server (NTRS)

Stockwell, Catherine

1993-01-01

This paper categorizes the qualitative behavior of the Command and Control Segment (CCS) differential correction algorithm as applied to attitude estimation using simultaneous spin axis sun angle and Earth cord length measurements. The categories of interest are the domains of convergence, divergence, and their boundaries. Three series of plots are discussed that show the dependence of the estimation algorithm on the vehicle radius, the sun/Earth angle, and the spacecraft attitude. Common qualitative dynamics to all three series are tabulated and discussed. Out-of-limits conditions for the estimation algorithm are identified and discussed.

Biclustering Models for Two-Mode Ordinal Data.

PubMed

Matechou, Eleni; Liu, Ivy; Fernández, Daniel; Farias, Miguel; Gjelsvik, Bergljot

2016-09-01

The work in this paper introduces finite mixture models that can be used to simultaneously cluster the rows and columns of two-mode ordinal categorical response data, such as those resulting from Likert scale responses. We use the popular proportional odds parameterisation and propose models which provide insights into major patterns in the data. Model-fitting is performed using the EM algorithm, and a fuzzy allocation of rows and columns to corresponding clusters is obtained. The clustering ability of the models is evaluated in a simulation study and demonstrated using two real data sets.

QML-AiNet: An immune network approach to learning qualitative differential equation models

PubMed Central

Pang, Wei; Coghill, George M.

2015-01-01

In this paper, we explore the application of Opt-AiNet, an immune network approach for search and optimisation problems, to learning qualitative models in the form of qualitative differential equations. The Opt-AiNet algorithm is adapted to qualitative model learning problems, resulting in the proposed system QML-AiNet. The potential of QML-AiNet to address the scalability and multimodal search space issues of qualitative model learning has been investigated. More importantly, to further improve the efficiency of QML-AiNet, we also modify the mutation operator according to the features of discrete qualitative model space. Experimental results show that the performance of QML-AiNet is comparable to QML-CLONALG, a QML system using the clonal selection algorithm (CLONALG). More importantly, QML-AiNet with the modified mutation operator can significantly improve the scalability of QML and is much more efficient than QML-CLONALG. PMID:25648212

QML-AiNet: An immune network approach to learning qualitative differential equation models.

PubMed

Pang, Wei; Coghill, George M

2015-02-01

In this paper, we explore the application of Opt-AiNet, an immune network approach for search and optimisation problems, to learning qualitative models in the form of qualitative differential equations. The Opt-AiNet algorithm is adapted to qualitative model learning problems, resulting in the proposed system QML-AiNet. The potential of QML-AiNet to address the scalability and multimodal search space issues of qualitative model learning has been investigated. More importantly, to further improve the efficiency of QML-AiNet, we also modify the mutation operator according to the features of discrete qualitative model space. Experimental results show that the performance of QML-AiNet is comparable to QML-CLONALG, a QML system using the clonal selection algorithm (CLONALG). More importantly, QML-AiNet with the modified mutation operator can significantly improve the scalability of QML and is much more efficient than QML-CLONALG.

Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field

PubMed Central

Jeong, Myeong-Hun; Duckham, Matt

2015-01-01

This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes’ coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks. PMID:26343672

Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field.

PubMed

Jeong, Myeong-Hun; Duckham, Matt

2015-08-28

This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes' coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks.

Learning Qualitative Differential Equation models: a survey of algorithms and applications.

PubMed

Pang, Wei; Coghill, George M

2010-03-01

Over the last two decades, qualitative reasoning (QR) has become an important domain in Artificial Intelligence. QDE (Qualitative Differential Equation) model learning (QML), as a branch of QR, has also received an increasing amount of attention; many systems have been proposed to solve various significant problems in this field. QML has been applied to a wide range of fields, including physics, biology and medical science. In this paper, we first identify the scope of this review by distinguishing QML from other QML systems, and then review all the noteworthy QML systems within this scope. The applications of QML in several application domains are also introduced briefly. Finally, the future directions of QML are explored from different perspectives.

Learning Qualitative Differential Equation models: a survey of algorithms and applications

PubMed Central

PANG, WEI; COGHILL, GEORGE M.

2013-01-01

Over the last two decades, qualitative reasoning (QR) has become an important domain in Artificial Intelligence. QDE (Qualitative Differential Equation) model learning (QML), as a branch of QR, has also received an increasing amount of attention; many systems have been proposed to solve various significant problems in this field. QML has been applied to a wide range of fields, including physics, biology and medical science. In this paper, we first identify the scope of this review by distinguishing QML from other QML systems, and then review all the noteworthy QML systems within this scope. The applications of QML in several application domains are also introduced briefly. Finally, the future directions of QML are explored from different perspectives. PMID:23704803

Analysis of image thresholding segmentation algorithms based on swarm intelligence

NASA Astrophysics Data System (ADS)

Zhang, Yi; Lu, Kai; Gao, Yinghui; Yang, Bo

2013-03-01

Swarm intelligence-based image thresholding segmentation algorithms are playing an important role in the research field of image segmentation. In this paper, we briefly introduce the theories of four existing image segmentation algorithms based on swarm intelligence including fish swarm algorithm, artificial bee colony, bacteria foraging algorithm and particle swarm optimization. Then some image benchmarks are tested in order to show the differences of the segmentation accuracy, time consumption, convergence and robustness for Salt & Pepper noise and Gaussian noise of these four algorithms. Through these comparisons, this paper gives qualitative analyses for the performance variance of the four algorithms. The conclusions in this paper would give a significant guide for the actual image segmentation.

Algorithmic detectability threshold of the stochastic block model

NASA Astrophysics Data System (ADS)

Kawamoto, Tatsuro

2018-03-01

The assumption that the values of model parameters are known or correctly learned, i.e., the Nishimori condition, is one of the requirements for the detectability analysis of the stochastic block model in statistical inference. In practice, however, there is no example demonstrating that we can know the model parameters beforehand, and there is no guarantee that the model parameters can be learned accurately. In this study, we consider the expectation-maximization (EM) algorithm with belief propagation (BP) and derive its algorithmic detectability threshold. Our analysis is not restricted to the community structure but includes general modular structures. Because the algorithm cannot always learn the planted model parameters correctly, the algorithmic detectability threshold is qualitatively different from the one with the Nishimori condition.

Segmentation of pomegranate MR images using spatial fuzzy c-means (SFCM) algorithm

NASA Astrophysics Data System (ADS)

Moradi, Ghobad; Shamsi, Mousa; Sedaaghi, M. H.; Alsharif, M. R.

2011-10-01

Segmentation is one of the fundamental issues of image processing and machine vision. It plays a prominent role in a variety of image processing applications. In this paper, one of the most important applications of image processing in MRI segmentation of pomegranate is explored. Pomegranate is a fruit with pharmacological properties such as being anti-viral and anti-cancer. Having a high quality product in hand would be critical factor in its marketing. The internal quality of the product is comprehensively important in the sorting process. The determination of qualitative features cannot be manually made. Therefore, the segmentation of the internal structures of the fruit needs to be performed as accurately as possible in presence of noise. Fuzzy c-means (FCM) algorithm is noise-sensitive and pixels with noise are classified inversely. As a solution, in this paper, the spatial FCM algorithm in pomegranate MR images' segmentation is proposed. The algorithm is performed with setting the spatial neighborhood information in FCM and modification of fuzzy membership function for each class. The segmentation algorithm results on the original and the corrupted Pomegranate MR images by Gaussian, Salt Pepper and Speckle noises show that the SFCM algorithm operates much more significantly than FCM algorithm. Also, after diverse steps of qualitative and quantitative analysis, we have concluded that the SFCM algorithm with 5×5 window size is better than the other windows.

Eye-Tracking Verification of the Strategy Used to Analyse Algorithms Expressed in a Flowchart and Pseudocode

ERIC Educational Resources Information Center

Andrzejewska, Magdalena; Stolinska, Anna; Blasiak, Wladyslaw; Peczkowski, Pawel; Rosiek, Roman; Rozek, Bozena; Sajka, Miroslawa; Wcislo, Dariusz

2016-01-01

The results of qualitative and quantitative investigations conducted with individuals who learned algorithms in school are presented in this article. In these investigations, eye-tracking technology was used to follow the process of solving algorithmic problems. The algorithmic problems were presented in two comparable variants: in a pseudocode…

Selection method of terrain matching area for TERCOM algorithm

NASA Astrophysics Data System (ADS)

Zhang, Qieqie; Zhao, Long

2017-10-01

The performance of terrain aided navigation is closely related to the selection of terrain matching area. The different matching algorithms have different adaptability to terrain. This paper mainly studies the adaptability to terrain of TERCOM algorithm, analyze the relation between terrain feature and terrain characteristic parameters by qualitative and quantitative methods, and then research the relation between matching probability and terrain characteristic parameters by the Monte Carlo method. After that, we propose a selection method of terrain matching area for TERCOM algorithm, and verify the method correctness with real terrain data by simulation experiment. Experimental results show that the matching area obtained by the method in this paper has the good navigation performance and the matching probability of TERCOM algorithm is great than 90%

Speckle-reduction algorithm for ultrasound images in complex wavelet domain using genetic algorithm-based mixture model.

PubMed

Uddin, Muhammad Shahin; Tahtali, Murat; Lambert, Andrew J; Pickering, Mark R; Marchese, Margaret; Stuart, Iain

2016-05-20

Compared with other medical-imaging modalities, ultrasound (US) imaging is a valuable way to examine the body's internal organs, and two-dimensional (2D) imaging is currently the most common technique used in clinical diagnoses. Conventional 2D US imaging systems are highly flexible cost-effective imaging tools that permit operators to observe and record images of a large variety of thin anatomical sections in real time. Recently, 3D US imaging has also been gaining popularity due to its considerable advantages over 2D US imaging. It reduces dependency on the operator and provides better qualitative and quantitative information for an effective diagnosis. Furthermore, it provides a 3D view, which allows the observation of volume information. The major shortcoming of any type of US imaging is the presence of speckle noise. Hence, speckle reduction is vital in providing a better clinical diagnosis. The key objective of any speckle-reduction algorithm is to attain a speckle-free image while preserving the important anatomical features. In this paper we introduce a nonlinear multi-scale complex wavelet-diffusion based algorithm for speckle reduction and sharp-edge preservation of 2D and 3D US images. In the proposed method we use a Rayleigh and Maxwell-mixture model for 2D and 3D US images, respectively, where a genetic algorithm is used in combination with an expectation maximization method to estimate mixture parameters. Experimental results using both 2D and 3D synthetic, physical phantom, and clinical data demonstrate that our proposed algorithm significantly reduces speckle noise while preserving sharp edges without discernible distortions. The proposed approach performs better than the state-of-the-art approaches in both qualitative and quantitative measures.

Research on AHP decision algorithms based on BP algorithm

NASA Astrophysics Data System (ADS)

Ma, Ning; Guan, Jianhe

2017-10-01

Decision making is the thinking activity that people choose or judge, and scientific decision-making has always been a hot issue in the field of research. Analytic Hierarchy Process (AHP) is a simple and practical multi-criteria and multi-objective decision-making method that combines quantitative and qualitative and can show and calculate the subjective judgment in digital form. In the process of decision analysis using AHP method, the rationality of the two-dimensional judgment matrix has a great influence on the decision result. However, in dealing with the real problem, the judgment matrix produced by the two-dimensional comparison is often inconsistent, that is, it does not meet the consistency requirements. BP neural network algorithm is an adaptive nonlinear dynamic system. It has powerful collective computing ability and learning ability. It can perfect the data by constantly modifying the weights and thresholds of the network to achieve the goal of minimizing the mean square error. In this paper, the BP algorithm is used to deal with the consistency of the two-dimensional judgment matrix of the AHP.

Nondestructive evaluation of degradation in papaya fruit using intensity based algorithms

NASA Astrophysics Data System (ADS)

Kumari, Shubhashri; Nirala, Anil Kumar

2018-05-01

In the proposed work degradation in Papaya fruit has been evaluated nondestructively using laser biospeckle technique. The biospeckle activity inside the fruit has been evaluated qualitatively and quantitatively during its maturity to degradation stage using intensity based algorithms. Co-occurrence matrix (COM) has been used for qualitative analysis whereas Inertia Moment (IM), Absolute value Difference (AVD) and Autocovariance methods have been used for quantitative analysis. The biospeckle activity has been found to first increase and then decrease during study period of five days. In addition Granulometric size distribution (GSD) has also been used for the first time for the evaluation of degradation of the papaya. It is concluded that the degradation process of papaya fruit can be evaluated nondestructively using all the mentioned algorithms.

An experimental comparison of online object-tracking algorithms

NASA Astrophysics Data System (ADS)

Wang, Qing; Chen, Feng; Xu, Wenli; Yang, Ming-Hsuan

2011-09-01

This paper reviews and evaluates several state-of-the-art online object tracking algorithms. Notwithstanding decades of efforts, object tracking remains a challenging problem due to factors such as illumination, pose, scale, deformation, motion blur, noise, and occlusion. To account for appearance change, most recent tracking algorithms focus on robust object representations and effective state prediction. In this paper, we analyze the components of each tracking method and identify their key roles in dealing with specific challenges, thereby shedding light on how to choose and design algorithms for different situations. We compare state-of-the-art online tracking methods including the IVT,1 VRT,2 FragT,3 BoostT,4 SemiT,5 BeSemiT,6 L1T,7 MILT,8 VTD9 and TLD10 algorithms on numerous challenging sequences, and evaluate them with different performance metrics. The qualitative and quantitative comparative results demonstrate the strength and weakness of these algorithms.

Anatomical relationships between serotonin 5-HT2A and dopamine D2 receptors in living human brain.

PubMed

Ishii, Tatsuya; Kimura, Yasuyuki; Ichise, Masanori; Takahata, Keisuke; Kitamura, Soichiro; Moriguchi, Sho; Kubota, Manabu; Zhang, Ming-Rong; Yamada, Makiko; Higuchi, Makoto; Okubo, Yoshinori; Suhara, Tetsuya

2017-01-01

Seven healthy volunteers underwent PET scans with [18F]altanserin and [11C]FLB 457 for 5-HT2A and D2 receptors, respectively. As a measure of receptor density, a binding potential (BP) was calculated from PET data for 76 cerebral cortical regions. A correlation matrix was calculated between the binding potentials of [18F]altanserin and [11C]FLB 457 for those regions. The regional relationships were investigated using a bicluster analysis of the correlation matrix with an iterative signature algorithm. We identified two clusters of regions. The first cluster identified a distinct profile of correlation coefficients between 5-HT2A and D2 receptors, with the former in regions related to sensorimotor integration (supplementary motor area, superior parietal gyrus, and paracentral lobule) and the latter in most cortical regions. The second cluster identified another distinct profile of correlation coefficients between 5-HT2A receptors in the bilateral hippocampi and D2 receptors in most cortical regions. The observation of two distinct clusters in the correlation matrix suggests regional interactions between 5-HT2A and D2 receptors in sensorimotor integration and hippocampal function. A bicluster analysis of the correlation matrix of these neuroreceptors may be beneficial in understanding molecular networks in the human brain.

Centrifugal compressor fault diagnosis based on qualitative simulation and thermal parameters

NASA Astrophysics Data System (ADS)

Lu, Yunsong; Wang, Fuli; Jia, Mingxing; Qi, Yuanchen

2016-12-01

This paper concerns fault diagnosis of centrifugal compressor based on thermal parameters. An improved qualitative simulation (QSIM) based fault diagnosis method is proposed to diagnose the faults of centrifugal compressor in a gas-steam combined-cycle power plant (CCPP). The qualitative models under normal and two faulty conditions have been built through the analysis of the principle of centrifugal compressor. To solve the problem of qualitative description of the observations of system variables, a qualitative trend extraction algorithm is applied to extract the trends of the observations. For qualitative states matching, a sliding window based matching strategy which consists of variables operating ranges constraints and qualitative constraints is proposed. The matching results are used to determine which QSIM model is more consistent with the running state of system. The correct diagnosis of two typical faults: seal leakage and valve stuck in the centrifugal compressor has validated the targeted performance of the proposed method, showing the advantages of fault roots containing in thermal parameters.

Research on Ratio of Dosage of Drugs in Traditional Chinese Prescriptions by Data Mining.

PubMed

Yu, Xing-Wen; Gong, Qing-Yue; Hu, Kong-Fa; Mao, Wen-Jing; Zhang, Wei-Ming

2017-01-01

Maximizing the effectiveness of prescriptions and minimizing adverse effects of drugs is a key component of the health care of patients. In the practice of traditional Chinese medicine (TCM), it is important to provide clinicians a reference for dosing of prescribed drugs. The traditional Cheng-Church biclustering algorithm (CC) is optimized and the data of TCM prescription dose is analyzed by using the optimization algorithm. Based on an analysis of 212 prescriptions related to TCM treatment of kidney diseases, the study generated 87 prescription dose quantum matrices and each sub-matrix represents the referential value of the doses of drugs in different recipes. The optimized CC algorithm can effectively eliminate the interference of zero in the original dose matrix of TCM prescriptions and avoid zero appearing in output sub-matrix. This results in the ability to effectively analyze the reference value of drugs in different prescriptions related to kidney diseases, so as to provide valuable reference for clinicians to use drugs rationally.

Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography.

PubMed

Liu, Li; Gao, Simon S; Bailey, Steven T; Huang, David; Li, Dengwang; Jia, Yali

2015-09-01

Optical coherence tomography angiography has recently been used to visualize choroidal neovascularization (CNV) in participants with age-related macular degeneration. Identification and quantification of CNV area is important clinically for disease assessment. An automated algorithm for CNV area detection is presented in this article. It relies on denoising and a saliency detection model to overcome issues such as projection artifacts and the heterogeneity of CNV. Qualitative and quantitative evaluations were performed on scans of 7 participants. Results from the algorithm agreed well with manual delineation of CNV area.

Algorithm integration using ADL (Algorithm Development Library) for improving CrIMSS EDR science product quality

NASA Astrophysics Data System (ADS)

Das, B.; Wilson, M.; Divakarla, M. G.; Chen, W.; Barnet, C.; Wolf, W.

2013-05-01

Algorithm Development Library (ADL) is a framework that mimics the operational system IDPS (Interface Data Processing Segment) that is currently being used to process data from instruments aboard Suomi National Polar-orbiting Partnership (S-NPP) satellite. The satellite was launched successfully in October 2011. The Cross-track Infrared and Microwave Sounder Suite (CrIMSS) consists of the Advanced Technology Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) instruments that are on-board of S-NPP. These instruments will also be on-board of JPSS (Joint Polar Satellite System) that will be launched in early 2017. The primary products of the CrIMSS Environmental Data Record (EDR) include global atmospheric vertical temperature, moisture, and pressure profiles (AVTP, AVMP and AVPP) and Ozone IP (Intermediate Product from CrIS radiances). Several algorithm updates have recently been proposed by CrIMSS scientists that include fixes to the handling of forward modeling errors, a more conservative identification of clear scenes, indexing corrections for daytime products, and relaxed constraints between surface temperature and air temperature for daytime land scenes. We have integrated these improvements into the ADL framework. This work compares the results from ADL emulation of future IDPS system incorporating all the suggested algorithm updates with the current official processing results by qualitative and quantitative evaluations. The results prove these algorithm updates improve science product quality.

Qualitative analysis of pure and adulterated canola oil via SIMCA

NASA Astrophysics Data System (ADS)

Basri, Katrul Nadia; Khir, Mohd Fared Abdul; Rani, Rozina Abdul; Sharif, Zaiton; Rusop, M.; Zoolfakar, Ahmad Sabirin

2018-05-01

This paper demonstrates the utilization of near infrared (NIR) spectroscopy to classify pure and adulterated sample of canola oil. Soft Independent Modeling Class Analogies (SIMCA) algorithm was implemented to discriminate the samples to its classes. Spectral data obtained was divided using Kennard Stone algorithm into training and validation dataset by a fixed ratio of 7:3. The model accuracy obtained based on the model built is 0.99 whereas the sensitivity and precision are 0.92 and 1.00. The result showed the classification model is robust to perform qualitative analysis of canola oil for future application.

ICT Teachers' Acceptance of "Scratch" as Algorithm Visualization Software

ERIC Educational Resources Information Center

Saltan, Fatih; Kara, Mehmet

2016-01-01

This study aims to investigate the acceptance of ICT teachers pertaining to the use of Scratch as an Algorithm Visualization (AV) software in terms of perceived ease of use and perceived usefulness. An embedded mixed method research design was used in the study, in which qualitative data were embedded in quantitative ones and used to explain the…

Probabilistic self-localisation on a qualitative map based on occlusions

NASA Astrophysics Data System (ADS)

Santos, Paulo E.; Martins, Murilo F.; Fenelon, Valquiria; Cozman, Fabio G.; Dee, Hannah M.

2016-09-01

Spatial knowledge plays an essential role in human reasoning, permitting tasks such as locating objects in the world (including oneself), reasoning about everyday actions and describing perceptual information. This is also the case in the field of mobile robotics, where one of the most basic (and essential) tasks is the autonomous determination of the pose of a robot with respect to a map, given its perception of the environment. This is the problem of robot self-localisation (or simply the localisation problem). This paper presents a probabilistic algorithm for robot self-localisation that is based on a topological map constructed from the observation of spatial occlusion. Distinct locations on the map are defined by means of a classical formalism for qualitative spatial reasoning, whose base definitions are closer to the human categorisation of space than traditional, numerical, localisation procedures. The approach herein proposed was systematically evaluated through experiments using a mobile robot equipped with a RGB-D sensor. The results obtained show that the localisation algorithm is successful in locating the robot in qualitatively distinct regions.

Using Computational Text Classification for Qualitative Research and Evaluation in Extension

ERIC Educational Resources Information Center

Smith, Justin G.; Tissing, Reid

2018-01-01

This article introduces a process for computational text classification that can be used in a variety of qualitative research and evaluation settings. The process leverages supervised machine learning based on an implementation of a multinomial Bayesian classifier. Applied to a community of inquiry framework, the algorithm was used to identify…

A tuning algorithm for model predictive controllers based on genetic algorithms and fuzzy decision making.

PubMed

van der Lee, J H; Svrcek, W Y; Young, B R

2008-01-01

Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.

Qualitative Event-Based Diagnosis: Case Study on the Second International Diagnostic Competition

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil

2010-01-01

We describe a diagnosis algorithm entered into the Second International Diagnostic Competition. We focus on the first diagnostic problem of the industrial track of the competition in which a diagnosis algorithm must detect, isolate, and identify faults in an electrical power distribution testbed and provide corresponding recovery recommendations. The diagnosis algorithm embodies a model-based approach, centered around qualitative event-based fault isolation. Faults produce deviations in measured values from model-predicted values. The sequence of these deviations is matched to those predicted by the model in order to isolate faults. We augment this approach with model-based fault identification, which determines fault parameters and helps to further isolate faults. We describe the diagnosis approach, provide diagnosis results from running the algorithm on provided example scenarios, and discuss the issues faced, and lessons learned, from implementing the approach

Algorithmic-Reducibility = Renormalization-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') Replacing CRUTCHES!!!: Gauss Modular/Clock-Arithmetic Congruences = Signal X Noise PRODUCTS..

NASA Astrophysics Data System (ADS)

Siegel, J.; Siegel, Edward Carl-Ludwig

2011-03-01

Cook-Levin computational-"complexity"(C-C) algorithmic-equivalence reduction-theorem reducibility equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited with Gauss modular/clock-arithmetic/model congruences = signal X noise PRODUCT reinterpretation. Siegel-Baez FUZZYICS=CATEGORYICS(SON of ``TRIZ''): Category-Semantics(C-S) tabular list-format truth-table matrix analytics predicts and implements "noise"-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics(1987)]-Sipser[Intro. Theory Computation(1997) algorithmic C-C: "NIT-picking" to optimize optimization-problems optimally(OOPO). Versus iso-"noise" power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, this "NIT-picking" is "noise" power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-"science" algorithmic C-C models: Turing-machine, finite-state-models/automata, are identified as early-days once-workable but NOW ONLY LIMITING CRUTCHES IMPEDING latter-days new-insights!!!

A Taylor weak-statement algorithm for hyperbolic conservation laws

NASA Technical Reports Server (NTRS)

Baker, A. J.; Kim, J. W.

1987-01-01

Finite element analysis, applied to computational fluid dynamics (CFD) problem classes, presents a formal procedure for establishing the ingredients of a discrete approximation numerical solution algorithm. A classical Galerkin weak-statement formulation, formed on a Taylor series extension of the conservation law system, is developed herein that embeds a set of parameters eligible for constraint according to specification of suitable norms. The derived family of Taylor weak statements is shown to contain, as special cases, over one dozen independently derived CFD algorithms published over the past several decades for the high speed flow problem class. A theoretical analysis is completed that facilitates direct qualitative comparisons. Numerical results for definitive linear and nonlinear test problems permit direct quantitative performance comparisons.

Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

PubMed

Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

2012-08-29

Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential

Qualitative reasoning for biological network inference from systematic perturbation experiments.

PubMed

Badaloni, Silvana; Di Camillo, Barbara; Sambo, Francesco

2012-01-01

The systematic perturbation of the components of a biological system has been proven among the most informative experimental setups for the identification of causal relations between the components. In this paper, we present Systematic Perturbation-Qualitative Reasoning (SPQR), a novel Qualitative Reasoning approach to automate the interpretation of the results of systematic perturbation experiments. Our method is based on a qualitative abstraction of the experimental data: for each perturbation experiment, measured values of the observed variables are modeled as lower, equal or higher than the measurements in the wild type condition, when no perturbation is applied. The algorithm exploits a set of IF-THEN rules to infer causal relations between the variables, analyzing the patterns of propagation of the perturbation signals through the biological network, and is specifically designed to minimize the rate of false positives among the inferred relations. Tested on both simulated and real perturbation data, SPQR indeed exhibits a significantly higher precision than the state of the art.

Looking at Algorithm Visualization through the Eyes of Pre-Service ICT Teachers

ERIC Educational Resources Information Center

Saltan, Fatih

2016-01-01

The study investigated pre-service ICT teachers' perceptions of algorithm visualization (AV) with regard to appropriateness of teaching levels and contribution to learning and motivation. In order to achieve this aim, a qualitative case study was carried out. The participants consisted of 218 pre-service ICT teachers from four different…

The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms

NASA Technical Reports Server (NTRS)

Brewin, Robert J.W.; Sathyendranath, Shubha; Muller, Dagmar; Brockmann, Carsten; Deschamps, Pierre-Yves; Devred, Emmanuel; Doerffer, Roland; Fomferra, Norman; Franz, Bryan; Grant, Mike;

Adaptive Grouping Cloud Model Shuffled Frog Leaping Algorithm for Solving Continuous Optimization Problems

PubMed Central

Liu, Haorui; Yi, Fengyan; Yang, Heli

2016-01-01

The shuffled frog leaping algorithm (SFLA) easily falls into local optimum when it solves multioptimum function optimization problem, which impacts the accuracy and convergence speed. Therefore this paper presents grouped SFLA for solving continuous optimization problems combined with the excellent characteristics of cloud model transformation between qualitative and quantitative research. The algorithm divides the definition domain into several groups and gives each group a set of frogs. Frogs of each region search in their memeplex, and in the search process the algorithm uses the “elite strategy” to update the location information of existing elite frogs through cloud model algorithm. This method narrows the searching space and it can effectively improve the situation of a local optimum; thus convergence speed and accuracy can be significantly improved. The results of computer simulation confirm this conclusion. PMID:26819584

A Graph-Algorithmic Approach for the Study of Metastability in Markov Chains

NASA Astrophysics Data System (ADS)

Gan, Tingyue; Cameron, Maria

2017-06-01

Large continuous-time Markov chains with exponentially small transition rates arise in modeling complex systems in physics, chemistry, and biology. We propose a constructive graph-algorithmic approach to determine the sequence of critical timescales at which the qualitative behavior of a given Markov chain changes, and give an effective description of the dynamics on each of them. This approach is valid for both time-reversible and time-irreversible Markov processes, with or without symmetry. Central to this approach are two graph algorithms, Algorithm 1 and Algorithm 2, for obtaining the sequences of the critical timescales and the hierarchies of Typical Transition Graphs or T-graphs indicating the most likely transitions in the system without and with symmetry, respectively. The sequence of critical timescales includes the subsequence of the reciprocals of the real parts of eigenvalues. Under a certain assumption, we prove sharp asymptotic estimates for eigenvalues (including pre-factors) and show how one can extract them from the output of Algorithm 1. We discuss the relationship between Algorithms 1 and 2 and explain how one needs to interpret the output of Algorithm 1 if it is applied in the case with symmetry instead of Algorithm 2. Finally, we analyze an example motivated by R. D. Astumian's model of the dynamics of kinesin, a molecular motor, by means of Algorithm 2.

A comparison of force control algorithms for robots in contact with flexible environments

NASA Technical Reports Server (NTRS)

Wilfinger, Lee S.

1992-01-01

In order to perform useful tasks, the robot end-effector must come into contact with its environment. For such tasks, force feedback is frequently used to control the interaction forces. Control of these forces is complicated by the fact that the flexibility of the environment affects the stability of the force control algorithm. Because of the wide variety of different materials present in everyday environments, it is necessary to gain an understanding of how environmental flexibility affects the stability of force control algorithms. This report presents the theory and experimental results of two force control algorithms: Position Accommodation Control and Direct Force Servoing. The implementation of each of these algorithms on a two-arm robotic test bed located in the Center for Intelligent Robotic Systems for Space Exploration (CIRSSE) is discussed in detail. The behavior of each algorithm when contacting materials of different flexibility is experimentally determined. In addition, several robustness improvements to the Direct Force Servoing algorithm are suggested and experimentally verified. Finally, a qualitative comparison of the force control algorithms is provided, along with a description of a general tuning process for each control method.

Cook-Levin Theorem Algorithmic-Reducibility/Completeness = Wilson Renormalization-(Semi)-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') REPLACING CRUTCHES!!!: Models: Turing-machine, finite-state-models, finite-automata

NASA Astrophysics Data System (ADS)

Young, Frederic; Siegel, Edward

Cook-Levin theorem theorem algorithmic computational-complexity(C-C) algorithmic-equivalence reducibility/completeness equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited via Siegel FUZZYICS =CATEGORYICS = ANALOGYICS =PRAGMATYICS/CATEGORY-SEMANTICS ONTOLOGY COGNITION ANALYTICS-Aristotle ``square-of-opposition'' tabular list-format truth-table matrix analytics predicts and implements ''noise''-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics (1987)]-Sipser[Intro.Thy. Computation(`97)] algorithmic C-C: ''NIT-picking''(!!!), to optimize optimization-problems optimally(OOPO). Versus iso-''noise'' power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, ''NIT-picking'' is ''noise'' power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-''science''/SEANCE algorithmic C-C models: Turing-machine, finite-state-models, finite-automata,..., discrete-maths graph-theory equivalence to physics Feynman-diagrams are identified as early-days once-workable valid but limiting IMPEDING CRUTCHES(!!!), ONLY IMPEDE latter-days new-insights!!!

An Example-Based Super-Resolution Algorithm for Selfie Images

PubMed Central

William, Jino Hans; Venkateswaran, N.; Narayanan, Srinath; Ramachandran, Sandeep

2016-01-01

A selfie is typically a self-portrait captured using the front camera of a smartphone. Most state-of-the-art smartphones are equipped with a high-resolution (HR) rear camera and a low-resolution (LR) front camera. As selfies are captured by front camera with limited pixel resolution, the fine details in it are explicitly missed. This paper aims to improve the resolution of selfies by exploiting the fine details in HR images captured by rear camera using an example-based super-resolution (SR) algorithm. HR images captured by rear camera carry significant fine details and are used as an exemplar to train an optimal matrix-value regression (MVR) operator. The MVR operator serves as an image-pair priori which learns the correspondence between the LR-HR patch-pairs and is effectively used to super-resolve LR selfie images. The proposed MVR algorithm avoids vectorization of image patch-pairs and preserves image-level information during both learning and recovering process. The proposed algorithm is evaluated for its efficiency and effectiveness both qualitatively and quantitatively with other state-of-the-art SR algorithms. The results validate that the proposed algorithm is efficient as it requires less than 3 seconds to super-resolve LR selfie and is effective as it preserves sharp details without introducing any counterfeit fine details. PMID:27064500

Pressure ulcer prevention algorithm content validation: a mixed-methods, quantitative study.

PubMed

van Rijswijk, Lia; Beitz, Janice M

2015-04-01

Translating pressure ulcer prevention (PUP) evidence-based recommendations into practice remains challenging for a variety of reasons, including the perceived quality, validity, and usability of the research or the guideline itself. Following the development and face validation testing of an evidence-based PUP algorithm, additional stakeholder input and testing were needed. Using convenience sampling methods, wound care experts attending a national wound care conference and a regional wound ostomy continence nursing (WOCN) conference and/or graduates of a WOCN program were invited to participate in an Internal Review Board-approved, mixed-methods quantitative survey with qualitative components to examine algorithm content validity. After participants provided written informed consent, demographic variables were collected and participants were asked to comment on and rate the relevance and appropriateness of each of the 26 algorithm decision points/steps using standard content validation study procedures. All responses were anonymous. Descriptive summary statistics, mean relevance/appropriateness scores, and the content validity index (CVI) were calculated. Qualitative comments were transcribed and thematically analyzed. Of the 553 wound care experts invited, 79 (average age 52.9 years, SD 10.1; range 23-73) consented to participate and completed the study (a response rate of 14%). Most (67, 85%) were female, registered (49, 62%) or advanced practice (12, 15%) nurses, and had > 10 years of health care experience (88, 92%). Other health disciplines included medical doctors, physical therapists, nurse practitioners, and certified nurse specialists. Almost all had received formal wound care education (75, 95%). On a Likert-type scale of 1 (not relevant/appropriate) to 4 (very relevant and appropriate), the average score for the entire algorithm/all decision points (N = 1,912) was 3.72 with an overall CVI of 0.94 (out of 1). The only decision point/step recommendation

Dynamic Transition and Resonance in Coupled Oscillators Under Symmetry-Breaking Fields

NASA Astrophysics Data System (ADS)

Choi, J.; Choi, M. Y.; Chung, M. S.; Yoon, B.-G.

2013-06-01

We investigate numerically the dynamic properties of a system of globally coupled oscillators driven by periodic symmetry-breaking fields in the presence of noise. The phase distribution of the oscillators is computed and a dynamic transition is disclosed. It is further found that the stochastic resonance is closely related to the behavior of the dynamic order parameter, which is in turn explained by the formation of a bi-cluster in the system. Here noise tends to symmetrize the motion of the oscillators, facilitating the bi-cluster formation. The observed resonance appears to be of the same class as the resonance present in the two-dimensional Ising model under oscillating fields.

Implementing and validating of pan-sharpening algorithms in open-source software

NASA Astrophysics Data System (ADS)

Pesántez-Cobos, Paúl; Cánovas-García, Fulgencio; Alonso-Sarría, Francisco

2017-10-01

Several approaches have been used in remote sensing to integrate images with different spectral and spatial resolutions in order to obtain fused enhanced images. The objective of this research is three-fold. To implement in R three image fusion techniques (High Pass Filter, Principal Component Analysis and Gram-Schmidt); to apply these techniques to merging multispectral and panchromatic images from five different images with different spatial resolutions; finally, to evaluate the results using the universal image quality index (Q index) and the ERGAS index. As regards qualitative analysis, Landsat-7 and Landsat-8 show greater colour distortion with the three pansharpening methods, although the results for the other images were better. Q index revealed that HPF fusion performs better for the QuickBird, IKONOS and Landsat-7 images, followed by GS fusion; whereas in the case of Landsat-8 and Natmur-08 images, the results were more even. Regarding the ERGAS spatial index, the ACP algorithm performed better for the QuickBird, IKONOS, Landsat-7 and Natmur-08 images, followed closely by the GS algorithm. Only for the Landsat-8 image did, the GS fusion present the best result. In the evaluation of spectral components, HPF results tended to be better and ACP results worse, the opposite was the case with the spatial components. Better quantitative results are obtained in Landsat-7 and Landsat-8 images with the three fusion methods than with the QuickBird, IKONOS and Natmur-08 images. This contrasts with the qualitative evaluation reflecting the importance of splitting the two evaluation approaches (qualitative and quantitative). Significant disagreement may arise when different methodologies are used to asses the quality of an image fusion. Moreover, it is not possible to designate, a priori, a given algorithm as the best, not only because of the different characteristics of the sensors, but also because of the different atmospherics conditions or peculiarities of the

Algorithm refinement for stochastic partial differential equations: II. Correlated systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexander, Francis J.; Garcia, Alejandro L.; Tartakovsky, Daniel M.

2005-08-10

We analyze a hybrid particle/continuum algorithm for a hydrodynamic system with long ranged correlations. Specifically, we consider the so-called train model for viscous transport in gases, which is based on a generalization of the random walk process for the diffusion of momentum. This discrete model is coupled with its continuous counterpart, given by a pair of stochastic partial differential equations. At the interface between the particle and continuum computations the coupling is by flux matching, giving exact mass and momentum conservation. This methodology is an extension of our stochastic Algorithm Refinement (AR) hybrid for simple diffusion [F. Alexander, A. Garcia,more » D. Tartakovsky, Algorithm refinement for stochastic partial differential equations: I. Linear diffusion, J. Comput. Phys. 182 (2002) 47-66]. Results from a variety of numerical experiments are presented for steady-state scenarios. In all cases the mean and variance of density and velocity are captured correctly by the stochastic hybrid algorithm. For a non-stochastic version (i.e., using only deterministic continuum fluxes) the long-range correlations of velocity fluctuations are qualitatively preserved but at reduced magnitude.« less

Development of an Algorithm for Satellite Remote Sensing of Sea and Lake Ice

NASA Astrophysics Data System (ADS)

Dorofy, Peter T.

Satellite remote sensing of snow and ice has a long history. The traditional method for many snow and ice detection algorithms has been the use of the Normalized Difference Snow Index (NDSI). This manuscript is composed of two parts. Chapter 1, Development of a Mid-Infrared Sea and Lake Ice Index (MISI) using the GOES Imager, discusses the desirability, development, and implementation of alternative index for an ice detection algorithm, application of the algorithm to the detection of lake ice, and qualitative validation against other ice mapping products; such as, the Ice Mapping System (IMS). Chapter 2, Application of Dynamic Threshold in a Lake Ice Detection Algorithm, continues with a discussion of the development of a method that considers the variable viewing and illumination geometry of observations throughout the day. The method is an alternative to Bidirectional Reflectance Distribution Function (BRDF) models. Evaluation of the performance of the algorithm is introduced by aggregating classified pixels within geometrical boundaries designated by IMS and obtaining sensitivity and specificity statistical measures.

Planning the FUSE Mission Using the SOVA Algorithm

NASA Technical Reports Server (NTRS)

Lanzi, James; Heatwole, Scott; Ward, Philip R.; Civeit, Thomas; Calvani, Humberto; Kruk, Jeffrey W.; Suchkov, Anatoly

2011-01-01

Three documents discuss the Sustainable Objective Valuation and Attainability (SOVA) algorithm and software as used to plan tasks (principally, scientific observations and associated maneuvers) for the Far Ultraviolet Spectroscopic Explorer (FUSE) satellite. SOVA is a means of managing risk in a complex system, based on a concept of computing the expected return value of a candidate ordered set of tasks as a product of pre-assigned task values and assessments of attainability made against qualitatively defined strategic objectives. For the FUSE mission, SOVA autonomously assembles a week-long schedule of target observations and associated maneuvers so as to maximize the expected scientific return value while keeping the satellite stable, managing the angular momentum of spacecraft attitude- control reaction wheels, and striving for other strategic objectives. A six-degree-of-freedom model of the spacecraft is used in simulating the tasks, and the attainability of a task is calculated at each step by use of strategic objectives as defined by use of fuzzy inference systems. SOVA utilizes a variant of a graph-search algorithm known as the A* search algorithm to assemble the tasks into a week-long target schedule, using the expected scientific return value to guide the search.

Computational Algorithmization: Limitations in Problem Solving Skills in Computational Sciences Majors at University of Oriente

ERIC Educational Resources Information Center

Castillo, Antonio S.; Berenguer, Isabel A.; Sánchez, Alexander G.; Álvarez, Tomás R. R.

2017-01-01

This paper analyzes the results of a diagnostic study carried out with second year students of the computational sciences majors at University of Oriente, Cuba, to determine the limitations that they present in computational algorithmization. An exploratory research was developed using quantitative and qualitative methods. The results allowed…

Development and validation of an online interactive, multimedia wound care algorithms program.

PubMed

Beitz, Janice M; van Rijswijk, Lia

2012-01-01

To provide education based on evidence-based and validated wound care algorithms we designed and implemented an interactive, Web-based learning program for teaching wound care. A mixed methods quantitative pilot study design with qualitative components was used to test and ascertain the ease of use, validity, and reliability of the online program. A convenience sample of 56 RN wound experts (formally educated, certified in wound care, or both) participated. The interactive, online program consists of a user introduction, interactive assessment of 15 acute and chronic wound photos, user feedback about the percentage correct, partially correct, or incorrect algorithm and dressing choices and a user survey. After giving consent, participants accessed the online program, provided answers to the demographic survey, and completed the assessment module and photographic test, along with a posttest survey. The construct validity of the online interactive program was strong. Eighty-five percent (85%) of algorithm and 87% of dressing choices were fully correct even though some programming design issues were identified. Online study results were consistently better than previously conducted comparable paper-pencil study results. Using a 5-point Likert-type scale, participants rated the program's value and ease of use as 3.88 (valuable to very valuable) and 3.97 (easy to very easy), respectively. Similarly the research process was described qualitatively as "enjoyable" and "exciting." This digital program was well received indicating its "perceived benefits" for nonexpert users, which may help reduce barriers to implementing safe, evidence-based care. Ongoing research using larger sample sizes may help refine the program or algorithms while identifying clinician educational needs. Initial design imperfections and programming problems identified also underscored the importance of testing all paper and Web-based programs designed to educate health care professionals or guide

Pruning Rogue Taxa Improves Phylogenetic Accuracy: An Efficient Algorithm and Webservice

PubMed Central

Aberer, Andre J.; Krompass, Denis; Stamatakis, Alexandros

2013-01-01

Abstract The presence of rogue taxa (rogues) in a set of trees can frequently have a negative impact on the results of a bootstrap analysis (e.g., the overall support in consensus trees). We introduce an efficient graph-based algorithm for rogue taxon identification as well as an interactive webservice implementing this algorithm. Compared with our previous method, the new algorithm is up to 4 orders of magnitude faster, while returning qualitatively identical results. Because of this significant improvement in scalability, the new algorithm can now identify substantially more complex and compute-intensive rogue taxon constellations. On a large and diverse collection of real-world data sets, we show that our method yields better supported reduced/pruned consensus trees than any competing rogue taxon identification method. Using the parallel version of our open-source code, we successfully identified rogue taxa in a set of 100 trees with 116 334 taxa each. For simulated data sets, we show that when removing/pruning rogue taxa with our method from a tree set, we consistently obtain bootstrap consensus trees as well as maximum-likelihood trees that are topologically closer to the respective true trees. PMID:22962004

Pruning rogue taxa improves phylogenetic accuracy: an efficient algorithm and webservice.

PubMed

Aberer, Andre J; Krompass, Denis; Stamatakis, Alexandros

2013-01-01

The presence of rogue taxa (rogues) in a set of trees can frequently have a negative impact on the results of a bootstrap analysis (e.g., the overall support in consensus trees). We introduce an efficient graph-based algorithm for rogue taxon identification as well as an interactive webservice implementing this algorithm. Compared with our previous method, the new algorithm is up to 4 orders of magnitude faster, while returning qualitatively identical results. Because of this significant improvement in scalability, the new algorithm can now identify substantially more complex and compute-intensive rogue taxon constellations. On a large and diverse collection of real-world data sets, we show that our method yields better supported reduced/pruned consensus trees than any competing rogue taxon identification method. Using the parallel version of our open-source code, we successfully identified rogue taxa in a set of 100 trees with 116 334 taxa each. For simulated data sets, we show that when removing/pruning rogue taxa with our method from a tree set, we consistently obtain bootstrap consensus trees as well as maximum-likelihood trees that are topologically closer to the respective true trees.

Are Female Applicants Disadvantaged in National Institutes of Health Peer Review? Combining Algorithmic Text Mining and Qualitative Methods to Detect Evaluative Differences in R01 Reviewers' Critiques.

PubMed

Magua, Wairimu; Zhu, Xiaojin; Bhattacharya, Anupama; Filut, Amarette; Potvien, Aaron; Leatherberry, Renee; Lee, You-Geon; Jens, Madeline; Malikireddy, Dastagiri; Carnes, Molly; Kaatz, Anna

2017-05-01

Women are less successful than men in renewing R01 grants from the National Institutes of Health. Continuing to probe text mining as a tool to identify gender bias in peer review, we used algorithmic text mining and qualitative analysis to examine a sample of critiques from men's and women's R01 renewal applications previously analyzed by counting and comparing word categories. We analyzed 241 critiques from 79 Summary Statements for 51 R01 renewals awarded to 45 investigators (64% male, 89% white, 80% PhD) at the University of Wisconsin-Madison between 2010 and 2014. We used latent Dirichlet allocation to discover evaluative "topics" (i.e., words that co-occur with high probability). We then qualitatively examined the context in which evaluative words occurred for male and female investigators. We also examined sex differences in assigned scores controlling for investigator productivity. Text analysis results showed that male investigators were described as "leaders" and "pioneers" in their "fields," with "highly innovative" and "highly significant research." By comparison, female investigators were characterized as having "expertise" and working in "excellent" environments. Applications from men received significantly better priority, approach, and significance scores, which could not be accounted for by differences in productivity. Results confirm our previous analyses suggesting that gender stereotypes operate in R01 grant peer review. Reviewers may more easily view male than female investigators as scientific leaders with significant and innovative research, and score their applications more competitively. Such implicit bias may contribute to sex differences in award rates for R01 renewals.

Using wound care algorithms: a content validation study.

PubMed

Beitz, J M; van Rijswijk, L

1999-09-01

Valid and reliable heuristic devices facilitating optimal wound care are lacking. The objectives of this study were to establish content validation data for a set of wound care algorithms, to identify their associated strengths and weaknesses, and to gain insight into the wound care decision-making process. Forty-four registered nurse wound care experts were surveyed and interviewed at national and regional educational meetings. Using a cross-sectional study design and an 83-item, 4-point Likert-type scale, this purposive sample was asked to quantify the degree of validity of the algorithms' decisions and components. Participants' comments were tape-recorded, transcribed, and themes were derived. On a scale of 1 to 4, the mean score of the entire instrument was 3.47 (SD +/- 0.87), the instrument's Content Validity Index was 0.86, and the individual Content Validity Index of 34 of 44 participants was > 0.8. Item scores were lower for those related to packing deep wounds (P < .001). No other significant differences were observed. Qualitative data analysis revealed themes of difficulty associated with wound assessment and care issues, that is, the absence of valid and reliable definitions. The wound care algorithms studied proved valid. However, the lack of valid and reliable wound assessment and care definitions hinders optimal use of these instruments. Further research documenting their clinical use is warranted. Research-based practice recommendations should direct the development of future valid and reliable algorithms designed to help nurses provide optimal wound care.

Modified algorithm for mineral identification in LWIR hyperspectral imagery

NASA Astrophysics Data System (ADS)

Yousefi, Bardia; Sojasi, Saeed; Liaigre, Kévin; Ibarra Castanedo, Clemente; Beaudoin, Georges; Huot, François; Maldague, Xavier P. V.; Chamberland, Martin

2017-05-01

The applications of hyperspectral infrared imagery in the different fields of research are significant and growing. It is mainly used in remote sensing for target detection, vegetation detection, urban area categorization, astronomy and geological applications. The geological applications of this technology mainly consist in mineral identification using in airborne or satellite imagery. We address a quantitative and qualitative assessment of mineral identification in the laboratory conditions. We strive to identify nine different mineral grains (Biotite, Diopside, Epidote, Goethite, Kyanite, Scheelite, Smithsonite, Tourmaline, Quartz). A hyperspectral camera in the Long Wave Infrared (LWIR, 7.7-11.8 ) with a LW-macro lens providing a spatial resolution of 100 μm, an infragold plate, and a heating source are the instruments used in the experiment. The proposed algorithm clusters all the pixel-spectra in different categories. Then the best representatives of each cluster are chosen and compared with the ASTER spectral library of JPL/NASA through spectral comparison techniques, such as Spectral angle mapper (SAM) and Normalized Cross Correlation (NCC). The results of the algorithm indicate significant computational efficiency (more than 20 times faster) as compared to previous algorithms and have shown a promising performance for mineral identification.

Application of a novel particle tracking algorithm in the flow visualization of an artificial abdominal aortic aneurysm.

PubMed

Zhang, Yang; Wang, Yuan; He, Wenbo; Yang, Bin

2014-01-01

A novel Particle Tracking Velocimetry (PTV) algorithm based on Voronoi Diagram (VD) is proposed and briefed as VD-PTV. The robustness of VD-PTV for pulsatile flow is verified through a test that includes a widely used artificial flow and a classic reference algorithm. The proposed algorithm is then applied to visualize the flow in an artificial abdominal aortic aneurysm included in a pulsatile circulation system that simulates the aortic blood flow in human body. Results show that, large particles tend to gather at the upstream boundary because of the backflow eddies that follow the pulsation. This qualitative description, together with VD-PTV, has laid a foundation for future works that demand high-level quantification.

Exploration of a physiologically-inspired hearing-aid algorithm using a computer model mimicking impaired hearing.

PubMed

Jürgens, Tim; Clark, Nicholas R; Lecluyse, Wendy; Meddis, Ray

2016-01-01

To use a computer model of impaired hearing to explore the effects of a physiologically-inspired hearing-aid algorithm on a range of psychoacoustic measures. A computer model of a hypothetical impaired listener's hearing was constructed by adjusting parameters of a computer model of normal hearing. Absolute thresholds, estimates of compression, and frequency selectivity (summarized to a hearing profile) were assessed using this model with and without pre-processing the stimuli by a hearing-aid algorithm. The influence of different settings of the algorithm on the impaired profile was investigated. To validate the model predictions, the effect of the algorithm on hearing profiles of human impaired listeners was measured. A computer model simulating impaired hearing (total absence of basilar membrane compression) was used, and three hearing-impaired listeners participated. The hearing profiles of the model and the listeners showed substantial changes when the test stimuli were pre-processed by the hearing-aid algorithm. These changes consisted of lower absolute thresholds, steeper temporal masking curves, and sharper psychophysical tuning curves. The hearing-aid algorithm affected the impaired hearing profile of the model to approximate a normal hearing profile. Qualitatively similar results were found with the impaired listeners' hearing profiles.

Optimal and heuristic algorithms of planning of low-rise residential buildings

NASA Astrophysics Data System (ADS)

Kartak, V. M.; Marchenko, A. A.; Petunin, A. A.; Sesekin, A. N.; Fabarisova, A. I.

2017-10-01

The problem of the optimal layout of low-rise residential building is considered. Each apartment must be no less than the corresponding apartment from the proposed list. Also all requests must be made and excess of the total square over of the total square of apartment from the list must be minimized. The difference in the squares formed due to with the discreteness of distances between bearing walls and a number of other technological limitations. It shown, that this problem is NP-hard. The authors built a linear-integer model and conducted her qualitative analysis. As well, authors developed a heuristic algorithm for the solution tasks of a high dimension. The computational experiment was conducted which confirming the efficiency of the proposed approach. Practical recommendations on the use the proposed algorithms are given.

Pushing for Particulate Level Models of Adiabatic and Isothermal Processes in Upper-Level Chemistry Courses: A Qualitative Study

ERIC Educational Resources Information Center

Hernandez, Gabriel E.; Criswell, Brett A.; Kirk, Nancy J.; Sauder, Deborah G.; Rushton, Gregory T.

2014-01-01

In the past three decades, researchers have noted the limitations of a problem-solving approach that overemphasizes algorithms and quantitation and neglects student misconceptions and an otherwise qualitative, conceptual understanding of chemical phenomena. Since then, studies and lessons designed to improve student understanding of chemistry has…

SEURAT: visual analytics for the integrated analysis of microarray data.

PubMed

Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

2010-06-03

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

SEURAT: Visual analytics for the integrated analysis of microarray data

PubMed Central

2010-01-01

Background In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. Results We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. Conclusions The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data. PMID:20525257

Assessment of the NPOESS/VIIRS Nighttime Infrared Cloud Optical Properties Algorithms

NASA Astrophysics Data System (ADS)

Wong, E.; Ou, S. C.

2008-12-01

In this paper we will describe two NPOESS VIIRS IR algorithms used to retrieve microphysical properties for water and ice clouds during nighttime conditions. Both algorithms employ four VIIRS IR channels: M12 (3.7 μm), M14 (8.55 μm), M15 (10.7 μm) and M16 (12 μm). The physical basis for the two algorithms is similar in that while the Cloud Top Temperature (CTT) is derived from M14 and M16 for ice clouds the Cloud Optical Thickness (COT) and Cloud Effective Particle Size (CEPS) are derived from M12 and M15. The two algorithms depart in the different radiative transfer parameterization equations used for ice and water clouds. Both the VIIRS nighttime IR algorithms and the CERES split-window method employ the 3.7 μm and 10.7 μm bands for cloud optical properties retrievals, apparently based on similar physical principles but with different implementations. It is reasonable to expect that the VIIRS and CERES IR algorithms produce comparable performance and similar limitations. To demonstrate the VIIRS nighttime IR algorithm performance, we will select a number of test cases using NASA MODIS L1b radiance products as proxy input data for VIIRS. The VIIRS retrieved COT and CEPS will then be compared to cloud products available from the MODIS, NASA CALIPSO, CloudSat and CERES sensors. For the MODIS product, the nighttime cloud emissivity will serve as an indirect comparison to VIIRS COT. For the CALIPSO and CloudSat products, the layered COT will be used for direct comparison. Finally, the CERES products will provide direct comparison with COT as well as CEPS. This study can only provide a qualitative assessment of the VIIRS IR algorithms due to the large uncertainties in these cloud products.

Are Female Applicants Disadvantaged in National Institutes of Health Peer Review? Combining Algorithmic Text Mining and Qualitative Methods to Detect Evaluative Differences in R01 Reviewers' Critiques

PubMed Central

Magua, Wairimu; Zhu, Xiaojin; Bhattacharya, Anupama; Filut, Amarette; Potvien, Aaron; Leatherberry, Renee; Lee, You-Geon; Jens, Madeline; Malikireddy, Dastagiri; Carnes, Molly

2017-01-01

Abstract Background: Women are less successful than men in renewing R01 grants from the National Institutes of Health. Continuing to probe text mining as a tool to identify gender bias in peer review, we used algorithmic text mining and qualitative analysis to examine a sample of critiques from men's and women's R01 renewal applications previously analyzed by counting and comparing word categories. Methods: We analyzed 241 critiques from 79 Summary Statements for 51 R01 renewals awarded to 45 investigators (64% male, 89% white, 80% PhD) at the University of Wisconsin-Madison between 2010 and 2014. We used latent Dirichlet allocation to discover evaluative “topics” (i.e., words that co-occur with high probability). We then qualitatively examined the context in which evaluative words occurred for male and female investigators. We also examined sex differences in assigned scores controlling for investigator productivity. Results: Text analysis results showed that male investigators were described as “leaders” and “pioneers” in their “fields,” with “highly innovative” and “highly significant research.” By comparison, female investigators were characterized as having “expertise” and working in “excellent” environments. Applications from men received significantly better priority, approach, and significance scores, which could not be accounted for by differences in productivity. Conclusions: Results confirm our previous analyses suggesting that gender stereotypes operate in R01 grant peer review. Reviewers may more easily view male than female investigators as scientific leaders with significant and innovative research, and score their applications more competitively. Such implicit bias may contribute to sex differences in award rates for R01 renewals. PMID:28281870

Mapping Publication Trends and Identifying Hot Spots of Research on Internet Health Information Seeking Behavior: A Quantitative and Co-Word Biclustering Analysis

PubMed Central

Li, Fan; Li, Min; Guan, Peng; Ma, Shuang

2015-01-01

Background The Internet has become an established source of health information for people seeking health information. In recent years, research on the health information seeking behavior of Internet users has become an increasingly important scholarly focus. However, there have been no long-term bibliometric studies to date on Internet health information seeking behavior. Objective The purpose of this study was to map publication trends and explore research hot spots of Internet health information seeking behavior. Methods A bibliometric analysis based on PubMed was conducted to investigate the publication trends of research on Internet health information seeking behavior. For the included publications, the annual publication number, the distribution of countries, authors, languages, journals, and annual distribution of highly frequent major MeSH (Medical Subject Headings) terms were determined. Furthermore, co-word biclustering analysis of highly frequent major MeSH terms was utilized to detect the hot spots in this field. Results A total of 533 publications were included. The research output was gradually increasing. There were five authors who published four or more articles individually. A total of 271 included publications (50.8%) were written by authors from the United States, and 516 of the 533 articles (96.8%) were published in English. The eight most active journals published 34.1% (182/533) of the publications on this topic. Ten research hot spots were found: (1) behavior of Internet health information seeking about HIV infection or sexually transmitted diseases, (2) Internet health information seeking behavior of students, (3) behavior of Internet health information seeking via mobile phone and its apps, (4) physicians’ utilization of Internet medical resources, (5) utilization of social media by parents, (6) Internet health information seeking behavior of patients with cancer (mainly breast cancer), (7) trust in or satisfaction with Web-based health

Mapping publication trends and identifying hot spots of research on Internet health information seeking behavior: a quantitative and co-word biclustering analysis.

PubMed

Li, Fan; Li, Min; Guan, Peng; Ma, Shuang; Cui, Lei

2015-03-25

The Internet has become an established source of health information for people seeking health information. In recent years, research on the health information seeking behavior of Internet users has become an increasingly important scholarly focus. However, there have been no long-term bibliometric studies to date on Internet health information seeking behavior. The purpose of this study was to map publication trends and explore research hot spots of Internet health information seeking behavior. A bibliometric analysis based on PubMed was conducted to investigate the publication trends of research on Internet health information seeking behavior. For the included publications, the annual publication number, the distribution of countries, authors, languages, journals, and annual distribution of highly frequent major MeSH (Medical Subject Headings) terms were determined. Furthermore, co-word biclustering analysis of highly frequent major MeSH terms was utilized to detect the hot spots in this field. A total of 533 publications were included. The research output was gradually increasing. There were five authors who published four or more articles individually. A total of 271 included publications (50.8%) were written by authors from the United States, and 516 of the 533 articles (96.8%) were published in English. The eight most active journals published 34.1% (182/533) of the publications on this topic. Ten research hot spots were found: (1) behavior of Internet health information seeking about HIV infection or sexually transmitted diseases, (2) Internet health information seeking behavior of students, (3) behavior of Internet health information seeking via mobile phone and its apps, (4) physicians' utilization of Internet medical resources, (5) utilization of social media by parents, (6) Internet health information seeking behavior of patients with cancer (mainly breast cancer), (7) trust in or satisfaction with Web-based health information by consumers, (8

A rapid place name locating algorithm based on ontology qualitative retrieval, ranking and recommendation

NASA Astrophysics Data System (ADS)

Fan, Hong; Zhu, Anfeng; Zhang, Weixia

2015-12-01

In order to meet the rapid positioning of 12315 complaints, aiming at the natural language expression of telephone complaints, a semantic retrieval framework is proposed which is based on natural language parsing and geographical names ontology reasoning. Among them, a search result ranking and recommended algorithms is proposed which is regarding both geo-name conceptual similarity and spatial geometry relation similarity. The experiments show that this method can assist the operator to quickly find location of 12,315 complaints, increased industry and commerce customer satisfaction.

STAR Algorithm Integration Team - Facilitating operational algorithm development

NASA Astrophysics Data System (ADS)

Mikles, V. J.

2015-12-01

The NOAA/NESDIS Center for Satellite Research and Applications (STAR) provides technical support of the Joint Polar Satellite System (JPSS) algorithm development and integration tasks. Utilizing data from the S-NPP satellite, JPSS generates over thirty Environmental Data Records (EDRs) and Intermediate Products (IPs) spanning atmospheric, ocean, cryosphere, and land weather disciplines. The Algorithm Integration Team (AIT) brings technical expertise and support to product algorithms, specifically in testing and validating science algorithms in a pre-operational environment. The AIT verifies that new and updated algorithms function in the development environment, enforces established software development standards, and ensures that delivered packages are functional and complete. AIT facilitates the development of new JPSS-1 algorithms by implementing a review approach based on the Enterprise Product Lifecycle (EPL) process. Building on relationships established during the S-NPP algorithm development process and coordinating directly with science algorithm developers, the AIT has implemented structured reviews with self-contained document suites. The process has supported algorithm improvements for products such as ozone, active fire, vegetation index, and temperature and moisture profiles.

Richardson-Lucy/maximum likelihood image restoration algorithm for fluorescence microscopy: further testing.

PubMed

Holmes, T J; Liu, Y H

1989-11-15

A maximum likelihood based iterative algorithm adapted from nuclear medicine imaging for noncoherent optical imaging was presented in a previous publication with some initial computer-simulation testing. This algorithm is identical in form to that previously derived in a different way by W. H. Richardson "Bayesian-Based Iterative Method of Image Restoration," J. Opt. Soc. Am. 62, 55-59 (1972) and L. B. Lucy "An Iterative Technique for the Rectification of Observed Distributions," Astron. J. 79, 745-765 (1974). Foreseen applications include superresolution and 3-D fluorescence microscopy. This paper presents further simulation testing of this algorithm and a preliminary experiment with a defocused camera. The simulations show quantified resolution improvement as a function of iteration number, and they show qualitatively the trend in limitations on restored resolution when noise is present in the data. Also shown are results of a simulation in restoring missing-cone information for 3-D imaging. Conclusions are in support of the feasibility of using these methods with real systems, while computational cost and timing estimates indicate that it should be realistic to implement these methods. Itis suggested in the Appendix that future extensions to the maximum likelihood based derivation of this algorithm will address some of the limitations that are experienced with the nonextended form of the algorithm presented here.

Qualitative research.

PubMed

Gelling, Leslie

2015-03-25

Qualitative research has an important role in helping nurses and other healthcare professionals understand patient experiences of health and illness. Qualitative researchers have a large number of methodological options and therefore should take care in planning and conducting their research. This article offers a brief overview of some of the key issues qualitative researchers should consider.

Selfish Gene Algorithm Vs Genetic Algorithm: A Review

NASA Astrophysics Data System (ADS)

Ariff, Norharyati Md; Khalid, Noor Elaiza Abdul; Hashim, Rathiah; Noor, Noorhayati Mohamed

2016-11-01

Evolutionary algorithm is one of the algorithms inspired by the nature. Within little more than a decade hundreds of papers have reported successful applications of EAs. In this paper, the Selfish Gene Algorithms (SFGA), as one of the latest evolutionary algorithms (EAs) inspired from the Selfish Gene Theory which is an interpretation of Darwinian Theory ideas from the biologist Richards Dawkins on 1989. In this paper, following a brief introduction to the Selfish Gene Algorithm (SFGA), the chronology of its evolution is presented. It is the purpose of this paper is to present an overview of the concepts of Selfish Gene Algorithm (SFGA) as well as its opportunities and challenges. Accordingly, the history, step involves in the algorithm are discussed and its different applications together with an analysis of these applications are evaluated.

SU-F-J-88: Comparison of Two Deformable Image Registration Algorithms for CT-To-CT Contour Propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gopal, A; Xu, H; Chen, S

Purpose: To compare the contour propagation accuracy of two deformable image registration (DIR) algorithms in the Raystation treatment planning system – the “Hybrid” algorithm based on image intensities and anatomical information; and the “Biomechanical” algorithm based on linear anatomical elasticity and finite element modeling. Methods: Both DIR algorithms were used for CT-to-CT deformation for 20 lung radiation therapy patients that underwent treatment plan revisions. Deformation accuracy was evaluated using landmark tracking to measure the target registration error (TRE) and inverse consistency error (ICE). The deformed contours were also evaluated against physician drawn contours using Dice similarity coefficients (DSC). Contour propagationmore » was qualitatively assessed using a visual quality score assigned by physicians, and a refinement quality score (0 0.9 for lungs, > 0.85 for heart, > 0.8 for liver) and similar qualitative assessments (VQS < 0.35, RQS > 0.75 for lungs). When anatomical structures were used to control the deformation, the DSC improved more significantly for the biomechanical DIR compared to the hybrid DIR, while the VQS and RQS improved only for the controlling structures. However, while the inclusion of controlling structures improved the TRE for the hybrid DIR, it increased the TRE for the biomechanical DIR. Conclusion: The hybrid DIR was found to perform slightly better than the biomechanical DIR based on lower TRE while the DSC, VQS, and RQS studies yielded comparable results for both. The use of controlling structures showed considerable improvement in the hybrid DIR results and is recommended for clinical use in contour propagation.« less

A hybrid algorithm for speckle noise reduction of ultrasound images.

PubMed

Singh, Karamjeet; Ranade, Sukhjeet Kaur; Singh, Chandan

2017-09-01

Medical images are contaminated by multiplicative speckle noise which significantly reduce the contrast of ultrasound images and creates a negative effect on various image interpretation tasks. In this paper, we proposed a hybrid denoising approach which collaborate the both local and nonlocal information in an efficient manner. The proposed hybrid algorithm consist of three stages in which at first stage the use of local statistics in the form of guided filter is used to reduce the effect of speckle noise initially. Then, an improved speckle reducing bilateral filter (SRBF) is developed to further reduce the speckle noise from the medical images. Finally, to reconstruct the diffused edges we have used the efficient post-processing technique which jointly considered the advantages of both bilateral and nonlocal mean (NLM) filter for the attenuation of speckle noise efficiently. The performance of proposed hybrid algorithm is evaluated on synthetic, simulated and real ultrasound images. The experiments conducted on various test images demonstrate that our proposed hybrid approach outperforms the various traditional speckle reduction approaches included recently proposed NLM and optimized Bayesian-based NLM. The results of various quantitative, qualitative measures and by visual inspection of denoise synthetic and real ultrasound images demonstrate that the proposed hybrid algorithm have strong denoising capability and able to preserve the fine image details such as edge of a lesion better than previously developed methods for speckle noise reduction. The denoising and edge preserving capability of hybrid algorithm is far better than existing traditional and recently proposed speckle reduction (SR) filters. The success of proposed algorithm would help in building the lay foundation for inventing the hybrid algorithms for denoising of ultrasound images. Copyright © 2017 Elsevier B.V. All rights reserved.

An efficient algorithm for function optimization: modified stem cells algorithm

NASA Astrophysics Data System (ADS)

Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad Hadi

2013-03-01

In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).

SU-G-201-09: Evaluation of a Novel Machine-Learning Algorithm for Permanent Prostate Brachytherapy Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicolae, A; Department of Physics, Ryerson University, Toronto, ON; Lu, L

Purpose: A novel, automated, algorithm for permanent prostate brachytherapy (PPB) treatment planning has been developed. The novel approach uses machine-learning (ML), a form of artificial intelligence, to substantially decrease planning time while simultaneously retaining the clinical intuition of plans created by radiation oncologists. This study seeks to compare the ML algorithm against expert-planned PPB plans to evaluate the equivalency of dosimetric and clinical plan quality. Methods: Plan features were computed from historical high-quality PPB treatments (N = 100) and stored in a relational database (RDB). The ML algorithm matched new PPB features to a highly similar case in the RDB;more » this initial plan configuration was then further optimized using a stochastic search algorithm. PPB pre-plans (N = 30) generated using the ML algorithm were compared to plan variants created by an expert dosimetrist (RT), and radiation oncologist (MD). Planning time and pre-plan dosimetry were evaluated using a one-way Student’s t-test and ANOVA, respectively (significance level = 0.05). Clinical implant quality was evaluated by expert PPB radiation oncologists as part of a qualitative study. Results: Average planning time was 0.44 ± 0.42 min compared to 17.88 ± 8.76 min for the ML algorithm and RT, respectively, a significant advantage [t(9), p = 0.01]. A post-hoc ANOVA [F(2,87) = 6.59, p = 0.002] using Tukey-Kramer criteria showed a significantly lower mean prostate V150% for the ML plans (52.9%) compared to the RT (57.3%), and MD (56.2%) plans. Preliminary qualitative study results indicate comparable clinical implant quality between RT and ML plans with a trend towards preference for ML plans. Conclusion: PPB pre-treatment plans highly comparable to those of an expert radiation oncologist can be created using a novel ML planning model. The use of an ML-based planning approach is expected to translate into improved PPB accessibility and plan uniformity.« less

Algorithms for detecting and predicting influenza outbreaks: metanarrative review of prospective evaluations

PubMed Central

Spreco, A; Timpka, T

2016-01-01

Objectives Reliable monitoring of influenza seasons and pandemic outbreaks is essential for response planning, but compilations of reports on detection and prediction algorithm performance in influenza control practice are largely missing. The aim of this study is to perform a metanarrative review of prospective evaluations of influenza outbreak detection and prediction algorithms restricted settings where authentic surveillance data have been used. Design The study was performed as a metanarrative review. An electronic literature search was performed, papers selected and qualitative and semiquantitative content analyses were conducted. For data extraction and interpretations, researcher triangulation was used for quality assurance. Results Eight prospective evaluations were found that used authentic surveillance data: three studies evaluating detection and five studies evaluating prediction. The methodological perspectives and experiences from the evaluations were found to have been reported in narrative formats representing biodefence informatics and health policy research, respectively. The biodefence informatics narrative having an emphasis on verification of technically and mathematically sound algorithms constituted a large part of the reporting. Four evaluations were reported as health policy research narratives, thus formulated in a manner that allows the results to qualify as policy evidence. Conclusions Awareness of the narrative format in which results are reported is essential when interpreting algorithm evaluations from an infectious disease control practice perspective. PMID:27154479

Improved hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW)

NASA Astrophysics Data System (ADS)

Zaiwani, B. E.; Zarlis, M.; Efendi, S.

2018-03-01

In this research, the improvement of hybridization algorithm of Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) in selecting the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. To improve the performance of the above research, FAHP algorithm hybridization with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW) algorithm was adopted, which applied FAHP algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee at a government institution. The result of improvement of the average value of Efficiency Rate (ER) is 85.24%, which means that this research has succeeded in improving the previous research that is equal to 77.82%. Keywords: Ranking and Selection, Fuzzy AHP, Fuzzy TOPSIS, FMADM-SAW.

Denni Algorithm An Enhanced Of SMS (Scan, Move and Sort) Algorithm

NASA Astrophysics Data System (ADS)

Aprilsyah Lubis, Denni; Salim Sitompul, Opim; Marwan; Tulus; Andri Budiman, M.

2017-12-01

Sorting has been a profound area for the algorithmic researchers, and many resources are invested to suggest a more working sorting algorithm. For this purpose many existing sorting algorithms were observed in terms of the efficiency of the algorithmic complexity. Efficient sorting is important to optimize the use of other algorithms that require sorted lists to work correctly. Sorting has been considered as a fundamental problem in the study of algorithms that due to many reasons namely, the necessary to sort information is inherent in many applications, algorithms often use sorting as a key subroutine, in algorithm design there are many essential techniques represented in the body of sorting algorithms, and many engineering issues come to the fore when implementing sorting algorithms., Many algorithms are very well known for sorting the unordered lists, and one of the well-known algorithms that make the process of sorting to be more economical and efficient is SMS (Scan, Move and Sort) algorithm, an enhancement of Quicksort invented Rami Mansi in 2010. This paper presents a new sorting algorithm called Denni-algorithm. The Denni algorithm is considered as an enhancement on the SMS algorithm in average, and worst cases. The Denni algorithm is compared with the SMS algorithm and the results were promising.

An improved algorithm for de-striping of ocean colour monitor imageries aided by measured sensor characteristics

NASA Astrophysics Data System (ADS)

Dutt, Ashutosh; Mishra, Ashish; Goswami, D. R.; Kumar, A. S. Kiran

2016-05-01

The push-broom sensors in bands meant to study oceans, in general suffer from residual non uniformity even after radiometric correction. The in-orbit data from OCM-2 shows pronounced striping in lower bands. There have been many attempts and different approaches to solve the problem using image data itself. The success or lack of it of each algorithm lies on the quality of the uniform region identified. In this paper, an image based destriping algorithm is presented with constraints being derived from Ground Calibration exercise. The basis of the methodology is determination of pixel to pixel non-uniformity through uniform segments identified and collected from large number of images, covering the dynamic range of the sensor. The results show the effectiveness of the algorithm over different targets. The performance is qualitatively evaluated by visual inspection and quantitatively measured by two parameters.

Using Qualitative Metasummary to Synthesize Qualitative and Quantitative Descriptive Findings

PubMed Central

Sandelowski, Margarete; Barroso, Julie; Voils, Corrine I.

2008-01-01

The new imperative in the health disciplines to be more methodologically inclusive has generated a growing interest in mixed research synthesis, or the integration of qualitative and quantitative research findings. Qualitative metasummary is a quantitatively oriented aggregation of qualitative findings originally developed to accommodate the distinctive features of qualitative surveys. Yet these findings are similar in form and mode of production to the descriptive findings researchers often present in addition to the results of bivariate and multivariable analyses. Qualitative metasummary, which includes the extraction, grouping, and formatting of findings, and the calculation of frequency and intensity effect sizes, can be used to produce mixed research syntheses and to conduct a posteriori analyses of the relationship between reports and findings. PMID:17243111

Algorithms for optimization of the transport system in living and artificial cells.

PubMed

Melkikh, A V; Sutormina, M I

2011-06-01

An optimization of the transport system in a cell has been considered from the viewpoint of the operations research. Algorithms for an optimization of the transport system of a cell in terms of both the efficiency and a weak sensitivity of a cell to environmental changes have been proposed. The switching of various systems of transport is considered as the mechanism of weak sensitivity of a cell to changes in environment. The use of the algorithms for an optimization of a cardiac cell has been considered by way of example. We received theoretically for a cell of a cardiac muscle that at the increase of potassium concentration in the environment switching of transport systems for this ion takes place. This conclusion qualitatively coincides with experiments. The problem of synthesizing an optimal system in an artificial cell has been stated.

Hybrid Cryptosystem Using Tiny Encryption Algorithm and LUC Algorithm

NASA Astrophysics Data System (ADS)

Rachmawati, Dian; Sharif, Amer; Jaysilen; Andri Budiman, Mohammad

2018-01-01

Security becomes a very important issue in data transmission and there are so many methods to make files more secure. One of that method is cryptography. Cryptography is a method to secure file by writing the hidden code to cover the original file. Therefore, if the people do not involve in cryptography, they cannot decrypt the hidden code to read the original file. There are many methods are used in cryptography, one of that method is hybrid cryptosystem. A hybrid cryptosystem is a method that uses a symmetric algorithm to secure the file and use an asymmetric algorithm to secure the symmetric algorithm key. In this research, TEA algorithm is used as symmetric algorithm and LUC algorithm is used as an asymmetric algorithm. The system is tested by encrypting and decrypting the file by using TEA algorithm and using LUC algorithm to encrypt and decrypt the TEA key. The result of this research is by using TEA Algorithm to encrypt the file, the cipher text form is the character from ASCII (American Standard for Information Interchange) table in the form of hexadecimal numbers and the cipher text size increase by sixteen bytes as the plaintext length is increased by eight characters.

Potential for false positive HIV test results with the serial rapid HIV testing algorithm.

PubMed

Baveewo, Steven; Kamya, Moses R; Mayanja-Kizza, Harriet; Fatch, Robin; Bangsberg, David R; Coates, Thomas; Hahn, Judith A; Wanyenze, Rhoda K

2012-03-19

Rapid HIV tests provide same-day results and are widely used in HIV testing programs in areas with limited personnel and laboratory infrastructure. The Uganda Ministry of Health currently recommends the serial rapid testing algorithm with Determine, STAT-PAK, and Uni-Gold for diagnosis of HIV infection. Using this algorithm, individuals who test positive on Determine, negative to STAT-PAK and positive to Uni-Gold are reported as HIV positive. We conducted further testing on this subgroup of samples using qualitative DNA PCR to assess the potential for false positive tests in this situation. Of the 3388 individuals who were tested, 984 were HIV positive on two consecutive tests, and 29 were considered positive by a tiebreaker (positive on Determine, negative on STAT-PAK, and positive on Uni-Gold). However, when the 29 samples were further tested using qualitative DNA PCR, 14 (48.2%) were HIV negative. Although this study was not primarily designed to assess the validity of rapid HIV tests and thus only a subset of the samples were retested, the findings show a potential for false positive HIV results in the subset of individuals who test positive when a tiebreaker test is used in serial testing. These findings highlight a need for confirmatory testing for this category of individuals.

A scale space based algorithm for automated segmentation of single shot tagged MRI of shearing deformation.

PubMed

Sprengers, Andre M J; Caan, Matthan W A; Moerman, Kevin M; Nederveen, Aart J; Lamerichs, Rolf M; Stoker, Jaap

2013-04-01

This study proposes a scale space based algorithm for automated segmentation of single-shot tagged images of modest SNR. Furthermore the algorithm was designed for analysis of discontinuous or shearing types of motion, i.e. segmentation of broken tag patterns. The proposed algorithm utilises non-linear scale space for automatic segmentation of single-shot tagged images. The algorithm's ability to automatically segment tagged shearing motion was evaluated in a numerical simulation and in vivo. A typical shearing deformation was simulated in a Shepp-Logan phantom allowing for quantitative evaluation of the algorithm's success rate as a function of both SNR and the amount of deformation. For a qualitative in vivo evaluation tagged images showing deformations in the calf muscles and eye movement in a healthy volunteer were acquired. Both the numerical simulation and the in vivo tagged data demonstrated the algorithm's ability for automated segmentation of single-shot tagged MR provided that SNR of the images is above 10 and the amount of deformation does not exceed the tag spacing. The latter constraint can be met by adjusting the tag delay or the tag spacing. The scale space based algorithm for automatic segmentation of single-shot tagged MR enables the application of tagged MR to complex (shearing) deformation and the processing of datasets with relatively low SNR.

Qualitative "trial-sibling" studies and "unrelated" qualitative studies contributed to complex intervention reviews.

PubMed

Noyes, Jane; Hendry, Margaret; Lewin, Simon; Glenton, Claire; Chandler, Jackie; Rashidian, Arash

2016-06-01

To compare the contribution of "trial-sibling" and "unrelated" qualitative studies in complex intervention reviews. Researchers are using qualitative "trial-sibling" studies undertaken alongside trials to provide explanations to understand complex interventions. In the absence of qualitative "trial-sibling" studies, it is not known if qualitative studies "unrelated" to trials are helpful. Trials, "trial-sibling," and "unrelated" qualitative studies looking at three health system interventions were identified. We looked for similarities and differences between the two types of qualitative studies, such as participants, intervention delivery, context, study quality and reporting, and contribution to understanding trial results. Reporting was generally poor in both qualitative study types. We detected no substantial differences in participant characteristics. Interventions in qualitative "trial-sibling" studies were delivered using standardized protocols, whereas interventions in "unrelated" qualitative studies were delivered in routine care. Qualitative "trial-sibling" studies alone provided insufficient data to develop meaningful transferrable explanations beyond the trial context, and their limited focus on immediate implementation did not address all phenomena of interest. Together, "trial-sibling" and "unrelated" qualitative studies provided larger, richer data sets across contexts to better understand the phenomena of interest. Findings support inclusion of "trial-sibling" and "unrelated" qualitative studies to explore complexity in complex intervention reviews. Copyright © 2016 Elsevier Inc. All rights reserved.

Preliminary Comparison of Multi-scale and Multi-model Direct Inversion Algorithms for 3T MR Elastography.

PubMed

Yoshimitsu, Kengo; Shinagawa, Yoshinobu; Mitsufuji, Toshimichi; Mutoh, Emi; Urakawa, Hiroshi; Sakamoto, Keiko; Fujimitsu, Ritsuko; Takano, Koichi

2017-01-10

To elucidate whether any differences are present in the stiffness map obtained with a multiscale direct inversion algorithm (MSDI) vs that with a multimodel direct inversion algorithm (MMDI), both qualitatively and quantitatively. The MR elastography (MRE) data of 37 consecutive patients who underwent liver MR elastography between September and October 2014 were retrospectively analyzed by using both MSDI and MMDI. Two radiologists qualitatively assessed the stiffness maps for the image quality in consensus, and the measured liver stiffness and measurable areas were quantitatively compared between MSDI and MMDI. MMDI provided a stiffness map of better image quality, with comparable or slightly less artifacts. Measurable areas by MMDI (43.7 ± 17.8 cm 2 ) was larger than that by MSDI (37.5 ± 14.7 cm 2 ) (P < 0.05). Liver stiffness measured by MMDI (4.51 ± 2.32 kPa) was slightly (7%), but significantly less than that by MSDI (4.86 ± 2.44 kPa) (P < 0.05). MMDI can provide stiffness map of better image quality, and slightly lower stiffness values as compared to MSDI at 3T MRE, which radiologists should be aware of.

Genetic algorithms

NASA Technical Reports Server (NTRS)

Wang, Lui; Bayer, Steven E.

1991-01-01

Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

Comparison of a single-view and a double-view aerosol optical depth retrieval algorithm

NASA Astrophysics Data System (ADS)

Henderson, Bradley G.; Chylek, Petr

2003-11-01

We compare the results of a single-view and a double-view aerosol optical depth (AOD) retrieval algorithm applied to image pairs acquired over NASA Stennis Space Center, Mississippi. The image data were acquired by the Department of Energy's (DOE) Multispectral Thermal Imager (MTI), a pushbroom satellite imager with 15 bands from the visible to the thermal infrared. MTI has the ability to acquire imagery in pairs in which the first image is a near-nadir view and the second image is off-nadir with a zenith angle of approximately 60°. A total of 15 image pairs were used in the analysis. For a given image pair, AOD retrieval is performed twice---once using a single-view algorithm applied to the near-nadir image, then again using a double-view algorithm. Errors for both retrievals are computed by comparing the results to AERONET AOD measurements obtained at the same time and place. The single-view algorithm showed an RMS error about the mean of 0.076 in AOD units, whereas the double-view algorithm showed a modest improvement with an RMS error of 0.06. The single-view errors show a positive bias which is presumed to be a result of the empirical relationship used to determine ground reflectance in the visible. A plot of AOD error of the double-view algorithm versus time shows a noticeable trend which is interpreted to be a calibration drift. When this trend is removed, the RMS error of the double-view algorithm drops to 0.030. The single-view algorithm qualitatively appears to perform better during the spring and summer whereas the double-view algorithm seems to be less sensitive to season.

ARTIST: A fully automated artifact rejection algorithm for single-pulse TMS-EEG data.

PubMed

Wu, Wei; Keller, Corey J; Rogasch, Nigel C; Longwell, Parker; Shpigel, Emmanuel; Rolle, Camarin E; Etkin, Amit

2018-04-01

Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings. © 2018 Wiley Periodicals, Inc.

Algorithm aversion: people erroneously avoid algorithms after seeing them err.

PubMed

Dietvorst, Berkeley J; Simmons, Joseph P; Massey, Cade

2015-02-01

Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In 5 studies, participants either saw an algorithm make forecasts, a human make forecasts, both, or neither. They then decided whether to tie their incentives to the future predictions of the algorithm or the human. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human.

Qualitative-Based Methodology to Teaching Qualitative Methodology in Higher Education

ERIC Educational Resources Information Center

Katz, Sara

2015-01-01

There is no defined theory for teaching Qualitative Inquiry, and very few studies have focused on the topic. This study is a qualitative case study focused on the Qualitative Methods course that I teach at a college of education in Israel. The aim of the study is to explore and describe the course, to provide a true picture of my pedagogy, and to…

Evaluation of a prototype correction algorithm to reduce metal artefacts in flat detector computed tomography of scaphoid fixation screws.

PubMed

Filli, Lukas; Marcon, Magda; Scholz, Bernhard; Calcagni, Maurizio; Finkenstädt, Tim; Andreisek, Gustav; Guggenberger, Roman

2014-12-01

The aim of this study was to evaluate a prototype correction algorithm to reduce metal artefacts in flat detector computed tomography (FDCT) of scaphoid fixation screws. FDCT has gained interest in imaging small anatomic structures of the appendicular skeleton. Angiographic C-arm systems with flat detectors allow fluoroscopy and FDCT imaging in a one-stop procedure emphasizing their role as an ideal intraoperative imaging tool. However, FDCT imaging can be significantly impaired by artefacts induced by fixation screws. Following ethical board approval, commercially available scaphoid fixation screws were inserted into six cadaveric specimens in order to fix artificially induced scaphoid fractures. FDCT images corrected with the algorithm were compared to uncorrected images both quantitatively and qualitatively by two independent radiologists in terms of artefacts, screw contour, fracture line visibility, bone visibility, and soft tissue definition. Normal distribution of variables was evaluated using the Kolmogorov-Smirnov test. In case of normal distribution, quantitative variables were compared using paired Student's t tests. The Wilcoxon signed-rank test was used for quantitative variables without normal distribution and all qualitative variables. A p value of < 0.05 was considered to indicate statistically significant differences. Metal artefacts were significantly reduced by the correction algorithm (p < 0.001), and the fracture line was more clearly defined (p < 0.01). The inter-observer reliability was "almost perfect" (intra-class correlation coefficient 0.85, p < 0.001). The prototype correction algorithm in FDCT for metal artefacts induced by scaphoid fixation screws may facilitate intra- and postoperative follow-up imaging. Flat detector computed tomography (FDCT) is a helpful imaging tool for scaphoid fixation. The correction algorithm significantly reduces artefacts in FDCT induced by scaphoid fixation screws. This may facilitate intra

The Texas Medication Algorithm Project (TMAP) schizophrenia algorithms.

PubMed

Miller, A L; Chiles, J A; Chiles, J K; Crismon, M L; Rush, A J; Shon, S P

1999-10-01

In the Texas Medication Algorithm Project (TMAP), detailed guidelines for medication management of schizophrenia and related disorders, bipolar disorders, and major depressive disorders have been developed and implemented. This article describes the algorithms developed for medication treatment of schizophrenia and related disorders. The guidelines recommend a sequence of medications and discuss dosing, duration, and switch-over tactics. They also specify response criteria at each stage of the algorithm for both positive and negative symptoms. The rationale and evidence for each aspect of the algorithms are presented.

Diagnostic accuracy of stress perfusion CMR in comparison with quantitative coronary angiography: fully quantitative, semiquantitative, and qualitative assessment.

PubMed

Mordini, Federico E; Haddad, Tariq; Hsu, Li-Yueh; Kellman, Peter; Lowrey, Tracy B; Aletras, Anthony H; Bandettini, W Patricia; Arai, Andrew E

2014-01-01

This study's primary objective was to determine the sensitivity, specificity, and accuracy of fully quantitative stress perfusion cardiac magnetic resonance (CMR) versus a reference standard of quantitative coronary angiography. We hypothesized that fully quantitative analysis of stress perfusion CMR would have high diagnostic accuracy for identifying significant coronary artery stenosis and exceed the accuracy of semiquantitative measures of perfusion and qualitative interpretation. Relatively few studies apply fully quantitative CMR perfusion measures to patients with coronary disease and comparisons to semiquantitative and qualitative methods are limited. Dual bolus dipyridamole stress perfusion CMR exams were performed in 67 patients with clinical indications for assessment of myocardial ischemia. Stress perfusion images alone were analyzed with a fully quantitative perfusion (QP) method and 3 semiquantitative methods including contrast enhancement ratio, upslope index, and upslope integral. Comprehensive exams (cine imaging, stress/rest perfusion, late gadolinium enhancement) were analyzed qualitatively with 2 methods including the Duke algorithm and standard clinical interpretation. A 70% or greater stenosis by quantitative coronary angiography was considered abnormal. The optimum diagnostic threshold for QP determined by receiver-operating characteristic curve occurred when endocardial flow decreased to <50% of mean epicardial flow, which yielded a sensitivity of 87% and specificity of 93%. The area under the curve for QP was 92%, which was superior to semiquantitative methods: contrast enhancement ratio: 78%; upslope index: 82%; and upslope integral: 75% (p = 0.011, p = 0.019, p = 0.004 vs. QP, respectively). Area under the curve for QP was also superior to qualitative methods: Duke algorithm: 70%; and clinical interpretation: 78% (p < 0.001 and p < 0.001 vs. QP, respectively). Fully quantitative stress perfusion CMR has high diagnostic accuracy for

Qualitative Student Models.

ERIC Educational Resources Information Center

Clancey, William J.

The concept of a qualitative model is used as the focus of this review of qualitative student models in order to compare alternative computational models and to contrast domain requirements. The report is divided into eight sections: (1) Origins and Goals (adaptive instruction, qualitative models of processes, components of an artificial…

Critiquing qualitative research.

PubMed

Beck, Cheryl Tatano

2009-10-01

The ability to critique research is a valuable skill that is fundamental to a perioperative nurse's ability to base his or her clinical practice on evidence derived from research. Criteria differ for critiquing a quantitative versus a qualitative study (ie, statistics are evaluated in a quantitative study, but not in a qualitative study). This article provides on guidelines for assessing qualitative research. Excerpts from a published qualitative research report are summarized and then critiqued. Questions are provided that help evaluate different sections of a research study (eg, sample, data collection methods, data analysis).

Algorithm Visualization System for Teaching Spatial Data Algorithms

ERIC Educational Resources Information Center

Nikander, Jussi; Helminen, Juha; Korhonen, Ari

2010-01-01

TRAKLA2 is a web-based learning environment for data structures and algorithms. The system delivers automatically assessed algorithm simulation exercises that are solved using a graphical user interface. In this work, we introduce a novel learning environment for spatial data algorithms, SDA-TRAKLA2, which has been implemented on top of the…

Motion Cueing Algorithm Development: Initial Investigation and Redesign of the Algorithms

NASA Technical Reports Server (NTRS)

Telban, Robert J.; Wu, Weimin; Cardullo, Frank M.; Houck, Jacob A. (Technical Monitor)

2000-01-01

In this project four motion cueing algorithms were initially investigated. The classical algorithm generated results with large distortion and delay and low magnitude. The NASA adaptive algorithm proved to be well tuned with satisfactory performance, while the UTIAS adaptive algorithm produced less desirable results. Modifications were made to the adaptive algorithms to reduce the magnitude of undesirable spikes. The optimal algorithm was found to have the potential for improved performance with further redesign. The center of simulator rotation was redefined. More terms were added to the cost function to enable more tuning flexibility. A new design approach using a Fortran/Matlab/Simulink setup was employed. A new semicircular canals model was incorporated in the algorithm. With these changes results show the optimal algorithm has some advantages over the NASA adaptive algorithm. Two general problems observed in the initial investigation required solutions. A nonlinear gain algorithm was developed that scales the aircraft inputs by a third-order polynomial, maximizing the motion cues while remaining within the operational limits of the motion system. A braking algorithm was developed to bring the simulator to a full stop at its motion limit and later release the brake to follow the cueing algorithm output.

The qualitative research proposal.

PubMed

Klopper, H

2008-12-01

Qualitative research in the health sciences has had to overcome many prejudices and a number of misunderstandings, but today qualitative research is as acceptable as quantitative research designs and is widely funded and published. Writing the proposal of a qualitative study, however, can be a challenging feat, due to the emergent nature of the qualitative research design and the description of the methodology as a process. Even today, many sub-standard proposals at post-graduate evaluation committees and application proposals to be considered for funding are still seen. This problem has led the researcher to develop a framework to guide the qualitative researcher in writing the proposal of a qualitative study based on the following research questions: (i) What is the process of writing a qualitative research proposal? and (ii) What does the structure and layout of a qualitative proposal look like? The purpose of this article is to discuss the process of writing the qualitative research proposal, as well as describe the structure and layout of a qualitative research proposal. The process of writing a qualitative research proposal is discussed with regards to the most important questions that need to be answered in your research proposal with consideration of the guidelines of being practical, being persuasive, making broader links, aiming for crystal clarity and planning before you write. While the structure of the qualitative research proposal is discussed with regards to the key sections of the proposal, namely the cover page, abstract, introduction, review of the literature, research problem and research questions, research purpose and objectives, research paradigm, research design, research method, ethical considerations, dissemination plan, budget and appendices.

Qualitative and quantitative evaluation of rigid and deformable motion correction algorithms using dual-energy CT images in view of application to CT perfusion measurements in abdominal organs affected by breathing motion

PubMed Central

Skornitzke, S; Fritz, F; Klauss, M; Pahn, G; Hansen, J; Hirsch, J; Grenacher, L; Kauczor, H-U

2015-01-01

Objective: To compare six different scenarios for correcting for breathing motion in abdominal dual-energy CT (DECT) perfusion measurements. Methods: Rigid [RRComm(80 kVp)] and non-rigid [NRComm(80 kVp)] registration of commercially available CT perfusion software, custom non-rigid registration [NRCustom(80 kVp], demons algorithm) and a control group [CG(80 kVp)] without motion correction were evaluated using 80 kVp images. Additionally, NRCustom was applied to dual-energy (DE)-blended [NRCustom(DE)] and virtual non-contrast [NRCustom(VNC)] images, yielding six evaluated scenarios. After motion correction, perfusion maps were calculated using a combined maximum slope/Patlak model. For qualitative evaluation, three blinded radiologists independently rated motion correction quality and resulting perfusion maps on a four-point scale (4 = best, 1 = worst). For quantitative evaluation, relative changes in metric values, R2 and residuals of perfusion model fits were calculated. Results: For motion-corrected images, mean ratings differed significantly [NRCustom(80 kVp) and NRCustom(DE), 3.3; NRComm(80 kVp), 3.1; NRCustom(VNC), 2.9; RRComm(80 kVp), 2.7; CG(80 kVp), 2.7; all p < 0.05], except when comparing NRCustom(80 kVp) with NRCustom(DE) and RRComm(80 kVp) with CG(80 kVp). NRCustom(80 kVp) and NRCustom(DE) achieved the highest reduction in metric values [NRCustom(80 kVp), 48.5%; NRCustom(DE), 45.6%; NRComm(80 kVp), 29.2%; NRCustom(VNC), 22.8%; RRComm(80 kVp), 0.6%; CG(80 kVp), 0%]. Regarding perfusion maps, NRCustom(80 kVp) and NRCustom(DE) were rated highest [NRCustom(80 kVp), 3.1; NRCustom(DE), 3.0; NRComm(80 kVp), 2.8; NRCustom(VNC), 2.6; CG(80 kVp), 2.5; RRComm(80 kVp), 2.4] and had significantly higher R2 and lower residuals. Correlation between qualitative and quantitative evaluation was low to moderate. Conclusion: Non-rigid motion correction improves spatial alignment of the target region and fit of CT

MRPack: Multi-Algorithm Execution Using Compute-Intensive Approach in MapReduce

PubMed Central

2015-01-01

Large quantities of data have been generated from multiple sources at exponential rates in the last few years. These data are generated at high velocity as real time and streaming data in variety of formats. These characteristics give rise to challenges in its modeling, computation, and processing. Hadoop MapReduce (MR) is a well known data-intensive distributed processing framework using the distributed file system (DFS) for Big Data. Current implementations of MR only support execution of a single algorithm in the entire Hadoop cluster. In this paper, we propose MapReducePack (MRPack), a variation of MR that supports execution of a set of related algorithms in a single MR job. We exploit the computational capability of a cluster by increasing the compute-intensiveness of MapReduce while maintaining its data-intensive approach. It uses the available computing resources by dynamically managing the task assignment and intermediate data. Intermediate data from multiple algorithms are managed using multi-key and skew mitigation strategies. The performance study of the proposed system shows that it is time, I/O, and memory efficient compared to the default MapReduce. The proposed approach reduces the execution time by 200% with an approximate 50% decrease in I/O cost. Complexity and qualitative results analysis shows significant performance improvement. PMID:26305223

MRPack: Multi-Algorithm Execution Using Compute-Intensive Approach in MapReduce.

PubMed

Idris, Muhammad; Hussain, Shujaat; Siddiqi, Muhammad Hameed; Hassan, Waseem; Syed Muhammad Bilal, Hafiz; Lee, Sungyoung

2015-01-01

Large quantities of data have been generated from multiple sources at exponential rates in the last few years. These data are generated at high velocity as real time and streaming data in variety of formats. These characteristics give rise to challenges in its modeling, computation, and processing. Hadoop MapReduce (MR) is a well known data-intensive distributed processing framework using the distributed file system (DFS) for Big Data. Current implementations of MR only support execution of a single algorithm in the entire Hadoop cluster. In this paper, we propose MapReducePack (MRPack), a variation of MR that supports execution of a set of related algorithms in a single MR job. We exploit the computational capability of a cluster by increasing the compute-intensiveness of MapReduce while maintaining its data-intensive approach. It uses the available computing resources by dynamically managing the task assignment and intermediate data. Intermediate data from multiple algorithms are managed using multi-key and skew mitigation strategies. The performance study of the proposed system shows that it is time, I/O, and memory efficient compared to the default MapReduce. The proposed approach reduces the execution time by 200% with an approximate 50% decrease in I/O cost. Complexity and qualitative results analysis shows significant performance improvement.

Mapping chemicals in air using an environmental CAT scanning system: evaluation of algorithms

NASA Astrophysics Data System (ADS)

Samanta, A.; Todd, L. A.

A new technique is being developed which creates near real-time maps of chemical concentrations in air for environmental and occupational environmental applications. This technique, we call Environmental CAT Scanning, combines the real-time measuring technique of open-path Fourier transform infrared spectroscopy with the mapping capabilitites of computed tomography to produce two-dimensional concentration maps. With this system, a network of open-path measurements is obtained over an area; measurements are then processed using a tomographic algorithm to reconstruct the concentrations. This research focussed on the process of evaluating and selecting appropriate reconstruction algorithms, for use in the field, by using test concentration data from both computer simultation and laboratory chamber studies. Four algorithms were tested using three types of data: (1) experimental open-path data from studies that used a prototype opne-path Fourier transform/computed tomography system in an exposure chamber; (2) synthetic open-path data generated from maps created by kriging point samples taken in the chamber studies (in 1), and; (3) synthetic open-path data generated using a chemical dispersion model to create time seires maps. The iterative algorithms used to reconstruct the concentration data were: Algebraic Reconstruction Technique without Weights (ART1), Algebraic Reconstruction Technique with Weights (ARTW), Maximum Likelihood with Expectation Maximization (MLEM) and Multiplicative Algebraic Reconstruction Technique (MART). Maps were evaluated quantitatively and qualitatively. In general, MART and MLEM performed best, followed by ARTW and ART1. However, algorithm performance varied under different contaminant scenarios. This study showed the importance of using a variety of maps, particulary those generated using dispersion models. The time series maps provided a more rigorous test of the algorithms and allowed distinctions to be made among the algorithms. A

Comment on “Symplectic integration of magnetic systems”: A proof that the Boris algorithm is not variational

DOE PAGES

Ellison, C. L.; Burby, J. W.; Qin, H.

2015-11-01

One popular technique for the numerical time advance of charged particles interacting with electric and magnetic fields according to the Lorentz force law [1], [2], [3] and [4] is the Boris algorithm. Its popularity stems from simple implementation, rapid iteration, and excellent long-term numerical fidelity [1] and [5]. Excellent long-term behavior strongly suggests the numerical dynamics exhibit conservation laws analogous to those governing the continuous Lorentz force system [6]. Moreover, without conserved quantities to constrain the numerical dynamics, algorithms typically dissipate or accumulate important observables such as energy and momentum over long periods of simulated time [6]. Identification of themore » conservative properties of an algorithm is important for establishing rigorous expectations on the long-term behavior; energy-preserving, symplectic, and volume-preserving methods each have particular implications for the qualitative numerical behavior [6], [7], [8], [9], [10] and [11].« less

Potential for false positive HIV test results with the serial rapid HIV testing algorithm

PubMed Central

2012-01-01

Background Rapid HIV tests provide same-day results and are widely used in HIV testing programs in areas with limited personnel and laboratory infrastructure. The Uganda Ministry of Health currently recommends the serial rapid testing algorithm with Determine, STAT-PAK, and Uni-Gold for diagnosis of HIV infection. Using this algorithm, individuals who test positive on Determine, negative to STAT-PAK and positive to Uni-Gold are reported as HIV positive. We conducted further testing on this subgroup of samples using qualitative DNA PCR to assess the potential for false positive tests in this situation. Results Of the 3388 individuals who were tested, 984 were HIV positive on two consecutive tests, and 29 were considered positive by a tiebreaker (positive on Determine, negative on STAT-PAK, and positive on Uni-Gold). However, when the 29 samples were further tested using qualitative DNA PCR, 14 (48.2%) were HIV negative. Conclusion Although this study was not primarily designed to assess the validity of rapid HIV tests and thus only a subset of the samples were retested, the findings show a potential for false positive HIV results in the subset of individuals who test positive when a tiebreaker test is used in serial testing. These findings highlight a need for confirmatory testing for this category of individuals. PMID:22429706

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of <24%, 24-30%, >30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

Modeling pilot interaction with automated digital avionics systems: Guidance and control algorithms for contour and nap-of-the-Earth flight

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1990-01-01

A collection of technical papers are presented that cover modeling pilot interaction with automated digital avionics systems and guidance and control algorithms for contour and nap-of-the-earth flight. The titles of the papers presented are as follows: (1) Automation effects in a multiloop manual control system; (2) A qualitative model of human interaction with complex dynamic systems; (3) Generalized predictive control of dynamic systems; (4) An application of generalized predictive control to rotorcraft terrain-following flight; (5) Self-tuning generalized predictive control applied to terrain-following flight; and (6) Precise flight path control using a predictive algorithm.

The cascaded moving k-means and fuzzy c-means clustering algorithms for unsupervised segmentation of malaria images

NASA Astrophysics Data System (ADS)

Abdul-Nasir, Aimi Salihah; Mashor, Mohd Yusoff; Halim, Nurul Hazwani Abd; Mohamed, Zeehaida

2015-05-01

Malaria is a life-threatening parasitic infectious disease that corresponds for nearly one million deaths each year. Due to the requirement of prompt and accurate diagnosis of malaria, the current study has proposed an unsupervised pixel segmentation based on clustering algorithm in order to obtain the fully segmented red blood cells (RBCs) infected with malaria parasites based on the thin blood smear images of P. vivax species. In order to obtain the segmented infected cell, the malaria images are first enhanced by using modified global contrast stretching technique. Then, an unsupervised segmentation technique based on clustering algorithm has been applied on the intensity component of malaria image in order to segment the infected cell from its blood cells background. In this study, cascaded moving k-means (MKM) and fuzzy c-means (FCM) clustering algorithms has been proposed for malaria slide image segmentation. After that, median filter algorithm has been applied to smooth the image as well as to remove any unwanted regions such as small background pixels from the image. Finally, seeded region growing area extraction algorithm has been applied in order to remove large unwanted regions that are still appeared on the image due to their size in which cannot be cleaned by using median filter. The effectiveness of the proposed cascaded MKM and FCM clustering algorithms has been analyzed qualitatively and quantitatively by comparing the proposed cascaded clustering algorithm with MKM and FCM clustering algorithms. Overall, the results indicate that segmentation using the proposed cascaded clustering algorithm has produced the best segmentation performances by achieving acceptable sensitivity as well as high specificity and accuracy values compared to the segmentation results provided by MKM and FCM algorithms.

Comparison study of reconstruction algorithms for prototype digital breast tomosynthesis using various breast phantoms.

PubMed

Kim, Ye-seul; Park, Hye-suk; Lee, Haeng-Hwa; Choi, Young-Wook; Choi, Jae-Gu; Kim, Hak Hee; Kim, Hee-Joung

2016-02-01

Digital breast tomosynthesis (DBT) is a recently developed system for three-dimensional imaging that offers the potential to reduce the false positives of mammography by preventing tissue overlap. Many qualitative evaluations of digital breast tomosynthesis were previously performed by using a phantom with an unrealistic model and with heterogeneous background and noise, which is not representative of real breasts. The purpose of the present work was to compare reconstruction algorithms for DBT by using various breast phantoms; validation was also performed by using patient images. DBT was performed by using a prototype unit that was optimized for very low exposures and rapid readout. Three algorithms were compared: a back-projection (BP) algorithm, a filtered BP (FBP) algorithm, and an iterative expectation maximization (EM) algorithm. To compare the algorithms, three types of breast phantoms (homogeneous background phantom, heterogeneous background phantom, and anthropomorphic breast phantom) were evaluated, and clinical images were also reconstructed by using the different reconstruction algorithms. The in-plane image quality was evaluated based on the line profile and the contrast-to-noise ratio (CNR), and out-of-plane artifacts were evaluated by means of the artifact spread function (ASF). Parenchymal texture features of contrast and homogeneity were computed based on reconstructed images of an anthropomorphic breast phantom. The clinical images were studied to validate the effect of reconstruction algorithms. The results showed that the CNRs of masses reconstructed by using the EM algorithm were slightly higher than those obtained by using the BP algorithm, whereas the FBP algorithm yielded much lower CNR due to its high fluctuations of background noise. The FBP algorithm provides the best conspicuity for larger calcifications by enhancing their contrast and sharpness more than the other algorithms; however, in the case of small-size and low

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

DOE PAGES

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

2014-12-01

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

Enhancement of lung sounds based on empirical mode decomposition and Fourier transform algorithm.

PubMed

Mondal, Ashok; Banerjee, Poulami; Somkuwar, Ajay

2017-02-01

There is always heart sound (HS) signal interfering during the recording of lung sound (LS) signals. This obscures the features of LS signals and creates confusion on pathological states, if any, of the lungs. In this work, a new method is proposed for reduction of heart sound interference which is based on empirical mode decomposition (EMD) technique and prediction algorithm. In this approach, first the mixed signal is split into several components in terms of intrinsic mode functions (IMFs). Thereafter, HS-included segments are localized and removed from them. The missing values of the gap thus produced, is predicted by a new Fast Fourier Transform (FFT) based prediction algorithm and the time domain LS signal is reconstructed by taking an inverse FFT of the estimated missing values. The experiments have been conducted on simulated and recorded HS corrupted LS signals at three different flow rates and various SNR levels. The performance of the proposed method is evaluated by qualitative and quantitative analysis of the results. It is found that the proposed method is superior to the baseline method in terms of quantitative and qualitative measurement. The developed method gives better results compared to baseline method for different SNR levels. Our method gives cross correlation index (CCI) of 0.9488, signal to deviation ratio (SDR) of 9.8262, and normalized maximum amplitude error (NMAE) of 26.94 for 0 dB SNR value. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Image processing meta-algorithm development via genetic manipulation of existing algorithm graphs

NASA Astrophysics Data System (ADS)

Schalkoff, Robert J.; Shaaban, Khaled M.

1999-07-01

Automatic algorithm generation for image processing applications is not a new idea, however previous work is either restricted to morphological operates or impractical. In this paper, we show recent research result in the development and use of meta-algorithms, i.e. algorithms which lead to new algorithms. Although the concept is generally applicable, the application domain in this work is restricted to image processing. The meta-algorithm concept described in this paper is based upon out work in dynamic algorithm. The paper first present the concept of dynamic algorithms which, on the basis of training and archived algorithmic experience embedded in an algorithm graph (AG), dynamically adjust the sequence of operations applied to the input image data. Each node in the tree-based representation of a dynamic algorithm with out degree greater than 2 is a decision node. At these nodes, the algorithm examines the input data and determines which path will most likely achieve the desired results. This is currently done using nearest-neighbor classification. The details of this implementation are shown. The constrained perturbation of existing algorithm graphs, coupled with a suitable search strategy, is one mechanism to achieve meta-algorithm an doffers rich potential for the discovery of new algorithms. In our work, a meta-algorithm autonomously generates new dynamic algorithm graphs via genetic recombination of existing algorithm graphs. The AG representation is well suited to this genetic-like perturbation, using a commonly- employed technique in artificial neural network synthesis, namely the blueprint representation of graphs. A number of exam. One of the principal limitations of our current approach is the need for significant human input in the learning phase. Efforts to overcome this limitation are discussed. Future research directions are indicated.

Motion Cueing Algorithm Development: Piloted Performance Testing of the Cueing Algorithms

NASA Technical Reports Server (NTRS)

Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.; Kelly, Lon C.

2005-01-01

The relative effectiveness in simulating aircraft maneuvers with both current and newly developed motion cueing algorithms was assessed with an eleven-subject piloted performance evaluation conducted on the NASA Langley Visual Motion Simulator (VMS). In addition to the current NASA adaptive algorithm, two new cueing algorithms were evaluated: the optimal algorithm and the nonlinear algorithm. The test maneuvers included a straight-in approach with a rotating wind vector, an offset approach with severe turbulence and an on/off lateral gust that occurs as the aircraft approaches the runway threshold, and a takeoff both with and without engine failure after liftoff. The maneuvers were executed with each cueing algorithm with added visual display delay conditions ranging from zero to 200 msec. Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. Piloted performance parameters for the approach maneuvers, the vertical velocity upon touchdown and the runway touchdown position, were also analyzed but did not show any noticeable difference among the cueing algorithms. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input analysis shows pilot-induced oscillations on a straight-in approach were less prevalent compared to the optimal algorithm. The augmented turbulence cues increased workload on an offset approach that the pilots deemed more realistic compared to the NASA adaptive algorithm. The takeoff with engine failure showed the least roll activity for the nonlinear algorithm, with the least rudder pedal activity for the optimal algorithm.

Super-Encryption Implementation Using Monoalphabetic Algorithm and XOR Algorithm for Data Security

NASA Astrophysics Data System (ADS)

Rachmawati, Dian; Andri Budiman, Mohammad; Aulia, Indra

2018-03-01

The exchange of data that occurs offline and online is very vulnerable to the threat of data theft. In general, cryptography is a science and art to maintain data secrecy. An encryption is a cryptography algorithm in which data is transformed into cipher text, which is something that is unreadable and meaningless so it cannot be read or understood by other parties. In super-encryption, two or more encryption algorithms are combined to make it more secure. In this work, Monoalphabetic algorithm and XOR algorithm are combined to form a super- encryption. Monoalphabetic algorithm works by changing a particular letter into a new letter based on existing keywords while the XOR algorithm works by using logic operation XOR Since Monoalphabetic algorithm is a classical cryptographic algorithm and XOR algorithm is a modern cryptographic algorithm, this scheme is expected to be both easy-to-implement and more secure. The combination of the two algorithms is capable of securing the data and restoring it back to its original form (plaintext), so the data integrity is still ensured.

Tree tensor network approach to simulating Shor's algorithm

NASA Astrophysics Data System (ADS)

Dumitrescu, Eugene

2017-12-01

Constructively simulating quantum systems furthers our understanding of qualitative and quantitative features which may be analytically intractable. In this paper, we directly simulate and explore the entanglement structure present in the paradigmatic example for exponential quantum speedups: Shor's algorithm. To perform our simulation, we construct a dynamic tree tensor network which manifestly captures two salient circuit features for modular exponentiation. These are the natural two-register bipartition and the invariance of entanglement with respect to permutations of the top-register qubits. Our construction help identify the entanglement entropy properties, which we summarize by a scaling relation. Further, the tree network is efficiently projected onto a matrix product state from which we efficiently execute the quantum Fourier transform. Future simulation of quantum information states with tensor networks exploiting circuit symmetries is discussed.

Variational Algorithms for Test Particle Trajectories

NASA Astrophysics Data System (ADS)

Ellison, C. Leland; Finn, John M.; Qin, Hong; Tang, William M.

2015-11-01

The theory of variational integration provides a novel framework for constructing conservative numerical methods for magnetized test particle dynamics. The retention of conservation laws in the numerical time advance captures the correct qualitative behavior of the long time dynamics. For modeling the Lorentz force system, new variational integrators have been developed that are both symplectic and electromagnetically gauge invariant. For guiding center test particle dynamics, discretization of the phase-space action principle yields multistep variational algorithms, in general. Obtaining the desired long-term numerical fidelity requires mitigation of the multistep method's parasitic modes or applying a discretization scheme that possesses a discrete degeneracy to yield a one-step method. Dissipative effects may be modeled using Lagrange-D'Alembert variational principles. Numerical results will be presented using a new numerical platform that interfaces with popular equilibrium codes and utilizes parallel hardware to achieve reduced times to solution. This work was supported by DOE Contract DE-AC02-09CH11466.

A novel algorithm for solving the true coincident counting issues in Monte Carlo simulations for radiation spectroscopy.

PubMed

Guan, Fada; Johns, Jesse M; Vasudevan, Latha; Zhang, Guoqing; Tang, Xiaobin; Poston, John W; Braby, Leslie A

2015-06-01

Coincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel "multi-primary coincident counting" algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.

Linear feature detection algorithm for astronomical surveys - I. Algorithm description

NASA Astrophysics Data System (ADS)

Bektešević, Dino; Vinković, Dejan

2017-11-01

Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars and galaxies, ignoring completely the detection of existing linear features. With the emergence of wide-field sky surveys, linear features attract scientific interest as possible trails of fast flybys of near-Earth asteroids and meteors. In this work, we describe a new linear feature detection algorithm designed specifically for implementation in big data astronomy. The algorithm combines a series of algorithmic steps that first remove other objects (stars and galaxies) from the image and then enhance the line to enable more efficient line detection with the Hough algorithm. The rate of false positives is greatly reduced thanks to a step that replaces possible line segments with rectangles and then compares lines fitted to the rectangles with the lines obtained directly from the image. The speed of the algorithm and its applicability in astronomical surveys are also discussed.

ADMIT: a toolbox for guaranteed model invalidation, estimation and qualitative-quantitative modeling.

PubMed

Streif, Stefan; Savchenko, Anton; Rumschinski, Philipp; Borchers, Steffen; Findeisen, Rolf

2012-05-01

Often competing hypotheses for biochemical networks exist in the form of different mathematical models with unknown parameters. Considering available experimental data, it is then desired to reject model hypotheses that are inconsistent with the data, or to estimate the unknown parameters. However, these tasks are complicated because experimental data are typically sparse, uncertain, and are frequently only available in form of qualitative if-then observations. ADMIT (Analysis, Design and Model Invalidation Toolbox) is a MatLab(TM)-based tool for guaranteed model invalidation, state and parameter estimation. The toolbox allows the integration of quantitative measurement data, a priori knowledge of parameters and states, and qualitative information on the dynamic or steady-state behavior. A constraint satisfaction problem is automatically generated and algorithms are implemented for solving the desired estimation, invalidation or analysis tasks. The implemented methods built on convex relaxation and optimization and therefore provide guaranteed estimation results and certificates for invalidity. ADMIT, tutorials and illustrative examples are available free of charge for non-commercial use at http://ifatwww.et.uni-magdeburg.de/syst/ADMIT/

The Orthogonally Partitioned EM Algorithm: Extending the EM Algorithm for Algorithmic Stability and Bias Correction Due to Imperfect Data.

PubMed

Regier, Michael D; Moodie, Erica E M

2016-05-01

We propose an extension of the EM algorithm that exploits the common assumption of unique parameterization, corrects for biases due to missing data and measurement error, converges for the specified model when standard implementation of the EM algorithm has a low probability of convergence, and reduces a potentially complex algorithm into a sequence of smaller, simpler, self-contained EM algorithms. We use the theory surrounding the EM algorithm to derive the theoretical results of our proposal, showing that an optimal solution over the parameter space is obtained. A simulation study is used to explore the finite sample properties of the proposed extension when there is missing data and measurement error. We observe that partitioning the EM algorithm into simpler steps may provide better bias reduction in the estimation of model parameters. The ability to breakdown a complicated problem in to a series of simpler, more accessible problems will permit a broader implementation of the EM algorithm, permit the use of software packages that now implement and/or automate the EM algorithm, and make the EM algorithm more accessible to a wider and more general audience.

Getting added value from using qualitative research with randomized controlled trials: a qualitative interview study

PubMed Central

2014-01-01

Background Qualitative research is undertaken with randomized controlled trials of health interventions. Our aim was to explore the perceptions of researchers with experience of this endeavour to understand the added value of qualitative research to the trial in practice. Methods A telephone semi-structured interview study with 18 researchers with experience of undertaking the trial and/or the qualitative research. Results Interviewees described the added value of qualitative research for the trial, explaining how it solved problems at the pretrial stage, explained findings, and helped to increase the utility of the evidence generated by the trial. From the interviews, we identified three models of relationship of the qualitative research to the trial. In ‘the peripheral’ model, the trial was an opportunity to undertake qualitative research, with no intention that it would add value to the trial. In ‘the add-on’ model, the qualitative researcher understood the potential value of the qualitative research but it was viewed as a separate and complementary endeavour by the trial lead investigator and wider team. Interviewees described how this could limit the value of the qualitative research to the trial. Finally ‘the integral’ model played out in two ways. In ‘integral-in-theory’ studies, the lead investigator viewed the qualitative research as essential to the trial. However, in practice the qualitative research was under-resourced relative to the trial, potentially limiting its ability to add value to the trial. In ‘integral-in-practice’ studies, interviewees described how the qualitative research was planned from the beginning of the study, senior qualitative expertise was on the team from beginning to end, and staff and time were dedicated to the qualitative research. In these studies interviewees described the qualitative research adding value to the trial although this value was not necessarily visible beyond the original research team due

Getting added value from using qualitative research with randomized controlled trials: a qualitative interview study.

PubMed

O'Cathain, Alicia; Goode, Jackie; Drabble, Sarah J; Thomas, Kate J; Rudolph, Anne; Hewison, Jenny

2014-06-09

Qualitative research is undertaken with randomized controlled trials of health interventions. Our aim was to explore the perceptions of researchers with experience of this endeavour to understand the added value of qualitative research to the trial in practice. A telephone semi-structured interview study with 18 researchers with experience of undertaking the trial and/or the qualitative research. Interviewees described the added value of qualitative research for the trial, explaining how it solved problems at the pretrial stage, explained findings, and helped to increase the utility of the evidence generated by the trial. From the interviews, we identified three models of relationship of the qualitative research to the trial. In 'the peripheral' model, the trial was an opportunity to undertake qualitative research, with no intention that it would add value to the trial. In 'the add-on' model, the qualitative researcher understood the potential value of the qualitative research but it was viewed as a separate and complementary endeavour by the trial lead investigator and wider team. Interviewees described how this could limit the value of the qualitative research to the trial. Finally 'the integral' model played out in two ways. In 'integral-in-theory' studies, the lead investigator viewed the qualitative research as essential to the trial. However, in practice the qualitative research was under-resourced relative to the trial, potentially limiting its ability to add value to the trial. In 'integral-in-practice' studies, interviewees described how the qualitative research was planned from the beginning of the study, senior qualitative expertise was on the team from beginning to end, and staff and time were dedicated to the qualitative research. In these studies interviewees described the qualitative research adding value to the trial although this value was not necessarily visible beyond the original research team due to the challenges of publishing this research

Brain tumor segmentation in MR slices using improved GrowCut algorithm

NASA Astrophysics Data System (ADS)

Ji, Chunhong; Yu, Jinhua; Wang, Yuanyuan; Chen, Liang; Shi, Zhifeng; Mao, Ying

2015-12-01

The detection of brain tumor from MR images is very significant for medical diagnosis and treatment. However, the existing methods are mostly based on manual or semiautomatic segmentation which are awkward when dealing with a large amount of MR slices. In this paper, a new fully automatic method for the segmentation of brain tumors in MR slices is presented. Based on the hypothesis of the symmetric brain structure, the method improves the interactive GrowCut algorithm by further using the bounding box algorithm in the pre-processing step. More importantly, local reflectional symmetry is used to make up the deficiency of the bounding box method. After segmentation, 3D tumor image is reconstructed. We evaluate the accuracy of the proposed method on MR slices with synthetic tumors and actual clinical MR images. Result of the proposed method is compared with the actual position of simulated 3D tumor qualitatively and quantitatively. In addition, our automatic method produces equivalent performance as manual segmentation and the interactive GrowCut with manual interference while providing fully automatic segmentation.

Advanced image fusion algorithms for Gamma Knife treatment planning. Evaluation and proposal for clinical use.

PubMed

Apostolou, N; Papazoglou, Th; Koutsouris, D

2006-01-01

Image fusion is a process of combining information from multiple sensors. It is a useful tool implemented in the treatment planning programme of Gamma Knife Radiosurgery. In this paper we evaluate advanced image fusion algorithms for Matlab platform and head images. We develop nine level grayscale image fusion methods: average, principal component analysis (PCA), discrete wavelet transform (DWT) and Laplacian, filter - subtract - decimate (FSD), contrast, gradient, morphological pyramid and a shift invariant discrete wavelet transform (SIDWT) method in Matlab platform. We test these methods qualitatively and quantitatively. The quantitative criteria we use are the Root Mean Square Error (RMSE), the Mutual Information (MI), the Standard Deviation (STD), the Entropy (H), the Difference Entropy (DH) and the Cross Entropy (CEN). The qualitative are: natural appearance, brilliance contrast, presence of complementary features and enhancement of common features. Finally we make clinically useful suggestions.

Sampling in Qualitative Research

PubMed Central

LUBORSKY, MARK R.; RUBINSTEIN, ROBERT L.

2011-01-01

In gerontology the most recognized and elaborate discourse about sampling is generally thought to be in quantitative research associated with survey research and medical research. But sampling has long been a central concern in the social and humanistic inquiry, albeit in a different guise suited to the different goals. There is a need for more explicit discussion of qualitative sampling issues. This article will outline the guiding principles and rationales, features, and practices of sampling in qualitative research. It then describes common questions about sampling in qualitative research. In conclusion it proposes the concept of qualitative clarity as a set of principles (analogous to statistical power) to guide assessments of qualitative sampling in a particular study or proposal. PMID:22058580

a Comprehensive Review of Pansharpening Algorithms for GÖKTÜRK-2 Satellite Images

NASA Astrophysics Data System (ADS)

Kahraman, S.; Ertürk, A.

2017-11-01

In this paper, a comprehensive review and performance evaluation of pansharpening algorithms for GÖKTÜRK-2 images is presented. GÖKTÜRK-2 is the first high resolution remote sensing satellite of Turkey which was designed and built in Turkey, by The Ministry of Defence, TUBITAK-UZAY and Turkish Aerospace Industry (TUSAŞ) collectively. GÖKTÜRK-2 was launched at 18th. December 2012 in Jinguan, China and provides 2.5 meter panchromatic (PAN) and 5 meter multispectral (MS) spatial resolution satellite images. In this study, a large number of pansharpening algorithms are implemented and evaluated for performance on multiple GÖKTÜRK-2 satellite images. Quality assessments are conducted both qualitatively through visual results and quantitatively using Root Mean Square Error (RMSE), Correlation Coefficient (CC), Spectral Angle Mapper (SAM), Erreur Relative Globale Adimensionnelle de Synthése (ERGAS), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Universal Image Quality Index (UIQI).

Is Qualitative Research Second Class Science? A Quantitative Longitudinal Examination of Qualitative Research in Medical Journals

PubMed Central

Shuval, Kerem; Harker, Karen; Roudsari, Bahman; Groce, Nora E.; Mills, Britain; Siddiqi, Zoveen; Shachak, Aviv

2011-01-01

Background Qualitative research appears to be gaining acceptability in medical journals. Yet, little is actually known about the proportion of qualitative research and factors affecting its publication. This study describes the proportion of qualitative research over a 10 year period and correlates associated with its publication. Design A quantitative longitudinal examination of the proportion of original qualitative research in 67 journals of general medicine during a 10 year period (1998–2007). The proportion of qualitative research was determined by dividing original qualitative studies published (numerator) by all original research articles published (denominator). We used a generalized estimating equations approach to assess the longitudinal association between the proportion of qualitative studies and independent variables (i.e. journals' country of publication and impact factor; editorial/methodological papers discussing qualitative research; and specific journal guidelines pertaining to qualitative research). Findings A 2.9% absolute increase and 3.4-fold relative increase in qualitative research publications occurred over a 10 year period (1.2% in 1998 vs. 4.1% in 2007). The proportion of original qualitative research was independently and significantly associated with the publication of editorial/methodological papers in the journal (b = 3.688, P = 0.012); and with qualitative research specifically mentioned in guidelines for authors (b = 6.847, P<0.001). Additionally, a higher proportion of qualitative research was associated only with journals published in the UK in comparison to other countries, yet with borderline statistical significance (b = 1.776, P = 0.075). The journals' impact factor was not associated with the publication of qualitative research. Conclusions Despite an increase in the proportion of qualitative research in medical journals over a 10 year period, the proportion remains low. Journals' policies pertaining to

Rock climbing: A local-global algorithm to compute minimum energy and minimum free energy pathways.

PubMed

Templeton, Clark; Chen, Szu-Hua; Fathizadeh, Arman; Elber, Ron

2017-10-21

The calculation of minimum energy or minimum free energy paths is an important step in the quantitative and qualitative studies of chemical and physical processes. The computations of these coordinates present a significant challenge and have attracted considerable theoretical and computational interest. Here we present a new local-global approach to study reaction coordinates, based on a gradual optimization of an action. Like other global algorithms, it provides a path between known reactants and products, but it uses a local algorithm to extend the current path in small steps. The local-global approach does not require an initial guess to the path, a major challenge for global pathway finders. Finally, it provides an exact answer (the steepest descent path) at the end of the calculations. Numerical examples are provided for the Mueller potential and for a conformational transition in a solvated ring system.

Infrared spectroscopy reveals both qualitative and quantitative differences in equine subchondral bone during maturation

NASA Astrophysics Data System (ADS)

Kobrina, Yevgeniya; Isaksson, Hanna; Sinisaari, Miikka; Rieppo, Lassi; Brama, Pieter A.; van Weeren, René; Helminen, Heikki J.; Jurvelin, Jukka S.; Saarakkala, Simo

2010-11-01

The collagen phase in bone is known to undergo major changes during growth and maturation. The objective of this study is to clarify whether Fourier transform infrared (FTIR) microspectroscopy, coupled with cluster analysis, can detect quantitative and qualitative changes in the collagen matrix of subchondral bone in horses during maturation and growth. Equine subchondral bone samples (n = 29) from the proximal joint surface of the first phalanx are prepared from two sites subjected to different loading conditions. Three age groups are studied: newborn (0 days old), immature (5 to 11 months old), and adult (6 to 10 years old) horses. Spatial collagen content and collagen cross-link ratio are quantified from the spectra. Additionally, normalized second derivative spectra of samples are clustered using the k-means clustering algorithm. In quantitative analysis, collagen content in the subchondral bone increases rapidly between the newborn and immature horses. The collagen cross-link ratio increases significantly with age. In qualitative analysis, clustering is able to separate newborn and adult samples into two different groups. The immature samples display some nonhomogeneity. In conclusion, this is the first study showing that FTIR spectral imaging combined with clustering techniques can detect quantitative and qualitative changes in the collagen matrix of subchondral bone during growth and maturation.

Algorithm improvement program nuclide identification algorithm scoring criteria and scoring application.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Enghauser, Michael

2016-02-01

The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.

Analyzing milestoning networks for molecular kinetics: definitions, algorithms, and examples.

PubMed

Viswanath, Shruthi; Kreuzer, Steven M; Cardenas, Alfredo E; Elber, Ron

2013-11-07

Network representations are becoming increasingly popular for analyzing kinetic data from techniques like Milestoning, Markov State Models, and Transition Path Theory. Mapping continuous phase space trajectories into a relatively small number of discrete states helps in visualization of the data and in dissecting complex dynamics to concrete mechanisms. However, not only are molecular networks derived from molecular dynamics simulations growing in number, they are also getting increasingly complex, owing partly to the growth in computer power that allows us to generate longer and better converged trajectories. The increased complexity of the networks makes simple interpretation and qualitative insight of the molecular systems more difficult to achieve. In this paper, we focus on various network representations of kinetic data and algorithms to identify important edges and pathways in these networks. The kinetic data can be local and partial (such as the value of rate coefficients between states) or an exact solution to kinetic equations for the entire system (such as the stationary flux between vertices). In particular, we focus on the Milestoning method that provides fluxes as the main output. We proposed Global Maximum Weight Pathways as a useful tool for analyzing molecular mechanism in Milestoning networks. A closely related definition was made in the context of Transition Path Theory. We consider three algorithms to find Global Maximum Weight Pathways: Recursive Dijkstra's, Edge-Elimination, and Edge-List Bisection. The asymptotic efficiency of the algorithms is analyzed and numerical tests on finite networks show that Edge-List Bisection and Recursive Dijkstra's algorithms are most efficient for sparse and dense networks, respectively. Pathways are illustrated for two examples: helix unfolding and membrane permeation. Finally, we illustrate that networks based on local kinetic information can lead to incorrect interpretation of molecular mechanisms.

Double-Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear-Array Photoacoustic Imaging.

PubMed

Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Adabi, Saba; Nasiriavanaki, Mohammadreza

2018-01-01

Photoacoustic imaging (PAI) is an emerging medical imaging modality capable of providing high spatial resolution of Ultrasound (US) imaging and high contrast of optical imaging. Delay-and-Sum (DAS) is the most common beamforming algorithm in PAI. However, using DAS beamformer leads to low resolution images and considerable contribution of off-axis signals. A new paradigm namely delay-multiply-and-sum (DMAS), which was originally used as a reconstruction algorithm in confocal microwave imaging, was introduced to overcome the challenges in DAS. DMAS was used in PAI systems and it was shown that this algorithm results in resolution improvement and sidelobe degrading. However, DMAS is still sensitive to high levels of noise, and resolution improvement is not satisfying. Here, we propose a novel algorithm based on DAS algebra inside DMAS formula expansion, double stage DMAS (DS-DMAS), which improves the image resolution and levels of sidelobe, and is much less sensitive to high level of noise compared to DMAS. The performance of DS-DMAS algorithm is evaluated numerically and experimentally. The resulted images are evaluated qualitatively and quantitatively using established quality metrics including signal-to-noise ratio (SNR), full-width-half-maximum (FWHM) and contrast ratio (CR). It is shown that DS-DMAS outperforms DAS and DMAS at the expense of higher computational load. DS-DMAS reduces the lateral valley for about 15 dB and improves the SNR and FWHM better than 13% and 30%, respectively. Moreover, the levels of sidelobe are reduced for about 10 dB in comparison with those in DMAS.

Network methods to support user involvement in qualitative data analyses: an introduction to Participatory Theme Elicitation.

PubMed

Best, Paul; Badham, Jennifer; Corepal, Rekesh; O'Neill, Roisin F; Tully, Mark A; Kee, Frank; Hunter, Ruth F

2017-11-23

While Patient and Public Involvement (PPI) is encouraged throughout the research process, engagement is typically limited to intervention design and post-analysis stages. There are few approaches to participatory data analyses within complex health interventions. Using qualitative data from a feasibility randomised controlled trial (RCT), this proof-of-concept study tests the value of a new approach to participatory data analysis called Participatory Theme Elicitation (PTE). Forty excerpts were given to eight members of a youth advisory PPI panel to sort into piles based on their perception of related thematic content. Using algorithms to detect communities in networks, excerpts were then assigned to a thematic cluster that combined the panel members' perspectives. Network analysis techniques were also used to identify key excerpts in each grouping that were then further explored qualitatively. While PTE analysis was, for the most part, consistent with the researcher-led analysis, young people also identified new emerging thematic content. PTE appears promising for encouraging user led identification of themes arising from qualitative data collected during complex interventions. Further work is required to validate and extend this method. ClinicalTrials.gov, ID: NCT02455986 . Retrospectively Registered on 21 May 2015.

Diagnosing acute HIV infection: The performance of quantitative HIV-1 RNA testing (viral load) in the 2014 laboratory testing algorithm.

PubMed

Wu, Hsiu; Cohen, Stephanie E; Westheimer, Emily; Gay, Cynthia L; Hall, Laura; Rose, Charles; Hightow-Weidman, Lisa B; Gose, Severin; Fu, Jie; Peters, Philip J

2017-08-01

New recommendations for laboratory diagnosis of HIV infection in the United States were published in 2014. The updated testing algorithm includes a qualitative HIV-1 RNA assay to resolve discordant immunoassay results and to identify acute HIV-1 infection (AHI). The qualitative HIV-1 RNA assay is not widely available; therefore, we evaluated the performance of a more widely available quantitative HIV-1 RNA assay, viral load, for diagnosing AHI. We determined that quantitative viral loads consistently distinguished AHI from a false-positive immunoassay result. Among 100 study participants with AHI and a viral load result, the estimated geometric mean viral load was 1,377,793copies/mL. Copyright © 2017 Elsevier B.V. All rights reserved.

The impact of smart metal artefact reduction algorithm for use in radiotherapy treatment planning.

PubMed

Guilfoile, Connor; Rampant, Peter; House, Michael

2017-06-01

The presence of metal artefacts in computed tomography (CT) create issues in radiation oncology. The loss of anatomical information and incorrect Hounsfield unit (HU) values produce inaccuracies in dose calculations, providing suboptimal patient treatment. Metal artefact reduction (MAR) algorithms were developed to combat these problems. This study provides a qualitative and quantitative analysis of the "Smart MAR" software (General Electric Healthcare, Chicago, IL, USA), determining its usefulness in a clinical setting. A detailed analysis was conducted using both patient and phantom data, noting any improvements in HU values and dosimetry with the GE-MAR enabled. This study indicates qualitative improvements in severity of the streak artefacts produced by metals, allowing for easier patient contouring. Furthermore, the GE-MAR managed to recover previously lost anatomical information. Additionally, phantom data showed an improvement in HU value with GE-MAR correction, producing more accurate point dose calculations in the treatment planning system. Overall, the GE-MAR is a useful tool and is suitable for clinical environments.

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

NASA Astrophysics Data System (ADS)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

Adaptive cockroach swarm algorithm

NASA Astrophysics Data System (ADS)

Obagbuwa, Ibidun C.; Abidoye, Ademola P.

2017-07-01

An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.

Robustness analysis of superpixel algorithms to image blur, additive Gaussian noise, and impulse noise

NASA Astrophysics Data System (ADS)

Brekhna, Brekhna; Mahmood, Arif; Zhou, Yuanfeng; Zhang, Caiming

2017-11-01

Superpixels have gradually become popular in computer vision and image processing applications. However, no comprehensive study has been performed to evaluate the robustness of superpixel algorithms in regard to common forms of noise in natural images. We evaluated the robustness of 11 recently proposed algorithms to different types of noise. The images were corrupted with various degrees of Gaussian blur, additive white Gaussian noise, and impulse noise that either made the object boundaries weak or added extra information to it. We performed a robustness analysis of simple linear iterative clustering (SLIC), Voronoi Cells (VCells), flooding-based superpixel generation (FCCS), bilateral geodesic distance (Bilateral-G), superpixel via geodesic distance (SSS-G), manifold SLIC (M-SLIC), Turbopixels, superpixels extracted via energy-driven sampling (SEEDS), lazy random walk (LRW), real-time superpixel segmentation by DBSCAN clustering, and video supervoxels using partially absorbing random walks (PARW) algorithms. The evaluation process was carried out both qualitatively and quantitatively. For quantitative performance comparison, we used achievable segmentation accuracy (ASA), compactness, under-segmentation error (USE), and boundary recall (BR) on the Berkeley image database. The results demonstrated that all algorithms suffered performance degradation due to noise. For Gaussian blur, Bilateral-G exhibited optimal results for ASA and USE measures, SLIC yielded optimal compactness, whereas FCCS and DBSCAN remained optimal for BR. For the case of additive Gaussian and impulse noises, FCCS exhibited optimal results for ASA, USE, and BR, whereas Bilateral-G remained a close competitor in ASA and USE for Gaussian noise only. Additionally, Turbopixel demonstrated optimal performance for compactness for both types of noise. Thus, no single algorithm was able to yield optimal results for all three types of noise across all performance measures. Conclusively, to solve real

Overview of qualitative research.

PubMed

Grossoehme, Daniel H

2014-01-01

Qualitative research methods are a robust tool for chaplaincy research questions. Similar to much of chaplaincy clinical care, qualitative research generally works with written texts, often transcriptions of individual interviews or focus group conversations and seeks to understand the meaning of experience in a study sample. This article describes three common methodologies: ethnography, grounded theory, and phenomenology. Issues to consider relating to the study sample, design, and analysis are discussed. Enhancing the validity of the data, as well reliability and ethical issues in qualitative research are described. Qualitative research is an accessible way for chaplains to contribute new knowledge about the sacred dimension of people's lived experience.

Segmentation of the hippocampus by transferring algorithmic knowledge for large cohort processing.

PubMed

Thyreau, Benjamin; Sato, Kazunori; Fukuda, Hiroshi; Taki, Yasuyuki

2018-01-01

The hippocampus is a particularly interesting target for neuroscience research studies due to its essential role within the human brain. In large human cohort studies, bilateral hippocampal structures are frequently identified and measured to gain insight into human behaviour or genomic variability in neuropsychiatric disorders of interest. Automatic segmentation is performed using various algorithms, with FreeSurfer being a popular option. In this manuscript, we present a method to segment the bilateral hippocampus using a deep-learned appearance model. Deep convolutional neural networks (ConvNets) have shown great success in recent years, due to their ability to learn meaningful features from a mass of training data. Our method relies on the following key novelties: (i) we use a wide and variable training set coming from multiple cohorts (ii) our training labels come in part from the output of the FreeSurfer algorithm, and (iii) we include synthetic data and use a powerful data augmentation scheme. Our method proves to be robust, and it has fast inference (<30s total per subject), with trained model available online (https://github.com/bthyreau/hippodeep). We depict illustrative results and show extensive qualitative and quantitative cohort-wide comparisons with FreeSurfer. Our work demonstrates that deep neural-network methods can easily encode, and even improve, existing anatomical knowledge, even when this knowledge exists in algorithmic form. Copyright © 2017 Elsevier B.V. All rights reserved.

Situating methodology within qualitative research.

PubMed

Kramer-Kile, Marnie L

2012-01-01

Qualitative nurse researchers are required to make deliberate and sometimes complex methodological decisions about their work. Methodology in qualitative research is a comprehensive approach in which theory (ideas) and method (doing) are brought into close alignment. It can be difficult, at times, to understand the concept of methodology. The purpose of this research column is to: (1) define qualitative methodology; (2) illuminate the relationship between epistemology, ontology and methodology; (3) explicate the connection between theory and method in qualitative research design; and 4) highlight relevant examples of methodological decisions made within cardiovascular nursing research. Although there is no "one set way" to do qualitative research, all qualitative researchers should account for the choices they make throughout the research process and articulate their methodological decision-making along the way.

Qualitative research methods for medical educators.

PubMed

Hanson, Janice L; Balmer, Dorene F; Giardino, Angelo P

2011-01-01

This paper provides a primer for qualitative research in medical education. Our aim is to equip readers with a basic understanding of qualitative research and prepare them to judge the goodness of fit between qualitative research and their own research questions. We provide an overview of the reasons for choosing a qualitative research approach and potential benefits of using these methods for systematic investigation. We discuss developing qualitative research questions, grounding research in a philosophical framework, and applying rigorous methods of data collection, sampling, and analysis. We also address methods to establish the trustworthiness of a qualitative study and introduce the reader to ethical concerns that warrant special attention when planning qualitative research. We conclude with a worksheet that readers may use for designing a qualitative study. Medical educators ask many questions that carefully designed qualitative research would address effectively. Careful attention to the design of qualitative studies will help to ensure credible answers that will illuminate many of the issues, challenges, and quandaries that arise while doing the work of medical education. Copyright © 2011 Academic Pediatric Association. All rights reserved.

Parallel consistent labeling algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samal, A.; Henderson, T.

Mackworth and Freuder have analyzed the time complexity of several constraint satisfaction algorithms. Mohr and Henderson have given new algorithms, AC-4 and PC-3, for arc and path consistency, respectively, and have shown that the arc consistency algorithm is optimal in time complexity and of the same order space complexity as the earlier algorithms. In this paper, they give parallel algorithms for solving node and arc consistency. They show that any parallel algorithm for enforcing arc consistency in the worst case must have O(na) sequential steps, where n is number of nodes, and a is the number of labels per node.more » They give several parallel algorithms to do arc consistency. It is also shown that they all have optimal time complexity. The results of running the parallel algorithms on a BBN Butterfly multiprocessor are also presented.« less

3D optic disc reconstruction via a global fundus stereo algorithm.

PubMed

Bansal, M; Sizintsev, M; Eledath, J; Sawhney, H; Pearson, D J; Stone, R A

2013-01-01

This paper presents a novel method to recover 3D structure of the optic disc in the retina from two uncalibrated fundus images. Retinal images are commonly uncalibrated when acquired clinically, creating rectification challenges as well as significant radiometric and blur differences within the stereo pair. By exploiting structural peculiarities of the retina, we modified the Graph Cuts computational stereo method (one of current state-of-the-art methods) to yield a high quality algorithm for fundus stereo reconstruction. Extensive qualitative and quantitative experimental evaluation (where OCT scans are used as 3D ground truth) on our and publicly available datasets shows the superiority of the proposed method in comparison to other alternatives.

Algorithm That Synthesizes Other Algorithms for Hashing

NASA Technical Reports Server (NTRS)

James, Mark

2010-01-01

An algorithm that includes a collection of several subalgorithms has been devised as a means of synthesizing still other algorithms (which could include computer code) that utilize hashing to determine whether an element (typically, a number or other datum) is a member of a set (typically, a list of numbers). Each subalgorithm synthesizes an algorithm (e.g., a block of code) that maps a static set of key hashes to a somewhat linear monotonically increasing sequence of integers. The goal in formulating this mapping is to cause the length of the sequence thus generated to be as close as practicable to the original length of the set and thus to minimize gaps between the elements. The advantage of the approach embodied in this algorithm is that it completely avoids the traditional approach of hash-key look-ups that involve either secondary hash generation and look-up or further searching of a hash table for a desired key in the event of collisions. This algorithm guarantees that it will never be necessary to perform a search or to generate a secondary key in order to determine whether an element is a member of a set. This algorithm further guarantees that any algorithm that it synthesizes can be executed in constant time. To enforce these guarantees, the subalgorithms are formulated to employ a set of techniques, each of which works very effectively covering a certain class of hash-key values. These subalgorithms are of two types, summarized as follows: Given a list of numbers, try to find one or more solutions in which, if each number is shifted to the right by a constant number of bits and then masked with a rotating mask that isolates a set of bits, a unique number is thereby generated. In a variant of the foregoing procedure, omit the masking. Try various combinations of shifting, masking, and/or offsets until the solutions are found. From the set of solutions, select the one that provides the greatest compression for the representation and is executable in the

Strategic Control Algorithm Development : Volume 3. Strategic Algorithm Report.

DOT National Transportation Integrated Search

1974-08-01

The strategic algorithm report presents a detailed description of the functional basic strategic control arrival algorithm. This description is independent of a particular computer or language. Contained in this discussion are the geometrical and env...

Visualizing Qualitative Information

ERIC Educational Resources Information Center

Slone, Debra J.

2009-01-01

The abundance of qualitative data in today's society and the need to easily scrutinize, digest, and share this information calls for effective visualization and analysis tools. Yet, no existing qualitative tools have the analytic power, visual effectiveness, and universality of familiar quantitative instruments like bar charts, scatter-plots, and…

A new morphology algorithm for shoreline extraction from DEM data

NASA Astrophysics Data System (ADS)

Yousef, Amr H.; Iftekharuddin, Khan; Karim, Mohammad

2013-03-01

Digital elevation models (DEMs) are a digital representation of elevations at regularly spaced points. They provide an accurate tool to extract the shoreline profiles. One of the emerging sources of creating them is light detection and ranging (LiDAR) that can capture a highly dense cloud points with high resolution that can reach 15 cm and 100 cm in the vertical and horizontal directions respectively in short periods of time. In this paper we present a multi-step morphological algorithm to extract shorelines locations from the DEM data and a predefined tidal datum. Unlike similar approaches, it utilizes Lowess nonparametric regression to estimate the missing values within the DEM file. Also, it will detect and eliminate the outliers and errors that result from waves, ships, etc by means of anomality test with neighborhood constrains. Because, there might be some significant broken regions such as branches and islands, it utilizes a constrained morphological open and close to reduce these artifacts that can affect the extracted shorelines. In addition, it eliminates docks, bridges and fishing piers along the extracted shorelines by means of Hough transform. Based on a specific tidal datum, the algorithm will segment the DEM data into water and land objects. Without sacrificing the accuracy and the spatial details of the extracted boundaries, the algorithm should smooth and extract the shoreline profiles by tracing the boundary pixels between the land and the water segments. For given tidal values, we qualitatively assess the visual quality of the extracted shorelines by superimposing them on the available aerial photographs.

Positivism and qualitative nursing research.

PubMed

Paley, J

2001-01-01

Despite the hostility to positivism shown by qualitative methodologists in nursing, as in other disciplines, the epistemological and ontological instincts of qualitative researchers seem to coincide with those of the positivists, especially Bayesian positivists. This article suggests that positivists and qualitative researchers alike are pro-observation, proinduction, pro-plausibility and pro-subjectivity. They are also anti-cause, anti-realist, anti-explanation, anti-correspondence, anti-truth. In only one respect is there a significant difference between positivist and qualitative methodologists: most positivists have believed that, methodologically, the natural sciences and the social sciences are the same; most qualitative researchers are adamant that they are not. However, if positivism fails as a philosophy of the natural sciences (which it probably does), it might well succeed as a philosophy of the social sciences, just because there is a methodological watershed between the two. Reflex antagonism to positivism might therefore be a major obstacle to understanding the real reasons why qualitative research and the natural sciences are methodologically divergent; and less hostility on the part of qualitative nurse researchers might bring certain advantages in its wake.

Performance of Machine Learning Algorithms for Qualitative and Quantitative Prediction Drug Blockade of hERG1 channel.

PubMed

Wacker, Soren; Noskov, Sergei Yu

2018-05-01

Drug-induced abnormal heart rhythm known as Torsades de Pointes (TdP) is a potential lethal ventricular tachycardia found in many patients. Even newly released anti-arrhythmic drugs, like ivabradine with HCN channel as a primary target, block the hERG potassium current in overlapping concentration interval. Promiscuous drug block to hERG channel may potentially lead to perturbation of the action potential duration (APD) and TdP, especially when with combined with polypharmacy and/or electrolyte disturbances. The example of novel anti-arrhythmic ivabradine illustrates clinically important and ongoing deficit in drug design and warrants for better screening methods. There is an urgent need to develop new approaches for rapid and accurate assessment of how drugs with complex interactions and multiple subcellular targets can predispose or protect from drug-induced TdP. One of the unexpected outcomes of compulsory hERG screening implemented in USA and European Union resulted in large datasets of IC 50 values for various molecules entering the market. The abundant data allows now to construct predictive machine-learning (ML) models. Novel ML algorithms and techniques promise better accuracy in determining IC 50 values of hERG blockade that is comparable or surpassing that of the earlier QSAR or molecular modeling technique. To test the performance of modern ML techniques, we have developed a computational platform integrating various workflows for quantitative structure activity relationship (QSAR) models using data from the ChEMBL database. To establish predictive powers of ML-based algorithms we computed IC 50 values for large dataset of molecules and compared it to automated patch clamp system for a large dataset of hERG blocking and non-blocking drugs, an industry gold standard in studies of cardiotoxicity. The optimal protocol with high sensitivity and predictive power is based on the novel eXtreme gradient boosting (XGBoost) algorithm. The ML-platform with XGBoost

[Qualitative Research in Health Services Research - Discussion Paper, Part 3: Quality of Qualitative Research].

PubMed

Stamer, M; Güthlin, C; Holmberg, C; Karbach, U; Patzelt, C; Meyer, T

2015-12-01

The third and final discussion paper of the German Network of Health Services Research's (DNVF) "Qualitative Methods Working Group" demonstrates methods for the evaluation and quality of qualitative research in health services research. In this paper we discuss approaches described in evaluating qualitative studies, including: an orientation to the general principles of empirical research, an approach-specific course of action, as well as procedures based on the research-process and criteria-oriented approaches. Divided into general and specific aspects to be considered in a qualitative study quality evaluation, the central focus of the discussion paper undertakes an extensive examination of the process and criteria-oriented approaches. The general aspects include the participation of relevant groups in the research process as well as ethical aspects of the research and data protection issues. The more specific aspects in evaluating the quality of qualitative research include considerations about the research interest, research questions, and the selection of data collection methods and types of analyses. The formulated questions are intended to guide reviewers and researchers to evaluate and to develop qualitative research projects appropriately. The intention of this discussion paper is to ensure a transparent research culture, and to reflect on and discuss the methodological and research approach of qualitative studies in health services research. With this paper we aim to initiate a discussion on high quality evaluation of qualitative health services research. © Georg Thieme Verlag KG Stuttgart · New York.

Quick fuzzy backpropagation algorithm.

PubMed

Nikov, A; Stoeva, S

2001-03-01

A modification of the fuzzy backpropagation (FBP) algorithm called QuickFBP algorithm is proposed, where the computation of the net function is significantly quicker. It is proved that the FBP algorithm is of exponential time complexity, while the QuickFBP algorithm is of polynomial time complexity. Convergence conditions of the QuickFBP, resp. the FBP algorithm are defined and proved for: (1) single output neural networks in case of training patterns with different targets; and (2) multiple output neural networks in case of training patterns with equivalued target vector. They support the automation of the weights training process (quasi-unsupervised learning) establishing the target value(s) depending on the network's input values. In these cases the simulation results confirm the convergence of both algorithms. An example with a large-sized neural network illustrates the significantly greater training speed of the QuickFBP rather than the FBP algorithm. The adaptation of an interactive web system to users on the basis of the QuickFBP algorithm is presented. Since the QuickFBP algorithm ensures quasi-unsupervised learning, this implies its broad applicability in areas of adaptive and adaptable interactive systems, data mining, etc. applications.

Algorithm Improvement Program Nuclide Identification Algorithm Scoring Criteria And Scoring Application - DNDO.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Enghauser, Michael

2015-02-01

The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.

Effect of Non-rigid Registration Algorithms on Deformation Based Morphometry: A Comparative Study with Control and Williams Syndrome Subjects

PubMed Central

Han, Zhaoying; Thornton-Wells, Tricia A.; Dykens, Elisabeth M.; Gore, John C.; Dawant, Benoit M.

2014-01-01

Deformation Based Morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by non-rigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared non-rigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established non-rigid registration algorithms using thirteen subjects with Williams Syndrome (WS) and thirteen Normal Control (NC) subjects. The five non-rigid registration algorithms include: (1) The Adaptive Bases Algorithm (ABA); (2) The Image Registration Toolkit (IRTK); (3) The FSL Nonlinear Image Registration Tool (FSL); (4) The Automatic Registration Tool (ART); and (5) the normalization algorithm available in SPM8. Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. The unique nature of the data set used in this study also permits comparison of visible anatomical differences between the groups and regions of difference detected by each algorithm. Results show that the interpretation of DBM results is difficult. Four out of the five algorithms we have evaluated detect bilateral differences between the two groups in the insular cortex, the basal ganglia, orbitofrontal cortex, as well as in the cerebellum. These correspond to differences that have been reported in the literature and that are visible in our samples. But our results also show that some algorithms detect regions that are not detected by the others and that the extent of the detected regions varies from algorithm to algorithm. These results suggest

Fault Detection of Roller-Bearings Using Signal Processing and Optimization Algorithms

PubMed Central

Kwak, Dae-Ho; Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2014-01-01

This study presents a fault detection of roller bearings through signal processing and optimization techniques. After the occurrence of scratch-type defects on the inner race of bearings, variations of kurtosis values are investigated in terms of two different data processing techniques: minimum entropy deconvolution (MED), and the Teager-Kaiser Energy Operator (TKEO). MED and the TKEO are employed to qualitatively enhance the discrimination of defect-induced repeating peaks on bearing vibration data with measurement noise. Given the perspective of the execution sequence of MED and the TKEO, the study found that the kurtosis sensitivity towards a defect on bearings could be highly improved. Also, the vibration signal from both healthy and damaged bearings is decomposed into multiple intrinsic mode functions (IMFs), through empirical mode decomposition (EMD). The weight vectors of IMFs become design variables for a genetic algorithm (GA). The weights of each IMF can be optimized through the genetic algorithm, to enhance the sensitivity of kurtosis on damaged bearing signals. Experimental results show that the EMD-GA approach successfully improved the resolution of detectability between a roller bearing with defect, and an intact system. PMID:24368701

What Is Qualitative Research?

PubMed

Otani, Takashi

2017-01-01

The article is an in-depth explanation of qualitative research, an approach increasingly prevalent among today's research communities. After discussing its present spread within the health sciences, the author addresses: 1. Its definition. 2. Its characteristics, as well as its theoretical and procedural background. 3. Its procedures. 4. Differences between qualitative and quantitative approaches. 5. Mixed methods incorporating quantitative research. And in conclusion: 6. The importance of establishing an epistemological perspective in qualitative research.

Qualitative Case Study Guidelines

DTIC Science & Technology

2013-11-01

Introduction to Sociological Methods. 2nd ed. New York, McGraw-Hill 14. Denzin , N. K. and Lincoln , Y. S. (2011) The SAGE Handbook of Qualitative...The Art of Science. In: Denzin , N. K. and Lincoln , Y. S. (eds.) Handbook of Qualitative Research. Thousand Oaks, Sage 19. GAO (1990) Case Study...Rinehart & Winston 39. Stake, R. E. (1994) Case Studies. In: Denzin , N. K. and Lincoln , Y. S. (eds.) Handbook of Qualitative Research. Thousand Oaks, Sage

Approach to estimation of level of information security at enterprise based on genetic algorithm

NASA Astrophysics Data System (ADS)

V, Stepanov L.; V, Parinov A.; P, Korotkikh L.; S, Koltsov A.

2018-05-01

In the article, the way of formalization of different types of threats of information security and vulnerabilities of an information system of the enterprise and establishment is considered. In a type of complexity of ensuring information security of application of any new organized system, the concept and decisions in the sphere of information security are expedient. One of such approaches is the method of a genetic algorithm. For the enterprises of any fields of activity, the question of complex estimation of the level of security of information systems taking into account the quantitative and qualitative factors characterizing components of information security is relevant.

Conducting Qualitative Data Analysis: Qualitative Data Analysis as a Metaphoric Process

ERIC Educational Resources Information Center

Chenail, Ronald J.

2012-01-01

In the second of a series of "how-to" essays on conducting qualitative data analysis, Ron Chenail argues the process can best be understood as a metaphoric process. From this orientation he suggests researchers follow Kenneth Burke's notion of metaphor and see qualitative data analysis as the analyst systematically considering the "this-ness" of…

Improved multivariate polynomial factoring algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, P.S.

1978-10-01

A new algorithm for factoring multivariate polynomials over the integers based on an algorithm by Wang and Rothschild is described. The new algorithm has improved strategies for dealing with the known problems of the original algorithm, namely, the leading coefficient problem, the bad-zero problem and the occurrence of extraneous factors. It has an algorithm for correctly predetermining leading coefficients of the factors. A new and efficient p-adic algorithm named EEZ is described. Bascially it is a linearly convergent variable-by-variable parallel construction. The improved algorithm is generally faster and requires less store then the original algorithm. Machine examples with comparative timingmore » are included.« less

Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling.

PubMed

de Santos-Sierra, Daniel; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A; Ayali, Amir; Anava, Sarit; Sánchez-Ávila, Carmen; Boccaletti, Stefano

2015-06-01

Large scale phase-contrast images taken at high resolution through the life of a cultured neuronal network are analyzed by a graph-based unsupervised segmentation algorithm with a very low computational cost, scaling linearly with the image size. The processing automatically retrieves the whole network structure, an object whose mathematical representation is a matrix in which nodes are identified neurons or neurons' clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocytochemistry techniques, our non invasive measures entitle us to perform a longitudinal analysis during the maturation of a single culture. Such an analysis furnishes the way of individuating the main physical processes underlying the self-organization of the neurons' ensemble into a complex network, and drives the formulation of a phenomenological model yet able to describe qualitatively the overall scenario observed during the culture growth. © 2014 International Society for Advancement of Cytometry.

Algorithmic and user study of an autocompletion algorithm on a large medical vocabulary.

PubMed

Sevenster, Merlijn; van Ommering, Rob; Qian, Yuechen

2012-02-01

Autocompletion supports human-computer interaction in software applications that let users enter textual data. We will be inspired by the use case in which medical professionals enter ontology concepts, catering the ongoing demand for structured and standardized data in medicine. Goal is to give an algorithmic analysis of one particular autocompletion algorithm, called multi-prefix matching algorithm, which suggests terms whose words' prefixes contain all words in the string typed by the user, e.g., in this sense, opt ner me matches optic nerve meningioma. Second we aim to investigate how well it supports users entering concepts from a large and comprehensive medical vocabulary (snomed ct). We give a concise description of the multi-prefix algorithm, and sketch how it can be optimized to meet required response time. Performance will be compared to a baseline algorithm, which gives suggestions that extend the string typed by the user to the right, e.g. optic nerve m gives optic nerve meningioma, but opt ner me does not. We conduct a user experiment in which 12 participants are invited to complete 40 snomed ct terms with the baseline algorithm and another set of 40 snomed ct terms with the multi-prefix algorithm. Our results show that users need significantly fewer keystrokes when supported by the multi-prefix algorithm than when supported by the baseline algorithm. The proposed algorithm is a competitive candidate for searching and retrieving terms from a large medical ontology. Copyright © 2011 Elsevier Inc. All rights reserved.

Qualitative Approaches to Evaluating Education.

ERIC Educational Resources Information Center

Fetterman, David M.

This paper explores the variety of qualitative methods available, in the context of a larger quantitative-qualitative debate in the field of educational evaluation. Each approach is reviewed in terms of the work of its major proponents. The dominant forms of qualitative evaluation include: (1) ethnography; (2) naturalistic inquiry; (3) generic…

Optimal Fungal Space Searching Algorithms.

PubMed

Asenova, Elitsa; Lin, Hsin-Yu; Fu, Eileen; Nicolau, Dan V; Nicolau, Dan V

2016-10-01

Previous experiments have shown that fungi use an efficient natural algorithm for searching the space available for their growth in micro-confined networks, e.g., mazes. This natural "master" algorithm, which comprises two "slave" sub-algorithms, i.e., collision-induced branching and directional memory, has been shown to be more efficient than alternatives, with one, or the other, or both sub-algorithms turned off. In contrast, the present contribution compares the performance of the fungal natural algorithm against several standard artificial homologues. It was found that the space-searching fungal algorithm consistently outperforms uninformed algorithms, such as Depth-First-Search (DFS). Furthermore, while the natural algorithm is inferior to informed ones, such as A*, this under-performance does not importantly increase with the increase of the size of the maze. These findings suggest that a systematic effort of harvesting the natural space searching algorithms used by microorganisms is warranted and possibly overdue. These natural algorithms, if efficient, can be reverse-engineered for graph and tree search strategies.

Knowledge representation and qualitative simulation of salmon redd functioning. Part I: qualitative modeling and simulation.

PubMed

Guerrin, F; Dumas, J

2001-02-01

This work aims at representing empirical knowledge of freshwater ecologists on the functioning of salmon redds (spawning areas of salmon) and its impact on mortality of early stages. For this, we use Qsim, a qualitative simulator. In this first part, we provide unfamiliar readers with the underlying qualitative differential equation (QDE) ontology of Qsim: representing quantities, qualitative variables, qualitative constraints, QDE structure. Based on a very simple example taken of the salmon redd application, we show how informal biological knowledge may be represented and simulated using an approach that was first intended to analyze qualitatively ordinary differential equations systems. A companion paper (Part II) gives the full description and simulation of the salmon redd qualitative model. This work was part of a project aimed at assessing the impact of the environment on salmon populations dynamics by the use of models of processes acting at different levels: catchment, river, and redds. Only the latter level is dealt with in this paper.

Development of automated system based on neural network algorithm for detecting defects on molds installed on casting machines

NASA Astrophysics Data System (ADS)

Bazhin, V. Yu; Danilov, I. V.; Petrov, P. A.

2018-05-01

During the casting of light alloys and ligatures based on aluminum and magnesium, problems of the qualitative distribution of the metal and its crystallization in the mold arise. To monitor the defects of molds on the casting conveyor, a camera with a resolution of 780 x 580 pixels and a shooting rate of 75 frames per second was selected. Images of molds from casting machines were used as input data for neural network algorithm. On the preparation of a digital database and its analytical evaluation stage, the architecture of the convolutional neural network was chosen for the algorithm. The information flow from the local controller is transferred to the OPC server and then to the SCADA system of foundry. After the training, accuracy of neural network defect recognition was about 95.1% on a validation split. After the training, weight coefficients of the neural network were used on testing split and algorithm had identical accuracy with validation images. The proposed technical solutions make it possible to increase the efficiency of the automated process control system in the foundry by expanding the digital database.

Learning the Structure of Biomedical Relationships from Unstructured Text

PubMed Central

Percha, Bethany; Altman, Russ B.

2015-01-01

The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured text of over 23 million articles. The creation of structured resources that catalog the relationships between drugs and genes would accelerate the translation of basic molecular knowledge into discoveries of genomic biomarkers for drug response and prediction of unexpected drug-drug interactions. Extracting these relationships from natural language sentences on such a large scale, however, requires text mining algorithms that can recognize when different-looking statements are expressing similar ideas. Here we describe a novel algorithm, Ensemble Biclustering for Classification (EBC), that learns the structure of biomedical relationships automatically from text, overcoming differences in word choice and sentence structure. We validate EBC's performance against manually-curated sets of (1) pharmacogenomic relationships from PharmGKB and (2) drug-target relationships from DrugBank, and use it to discover new drug-gene relationships for both knowledge bases. We then apply EBC to map the complete universe of drug-gene relationships based on their descriptions in Medline, revealing unexpected structure that challenges current notions about how these relationships are expressed in text. For instance, we learn that newer experimental findings are described in consistently different ways than established knowledge, and that seemingly pure classes of relationships can exhibit interesting chimeric structure. The EBC algorithm is flexible and adaptable to a wide range of problems in biomedical text mining. PMID:26219079

Quantitative 3D breast magnetic resonance imaging fibroglandular tissue analysis and correlation with qualitative assessments: a feasibility study.

PubMed

Ha, Richard; Mema, Eralda; Guo, Xiaotao; Mango, Victoria; Desperito, Elise; Ha, Jason; Wynn, Ralph; Zhao, Binsheng

2016-04-01

The amount of fibroglandular tissue (FGT) has been linked to breast cancer risk based on mammographic density studies. Currently, the qualitative assessment of FGT on mammogram (MG) and magnetic resonance imaging (MRI) is prone to intra and inter-observer variability. The purpose of this study is to develop an objective quantitative FGT measurement tool for breast MRI that could provide significant clinical value. An IRB approved study was performed. Sixty breast MRI cases with qualitative assessment of mammographic breast density and MRI FGT were randomly selected for quantitative analysis from routine breast MRIs performed at our institution from 1/2013 to 12/2014. Blinded to the qualitative data, whole breast and FGT contours were delineated on T1-weighted pre contrast sagittal images using an in-house, proprietary segmentation algorithm which combines the region-based active contours and a level set approach. FGT (%) was calculated by: [segmented volume of FGT (mm(3))/(segmented volume of whole breast (mm(3))] ×100. Statistical correlation analysis was performed between quantified FGT (%) on MRI and qualitative assessments of mammographic breast density and MRI FGT. There was a significant positive correlation between quantitative MRI FGT assessment and qualitative MRI FGT (r=0.809, n=60, P<0.001) and mammographic density assessment (r=0.805, n=60, P<0.001). There was a significant correlation between qualitative MRI FGT assessment and mammographic density assessment (r=0.725, n=60, P<0.001). The four qualitative assessment categories of FGT correlated with the calculated mean quantitative FGT (%) of 4.61% (95% CI, 0-12.3%), 8.74% (7.3-10.2%), 18.1% (15.1-21.1%), 37.4% (29.5-45.3%). Quantitative measures of FGT (%) were computed with data derived from breast MRI and correlated significantly with conventional qualitative assessments. This quantitative technique may prove to be a valuable tool in clinical use by providing computer generated standardized

sNebula, a network-based algorithm to predict binding between human leukocyte antigens and peptides

PubMed Central

Luo, Heng; Ye, Hao; Ng, Hui Wen; Sakkiah, Sugunadevi; Mendrick, Donna L.; Hong, Huixiao

2016-01-01

Understanding the binding between human leukocyte antigens (HLAs) and peptides is important to understand the functioning of the immune system. Since it is time-consuming and costly to measure the binding between large numbers of HLAs and peptides, computational methods including machine learning models and network approaches have been developed to predict HLA-peptide binding. However, there are several limitations for the existing methods. We developed a network-based algorithm called sNebula to address these limitations. We curated qualitative Class I HLA-peptide binding data and demonstrated the prediction performance of sNebula on this dataset using leave-one-out cross-validation and five-fold cross-validations. This algorithm can predict not only peptides of different lengths and different types of HLAs, but also the peptides or HLAs that have no existing binding data. We believe sNebula is an effective method to predict HLA-peptide binding and thus improve our understanding of the immune system. PMID:27558848

On factoring RSA modulus using random-restart hill-climbing algorithm and Pollard’s rho algorithm

NASA Astrophysics Data System (ADS)

Budiman, M. A.; Rachmawati, D.

2017-12-01

The security of the widely-used RSA public key cryptography algorithm depends on the difficulty of factoring a big integer into two large prime numbers. For many years, the integer factorization problem has been intensively and extensively studied in the field of number theory. As a result, a lot of deterministic algorithms such as Euler’s algorithm, Kraitchik’s, and variants of Pollard’s algorithms have been researched comprehensively. Our study takes a rather uncommon approach: rather than making use of intensive number theories, we attempt to factorize RSA modulus n by using random-restart hill-climbing algorithm, which belongs the class of metaheuristic algorithms. The factorization time of RSA moduli with different lengths is recorded and compared with the factorization time of Pollard’s rho algorithm, which is a deterministic algorithm. Our experimental results indicates that while random-restart hill-climbing algorithm is an acceptable candidate to factorize smaller RSA moduli, the factorization speed is much slower than that of Pollard’s rho algorithm.

Simulation of Long Lived Tracers Using an Improved Empirically Based Two-Dimensional Model Transport Algorithm

NASA Technical Reports Server (NTRS)

Fleming, E. L.; Jackman, C. H.; Stolarski, R. S.; Considine, D. B.

1998-01-01

We have developed a new empirically-based transport algorithm for use in our GSFC two-dimensional transport and chemistry model. The new algorithm contains planetary wave statistics, and parameterizations to account for the effects due to gravity waves and equatorial Kelvin waves. As such, this scheme utilizes significantly more information compared to our previous algorithm which was based only on zonal mean temperatures and heating rates. The new model transport captures much of the qualitative structure and seasonal variability observed in long lived tracers, such as: isolation of the tropics and the southern hemisphere winter polar vortex; the well mixed surf-zone region of the winter sub-tropics and mid-latitudes; the latitudinal and seasonal variations of total ozone; and the seasonal variations of mesospheric H2O. The model also indicates a double peaked structure in methane associated with the semiannual oscillation in the tropical upper stratosphere. This feature is similar in phase but is significantly weaker in amplitude compared to the observations. The model simulations of carbon-14 and strontium-90 are in good agreement with observations, both in simulating the peak in mixing ratio at 20-25 km, and the decrease with altitude in mixing ratio above 25 km. We also find mostly good agreement between modeled and observed age of air determined from SF6 outside of the northern hemisphere polar vortex. However, observations inside the vortex reveal significantly older air compared to the model. This is consistent with the model deficiencies in simulating CH4 in the northern hemisphere winter high latitudes and illustrates the limitations of the current climatological zonal mean model formulation. The propagation of seasonal signals in water vapor and CO2 in the lower stratosphere showed general agreement in phase, and the model qualitatively captured the observed amplitude decrease in CO2 from the tropics to midlatitudes. However, the simulated seasonal

Qualitative research: comments and controversies.

PubMed

Schutz, R W

1989-03-01

Larry Locke's timely and well-written introduction to qualitative research procedures will undoubtedly serve its purpose. It makes us reassess our traditional beliefs and practices, educates us on the rudiments of qualitative methodology, and, hopefully, makes us more tolerant and appreciative of alternate ways of conducting research. Although Locke focuses his paper on pedagogical research issues, it is important to realize that many other sub-disciplines within the general field of physical education also utilize qualitative procedures. For example, 10 years ago Martens (1979) called for a paradigm shift in sport psychology by appealing to researchers to abandon their labs and to embark on naturalistic field studies. While North American sport psychologists, and psychologists in general, have been slow to formalize qualitative techniques, the European psychology community has been much more active (e.g., Ashworth, Giorgi, & de Koning, 1986). Perhaps Locke's article will encourage researchers in all our sub-disciplines to consider the utility of qualitative research. Hopefully, readers will treat Locke's article as an introduction to the broad area of qualitative research and not as a rigorous set of procedures for conducting participant observation research in school physical education studies. Additionally, it must be recognized that there are other approaches and other applications, that the area has its critics and its unresolved methodological problems, and that qualitative research does not necessarily exclude the application of formalized data analyses. Keeping these issues in mind, the addition of qualitative approaches to our repetoire of research methodologies can only enhance the quality of research in physical education and exercise and sport science.

Further exploration of dissemination bias in qualitative research required to facilitate assessment within qualitative evidence syntheses.

PubMed

Toews, Ingrid; Booth, Andrew; Berg, Rigmor C; Lewin, Simon; Glenton, Claire; Munthe-Kaas, Heather M; Noyes, Jane; Schroter, Sara; Meerpohl, Joerg J

2017-08-01

To conceptualise and discuss dissemination bias in qualitative research. It is likely that the mechanisms leading to dissemination bias in quantitative research, including time lag, language, gray literature, and truncation bias also contribute to dissemination bias in qualitative research. These conceptual considerations have informed the development of a research agenda. Further exploration of dissemination bias in qualitative research is needed, including the extent of non-dissemination and related dissemination bias, and how to assess dissemination bias within qualitative evidence syntheses. We also need to consider the mechanisms through which dissemination bias in qualitative research could occur to explore approaches for reducing it. Copyright © 2017 Elsevier Inc. All rights reserved.

A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem

PubMed Central

Liu, Dong-sheng; Fan, Shu-jiang

2014-01-01

In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389

Structured Qualitative Research: Organizing “Mountains of Words” for Data Analysis, both Qualitative and Quantitative

PubMed Central

Johnson, Bruce D.; Dunlap, Eloise; Benoit, Ellen

2008-01-01

Qualitative research creates mountains of words. U.S. federal funding supports mostly structured qualitative research, which is designed to test hypotheses using semi-quantitative coding and analysis. The authors have 30 years of experience in designing and completing major qualitative research projects, mainly funded by the US National Institute on Drug Abuse [NIDA]. This article reports on strategies for planning, organizing, collecting, managing, storing, retrieving, analyzing, and writing about qualitative data so as to most efficiently manage the mountains of words collected in large-scale ethnographic projects. Multiple benefits accrue from this approach. Several different staff members can contribute to the data collection, even when working from remote locations. Field expenditures are linked to units of work so productivity is measured, many staff in various locations have access to use and analyze the data, quantitative data can be derived from data that is primarily qualitative, and improved efficiencies of resources are developed. The major difficulties involve a need for staff who can program and manage large databases, and who can be skillful analysts of both qualitative and quantitative data. PMID:20222777

Genetic Algorithms and Local Search

NASA Technical Reports Server (NTRS)

Whitley, Darrell

1996-01-01

The first part of this presentation is a tutorial level introduction to the principles of genetic search and models of simple genetic algorithms. The second half covers the combination of genetic algorithms with local search methods to produce hybrid genetic algorithms. Hybrid algorithms can be modeled within the existing theoretical framework developed for simple genetic algorithms. An application of a hybrid to geometric model matching is given. The hybrid algorithm yields results that improve on the current state-of-the-art for this problem.

Qualitative Descriptive Methods in Health Science Research.

PubMed

Colorafi, Karen Jiggins; Evans, Bronwynne

2016-07-01

The purpose of this methodology paper is to describe an approach to qualitative design known as qualitative descriptive that is well suited to junior health sciences researchers because it can be used with a variety of theoretical approaches, sampling techniques, and data collection strategies. It is often difficult for junior qualitative researchers to pull together the tools and resources they need to embark on a high-quality qualitative research study and to manage the volumes of data they collect during qualitative studies. This paper seeks to pull together much needed resources and provide an overview of methods. A step-by-step guide to planning a qualitative descriptive study and analyzing the data is provided, utilizing exemplars from the authors' research. This paper presents steps to conducting a qualitative descriptive study under the following headings: describing the qualitative descriptive approach, designing a qualitative descriptive study, steps to data analysis, and ensuring rigor of findings. The qualitative descriptive approach results in a summary in everyday, factual language that facilitates understanding of a selected phenomenon across disciplines of health science researchers. © The Author(s) 2016.

The Texas Medication Algorithm Project antipsychotic algorithm for schizophrenia: 2003 update.

PubMed

Miller, Alexander L; Hall, Catherine S; Buchanan, Robert W; Buckley, Peter F; Chiles, John A; Conley, Robert R; Crismon, M Lynn; Ereshefsky, Larry; Essock, Susan M; Finnerty, Molly; Marder, Stephen R; Miller, Del D; McEvoy, Joseph P; Rush, A John; Saeed, Sy A; Schooler, Nina R; Shon, Steven P; Stroup, Scott; Tarin-Godoy, Bernardo

2004-04-01

The Texas Medication Algorithm Project (TMAP) has been a public-academic collaboration in which guidelines for medication treatment of schizophrenia, bipolar disorder, and major depressive disorder were used in selected public outpatient clinics in Texas. Subsequently, these algorithms were implemented throughout Texas and are being used in other states. Guidelines require updating when significant new evidence emerges; the antipsychotic algorithm for schizophrenia was last updated in 1999. This article reports the recommendations developed in 2002 and 2003 by a group of experts, clinicians, and administrators. A conference in January 2002 began the update process. Before the conference, experts in the pharmacologic treatment of schizophrenia, clinicians, and administrators reviewed literature topics and prepared presentations. Topics included ziprasidone's inclusion in the algorithm, the number of antipsychotics tried before clozapine, and the role of first generation antipsychotics. Data were rated according to Agency for Healthcare Research and Quality criteria. After discussing the presentations, conference attendees arrived at consensus recommendations. Consideration of aripiprazole's inclusion was subsequently handled by electronic communications. The antipsychotic algorithm for schizophrenia was updated to include ziprasidone and aripiprazole among the first-line agents. Relative to the prior algorithm, the number of stages before clozapine was reduced. First generation antipsychotics were included but not as first-line choices. For patients refusing or not responding to clozapine and clozapine augmentation, preference was given to trying monotherapy with another antipsychotic before resorting to antipsychotic combinations. Consensus on algorithm revisions was achieved, but only further well-controlled research will answer many key questions about sequence and type of medication treatments of schizophrenia.

Part two: Qualitative research.

PubMed

Quick, J; Hall, S

2015-01-01

This second article in the series Spotlight on Research focuses on qualitative research, its applications, principles and methodologies. It provides an insight into how this approach can be used within the perioperative setting and gives advice for practitioners looking to undertake a qualitative research study.

Accurate Finite Difference Algorithms

NASA Technical Reports Server (NTRS)

Goodrich, John W.

1996-01-01

Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.

JPSS Cryosphere Algorithms: Integration and Testing in Algorithm Development Library (ADL)

NASA Astrophysics Data System (ADS)

Tsidulko, M.; Mahoney, R. L.; Meade, P.; Baldwin, D.; Tschudi, M. A.; Das, B.; Mikles, V. J.; Chen, W.; Tang, Y.; Sprietzer, K.; Zhao, Y.; Wolf, W.; Key, J.

2014-12-01

JPSS is a next generation satellite system that is planned to be launched in 2017. The satellites will carry a suite of sensors that are already on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The NOAA/NESDIS/STAR Algorithm Integration Team (AIT) works within the Algorithm Development Library (ADL) framework which mimics the operational JPSS Interface Data Processing Segment (IDPS). The AIT contributes in development, integration and testing of scientific algorithms employed in the IDPS. This presentation discusses cryosphere related activities performed in ADL. The addition of a new ancillary data set - NOAA Global Multisensor Automated Snow/Ice data (GMASI) - with ADL code modifications is described. Preliminary GMASI impact on the gridded Snow/Ice product is estimated. Several modifications to the Ice Age algorithm that demonstrates mis-classification of ice type for certain areas/time periods are tested in the ADL. Sensitivity runs for day time, night time and terminator zone are performed and presented. Comparisons between the original and modified versions of the Ice Age algorithm are also presented.

Algorithm-development activities

NASA Technical Reports Server (NTRS)

Carder, Kendall L.

1994-01-01

The task of algorithm-development activities at USF continues. The algorithm for determining chlorophyll alpha concentration, (Chl alpha) and gelbstoff absorption coefficient for SeaWiFS and MODIS-N radiance data is our current priority.

The qualitative orientation in medical education research.

PubMed

Cleland, Jennifer Anne

2017-06-01

Qualitative research is very important in educational research as it addresses the "how" and "why" research questions and enables deeper understanding of experiences, phenomena and context. Qualitative research allows you to ask questions that cannot be easily put into numbers to understand human experience. Getting at the everyday realities of some social phenomenon and studying important questions as they are really practiced helps extend knowledge and understanding. To do so, you need to understand the philosophical stance of qualitative research and work from this to develop the research question, study design, data collection methods and data analysis. In this article, I provide an overview of the assumptions underlying qualitative research and the role of the researcher in the qualitative process. I then go on to discuss the type of research objectives which are common in qualitative research, then introduce the main qualitative designs, data collection tools, and finally the basics of qualitative analysis. I introduce the criteria by which you can judge the quality of qualitative research. Many classic references are cited in this article, and I urge you to seek out some of these further reading to inform your qualitative research program.

The qualitative orientation in medical education research

PubMed Central

2017-01-01

Qualitative research is very important in educational research as it addresses the “how” and “why” research questions and enables deeper understanding of experiences, phenomena and context. Qualitative research allows you to ask questions that cannot be easily put into numbers to understand human experience. Getting at the everyday realities of some social phenomenon and studying important questions as they are really practiced helps extend knowledge and understanding. To do so, you need to understand the philosophical stance of qualitative research and work from this to develop the research question, study design, data collection methods and data analysis. In this article, I provide an overview of the assumptions underlying qualitative research and the role of the researcher in the qualitative process. I then go on to discuss the type of research objectives which are common in qualitative research, then introduce the main qualitative designs, data collection tools, and finally the basics of qualitative analysis. I introduce the criteria by which you can judge the quality of qualitative research. Many classic references are cited in this article, and I urge you to seek out some of these further reading to inform your qualitative research program. PMID:28597869

Theoretic derivation of directed acyclic subgraph algorithm and comparisons with message passing algorithm

NASA Astrophysics Data System (ADS)

Ha, Jeongmok; Jeong, Hong

2016-07-01

This study investigates the directed acyclic subgraph (DAS) algorithm, which is used to solve discrete labeling problems much more rapidly than other Markov-random-field-based inference methods but at a competitive accuracy. However, the mechanism by which the DAS algorithm simultaneously achieves competitive accuracy and fast execution speed, has not been elucidated by a theoretical derivation. We analyze the DAS algorithm by comparing it with a message passing algorithm. Graphical models, inference methods, and energy-minimization frameworks are compared between DAS and message passing algorithms. Moreover, the performances of DAS and other message passing methods [sum-product belief propagation (BP), max-product BP, and tree-reweighted message passing] are experimentally compared.

Qualitative models for space system engineering

NASA Technical Reports Server (NTRS)

Forbus, Kenneth D.

1990-01-01

The objectives of this project were: (1) to investigate the implications of qualitative modeling techniques for problems arising in the monitoring, diagnosis, and design of Space Station subsystems and procedures; (2) to identify the issues involved in using qualitative models to enhance and automate engineering functions. These issues include representing operational criteria, fault models, alternate ontologies, and modeling continuous signals at a functional level of description; and (3) to develop a prototype collection of qualitative models for fluid and thermal systems commonly found in Space Station subsystems. Potential applications of qualitative modeling to space-systems engineering, including the notion of intelligent computer-aided engineering are summarized. Emphasis is given to determining which systems of the proposed Space Station provide the most leverage for study, given the current state of the art. Progress on using qualitative models, including development of the molecular collection ontology for reasoning about fluids, the interaction of qualitative and quantitative knowledge in analyzing thermodynamic cycles, and an experiment on building a natural language interface to qualitative reasoning is reported. Finally, some recommendations are made for future research.

A Winner Determination Algorithm for Combinatorial Auctions Based on Hybrid Artificial Fish Swarm Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Genrang; Lin, ZhengChun

The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.

A review on quantum search algorithms

NASA Astrophysics Data System (ADS)

Giri, Pulak Ranjan; Korepin, Vladimir E.

2017-12-01

The use of superposition of states in quantum computation, known as quantum parallelism, has significant advantage in terms of speed over the classical computation. It is evident from the early invented quantum algorithms such as Deutsch's algorithm, Deutsch-Jozsa algorithm and its variation as Bernstein-Vazirani algorithm, Simon algorithm, Shor's algorithms, etc. Quantum parallelism also significantly speeds up the database search algorithm, which is important in computer science because it comes as a subroutine in many important algorithms. Quantum database search of Grover achieves the task of finding the target element in an unsorted database in a time quadratically faster than the classical computer. We review Grover's quantum search algorithms for a singe and multiple target elements in a database. The partial search algorithm of Grover and Radhakrishnan and its optimization by Korepin called GRK algorithm are also discussed.

Qualitative Secondary Analysis: A Case Exemplar.

PubMed

Tate, Judith Ann; Happ, Mary Beth

Qualitative secondary analysis (QSA) is the use of qualitative data that was collected by someone else or was collected to answer a different research question. Secondary analysis of qualitative data provides an opportunity to maximize data utility, particularly with difficult-to-reach patient populations. However, qualitative secondary analysis methods require careful consideration and explicit description to best understand, contextualize, and evaluate the research results. In this article, we describe methodologic considerations using a case exemplar to illustrate challenges specific to qualitative secondary analysis and strategies to overcome them. Copyright © 2017 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.

Commentary: Writing and evaluating qualitative research reports

USDA-ARS?s Scientific Manuscript database

An overview of qualitative methods is provided, particularly for reviewers and authors who may be less familiar with qualitative research. A question and answer format is used to address considerations for writing and evaluating qualitative research. When producing qualitative research, individuals ...

Optimization Of Feature Weight TheVoting Feature Intervals 5 Algorithm Using Partical Swarm Optimization Algorithm

NASA Astrophysics Data System (ADS)

Hayana Hasibuan, Eka; Mawengkang, Herman; Efendi, Syahril

2017-12-01

The use of Partical Swarm Optimization Algorithm in this research is to optimize the feature weights on the Voting Feature Interval 5 algorithm so that we can find the model of using PSO algorithm with VFI 5. Optimization of feature weight on Diabetes or Dyspesia data is considered important because it is very closely related to the livelihood of many people, so if there is any inaccuracy in determining the most dominant feature weight in the data will cause death. Increased accuracy by using PSO Algorithm ie fold 1 from 92.31% to 96.15% increase accuracy of 3.8%, accuracy of fold 2 on Algorithm VFI5 of 92.52% as well as generated on PSO Algorithm means accuracy fixed, then in fold 3 increase accuracy of 85.19% Increased to 96.29% Accuracy increased by 11%. The total accuracy of all three trials increased by 14%. In general the Partical Swarm Optimization algorithm has succeeded in increasing the accuracy to several fold, therefore it can be concluded the PSO algorithm is well used in optimizing the VFI5 Classification Algorithm.

Artifact removal algorithms for stroke detection using a multistatic MIST beamforming algorithm.

PubMed

Ricci, E; Di Domenico, S; Cianca, E; Rossi, T

2015-01-01

Microwave imaging (MWI) has been recently proved as a promising imaging modality for low-complexity, low-cost and fast brain imaging tools, which could play a fundamental role to efficiently manage emergencies related to stroke and hemorrhages. This paper focuses on the UWB radar imaging approach and in particular on the processing algorithms of the backscattered signals. Assuming the use of the multistatic version of the MIST (Microwave Imaging Space-Time) beamforming algorithm, developed by Hagness et al. for the early detection of breast cancer, the paper proposes and compares two artifact removal algorithms. Artifacts removal is an essential step of any UWB radar imaging system and currently considered artifact removal algorithms have been shown not to be effective in the specific scenario of brain imaging. First of all, the paper proposes modifications of a known artifact removal algorithm. These modifications are shown to be effective to achieve good localization accuracy and lower false positives. However, the main contribution is the proposal of an artifact removal algorithm based on statistical methods, which allows to achieve even better performance but with much lower computational complexity.

Portfolios of quantum algorithms.

PubMed

Maurer, S M; Hogg, T; Huberman, B A

2001-12-17

Quantum computation holds promise for the solution of many intractable problems. However, since many quantum algorithms are stochastic in nature they can find the solution of hard problems only probabilistically. Thus the efficiency of the algorithms has to be characterized by both the expected time to completion and the associated variance. In order to minimize both the running time and its uncertainty, we show that portfolios of quantum algorithms analogous to those of finance can outperform single algorithms when applied to the NP-complete problems such as 3-satisfiability.

DNABIT Compress - Genome compression algorithm.

PubMed

Rajarajeswari, Pothuraju; Apparao, Allam

2011-01-22

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, "DNABIT Compress" for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that "DNABIT Compress" algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases.

File text security using Hybrid Cryptosystem with Playfair Cipher Algorithm and Knapsack Naccache-Stern Algorithm

NASA Astrophysics Data System (ADS)

Amalia; Budiman, M. A.; Sitepu, R.

2018-03-01

Cryptography is one of the best methods to keep the information safe from security attack by unauthorized people. At present, Many studies had been done by previous researchers to generate a more robust cryptographic algorithm to provide high security for data communication. To strengthen data security, one of the methods is hybrid cryptosystem method that combined symmetric and asymmetric algorithm. In this study, we observed a hybrid cryptosystem method contain Modification Playfair Cipher 16x16 algorithm as a symmetric algorithm and Knapsack Naccache-Stern as an asymmetric algorithm. We observe a running time of this hybrid algorithm with some of the various experiments. We tried different amount of characters to be tested which are 10, 100, 1000, 10000 and 100000 characters and we also examined the algorithm with various key’s length which are 10, 20, 30, 40 of key length. The result of our study shows that the processing time for encryption and decryption process each algorithm is linearly proportional, it means the longer messages character then, the more significant times needed to encrypt and decrypt the messages. The encryption running time of Knapsack Naccache-Stern algorithm takes a longer time than its decryption, while the encryption running time of modification Playfair Cipher 16x16 algorithm takes less time than its decryption.

Content validation of a standardized algorithm for ostomy care.

PubMed

Beitz, Janice; Gerlach, Mary; Ginsburg, Pat; Ho, Marianne; McCann, Eileen; Schafer, Vickie; Scott, Vera; Stallings, Bobbie; Turnbull, Gwen

2010-10-01

The number of ostomy care clinician experts is limited and the majority of ostomy care is provided by non-specialized clinicians or unskilled caregivers and family. The purpose of this study was to obtain content validation data for a new standardized algorithm for ostomy care developed by expert wound ostomy continence nurse (WOCN) clinicians. After face validity was established using overall review and suggestions from WOCN experts, 166 WOCNs self-identified as having expertise in ostomy care were surveyed online for 6 weeks in 2009. Using a cross-sectional, mixed methods study design and a 30-item instrument with a 4-point Likert-type scale, the participants were asked to quantify the degree of validity of the Ostomy Algorithm's decisions and components. Participants' open-ended comments also were thematically analyzed. Using a scale of 1 to 4, the mean score of the entire algorithm was 3.8 (4 = relevant/very relevant). The algorithm's content validity index (CVI) was 0.95 (out of 1.0). Individual component mean scores ranged from 3.59 to 3.91. Individual CVIs ranged from 0.90 to 0.98. Qualitative data analysis revealed themes of difficulty associated with algorithm formatting, especially orientation and use of the Studio Alterazioni Cutanee Stomali (Study on Peristomal Skin Lesions [SACS™ Instrument]) and the inability of algorithms to capture all individual patient attributes affecting ostomy care. Positive themes included content thoroughness and the helpful clinical photos. Suggestions were offered for algorithm improvement. Study results support the strong content validity of the algorithm and research to ascertain its construct validity and effect on care outcomes is warranted.

The global Minmax k-means algorithm.

PubMed

Wang, Xiaoyan; Bai, Yanping

2016-01-01

The global k -means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k -means to minimize the sum of the intra-cluster variances. However the global k -means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k -means algorithm. In this paper, we modified the global k -means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k -means clustering error method to global k -means algorithm to overcome the effect of bad initialization, proposed the global Minmax k -means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k -means algorithm, the global k -means algorithm and the MinMax k -means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper.

Publishing Qualitative Research in Counseling Journals

ERIC Educational Resources Information Center

Hunt, Brandon

2011-01-01

This article focuses on the essential elements to be included when developing a qualitative study and preparing the findings for publication. Using the sections typically found in a qualitative article, the author describes content relevant to each section, with additional suggestions for publishing qualitative research.

System monitoring and diagnosis with qualitative models

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin

1991-01-01

A substantial foundation of tools for model-based reasoning with incomplete knowledge was developed: QSIM (a qualitative simulation program) and its extensions for qualitative simulation; Q2, Q3 and their successors for quantitative reasoning on a qualitative framework; and the CC (component-connection) and QPC (Qualitative Process Theory) model compilers for building QSIM QDE (qualitative differential equation) models starting from different ontological assumptions. Other model-compilers for QDE's, e.g., using bond graphs or compartmental models, have been developed elsewhere. These model-building tools will support automatic construction of qualitative models from physical specifications, and further research into selection of appropriate modeling viewpoints. For monitoring and diagnosis, plausible hypotheses are unified against observations to strengthen or refute the predicted behaviors. In MIMIC (Model Integration via Mesh Interpolation Coefficients), multiple hypothesized models of the system are tracked in parallel in order to reduce the 'missing model' problem. Each model begins as a qualitative model, and is unified with a priori quantitative knowledge and with the stream of incoming observational data. When the model/data unification yields a contradiction, the model is refuted. When there is no contradiction, the predictions of the model are progressively strengthened, for use in procedure planning and differential diagnosis. Only under a qualitative level of description can a finite set of models guarantee the complete coverage necessary for this performance. The results of this research are presented in several publications. Abstracts of these published papers are presented along with abtracts of papers representing work that was synergistic with the NASA grant but funded otherwise. These 28 papers include but are not limited to: 'Combined qualitative and numerical simulation with Q3'; 'Comparative analysis and qualitative integral representations

Clustering single cells: a review of approaches on high-and low-depth single-cell RNA-seq data.

PubMed

Menon, Vilas

2017-12-11

Advances in single-cell RNA-sequencing technology have resulted in a wealth of studies aiming to identify transcriptomic cell types in various biological systems. There are multiple experimental approaches to isolate and profile single cells, which provide different levels of cellular and tissue coverage. In addition, multiple computational strategies have been proposed to identify putative cell types from single-cell data. From a data generation perspective, recent single-cell studies can be classified into two groups: those that distribute reads shallowly over large numbers of cells and those that distribute reads more deeply over a smaller cell population. Although there are advantages to both approaches in terms of cellular and tissue coverage, it is unclear whether different computational cell type identification methods are better suited to one or the other experimental paradigm. This study reviews three cell type clustering algorithms, each representing one of three broad approaches, and finds that PCA-based algorithms appear most suited to low read depth data sets, whereas gene clustering-based and biclustering algorithms perform better on high read depth data sets. In addition, highly related cell classes are better distinguished by higher-depth data, given the same total number of reads; however, simultaneous discovery of distinct and similar types is better served by lower-depth, higher cell number data. Overall, this study suggests that the depth of profiling should be determined by initial assumptions about the diversity of cells in the population, and that the selection of clustering algorithm(s) is subsequently based on the depth of profiling will allow for better identification of putative transcriptomic cell types. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Algorithmic Coordination in Robotic Networks

DTIC Science & Technology

2010-11-29

appropriate performance, robustness and scalability properties for various task allocation , surveillance, and information gathering applications is...networking, we envision designing and analyzing algorithms with appropriate performance, robustness and scalability properties for various task ...distributed algorithms for target assignments; based on the classic auction algorithms in static networks, we intend to design efficient algorithms in worst

Qualitative Studies: Historiographical Antecedents.

ERIC Educational Resources Information Center

Mills, Rilla Dean

This paper provides an overview of qualitative studies' antecedents among historiographers and of the positivist tide which nearly engulfed them. Humans live by interpretations. The task of social science--the basic task of qualitative studies--is to study these interpretations so that we can better understand the meanings which people use to…

Conducting qualitative research in audiology: a tutorial.

PubMed

Knudsen, Line V; Laplante-Lévesque, Ariane; Jones, Lesley; Preminger, Jill E; Nielsen, Claus; Lunner, Thomas; Hickson, Louise; Naylor, Graham; Kramer, Sophia E

2012-02-01

Qualitative research methodologies are being used more frequently in audiology as it allows for a better understanding of the perspectives of people with hearing impairment. This article describes why and how international interdisciplinary qualitative research can be conducted. This paper is based on a literature review and our recent experience with the conduction of an international interdisciplinary qualitative study in audiology. We describe some available qualitative methods for sampling, data collection, and analysis and we discuss the rationale for choosing particular methods. The focus is on four approaches which have all previously been applied to audiologic research: grounded theory, interpretative phenomenological analysis, conversational analysis, and qualitative content analysis. This article provides a review of methodological issues useful for those designing qualitative research projects in audiology or needing assistance in the interpretation of qualitative literature.

Simulation of Long Lived Tracers Using an Improved Empirically-Based Two-Dimensional Model Transport Algorithm

NASA Technical Reports Server (NTRS)

Fleming, Eric L.; Jackman, Charles H.; Stolarski, Richard S.; Considine, David B.

1998-01-01

We have developed a new empirically-based transport algorithm for use in our GSFC two-dimensional transport and chemistry assessment model. The new algorithm contains planetary wave statistics, and parameterizations to account for the effects due to gravity waves and equatorial Kelvin waves. We will present an overview of the new algorithm, and show various model-data comparisons of long-lived tracers as part of the model validation. We will also show how the new algorithm gives substantially better agreement with observations compared to our previous model transport. The new model captures much of the qualitative structure and seasonal variability observed methane, water vapor, and total ozone. These include: isolation of the tropics and winter polar vortex, the well mixed surf-zone region of the winter sub-tropics and mid-latitudes, and the propagation of seasonal signals in the tropical lower stratosphere. Model simulations of carbon-14 and strontium-90 compare fairly well with observations in reproducing the peak in mixing ratio at 20-25 km, and the decrease with altitude in mixing ratio above 25 km. We also ran time dependent simulations of SF6 from which the model mean age of air values were derived. The oldest air (5.5 to 6 years) occurred in the high latitude upper stratosphere during fall and early winter of both hemispheres, and in the southern hemisphere lower stratosphere during late winter and early spring. The latitudinal gradient of the mean ages also compare well with ER-2 aircraft observations in the lower stratosphere.

Teaching Qualitative Research to Practitioner-Researchers

ERIC Educational Resources Information Center

Cox, Rebecca D.

2012-01-01

Practitioner-researchers are well-positioned to apply qualitative methods to the study of significant problems of educational practice. However, while learning the skills of qualitative inquiry, practitioners may be compelled by forces outside of qualitative research classrooms to think quantitatively. In this article, the author considers two…

Algorithm Engineering: Concepts and Practice

NASA Astrophysics Data System (ADS)

Chimani, Markus; Klein, Karsten

Over the last years the term algorithm engineering has become wide spread synonym for experimental evaluation in the context of algorithm development. Yet it implies even more. We discuss the major weaknesses of traditional "pen and paper" algorithmics and the ever-growing gap between theory and practice in the context of modern computer hardware and real-world problem instances. We present the key ideas and concepts of the central algorithm engineering cycle that is based on a full feedback loop: It starts with the design of the algorithm, followed by the analysis, implementation, and experimental evaluation. The results of the latter can then be reused for modifications to the algorithmic design, stronger or input-specific theoretic performance guarantees, etc. We describe the individual steps of the cycle, explaining the rationale behind them and giving examples of how to conduct these steps thoughtfully. Thereby we give an introduction to current algorithmic key issues like I/O-efficient or parallel algorithms, succinct data structures, hardware-aware implementations, and others. We conclude with two especially insightful success stories—shortest path problems and text search—where the application of algorithm engineering techniques led to tremendous performance improvements compared with previous state-of-the-art approaches.

A smartphone-based pain management app for adolescents with cancer: establishing system requirements and a pain care algorithm based on literature review, interviews, and consensus.

PubMed

Jibb, Lindsay A; Stevens, Bonnie J; Nathan, Paul C; Seto, Emily; Cafazzo, Joseph A; Stinson, Jennifer N

2014-03-19

Pain that occurs both within and outside of the hospital setting is a common and distressing problem for adolescents with cancer. The use of smartphone technology may facilitate rapid, in-the-moment pain support for this population. To ensure the best possible pain management advice is given, evidence-based and expert-vetted care algorithms and system design features, which are designed using user-centered methods, are required. To develop the decision algorithm and system requirements that will inform the pain management advice provided by a real-time smartphone-based pain management app for adolescents with cancer. A systematic approach to algorithm development and system design was utilized. Initially, a comprehensive literature review was undertaken to understand the current body of knowledge pertaining to pediatric cancer pain management. A user-centered approach to development was used as the results of the review were disseminated to 15 international experts (clinicians, scientists, and a consumer) in pediatric pain, pediatric oncology and mHealth design, who participated in a 2-day consensus conference. This conference used nominal group technique to develop consensus on important pain inputs, pain management advice, and system design requirements. Using data generated at the conference, a prototype algorithm was developed. Iterative qualitative testing was conducted with adolescents with cancer, as well as pediatric oncology and pain health care providers to vet and refine the developed algorithm and system requirements for the real-time smartphone app. The systematic literature review established the current state of research related to nonpharmacological pediatric cancer pain management. The 2-day consensus conference established which clinically important pain inputs by adolescents would require action (pain management advice) from the app, the appropriate advice the app should provide to adolescents in pain, and the functional requirements of the app

A Smartphone-Based Pain Management App for Adolescents With Cancer: Establishing System Requirements and a Pain Care Algorithm Based on Literature Review, Interviews, and Consensus

PubMed Central

Stevens, Bonnie J; Nathan, Paul C; Seto, Emily; Cafazzo, Joseph A; Stinson, Jennifer N

2014-01-01

Background Pain that occurs both within and outside of the hospital setting is a common and distressing problem for adolescents with cancer. The use of smartphone technology may facilitate rapid, in-the-moment pain support for this population. To ensure the best possible pain management advice is given, evidence-based and expert-vetted care algorithms and system design features, which are designed using user-centered methods, are required. Objective To develop the decision algorithm and system requirements that will inform the pain management advice provided by a real-time smartphone-based pain management app for adolescents with cancer. Methods A systematic approach to algorithm development and system design was utilized. Initially, a comprehensive literature review was undertaken to understand the current body of knowledge pertaining to pediatric cancer pain management. A user-centered approach to development was used as the results of the review were disseminated to 15 international experts (clinicians, scientists, and a consumer) in pediatric pain, pediatric oncology and mHealth design, who participated in a 2-day consensus conference. This conference used nominal group technique to develop consensus on important pain inputs, pain management advice, and system design requirements. Using data generated at the conference, a prototype algorithm was developed. Iterative qualitative testing was conducted with adolescents with cancer, as well as pediatric oncology and pain health care providers to vet and refine the developed algorithm and system requirements for the real-time smartphone app. Results The systematic literature review established the current state of research related to nonpharmacological pediatric cancer pain management. The 2-day consensus conference established which clinically important pain inputs by adolescents would require action (pain management advice) from the app, the appropriate advice the app should provide to adolescents in pain, and the

Mind mapping in qualitative research.

PubMed

Tattersall, Christopher; Powell, Julia; Stroud, James; Pringle, Jan

We tested a theory that mind mapping could be used as a tool in qualitative research to transcribe and analyse an interview. We compared results derived from mind mapping with those from interpretive phenomenological analysis by examining patients' and carers' perceptions of a new nurse-led service. Mind mapping could be used to rapidly analyse simple qualitative audio-recorded interviews. More research is needed to establish the extent to which mind mapping can assist qualitative researchers.

CURE-SMOTE algorithm and hybrid algorithm for feature selection and parameter optimization based on random forests.

PubMed

Ma, Li; Fan, Suohai

2017-03-14

The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve imbalanced data processing, feature selection and parameter optimization. We propose the CURE-SMOTE algorithm for the imbalanced data classification problem. Experiments on imbalanced UCI data reveal that the combination of Clustering Using Representatives (CURE) enhances the original synthetic minority oversampling technique (SMOTE) algorithms effectively compared with the classification results on the original data using random sampling, Borderline-SMOTE1, safe-level SMOTE, C-SMOTE, and k-means-SMOTE. Additionally, the hybrid RF (random forests) algorithm has been proposed for feature selection and parameter optimization, which uses the minimum out of bag (OOB) data error as its objective function. Simulation results on binary and higher-dimensional data indicate that the proposed hybrid RF algorithms, hybrid genetic-random forests algorithm, hybrid particle swarm-random forests algorithm and hybrid fish swarm-random forests algorithm can achieve the minimum OOB error and show the best generalization ability. The training set produced from the proposed CURE-SMOTE algorithm is closer to the original data distribution because it contains minimal noise. Thus, better classification results are produced from this feasible and effective algorithm. Moreover, the hybrid algorithm's F-value, G-mean, AUC and OOB scores demonstrate that they surpass the performance of the original RF algorithm. Hence, this hybrid algorithm provides a new way to perform feature selection and parameter optimization.

Strategies of Qualitative Inquiry. Third Edition

ERIC Educational Resources Information Center

Denzin, Norman K., Ed.; Lincoln, Yvonna S., Ed.

2007-01-01

"Strategies of Qualitative Inquiry, Third Edition," the second volume in the paperback version of "The SAGE Handbook of Qualitative Research, 3rd Edition," consists of Part III of the handbook ("Strategies of Inquiry"). "Strategies of Qualitative Inquiry, Third Edition" presents the major tactics--historically, the research methods--that…

Biological sequence compression algorithms.

PubMed

Matsumoto, T; Sadakane, K; Imai, H

2000-01-01

Today, more and more DNA sequences are becoming available. The information about DNA sequences are stored in molecular biology databases. The size and importance of these databases will be bigger and bigger in the future, therefore this information must be stored or communicated efficiently. Furthermore, sequence compression can be used to define similarities between biological sequences. The standard compression algorithms such as gzip or compress cannot compress DNA sequences, but only expand them in size. On the other hand, CTW (Context Tree Weighting Method) can compress DNA sequences less than two bits per symbol. These algorithms do not use special structures of biological sequences. Two characteristic structures of DNA sequences are known. One is called palindromes or reverse complements and the other structure is approximate repeats. Several specific algorithms for DNA sequences that use these structures can compress them less than two bits per symbol. In this paper, we improve the CTW so that characteristic structures of DNA sequences are available. Before encoding the next symbol, the algorithm searches an approximate repeat and palindrome using hash and dynamic programming. If there is a palindrome or an approximate repeat with enough length then our algorithm represents it with length and distance. By using this preprocessing, a new program achieves a little higher compression ratio than that of existing DNA-oriented compression algorithms. We also describe new compression algorithm for protein sequences.

Focused Group Interviews as an Innovative Quanti-Qualitative Methodology (QQM): Integrating Quantitative Elements into a Qualitative Methodology

ERIC Educational Resources Information Center

Grim, Brian J.; Harmon, Alison H.; Gromis, Judy C.

2006-01-01

There is a sharp divide between quantitative and qualitative methodologies in the social sciences. We investigate an innovative way to bridge this gap that incorporates quantitative techniques into a qualitative method, the "quanti-qualitative method" (QQM). Specifically, our research utilized small survey questionnaires and experiment-like…

Classification of Time Series Gene Expression in Clinical Studies via Integration of Biological Network

PubMed Central

Qian, Liwei; Zheng, Haoran; Zhou, Hong; Qin, Ruibin; Li, Jinlong

2013-01-01

The increasing availability of time series expression datasets, although promising, raises a number of new computational challenges. Accordingly, the development of suitable classification methods to make reliable and sound predictions is becoming a pressing issue. We propose, here, a new method to classify time series gene expression via integration of biological networks. We evaluated our approach on 2 different datasets and showed that the use of a hidden Markov model/Gaussian mixture models hybrid explores the time-dependence of the expression data, thereby leading to better prediction results. We demonstrated that the biclustering procedure identifies function-related genes as a whole, giving rise to high accordance in prognosis prediction across independent time series datasets. In addition, we showed that integration of biological networks into our method significantly improves prediction performance. Moreover, we compared our approach with several state-of–the-art algorithms and found that our method outperformed previous approaches with regard to various criteria. Finally, our approach achieved better prediction results on early-stage data, implying the potential of our method for practical prediction. PMID:23516469

Hybrid cryptosystem implementation using fast data encipherment algorithm (FEAL) and goldwasser-micali algorithm for file security

NASA Astrophysics Data System (ADS)

Rachmawati, D.; Budiman, M. A.; Siburian, W. S. E.

2018-05-01

On the process of exchanging files, security is indispensable to avoid the theft of data. Cryptography is one of the sciences used to secure the data by way of encoding. Fast Data Encipherment Algorithm (FEAL) is a block cipher symmetric cryptographic algorithms. Therefore, the file which wants to protect is encrypted and decrypted using the algorithm FEAL. To optimize the security of the data, session key that is utilized in the algorithm FEAL encoded with the Goldwasser-Micali algorithm, which is an asymmetric cryptographic algorithm and using probabilistic concept. In the encryption process, the key was converted into binary form. The selection of values of x that randomly causes the results of the cipher key is different for each binary value. The concept of symmetry and asymmetry algorithm merger called Hybrid Cryptosystem. The use of the algorithm FEAL and Goldwasser-Micali can restore the message to its original form and the algorithm FEAL time required for encryption and decryption is directly proportional to the length of the message. However, on Goldwasser- Micali algorithm, the length of the message is not directly proportional to the time of encryption and decryption.

Commentary: Writing and Evaluating Qualitative Research Reports

PubMed Central

Thompson, Deborah; Aroian, Karen J.; McQuaid, Elizabeth L.; Deatrick, Janet A.

2016-01-01

Objective To provide an overview of qualitative methods, particularly for reviewers and authors who may be less familiar with qualitative research. Methods A question and answer format is used to address considerations for writing and evaluating qualitative research. Results and Conclusions When producing qualitative research, individuals are encouraged to address the qualitative research considerations raised and to explicitly identify the systematic strategies used to ensure rigor in study design and methods, analysis, and presentation of findings. Increasing capacity for review and publication of qualitative research within pediatric psychology will advance the field’s ability to gain a better understanding of the specific needs of pediatric populations, tailor interventions more effectively, and promote optimal health. PMID:27118271

Quantifying Qualitative Data Using Cognitive Maps

ERIC Educational Resources Information Center

Scherp, Hans-Ake

2013-01-01

The aim of the article is to show how substantial qualitative material consisting of graphic cognitive maps can be analysed by using digital CmapTools, Excel and SPSS. Evidence is provided of how qualitative and quantitative methods can be combined in educational research by transforming qualitative data into quantitative data to facilitate…

Knowledge representation and qualitative simulation of salmon redd functioning. Part II: qualitative model of redds.

PubMed

Guerrin, F; Dumas, J

2001-02-01

This paper describes a qualitative model of the functioning of salmon redds (spawning areas of salmon) and its impact on mortality rates of early stages. For this, we use Qsim, a qualitative simulator, which appeared adequate for representing available qualitative knowledge of freshwater ecology experts (see Part I of this paper). Since the number of relevant variables was relatively large, it appeared necessary to decompose the model into two parts, corresponding to processes occurring at separate time-scales. A qualitative clock allows us to submit the simulation of salmon developmental stages to the calculation of accumulated daily temperatures (degree-days), according to the clock ticks and a water temperature regime set by the user. Therefore, this introduces some way of real-time dating and duration in a purely qualitative model. Simulating both sub-models, either separately or by means of alternate transitions, allows us to generate the evolutions of variables of interest, such as the mortality rates according to two factors (flow of oxygenated water and plugging of gravel interstices near the bed surface), under various scenarios.

Qualitative versus quantitative methods in psychiatric research.

PubMed

Razafsha, Mahdi; Behforuzi, Hura; Azari, Hassan; Zhang, Zhiqun; Wang, Kevin K; Kobeissy, Firas H; Gold, Mark S

2012-01-01

Qualitative studies are gaining their credibility after a period of being misinterpreted as "not being quantitative." Qualitative method is a broad umbrella term for research methodologies that describe and explain individuals' experiences, behaviors, interactions, and social contexts. In-depth interview, focus groups, and participant observation are among the qualitative methods of inquiry commonly used in psychiatry. Researchers measure the frequency of occurring events using quantitative methods; however, qualitative methods provide a broader understanding and a more thorough reasoning behind the event. Hence, it is considered to be of special importance in psychiatry. Besides hypothesis generation in earlier phases of the research, qualitative methods can be employed in questionnaire design, diagnostic criteria establishment, feasibility studies, as well as studies of attitude and beliefs. Animal models are another area that qualitative methods can be employed, especially when naturalistic observation of animal behavior is important. However, since qualitative results can be researcher's own view, they need to be statistically confirmed, quantitative methods. The tendency to combine both qualitative and quantitative methods as complementary methods has emerged over recent years. By applying both methods of research, scientists can take advantage of interpretative characteristics of qualitative methods as well as experimental dimensions of quantitative methods.

Revisiting negative selection algorithms.

PubMed

Ji, Zhou; Dasgupta, Dipankar

2007-01-01

This paper reviews the progress of negative selection algorithms, an anomaly/change detection approach in Artificial Immune Systems (AIS). Following its initial model, we try to identify the fundamental characteristics of this family of algorithms and summarize their diversities. There exist various elements in this method, including data representation, coverage estimate, affinity measure, and matching rules, which are discussed for different variations. The various negative selection algorithms are categorized by different criteria as well. The relationship and possible combinations with other AIS or other machine learning methods are discussed. Prospective development and applicability of negative selection algorithms and their influence on related areas are then speculated based on the discussion.

Study of image matching algorithm and sub-pixel fitting algorithm in target tracking

NASA Astrophysics Data System (ADS)

Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu

2015-03-01

Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image

Statistical efficiency of adaptive algorithms.

PubMed

Widrow, Bernard; Kamenetsky, Max

2003-01-01

The statistical efficiency of a learning algorithm applied to the adaptation of a given set of variable weights is defined as the ratio of the quality of the converged solution to the amount of data used in training the weights. Statistical efficiency is computed by averaging over an ensemble of learning experiences. A high quality solution is very close to optimal, while a low quality solution corresponds to noisy weights and less than optimal performance. In this work, two gradient descent adaptive algorithms are compared, the LMS algorithm and the LMS/Newton algorithm. LMS is simple and practical, and is used in many applications worldwide. LMS/Newton is based on Newton's method and the LMS algorithm. LMS/Newton is optimal in the least squares sense. It maximizes the quality of its adaptive solution while minimizing the use of training data. Many least squares adaptive algorithms have been devised over the years, but no other least squares algorithm can give better performance, on average, than LMS/Newton. LMS is easily implemented, but LMS/Newton, although of great mathematical interest, cannot be implemented in most practical applications. Because of its optimality, LMS/Newton serves as a benchmark for all least squares adaptive algorithms. The performances of LMS and LMS/Newton are compared, and it is found that under many circumstances, both algorithms provide equal performance. For example, when both algorithms are tested with statistically nonstationary input signals, their average performances are equal. When adapting with stationary input signals and with random initial conditions, their respective learning times are on average equal. However, under worst-case initial conditions, the learning time of LMS can be much greater than that of LMS/Newton, and this is the principal disadvantage of the LMS algorithm. But the strong points of LMS are ease of implementation and optimal performance under important practical conditions. For these reasons, the LMS

New development of the image matching algorithm

NASA Astrophysics Data System (ADS)

Zhang, Xiaoqiang; Feng, Zhao

2018-04-01

To study the image matching algorithm, algorithm four elements are described, i.e., similarity measurement, feature space, search space and search strategy. Four common indexes for evaluating the image matching algorithm are described, i.e., matching accuracy, matching efficiency, robustness and universality. Meanwhile, this paper describes the principle of image matching algorithm based on the gray value, image matching algorithm based on the feature, image matching algorithm based on the frequency domain analysis, image matching algorithm based on the neural network and image matching algorithm based on the semantic recognition, and analyzes their characteristics and latest research achievements. Finally, the development trend of image matching algorithm is discussed. This study is significant for the algorithm improvement, new algorithm design and algorithm selection in practice.

Disrupting Qualitative Inquiry: Possibilities and Tensions in Educational Research. Critical Qualitative Research. Volume 10

ERIC Educational Resources Information Center

Brown, Ruth Nicole, Ed.; Carducci, Rozana, Ed.; Kuby, Candace R., Ed.

2014-01-01

"Disrupting Qualitative Inquiry" is an edited volume that examines the possibilities and tensions encountered by scholars who adopt disruptive qualitative approaches to the study of educational contexts, issues, and phenomena. It presents a collection of innovative and intellectually stimulating chapters which illustrate the potential…

Ecosystems and People: Qualitative Insights

EPA Science Inventory

Both qualitative and quantitative techniques are crucial in researching human impacts from ecological changes. This matches the importance of ?mixed methods? approaches in other disciplines. Qualitative research helps explore the relevancy and transferability of the foundational ...

Fusing face-verification algorithms and humans.

PubMed

O'Toole, Alice J; Abdi, Hervé; Jiang, Fang; Phillips, P Jonathon

2007-10-01

It has been demonstrated recently that state-of-the-art face-recognition algorithms can surpass human accuracy at matching faces over changes in illumination. The ranking of algorithms and humans by accuracy, however, does not provide information about whether algorithms and humans perform the task comparably or whether algorithms and humans can be fused to improve performance. In this paper, we fused humans and algorithms using partial least square regression (PLSR). In the first experiment, we applied PLSR to face-pair similarity scores generated by seven algorithms participating in the Face Recognition Grand Challenge. The PLSR produced an optimal weighting of the similarity scores, which we tested for generality with a jackknife procedure. Fusing the algorithms' similarity scores using the optimal weights produced a twofold reduction of error rate over the most accurate algorithm. Next, human-subject-generated similarity scores were added to the PLSR analysis. Fusing humans and algorithms increased the performance to near-perfect classification accuracy. These results are discussed in terms of maximizing face-verification accuracy with hybrid systems consisting of multiple algorithms and humans.

Qualitative interviews in medical research.

PubMed Central

Britten, N.

1995-01-01

Much qualitative research is interview based, and this paper provides an outline of qualitative interview techniques and their application in medical settings. It explains the rationale for these techniques and shows how they can be used to research kinds of questions that are different from those dealt with by quantitative methods. Different types of qualitative interviews are described, and the way in which they differ from clinical consultations is emphasised. Practical guidance for conducting such interviews is given. Images p252-a PMID:7627048

Evidence-based algorithm for heparin dosing before cardiopulmonary bypass. Part 1: Development of the algorithm.

PubMed

McKinney, Mark C; Riley, Jeffrey B

2007-12-01

The incidence of heparin resistance during adult cardiac surgery with cardiopulmonary bypass has been reported at 15%-20%. The consistent use of a clinical decision-making algorithm may increase the consistency of patient care and likely reduce the total required heparin dose and other problems associated with heparin dosing. After a directed survey of practicing perfusionists regarding treatment of heparin resistance and a literature search for high-level evidence regarding the diagnosis and treatment of heparin resistance, an evidence-based decision-making algorithm was constructed. The face validity of the algorithm decisive steps and logic was confirmed by a second survey of practicing perfusionists. The algorithm begins with review of the patient history to identify predictors for heparin resistance. The definition for heparin resistance contained in the algorithm is an activated clotting time < 450 seconds with > 450 IU/kg heparin loading dose. Based on the literature, the treatment for heparin resistance used in the algorithm is anti-thrombin III supplement. The algorithm seems to be valid and is supported by high-level evidence and clinician opinion. The next step is a human randomized clinical trial to test the clinical procedure guideline algorithm vs. current standard clinical practice.

[Qualitative research in health services research - discussion paper, Part 2: Qualitative research in health services research in Germany - an overview].

PubMed

Karbach, U; Stamer, M; Holmberg, C; Güthlin, C; Patzelt, C; Meyer, T

2012-08-01

This is the second part of a 3-part discussion paper by the working group on "Qualitative Methods" in the German network of health services research (DNVF) that shall contribute to the development of a memorandum concerning qualitative health services research. It aims to depict the different types of qualitative research that are conducted in health services research in Germany. In addition, the authors present a specific set of qualitative data collection and analysis tools to demonstrate the potential of qualitative research for health services research. QUALITATIVE RESEARCH IN HEALTH SERVICES RESEARCH - AN OVERVIEW: To give an overview of the types of qualitative research conducted in German health services research, the abstracts of the 8th German Conference on Health Services Research were filtered to identify qualitative or mixed-methods studies. These were then analysed by looking at the context which was studied, who was studied, the aims of the studies, and what type of methods were used. Those methods that were mentioned most often for data collection and analysis are described in detail. QUALITATIVE RESEARCH AT THE CONFERENCE FOR HEALTH SERVICES RESEARCH 2009: Approximately a fifth of all abstracts (n=74) had a qualitative (n=47) or a mixed-methods approach combining quantitative and qualitative methods (n=27). Research aims included needs assessment (41%), survey development (36%), evaluation (22%), and theorizing (1%). Data collection mostly consisted of one-on-one interviews (n=45) and group discussions (n=29). Qualitative content analysis was named in 35 abstracts, 30 abstracts did not reference their method of analysis. In addition to a quantitative summary of the abstract findings, the diversity of fields addressed by qualitative methods is highlighted. Although drawing conclusions on the use of qualitative methods in German health services research from the analysis of conference abstracts is not possible, the overview we present demonstrates the

Qualitative Methods in Patient-Centered Outcomes Research.

PubMed

Vandermause, Roxanne; Barg, Frances K; Esmail, Laura; Edmundson, Lauren; Girard, Samantha; Perfetti, A Ross

2017-02-01

The Patient-Centered Outcomes Research Institute (PCORI), created to fund research guided by patients, caregivers, and the broader health care community, offers a new research venue. Many (41 of 50) first funded projects involved qualitative research methods. This study was completed to examine the current state of the science of qualitative methodologies used in PCORI-funded research. Principal investigators participated in phenomenological interviews to learn (a) how do researchers using qualitative methods experience seeking funding for, implementing and disseminating their work; and (b) how may qualitative methods advance the quality and relevance of evidence for patients? Results showed the experience of doing qualitative research in the current research climate as "Being a bona fide qualitative researcher: Staying true to research aims while negotiating challenges," with overlapping patterns: (a) researching the elemental, (b) expecting surprise, and (c) pushing boundaries. The nature of qualitative work today was explicitly described and is rendered in this article.

Decryption of pure-position permutation algorithms.

PubMed

Zhao, Xiao-Yu; Chen, Gang; Zhang, Dan; Wang, Xiao-Hong; Dong, Guang-Chang

2004-07-01

Pure position permutation image encryption algorithms, commonly used as image encryption investigated in this work are unfortunately frail under known-text attack. In view of the weakness of pure position permutation algorithm, we put forward an effective decryption algorithm for all pure-position permutation algorithms. First, a summary of the pure position permutation image encryption algorithms is given by introducing the concept of ergodic matrices. Then, by using probability theory and algebraic principles, the decryption probability of pure-position permutation algorithms is verified theoretically; and then, by defining the operation system of fuzzy ergodic matrices, we improve a specific decryption algorithm. Finally, some simulation results are shown.

The Superior Lambert Algorithm

NASA Astrophysics Data System (ADS)

der, G.

2011-09-01

Lambert algorithms are used extensively for initial orbit determination, mission planning, space debris correlation, and missile targeting, just to name a few applications. Due to the significance of the Lambert problem in Astrodynamics, Gauss, Battin, Godal, Lancaster, Gooding, Sun and many others (References 1 to 15) have provided numerous formulations leading to various analytic solutions and iterative methods. Most Lambert algorithms and their computer programs can only work within one revolution, break down or converge slowly when the transfer angle is near zero or 180 degrees, and their multi-revolution limitations are either ignored or barely addressed. Despite claims of robustness, many Lambert algorithms fail without notice, and the users seldom have a clue why. The DerAstrodynamics lambert2 algorithm, which is based on the analytic solution formulated by Sun, works for any number of revolutions and converges rapidly at any transfer angle. It provides significant capability enhancements over every other Lambert algorithm in use today. These include improved speed, accuracy, robustness, and multirevolution capabilities as well as implementation simplicity. Additionally, the lambert2 algorithm provides a powerful tool for solving the angles-only problem without artificial singularities (pointed out by Gooding in Reference 16), which involves 3 lines of sight captured by optical sensors, or systems such as the Air Force Space Surveillance System (AFSSS). The analytic solution is derived from the extended Godal’s time equation by Sun, while the iterative method of solution is that of Laguerre, modified for robustness. The Keplerian solution of a Lambert algorithm can be extended to include the non-Keplerian terms of the Vinti algorithm via a simple targeting technique (References 17 to 19). Accurate analytic non-Keplerian trajectories can be predicted for satellites and ballistic missiles, while performing at least 100 times faster in speed than most

The Texas Medication Algorithm Project antipsychotic algorithm for schizophrenia: 2006 update.

PubMed

Moore, Troy A; Buchanan, Robert W; Buckley, Peter F; Chiles, John A; Conley, Robert R; Crismon, M Lynn; Essock, Susan M; Finnerty, Molly; Marder, Stephen R; Miller, Del D; McEvoy, Joseph P; Robinson, Delbert G; Schooler, Nina R; Shon, Steven P; Stroup, T Scott; Miller, Alexander L

2007-11-01

A panel of academic psychiatrists and pharmacists, clinicians from the Texas public mental health system, advocates, and consumers met in June 2006 in Dallas, Tex., to review recent evidence in the pharmacologic treatment of schizophrenia. The goal of the consensus conference was to update and revise the Texas Medication Algorithm Project (TMAP) algorithm for schizophrenia used in the Texas Implementation of Medication Algorithms, a statewide quality assurance program for treatment of major psychiatric illness. Four questions were identified via premeeting teleconferences. (1) Should antipsychotic treatment of first-episode schizophrenia be different from that of multiepisode schizophrenia? (2) In which algorithm stages should first-generation antipsychotics (FGAs) be an option? (3) How many antipsychotic trials should precede a clozapine trial? (4) What is the status of augmentation strategies for clozapine? Subgroups reviewed the evidence in each area and presented their findings at the conference. The algorithm was updated to incorporate the following recommendations. (1) Persons with first-episode schizophrenia typically require lower antipsychotic doses and are more sensitive to side effects such as weight gain and extrapyramidal symptoms (group consensus). Second-generation antipsychotics (SGAs) are preferred for treatment of first-episode schizophrenia (majority opinion). (2) FGAs should be included in algorithm stages after first episode that include SGAs other than clozapine as options (group consensus). (3) The recommended number of trials of other antipsychotics that should precede a clozapine trial is 2, but earlier use of clozapine should be considered in the presence of persistent problems such as suicidality, comorbid violence, and substance abuse (group consensus). (4) Augmentation is reasonable for persons with inadequate response to clozapine, but published results on augmenting agents have not identified replicable positive results (group

A modified Dodge algorithm for the parabolized Navier-Stokes equation and compressible duct flows

NASA Technical Reports Server (NTRS)

Cooke, C. H.

1981-01-01

A revised version of Dodge's split-velocity method for numerical calculation of compressible duct flow was developed. The revision incorporates balancing of mass flow rates on each marching step in order to maintain front-to-back continuity during the calculation. The (checkerboard) zebra algorithm is applied to solution of the three dimensional continuity equation in conservative form. A second-order A-stable linear multistep method is employed in effecting a marching solution of the parabolized momentum equations. A checkerboard iteration is used to solve the resulting implicit nonlinear systems of finite-difference equations which govern stepwise transition. Qualitive agreement with analytical predictions and experimental results was obtained for some flows with well-known solutions.

Algorithms and Libraries

NASA Technical Reports Server (NTRS)

Dongarra, Jack

1998-01-01

This exploratory study initiated our inquiry into algorithms and applications that would benefit by latency tolerant approach to algorithm building, including the construction of new algorithms where appropriate. In a multithreaded execution, when a processor reaches a point where remote memory access is necessary, the request is sent out on the network and a context--switch occurs to a new thread of computation. This effectively masks a long and unpredictable latency due to remote loads, thereby providing tolerance to remote access latency. We began to develop standards to profile various algorithm and application parameters, such as the degree of parallelism, granularity, precision, instruction set mix, interprocessor communication, latency etc. These tools will continue to develop and evolve as the Information Power Grid environment matures. To provide a richer context for this research, the project also focused on issues of fault-tolerance and computation migration of numerical algorithms and software. During the initial phase we tried to increase our understanding of the bottlenecks in single processor performance. Our work began by developing an approach for the automatic generation and optimization of numerical software for processors with deep memory hierarchies and pipelined functional units. Based on the results we achieved in this study we are planning to study other architectures of interest, including development of cost models, and developing code generators appropriate to these architectures.

Doing qualitative research in dentistry and dental education.

PubMed

Edmunds, S; Brown, G

2012-05-01

The purpose of this paper is to assist dental researchers to develop their expertise in qualitative research. It sketches the key characteristics of qualitative research; summarises theoretical perspectives; outlines the core skills of qualitative data collection and the procedures which underlie three methods of qualitative research: interviewing, focus groups and concept maps. The paper offers some guidance on writing qualitative research and provides examples of qualitative research drawn from dentistry and dental education. © 2012 John Wiley & Sons A/S.

Qualitative methods in environmental health research.

PubMed Central

Brown, Phil

2003-01-01

Public health researchers increasingly turn to qualitative methods either on their own or in combination with quantitative methods. Qualitative methods are especially important to community environmental health research, as they provide a way to produce community narratives that give voice to individuals and characterize the community in a full and complex fashion. This article first traces the legacy of qualitative research in environmental health, then uses a case study of the author's experiences studying the Woburn, Massachusetts, childhood leukemia cluster to provide personal and scholarly insights on qualitative approaches. That material then informs a discussion of important components of qualitative methods in environmental health research, including flexible study design, access, trust, empathy, and personal shifts in the researcher's worldview, bias, and the nature of the researcher's roles. A concluding discussion addresses issues in funding policy and research practices. PMID:14594634

Qualitative methods: beyond the cookbook.

PubMed

Harding, G; Gantley, M

1998-02-01

Qualitative methods appear increasingly in vogue in health services research (HSR). Such research, however, has utilized, often uncritically, a 'cookbook' of methods for data collection, and common-sense principles for data analysis. This paper argues that qualitative HSR benefits from recognizing and drawing upon theoretical principles underlying qualitative data collection and analysis. A distinction is drawn between problem-orientated and theory-orientated research, in order to illustrate how problem-orientated research would benefit from the introduction of theoretical perspectives in order to develop the knowledge base of health services research.

Qualitative tools and experimental philosophy

PubMed Central

Andow, James

2016-01-01

Abstract Experimental philosophy brings empirical methods to philosophy. These methods are used to probe how people think about philosophically interesting things such as knowledge, morality, and freedom. This paper explores the contribution that qualitative methods have to make in this enterprise. I argue that qualitative methods have the potential to make a much greater contribution than they have so far. Along the way, I acknowledge a few types of resistance that proponents of qualitative methods in experimental philosophy might encounter, and provide reasons to think they are ill-founded. PMID:28392629

Qualitative tools and experimental philosophy.

PubMed

Andow, James

2016-11-16

Experimental philosophy brings empirical methods to philosophy. These methods are used to probe how people think about philosophically interesting things such as knowledge, morality, and freedom. This paper explores the contribution that qualitative methods have to make in this enterprise. I argue that qualitative methods have the potential to make a much greater contribution than they have so far. Along the way, I acknowledge a few types of resistance that proponents of qualitative methods in experimental philosophy might encounter, and provide reasons to think they are ill-founded.

On Bayesian methods of exploring qualitative interactions for targeted treatment.

PubMed

Chen, Wei; Ghosh, Debashis; Raghunathan, Trivellore E; Norkin, Maxim; Sargent, Daniel J; Bepler, Gerold

2012-12-10

Providing personalized treatments designed to maximize benefits and minimizing harms is of tremendous current medical interest. One problem in this area is the evaluation of the interaction between the treatment and other predictor variables. Treatment effects in subgroups having the same direction but different magnitudes are called quantitative interactions, whereas those having opposite directions in subgroups are called qualitative interactions (QIs). Identifying QIs is challenging because they are rare and usually unknown among many potential biomarkers. Meanwhile, subgroup analysis reduces the power of hypothesis testing and multiple subgroup analyses inflate the type I error rate. We propose a new Bayesian approach to search for QI in a multiple regression setting with adaptive decision rules. We consider various regression models for the outcome. We illustrate this method in two examples of phase III clinical trials. The algorithm is straightforward and easy to implement using existing software packages. We provide a sample code in Appendix A. Copyright © 2012 John Wiley & Sons, Ltd.

An efficient parallel termination detection algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, A. H.; Crivelli, S.; Jessup, E. R.

2004-05-27

Information local to any one processor is insufficient to monitor the overall progress of most distributed computations. Typically, a second distributed computation for detecting termination of the main computation is necessary. In order to be a useful computational tool, the termination detection routine must operate concurrently with the main computation, adding minimal overhead, and it must promptly and correctly detect termination when it occurs. In this paper, we present a new algorithm for detecting the termination of a parallel computation on distributed-memory MIMD computers that satisfies all of those criteria. A variety of termination detection algorithms have been devised. Ofmore » these, the algorithm presented by Sinha, Kale, and Ramkumar (henceforth, the SKR algorithm) is unique in its ability to adapt to the load conditions of the system on which it runs, thereby minimizing the impact of termination detection on performance. Because their algorithm also detects termination quickly, we consider it to be the most efficient practical algorithm presently available. The termination detection algorithm presented here was developed for use in the PMESC programming library for distributed-memory MIMD computers. Like the SKR algorithm, our algorithm adapts to system loads and imposes little overhead. Also like the SKR algorithm, ours is tree-based, and it does not depend on any assumptions about the physical interconnection topology of the processors or the specifics of the distributed computation. In addition, our algorithm is easier to implement and requires only half as many tree traverses as does the SKR algorithm. This paper is organized as follows. In section 2, we define our computational model. In section 3, we review the SKR algorithm. We introduce our new algorithm in section 4, and prove its correctness in section 5. We discuss its efficiency and present experimental results in section 6.« less

Verifying a Computer Algorithm Mathematically.

ERIC Educational Resources Information Center

Olson, Alton T.

1986-01-01

Presents an example of mathematics from an algorithmic point of view, with emphasis on the design and verification of this algorithm. The program involves finding roots for algebraic equations using the half-interval search algorithm. The program listing is included. (JN)

A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm

PubMed Central

Zhang, Xin; Cui, Jintian; Wang, Weisheng; Lin, Chao

2017-01-01

To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved. PMID:28640181

Adaptive reference update (ARU) algorithm. A stochastic search algorithm for efficient optimization of multi-drug cocktails

PubMed Central

2012-01-01

Background Multi-target therapeutics has been shown to be effective for treating complex diseases, and currently, it is a common practice to combine multiple drugs to treat such diseases to optimize the therapeutic outcomes. However, considering the huge number of possible ways to mix multiple drugs at different concentrations, it is practically difficult to identify the optimal drug combination through exhaustive testing. Results In this paper, we propose a novel stochastic search algorithm, called the adaptive reference update (ARU) algorithm, that can provide an efficient and systematic way for optimizing multi-drug cocktails. The ARU algorithm iteratively updates the drug combination to improve its response, where the update is made by comparing the response of the current combination with that of a reference combination, based on which the beneficial update direction is predicted. The reference combination is continuously updated based on the drug response values observed in the past, thereby adapting to the underlying drug response function. To demonstrate the effectiveness of the proposed algorithm, we evaluated its performance based on various multi-dimensional drug functions and compared it with existing algorithms. Conclusions Simulation results show that the ARU algorithm significantly outperforms existing stochastic search algorithms, including the Gur Game algorithm. In fact, the ARU algorithm can more effectively identify potent drug combinations and it typically spends fewer iterations for finding effective combinations. Furthermore, the ARU algorithm is robust to random fluctuations and noise in the measured drug response, which makes the algorithm well-suited for practical drug optimization applications. PMID:23134742

The PlusCal Algorithm Language

NASA Astrophysics Data System (ADS)

Lamport, Leslie

Algorithms are different from programs and should not be described with programming languages. The only simple alternative to programming languages has been pseudo-code. PlusCal is an algorithm language that can be used right now to replace pseudo-code, for both sequential and concurrent algorithms. It is based on the TLA + specification language, and a PlusCal algorithm is automatically translated to a TLA + specification that can be checked with the TLC model checker and reasoned about formally.

Qualitative Research David Silverman Qualitative Research Sage Publications £26.99 464pp 9781849204170 1849204179 [Formula: see text].

PubMed

2012-01-26

DAVID SILVERMAN'S latest book builds on previous editions to provide up-to-date development in qualitative research and offers an overview of theoretical and practical considerations. Unlike many other qualitative research methodology books there is an emphasis on the function of qualitative research to articulate meaning.

G/SPLINES: A hybrid of Friedman's Multivariate Adaptive Regression Splines (MARS) algorithm with Holland's genetic algorithm

NASA Technical Reports Server (NTRS)

Rogers, David

1991-01-01

G/SPLINES are a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least squares computations, and allows significantly larger problems to be considered.

Software For Genetic Algorithms

NASA Technical Reports Server (NTRS)

Wang, Lui; Bayer, Steve E.

1992-01-01

SPLICER computer program is genetic-algorithm software tool used to solve search and optimization problems. Provides underlying framework and structure for building genetic-algorithm application program. Written in Think C.

Research MethodologyOverview of Qualitative Research

PubMed Central

GROSSOEHME, DANIEL H.

2015-01-01

Qualitative research methods are a robust tool for chaplaincy research questions. Similar to much of chaplaincy clinical care, qualitative research generally works with written texts, often transcriptions of individual interviews or focus group conversations and seeks to understand the meaning of experience in a study sample. This article describes three common methodologies: ethnography, grounded theory, and phenomenology. Issues to consider relating to the study sample, design, and analysis are discussed. Enhancing the validity of the data, as well reliability and ethical issues in qualitative research are described. Qualitative research is an accessible way for chaplains to contribute new knowledge about the sacred dimension of people's lived experience. PMID:24926897

Distributed k-Means Algorithm and Fuzzy c-Means Algorithm for Sensor Networks Based on Multiagent Consensus Theory.

PubMed

Qin, Jiahu; Fu, Weiming; Gao, Huijun; Zheng, Wei Xing

2016-03-03

This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

Quantum algorithm for support matrix machines

NASA Astrophysics Data System (ADS)

Duan, Bojia; Yuan, Jiabin; Liu, Ying; Li, Dan

2017-09-01

We propose a quantum algorithm for support matrix machines (SMMs) that efficiently addresses an image classification problem by introducing a least-squares reformulation. This algorithm consists of two core subroutines: a quantum matrix inversion (Harrow-Hassidim-Lloyd, HHL) algorithm and a quantum singular value thresholding (QSVT) algorithm. The two algorithms can be implemented on a universal quantum computer with complexity O[log(npq) ] and O[log(pq)], respectively, where n is the number of the training data and p q is the size of the feature space. By iterating the algorithms, we can find the parameters for the SMM classfication model. Our analysis shows that both HHL and QSVT algorithms achieve an exponential increase of speed over their classical counterparts.

Commentary: Writing and Evaluating Qualitative Research Reports.

PubMed

Wu, Yelena P; Thompson, Deborah; Aroian, Karen J; McQuaid, Elizabeth L; Deatrick, Janet A

2016-06-01

To provide an overview of qualitative methods, particularly for reviewers and authors who may be less familiar with qualitative research. A question and answer format is used to address considerations for writing and evaluating qualitative research. When producing qualitative research, individuals are encouraged to address the qualitative research considerations raised and to explicitly identify the systematic strategies used to ensure rigor in study design and methods, analysis, and presentation of findings. Increasing capacity for review and publication of qualitative research within pediatric psychology will advance the field's ability to gain a better understanding of the specific needs of pediatric populations, tailor interventions more effectively, and promote optimal health. © The Author 2016. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evolutionary pattern search algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1995-09-19

This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolutionary strategie and real-coded genetic algorithms. EPSAs are self-adapting systems that modify the step size of the mutation operator in response to the success of previous optimization steps. The rule used to adapt the step size can be used to provide a stationary point convergence theory for EPSAs on any continuous function. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods. An experimentalmore » analysis of the performance of EPSAs demonstrates that these algorithms can perform a level of global search that is comparable to that of canonical EAs. We also describe a stopping rule for EPSAs, which reliably terminated near stationary points in our experiments. This is the first stopping rule for any class of EAs that can terminate at a given distance from stationary points.« less

Effects of visualization on algorithm comprehension

NASA Astrophysics Data System (ADS)

Mulvey, Matthew

Computer science students are expected to learn and apply a variety of core algorithms which are an essential part of the field. Any one of these algorithms by itself is not necessarily extremely complex, but remembering the large variety of algorithms and the differences between them is challenging. To address this challenge, we present a novel algorithm visualization tool designed to enhance students understanding of Dijkstra's algorithm by allowing them to discover the rules of the algorithm for themselves. It is hoped that a deeper understanding of the algorithm will help students correctly select, adapt and apply the appropriate algorithm when presented with a problem to solve, and that what is learned here will be applicable to the design of other visualization tools designed to teach different algorithms. Our visualization tool is currently in the prototype stage, and this thesis will discuss the pedagogical approach that informs its design, as well as the results of some initial usability testing. Finally, to clarify the direction for further development of the tool, four different variations of the prototype were implemented, and the instructional effectiveness of each was assessed by having a small sample participants use the different versions of the prototype and then take a quiz to assess their comprehension of the algorithm.

Two Meanings of Algorithmic Mathematics.

ERIC Educational Resources Information Center

Maurer, Stephen B.

1984-01-01

Two mathematical topics are interpreted from the viewpoints of traditional (performing algorithms) and contemporary (creating algorithms and thinking in terms of them for solving problems and developing theory) algorithmic mathematics. The two topics are Horner's method for evaluating polynomials and Gauss's method for solving systems of linear…

Methodological Issues and Practices in Qualitative Research.

ERIC Educational Resources Information Center

Bradley, Jana

1993-01-01

Discusses methodological issues concerning qualitative research and describes research practices that qualitative researchers use to address these methodological issues. Topics discussed include the researcher as interpreter, the emergent nature of qualitative research, understanding the experience of others, trustworthiness in qualitative…

Recursive Branching Simulated Annealing Algorithm

NASA Technical Reports Server (NTRS)

Bolcar, Matthew; Smith, J. Scott; Aronstein, David

2012-01-01

This innovation is a variation of a simulated-annealing optimization algorithm that uses a recursive-branching structure to parallelize the search of a parameter space for the globally optimal solution to an objective. The algorithm has been demonstrated to be more effective at searching a parameter space than traditional simulated-annealing methods for a particular problem of interest, and it can readily be applied to a wide variety of optimization problems, including those with a parameter space having both discrete-value parameters (combinatorial) and continuous-variable parameters. It can take the place of a conventional simulated- annealing, Monte-Carlo, or random- walk algorithm. In a conventional simulated-annealing (SA) algorithm, a starting configuration is randomly selected within the parameter space. The algorithm randomly selects another configuration from the parameter space and evaluates the objective function for that configuration. If the objective function value is better than the previous value, the new configuration is adopted as the new point of interest in the parameter space. If the objective function value is worse than the previous value, the new configuration may be adopted, with a probability determined by a temperature parameter, used in analogy to annealing in metals. As the optimization continues, the region of the parameter space from which new configurations can be selected shrinks, and in conjunction with lowering the annealing temperature (and thus lowering the probability for adopting configurations in parameter space with worse objective functions), the algorithm can converge on the globally optimal configuration. The Recursive Branching Simulated Annealing (RBSA) algorithm shares some features with the SA algorithm, notably including the basic principles that a starting configuration is randomly selected from within the parameter space, the algorithm tests other configurations with the goal of finding the globally optimal

Estimation of TOA based MUSIC algorithm and cross correlation algorithm of appropriate interval

NASA Astrophysics Data System (ADS)

Lin, Wei; Liu, Jun; Zhou, Yineng; Huang, Jiyan

2017-03-01

Localization of mobile station (MS) has now gained considerable attention due to its wide applications in military, environmental, health and commercial systems. Phrase angle and encode data of MSK system model are two critical parameters in time-of-arrival (TOA) localization technique; nevertheless, precise value of phrase angle and encode data are not easy to achieved in general. In order to meet the actual situation, we should consider the condition that phase angle and encode data is unknown. In this paper, a novel TOA localization method, which combine MUSIC algorithm and cross correlation algorithm in an appropriate interval, is proposed. Simulations show that the proposed method has better performance than music algorithm and cross correlation algorithm of the whole interval.

An overview of smart grid routing algorithms

NASA Astrophysics Data System (ADS)

Wang, Junsheng; OU, Qinghai; Shen, Haijuan

2017-08-01

This paper summarizes the typical routing algorithm in smart grid by analyzing the communication business and communication requirements of intelligent grid. Mainly from the two kinds of routing algorithm is analyzed, namely clustering routing algorithm and routing algorithm, analyzed the advantages and disadvantages of two kinds of typical routing algorithm in routing algorithm and applicability.

Solar Occultation Retrieval Algorithm Development

NASA Technical Reports Server (NTRS)

Lumpe, Jerry D.

2004-01-01

This effort addresses the comparison and validation of currently operational solar occultation retrieval algorithms, and the development of generalized algorithms for future application to multiple platforms. initial development of generalized forward model algorithms capable of simulating transmission data from of the POAM II/III and SAGE II/III instruments. Work in the 2" quarter will focus on: completion of forward model algorithms, including accurate spectral characteristics for all instruments, and comparison of simulated transmission data with actual level 1 instrument data for specific occultation events.

A Parametric k-Means Algorithm

PubMed Central

Tarpey, Thaddeus

2007-01-01

Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692

Teaching Qualitative Research Methods Using "Undercover Boss"

ERIC Educational Resources Information Center

Graham, LaKresha; Schuwerk, Tara J.

2017-01-01

Course(s): Research Methods, Qualitative Research Methods, Organizational Communication, Business Communication. Objectives: After completing this class exercise, students should be able to identify the major components of a qualitative research study, along with the ethical dilemmas that come with doing qualitative research.

Infusing Qualitative Traditions in Counseling Research Designs

ERIC Educational Resources Information Center

Hays, Danica G.; Wood, Chris

2011-01-01

Research traditions serve as a blueprint or guide for a variety of design decisions throughout qualitative inquiry. This article presents 6 qualitative research traditions: grounded theory, phenomenology, consensual qualitative research, ethnography, narratology, and participatory action research. For each tradition, the authors describe its…

Analysis of an Optimized MLOS Tomographic Reconstruction Algorithm and Comparison to the MART Reconstruction Algorithm

NASA Astrophysics Data System (ADS)

La Foy, Roderick; Vlachos, Pavlos

2011-11-01

An optimally designed MLOS tomographic reconstruction algorithm for use in 3D PIV and PTV applications is analyzed. Using a set of optimized reconstruction parameters, the reconstructions produced by the MLOS algorithm are shown to be comparable to reconstructions produced by the MART algorithm for a range of camera geometries, camera numbers, and particle seeding densities. The resultant velocity field error calculated using PIV and PTV algorithms is further minimized by applying both pre and post processing to the reconstructed data sets.

DNABIT Compress – Genome compression algorithm

PubMed Central

Rajarajeswari, Pothuraju; Apparao, Allam

2011-01-01

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, “DNABIT Compress” for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that “DNABIT Compress” algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases. PMID:21383923

[A call for qualitative research in Orthodontics].

PubMed

Yitschaky, O; Hofnung, T; Zini, A

2015-01-01

Qualitative research is an umbrella term for an array of attitudes and strategies for conducting inquiries that are aimed at discerning how human beings understand, experience, and interpret the social world. It is employed in many different academic disciplines most particularly in the social sciences and humanities, however recently more and more qualitative research is being conducted under the medical sciences including dentistry and orthodontics. This is due to its nature of in-depth investigation, which can provide answers to questions that cannot be satisfactorily answered using quantitative methods alone. The aims of this article are to discuss the characteristics of qualitative research, to review the orthodontic English literature, and to highlight the advantages of qualitative research in orthodontics. The literature review yielded several important conclusions regarding qualitative research in orthodontics: 1. most of the qualitative research done in orthodontics chose to use semi structured in-depth interviews for data collection; 2. qualitative research highlights aspects that are very important, and sometimes crucial to everyday practice and long term treatment; 3. there is a lack of qualitative studies in the field of orthodontics. Taking into account the nature of the orthodontic treatment, which is a prolonged one, demanding of a good orthodontist-patient rapport, and a wide perspective on behalf of the clinician, filling the gap in the discipline through conducting more qualitative studies aimed at understanding the point of view of the patient, as well as that of the clinician, may be beneficial for the improvement of the treatment.

Qualitative data analysis: conceptual and practical considerations.

PubMed

Liamputtong, Pranee

2009-08-01

Qualitative inquiry requires that collected data is organised in a meaningful way, and this is referred to as data analysis. Through analytic processes, researchers turn what can be voluminous data into understandable and insightful analysis. This paper sets out the different approaches that qualitative researchers can use to make sense of their data including thematic analysis, narrative analysis, discourse analysis and semiotic analysis and discusses the ways that qualitative researchers can analyse their data. I first discuss salient issues in performing qualitative data analysis, and then proceed to provide some suggestions on different methods of data analysis in qualitative research. Finally, I provide some discussion on the use of computer-assisted data analysis.

A fast least-squares algorithm for population inference

PubMed Central

2013-01-01

Background Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual’s genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning. Results We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1

A fast least-squares algorithm for population inference.

PubMed

Parry, R Mitchell; Wang, May D

2013-01-23

Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual's genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning. We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1.5- to 6-times faster

Employing a Qualitative Description Approach in Health Care Research.

PubMed

Bradshaw, Carmel; Atkinson, Sandra; Doody, Owen

2017-01-01

A qualitative description design is particularly relevant where information is required directly from those experiencing the phenomenon under investigation and where time and resources are limited. Nurses and midwives often have clinical questions suitable to a qualitative approach but little time to develop an exhaustive comprehension of qualitative methodological approaches. Qualitative description research is sometimes considered a less sophisticated approach for epistemological reasons. Another challenge when considering qualitative description design is differentiating qualitative description from other qualitative approaches. This article provides a systematic and robust journey through the philosophical, ontological, and epistemological perspectives, which evidences the purpose of qualitative description research. Methods and rigor issues underpinning qualitative description research are also appraised to provide the researcher with a systematic approach to conduct research utilizing this approach. The key attributes and value of qualitative description research in the health care professions will be highlighted with the aim of extending its usage.

Language barriers and qualitative nursing research: methodological considerations.

PubMed

Squires, A

2008-09-01

This review of the literature synthesizes methodological recommendations for the use of translators and interpreters in cross-language qualitative research. Cross-language qualitative research involves the use of interpreters and translators to mediate a language barrier between researchers and participants. Qualitative nurse researchers successfully address language barriers between themselves and their participants when they systematically plan for how they will use interpreters and translators throughout the research process. Experienced qualitative researchers recognize that translators can generate qualitative data through translation processes and by participating in data analysis. Failure to address language barriers and the methodological challenges they present threatens the credibility, transferability, dependability and confirmability of cross-language qualitative nursing research. Through a synthesis of the cross-language qualitative methods literature, this article reviews the basics of language competence, translator and interpreter qualifications, and roles for each kind of qualitative research approach. Methodological and ethical considerations are also provided. By systematically addressing the methodological challenges cross-language research presents, nurse researchers can produce better evidence for nursing practice and policy making when working across different language groups. Findings from qualitative studies will also accurately represent the experiences of the participants without concern that the meaning was lost in translation.

SU-E-J-218: Evaluation of CT Images Created Using a New Metal Artifact Reduction Reconstruction Algorithm for Radiation Therapy Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niemkiewicz, J; Palmiotti, A; Miner, M

2014-06-01

Purpose: Metal in patients creates streak artifacts in CT images. When used for radiation treatment planning, these artifacts make it difficult to identify internal structures and affects radiation dose calculations, which depend on HU numbers for inhomogeneity correction. This work quantitatively evaluates a new metal artifact reduction (MAR) CT image reconstruction algorithm (GE Healthcare CT-0521-04.13-EN-US DOC1381483) when metal is present. Methods: A Gammex Model 467 Tissue Characterization phantom was used. CT images were taken of this phantom on a GE Optima580RT CT scanner with and without steel and titanium plugs using both the standard and MAR reconstruction algorithms. HU valuesmore » were compared pixel by pixel to determine if the MAR algorithm altered the HUs of normal tissues when no metal is present, and to evaluate the effect of using the MAR algorithm when metal is present. Also, CT images of patients with internal metal objects using standard and MAR reconstruction algorithms were compared. Results: Comparing the standard and MAR reconstructed images of the phantom without metal, 95.0% of pixels were within ±35 HU and 98.0% of pixels were within ±85 HU. Also, the MAR reconstruction algorithm showed significant improvement in maintaining HUs of non-metallic regions in the images taken of the phantom with metal. HU Gamma analysis (2%, 2mm) of metal vs. non-metal phantom imaging using standard reconstruction resulted in an 84.8% pass rate compared to 96.6% for the MAR reconstructed images. CT images of patients with metal show significant artifact reduction when reconstructed with the MAR algorithm. Conclusion: CT imaging using the MAR reconstruction algorithm provides improved visualization of internal anatomy and more accurate HUs when metal is present compared to the standard reconstruction algorithm. MAR reconstructed CT images provide qualitative and quantitative improvements over current reconstruction algorithms, thus improving radiation

Methodology Series Module 10: Qualitative Health Research

PubMed Central

Setia, Maninder Singh

2017-01-01

Although quantitative designs are commonly used in clinical research, some studies require qualitative methods. These designs are different from quantitative methods; thus, researchers should be aware of data collection methods and analyses for qualitative research. Qualitative methods are particularly useful to understand patient experiences with the treatment or new methods of management or to explore issues in detail. These methods are useful in social and behavioral research. In qualitative research, often, the main focus is to understand the issue in detail rather than generalizability; thus, the sampling methods commonly used are purposive sampling; quota sampling; and snowball sampling (for hard to reach groups). Data can be collected using in-depth interviews (IDIs) or focus group discussions (FGDs). IDI is a one-to-one interview with the participant. FGD is a method of group interview or discussion, in which more than one participant is interviewed at the same time and is usually led by a facilitator. The commonly used methods for data analysis are: thematic analysis; grounded theory analysis; and framework analysis. Qualitative data collection and analysis require special expertise. Hence, if the reader plans to conduct qualitative research, they should team up with a qualitative researcher. PMID:28794545

Methodology Series Module 10: Qualitative Health Research.

PubMed

Setia, Maninder Singh

2017-01-01

Although quantitative designs are commonly used in clinical research, some studies require qualitative methods. These designs are different from quantitative methods; thus, researchers should be aware of data collection methods and analyses for qualitative research. Qualitative methods are particularly useful to understand patient experiences with the treatment or new methods of management or to explore issues in detail. These methods are useful in social and behavioral research. In qualitative research, often, the main focus is to understand the issue in detail rather than generalizability; thus, the sampling methods commonly used are purposive sampling; quota sampling; and snowball sampling (for hard to reach groups). Data can be collected using in-depth interviews (IDIs) or focus group discussions (FGDs). IDI is a one-to-one interview with the participant. FGD is a method of group interview or discussion, in which more than one participant is interviewed at the same time and is usually led by a facilitator. The commonly used methods for data analysis are: thematic analysis; grounded theory analysis; and framework analysis. Qualitative data collection and analysis require special expertise. Hence, if the reader plans to conduct qualitative research, they should team up with a qualitative researcher.

Smell Detection Agent Based Optimization Algorithm

NASA Astrophysics Data System (ADS)

Vinod Chandra, S. S.

2016-09-01

In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

Quantum algorithm for linear regression

NASA Astrophysics Data System (ADS)

Wang, Guoming

2017-07-01

We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.

Contact solution algorithms

NASA Technical Reports Server (NTRS)

Tielking, John T.

1989-01-01

Two algorithms for obtaining static contact solutions are described in this presentation. Although they were derived for contact problems involving specific structures (a tire and a solid rubber cylinder), they are sufficiently general to be applied to other shell-of-revolution and solid-body contact problems. The shell-of-revolution contact algorithm is a method of obtaining a point load influence coefficient matrix for the portion of shell surface that is expected to carry a contact load. If the shell is sufficiently linear with respect to contact loading, a single influence coefficient matrix can be used to obtain a good approximation of the contact pressure distribution. Otherwise, the matrix will be updated to reflect nonlinear load-deflection behavior. The solid-body contact algorithm utilizes a Lagrange multiplier to include the contact constraint in a potential energy functional. The solution is found by applying the principle of minimum potential energy. The Lagrange multiplier is identified as the contact load resultant for a specific deflection. At present, only frictionless contact solutions have been obtained with these algorithms. A sliding tread element has been developed to calculate friction shear force in the contact region of the rolling shell-of-revolution tire model.

A General Survey of Qualitative Research Methodology.

ERIC Educational Resources Information Center

Cary, Rick

Current definitions and philosophical foundations of qualitative research are presented; and designs, evaluation methods, and issues in application of qualitative research to education are discussed. The effects of positivism and the post-positivist era on qualitative research are outlined, and naturalist and positivist approaches are contrasted.…

Synthesis of Greedy Algorithms Using Dominance Relations

NASA Technical Reports Server (NTRS)

Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.

2010-01-01

Greedy algorithms exploit problem structure and constraints to achieve linear-time performance. Yet there is still no completely satisfactory way of constructing greedy algorithms. For example, the Greedy Algorithm of Edmonds depends upon translating a problem into an algebraic structure called a matroid, but the existence of such a translation can be as hard to determine as the existence of a greedy algorithm itself. An alternative characterization of greedy algorithms is in terms of dominance relations, a well-known algorithmic technique used to prune search spaces. We demonstrate a process by which dominance relations can be methodically derived for a number of greedy algorithms, including activity selection, and prefix-free codes. By incorporating our approach into an existing framework for algorithm synthesis, we demonstrate that it could be the basis for an effective engineering method for greedy algorithms. We also compare our approach with other characterizations of greedy algorithms.

Algorithm for Compressing Time-Series Data

NASA Technical Reports Server (NTRS)

Hawkins, S. Edward, III; Darlington, Edward Hugo

2012-01-01

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

Novel medical image enhancement algorithms

NASA Astrophysics Data System (ADS)

Agaian, Sos; McClendon, Stephen A.

2010-01-01

In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

Tactical Synthesis Of Efficient Global Search Algorithms

NASA Technical Reports Server (NTRS)

Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.

2009-01-01

Algorithm synthesis transforms a formal specification into an efficient algorithm to solve a problem. Algorithm synthesis in Specware combines the formal specification of a problem with a high-level algorithm strategy. To derive an efficient algorithm, a developer must define operators that refine the algorithm by combining the generic operators in the algorithm with the details of the problem specification. This derivation requires skill and a deep understanding of the problem and the algorithmic strategy. In this paper we introduce two tactics to ease this process. The tactics serve a similar purpose to tactics used for determining indefinite integrals in calculus, that is suggesting possible ways to attack the problem.

Trees, bialgebras and intrinsic numerical algorithms

NASA Technical Reports Server (NTRS)

Crouch, Peter; Grossman, Robert; Larson, Richard

1990-01-01

Preliminary work about intrinsic numerical integrators evolving on groups is described. Fix a finite dimensional Lie group G; let g denote its Lie algebra, and let Y(sub 1),...,Y(sub N) denote a basis of g. A class of numerical algorithms is presented that approximate solutions to differential equations evolving on G of the form: dot-x(t) = F(x(t)), x(0) = p is an element of G. The algorithms depend upon constants c(sub i) and c(sub ij), for i = 1,...,k and j is less than i. The algorithms have the property that if the algorithm starts on the group, then it remains on the group. In addition, they also have the property that if G is the abelian group R(N), then the algorithm becomes the classical Runge-Kutta algorithm. The Cayley algebra generated by labeled, ordered trees is used to generate the equations that the coefficients c(sub i) and c(sub ij) must satisfy in order for the algorithm to yield an rth order numerical integrator and to analyze the resulting algorithms.

Employing a Qualitative Description Approach in Health Care Research

PubMed Central

Bradshaw, Carmel; Atkinson, Sandra; Doody, Owen

2017-01-01

A qualitative description design is particularly relevant where information is required directly from those experiencing the phenomenon under investigation and where time and resources are limited. Nurses and midwives often have clinical questions suitable to a qualitative approach but little time to develop an exhaustive comprehension of qualitative methodological approaches. Qualitative description research is sometimes considered a less sophisticated approach for epistemological reasons. Another challenge when considering qualitative description design is differentiating qualitative description from other qualitative approaches. This article provides a systematic and robust journey through the philosophical, ontological, and epistemological perspectives, which evidences the purpose of qualitative description research. Methods and rigor issues underpinning qualitative description research are also appraised to provide the researcher with a systematic approach to conduct research utilizing this approach. The key attributes and value of qualitative description research in the health care professions will be highlighted with the aim of extending its usage. PMID:29204457

Empirical study of parallel LRU simulation algorithms

NASA Technical Reports Server (NTRS)

Carr, Eric; Nicol, David M.

1994-01-01

This paper reports on the performance of five parallel algorithms for simulating a fully associative cache operating under the LRU (Least-Recently-Used) replacement policy. Three of the algorithms are SIMD, and are implemented on the MasPar MP-2 architecture. Two other algorithms are parallelizations of an efficient serial algorithm on the Intel Paragon. One SIMD algorithm is quite simple, but its cost is linear in the cache size. The two other SIMD algorithm are more complex, but have costs that are independent on the cache size. Both the second and third SIMD algorithms compute all stack distances; the second SIMD algorithm is completely general, whereas the third SIMD algorithm presumes and takes advantage of bounds on the range of reference tags. Both MIMD algorithm implemented on the Paragon are general and compute all stack distances; they differ in one step that may affect their respective scalability. We assess the strengths and weaknesses of these algorithms as a function of problem size and characteristics, and compare their performance on traces derived from execution of three SPEC benchmark programs.

Using Qualitative Research Methods in Higher Education

ERIC Educational Resources Information Center

Savenye, Wilhelmina C.; Robinson, Rhonda S.

2005-01-01

Researchers investigating issues related to computing in higher education are increasingly using qualitative research methods to conduct their investigations. However, they may have little training or experience in qualitative research. The purpose of this paper is to introduce researchers to the appropriate use of qualitative methods. It begins…

Rocket engine diagnostics using qualitative modeling techniques

NASA Technical Reports Server (NTRS)

Binder, Michael; Maul, William; Meyer, Claudia; Sovie, Amy

1992-01-01

Researchers at NASA Lewis Research Center are presently developing qualitative modeling techniques for automated rocket engine diagnostics. A qualitative model of a turbopump interpropellant seal system was created. The qualitative model describes the effects of seal failures on the system steady state behavior. This model is able to diagnose the failure of particular seals in the system based on anomalous temperature and pressure values. The anomalous values input to the qualitative model are generated using numerical simulations. Diagnostic test cases include both single and multiple seal failures.

Firefly algorithm with chaos

NASA Astrophysics Data System (ADS)

Gandomi, A. H.; Yang, X.-S.; Talatahari, S.; Alavi, A. H.

2013-01-01

A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA.

Conducting Qualitative Data Analysis: Managing Dynamic Tensions within

ERIC Educational Resources Information Center

Chenail, Ronald J.

2012-01-01

In the third of a series of "how-to" essays on conducting qualitative data analysis, Ron Chenail examines the dynamic tensions within the process of qualitative data analysis that qualitative researchers must manage in order to produce credible and creative results. These tensions include (a) the qualities of the data and the qualitative data…

Conducting Qualitative Data Analysis: Reading Line-by-Line, but Analyzing by Meaningful Qualitative Units

ERIC Educational Resources Information Center

Chenail, Ronald J.

2012-01-01

In the first of a series of "how-to" essays on conducting qualitative data analysis, Ron Chenail points out the challenges of determining units to analyze qualitatively when dealing with text. He acknowledges that although we may read a document word-by-word or line-by-line, we need to adjust our focus when processing the text for purposes of…

The role of qualitative research in psychological journals.

PubMed

Kidd, Sean A

2002-03-01

The acceptance of qualitative research in 15 journals published and distributed by the American Psychological Association (APA) was investigated. This investigation included a PsycINFO search using the keyword qualitative, an analysis of 15 APA journals for frequency of qualitative publication, a content analysis of the journal descriptions, and the results of qualitative interviews with 10 of the chief editors of those journals. The results indicate that there exists a substantial amount of interest in the potential contribution of qualitative methods in major psychological journals, although this interest is not ubiquitous, well defined, or communicated. These findings highlight the need for APA to state its position regarding the applicability of qualitative methods in the study of psychology.

Computer-Assisted Analysis of Qualitative Gerontological Research.

ERIC Educational Resources Information Center

Hiemstra, Roger; And Others

1987-01-01

Asserts that qualitative research has great potential for use in gerontological research. Describes QUALOG, a computer-assisted, qualitative data analysis scheme using logic programming developed at Syracuse University. Reviews development of QUALOG and discusses how QUALOG was used to analyze data from a qualitative study of older adult learners.…

A modified Dodge algorithm for the parabolized Navier-Stokes equations and compressible duct flows

NASA Technical Reports Server (NTRS)

Cooke, C. H.; Dwoyer, D. M.

1983-01-01

A revised version of Dodge's split-velocity method for numerical calculation of compressible duct flow was developed. The revision incorporates balancing of mass flow rates on each marching step in order to maintain front-to-back continuity during the calculation. The (checkerboard) zebra algorithm is applied to solution of the three dimensional continuity equation in conservative form. A second-order A-stable linear multistep method is employed in effecting a marching solution of the parabolized momentum equations. A checkerboard iteration is used to solve the resulting implicit nonlinear systems of finite-difference equations which govern stepwise transition. Qualitative agreement with analytical predictions and experimental results was obtained for some flows with well-known solutions. Previously announced in STAR as N82-16363

NOSS Altimeter Detailed Algorithm specifications

NASA Technical Reports Server (NTRS)

Hancock, D. W.; Mcmillan, J. D.

1982-01-01

The details of the algorithms and data sets required for satellite radar altimeter data processing are documented in a form suitable for (1) development of the benchmark software and (2) coding the operational software. The algorithms reported in detail are those established for altimeter processing. The algorithms which required some additional development before documenting for production were only scoped. The algorithms are divided into two levels of processing. The first level converts the data to engineering units and applies corrections for instrument variations. The second level provides geophysical measurements derived from altimeter parameters for oceanographic users.

Algorithmic complexity of quantum capacity

NASA Astrophysics Data System (ADS)

Oskouei, Samad Khabbazi; Mancini, Stefano

2018-04-01

We analyze the notion of quantum capacity from the perspective of algorithmic (descriptive) complexity. To this end, we resort to the concept of semi-computability in order to describe quantum states and quantum channel maps. We introduce algorithmic entropies (like algorithmic quantum coherent information) and derive relevant properties for them. Then we show that quantum capacity based on semi-computable concept equals the entropy rate of algorithmic coherent information, which in turn equals the standard quantum capacity. Thanks to this, we finally prove that the quantum capacity, for a given semi-computable channel, is limit computable.

Language barriers and qualitative nursing research: methodological considerations

PubMed Central

Squires, A.

2009-01-01

Aim This review of the literature synthesizes methodological recommendations for the use of translators and interpreters in cross-language qualitative research. Background Cross-language qualitative research involves the use of interpreters and translators to mediate a language barrier between researchers and participants. Qualitative nurse researchers successfully address language barriers between themselves and their participants when they systematically plan for how they will use interpreters and translators throughout the research process. Experienced qualitative researchers recognize that translators can generate qualitative data through translation processes and by participating in data analysis. Failure to address language barriers and the methodological challenges they present threatens the credibility, transferability, dependability and confirmability of cross-language qualitative nursing research. Through a synthesis of the cross-language qualitative methods literature, this article reviews the basics of language competence, translator and interpreter qualifications, and roles for each kind of qualitative research approach. Methodological and ethical considerations are also provided. Conclusion By systematically addressing the methodological challenges cross-language research presents, nurse researchers can produce better evidence for nursing practice and policy making when working across different language groups. Findings from qualitative studies will also accurately represent the experiences of the participants without concern that the meaning was lost in translation. PMID:19522941

[Qualitative research methodology in health care].

PubMed

Bedregal, Paula; Besoain, Carolina; Reinoso, Alejandro; Zubarew, Tamara

2017-03-01

Health care research requires different methodological approaches such as qualitative and quantitative analyzes to understand the phenomena under study. Qualitative research is usually the least considered. Central elements of the qualitative method are that the object of study is constituted by perceptions, emotions and beliefs, non-random sampling by purpose, circular process of knowledge construction, and methodological rigor throughout the research process, from quality design to the consistency of results. The objective of this work is to contribute to the methodological knowledge about qualitative research in health services, based on the implementation of the study, “The transition process from pediatric to adult services: perspectives from adolescents with chronic diseases, caregivers and health professionals”. The information gathered through the qualitative methodology facilitated the understanding of critical points, barriers and facilitators of the transition process of adolescents with chronic diseases, considering the perspective of users and the health team. This study allowed the design of a transition services model from pediatric to adult health services based on the needs of adolescents with chronic diseases, their caregivers and the health team.

OC24 - An algorithm proposal to oral feeding in premature infants.

PubMed

Neto, Florbela; França, Ana Paula; Cruz, Sandra

2016-05-09

Theme: Transition of care. Oral feeding is one of the hardest steps for premature infants after respiratory independence and is a challenge for nurses in neonatology. To know the characteristics of preterm infants, essential for oral feeding; to know the nurses' opinion on nursing interventions, that promote the transition of gavage feeding for oral feeding in preterm infants. An exploratory, descriptive study with a qualitative approach was used. Semi-structured interviews with neonatal nurses were conducted and data was submitted to content analysis. Weight, gestational age, physiological stability, sucking coordination, swallowing and breathing, and the overall look and feeding involvement are fundamental parameters to begin oral feeding. Positioning the baby, reflexes stimulation, control stress levels, monitoring the temperature and the milk flow are nursing interventions that promote the development of feeding skills. An algorithm for the oral feeding of preterm infants was developed grounded in the opinions of nurses.

An Extensive Study on Data Anonymization Algorithms Based on K-Anonymity

NASA Astrophysics Data System (ADS)

Simi, Ms. M. S.; Sankara Nayaki, Mrs. K.; Sudheep Elayidom, M., Dr.

2017-08-01

For business and research oriented works engaging Data Analysis and Cloud services needing qualitative data, many organizations release huge microdata. It excludes an individual’s explicit identity marks like name, address and comprises of specific information like DOB, Pin-code, sex, marital status, which can be combined with other public data to recognize a person. This implication attack can be manipulated to acquire any sensitive information from social network platform, thereby putting the privacy of a person in grave danger. To prevent such attacks by modifying microdata, K-anonymization is used. With potentially increasing data, the effective method to anonymize it stands challenging. After series of trails and systematic comparison, in this paper, we propose three best algorithms along with its efficiency and effectiveness. Studies help researchers to identify the relationship between the values of k, degree of anonymization, choosing a quasi-identifier and focus on execution time.

Families of Graph Algorithms: SSSP Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanewala Appuhamilage, Thejaka Amila Jay; Zalewski, Marcin J.; Lumsdaine, Andrew

2017-08-28

Single-Source Shortest Paths (SSSP) is a well-studied graph problem. Examples of SSSP algorithms include the original Dijkstra’s algorithm and the parallel Δ-stepping and KLA-SSSP algorithms. In this paper, we use a novel Abstract Graph Machine (AGM) model to show that all these algorithms share a common logic and differ from one another by the order in which they perform work. We use the AGM model to thoroughly analyze the family of algorithms that arises from the common logic. We start with the basic algorithm without any ordering (Chaotic), and then we derive the existing and new algorithms by methodically exploringmore » semantic and spatial ordering of work. Our experimental results show that new derived algorithms show better performance than the existing distributed memory parallel algorithms, especially at higher scales.« less

A Qualitative Toolkit for Institutional Research

ERIC Educational Resources Information Center

George Mwangi, Chrystal A.; Bettencourt, Genia M.

2017-01-01

This chapter provides tools, resources, and examples for engaging qualitative inquiry as a part of institutional research and assessment. It supports the development of individual ability and organizational intelligence in qualitative inquiry.

Qualitative research methods in renal medicine: an introduction.

PubMed

Bristowe, Katherine; Selman, Lucy; Murtagh, Fliss E M

2015-09-01

Qualitative methodologies are becoming increasingly widely used in health research. However, within some specialties, including renal medicine, qualitative approaches remain under-represented in the high-impact factor journals. Qualitative research can be undertaken: (i) as a stand-alone research method, addressing specific research questions; (ii) as part of a mixed methods approach alongside quantitative approaches or (iii) embedded in clinical trials, or during the development of complex interventions. The aim of this paper is to introduce qualitative research, including the rationale for choosing qualitative approaches, and guidance for ensuring quality when undertaking and reporting qualitative research. In addition, we introduce types of qualitative data (observation, interviews and focus groups) as well as some of the most commonly encountered methodological approaches (case studies, ethnography, phenomenology, grounded theory, thematic analysis, framework analysis and content analysis). © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Rocket engine diagnostics using qualitative modeling techniques

NASA Technical Reports Server (NTRS)

Binder, Michael; Maul, William; Meyer, Claudia; Sovie, Amy

1992-01-01

Researchers at NASA Lewis Research Center are presently developing qualitative modeling techniques for automated rocket engine diagnostics. A qualitative model of a turbopump interpropellant seal system has been created. The qualitative model describes the effects of seal failures on the system steady-state behavior. This model is able to diagnose the failure of particular seals in the system based on anomalous temperature and pressure values. The anomalous values input to the qualitative model are generated using numerical simulations. Diagnostic test cases include both single and multiple seal failures.

Evaluation of a Machine-Learning Algorithm for Treatment Planning in Prostate Low-Dose-Rate Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicolae, Alexandru; Department of Medical Physics, Odette Cancer Center, Sunnybrook Health Sciences Centre, Toronto, Ontario; Morton, Gerard

Purpose: This work presents the application of a machine learning (ML) algorithm to automatically generate high-quality, prostate low-dose-rate (LDR) brachytherapy treatment plans. The ML algorithm can mimic characteristics of preoperative treatment plans deemed clinically acceptable by brachytherapists. The planning efficiency, dosimetry, and quality (as assessed by experts) of preoperative plans generated with an ML planning approach was retrospectively evaluated in this study. Methods and Materials: Preimplantation and postimplantation treatment plans were extracted from 100 high-quality LDR treatments and stored within a training database. The ML training algorithm matches similar features from a new LDR case to those within the trainingmore » database to rapidly obtain an initial seed distribution; plans were then further fine-tuned using stochastic optimization. Preimplantation treatment plans generated by the ML algorithm were compared with brachytherapist (BT) treatment plans in terms of planning time (Wilcoxon rank sum, α = 0.05) and dosimetry (1-way analysis of variance, α = 0.05). Qualitative preimplantation plan quality was evaluated by expert LDR radiation oncologists using a Likert scale questionnaire. Results: The average planning time for the ML approach was 0.84 ± 0.57 minutes, compared with 17.88 ± 8.76 minutes for the expert planner (P=.020). Preimplantation plans were dosimetrically equivalent to the BT plans; the average prostate V150% was 4% lower for ML plans (P=.002), although the difference was not clinically significant. Respondents ranked the ML-generated plans as equivalent to expert BT treatment plans in terms of target coverage, normal tissue avoidance, implant confidence, and the need for plan modifications. Respondents had difficulty differentiating between plans generated by a human or those generated by the ML algorithm. Conclusions: Prostate LDR preimplantation treatment plans that have equivalent quality to plans

Portable Health Algorithms Test System

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.; Wong, Edmond; Fulton, Christopher E.; Sowers, Thomas S.; Maul, William A.

2010-01-01

A document discusses the Portable Health Algorithms Test (PHALT) System, which has been designed as a means for evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT system allows systems health management algorithms to be developed in a graphical programming environment, to be tested and refined using system simulation or test data playback, and to be evaluated in a real-time hardware-in-the-loop mode with a live test article. The integrated hardware and software development environment provides a seamless transition from algorithm development to real-time implementation. The portability of the hardware makes it quick and easy to transport between test facilities. This hard ware/software architecture is flexible enough to support a variety of diagnostic applications and test hardware, and the GUI-based rapid prototyping capability is sufficient to support development execution, and testing of custom diagnostic algorithms. The PHALT operating system supports execution of diagnostic algorithms under real-time constraints. PHALT can perform real-time capture and playback of test rig data with the ability to augment/ modify the data stream (e.g. inject simulated faults). It performs algorithm testing using a variety of data input sources, including real-time data acquisition, test data playback, and system simulations, and also provides system feedback to evaluate closed-loop diagnostic response and mitigation control.

Hardware Acceleration of Adaptive Neural Algorithms.

DOE Office of Scientific and Technical Information (OSTI.GOV)

James, Conrad D.

As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - worldmore » conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.« less

A genetic algorithm for replica server placement

NASA Astrophysics Data System (ADS)

Eslami, Ghazaleh; Toroghi Haghighat, Abolfazl

2012-01-01

Modern distribution systems use replication to improve communication delay experienced by their clients. Some techniques have been developed for web server replica placement. One of the previous studies was Greedy algorithm proposed by Qiu et al, that needs knowledge about network topology. In This paper, first we introduce a genetic algorithm for web server replica placement. Second, we compare our algorithm with Greedy algorithm proposed by Qiu et al, and Optimum algorithm. We found that our approach can achieve better results than Greedy algorithm proposed by Qiu et al but it's computational time is more than Greedy algorithm.

A genetic algorithm for replica server placement

NASA Astrophysics Data System (ADS)

Eslami, Ghazaleh; Toroghi Haghighat, Abolfazl

2011-12-01

Modern distribution systems use replication to improve communication delay experienced by their clients. Some techniques have been developed for web server replica placement. One of the previous studies was Greedy algorithm proposed by Qiu et al, that needs knowledge about network topology. In This paper, first we introduce a genetic algorithm for web server replica placement. Second, we compare our algorithm with Greedy algorithm proposed by Qiu et al, and Optimum algorithm. We found that our approach can achieve better results than Greedy algorithm proposed by Qiu et al but it's computational time is more than Greedy algorithm.

Qualitative data collection with children.

PubMed

Spratling, Regena; Coke, Sallie; Minick, Ptlene

2012-02-01

Qualitative researchers have clear methods to guide them in data collection with adult participants, but little is known about effective interview techniques with children. The findings from this methodological study on qualitative interviews with children indicate that children are able to articulate their experiences in interviews. Copyright © 2012 Elsevier Inc. All rights reserved.

Greedy algorithms in disordered systems

NASA Astrophysics Data System (ADS)

Duxbury, P. M.; Dobrin, R.

1999-08-01

We discuss search, minimal path and minimal spanning tree algorithms and their applications to disordered systems. Greedy algorithms solve these problems exactly, and are related to extremal dynamics in physics. Minimal cost path (Dijkstra) and minimal cost spanning tree (Prim) algorithms provide extremal dynamics for a polymer in a random medium (the KPZ universality class) and invasion percolation (without trapping) respectively.

"Phenomenology" and qualitative research methods.

PubMed

Nakayama, Y

1994-01-01

Phenomenology is generally based on phenomenological tradition from Husserl to Heidegger and Merleau-Ponty. As philosophical stances provide the assumptions in research methods, different philosophical stances produce different methods. However, the term "phenomenology" is used in various ways without the definition being given, such as phenomenological approach, phenomenological method, phenomenological research, etc. The term "phenomenology" is sometimes used as a paradigm and it is sometimes even viewed as synonymous with qualitative methods. As a result, the term "phenomenology" leads to conceptual confusions in qualitative research methods. The purpose of this paper is to examine the term "phenomenology" and explore philosophical assumptions, and discuss the relationship between philosophical stance and phenomenology as a qualitative research method in nursing.

A hardware-algorithm co-design approach to optimize seizure detection algorithms for implantable applications.

PubMed

Raghunathan, Shriram; Gupta, Sumeet K; Markandeya, Himanshu S; Roy, Kaushik; Irazoqui, Pedro P

2010-10-30

Implantable neural prostheses that deliver focal electrical stimulation upon demand are rapidly emerging as an alternate therapy for roughly a third of the epileptic patient population that is medically refractory. Seizure detection algorithms enable feedback mechanisms to provide focally and temporally specific intervention. Real-time feasibility and computational complexity often limit most reported detection algorithms to implementations using computers for bedside monitoring or external devices communicating with the implanted electrodes. A comparison of algorithms based on detection efficacy does not present a complete picture of the feasibility of the algorithm with limited computational power, as is the case with most battery-powered applications. We present a two-dimensional design optimization approach that takes into account both detection efficacy and hardware cost in evaluating algorithms for their feasibility in an implantable application. Detection features are first compared for their ability to detect electrographic seizures from micro-electrode data recorded from kainate-treated rats. Circuit models are then used to estimate the dynamic and leakage power consumption of the compared features. A score is assigned based on detection efficacy and the hardware cost for each of the features, then plotted on a two-dimensional design space. An optimal combination of compared features is used to construct an algorithm that provides maximal detection efficacy per unit hardware cost. The methods presented in this paper would facilitate the development of a common platform to benchmark seizure detection algorithms for comparison and feasibility analysis in the next generation of implantable neuroprosthetic devices to treat epilepsy. Copyright © 2010 Elsevier B.V. All rights reserved.

Efficient image compression algorithm for computer-animated images

NASA Astrophysics Data System (ADS)

Yfantis, Evangelos A.; Au, Matthew Y.; Miel, G.

1992-10-01

An image compression algorithm is described. The algorithm is an extension of the run-length image compression algorithm and its implementation is relatively easy. This algorithm was implemented and compared with other existing popular compression algorithms and with the Lempel-Ziv (LZ) coding. The Lempel-Ziv algorithm is available as a utility in the UNIX operating system and is also referred to as the UNIX uncompress. Sometimes our algorithm is best in terms of saving memory space, and sometimes one of the competing algorithms is best. The algorithm is lossless, and the intent is for the algorithm to be used in computer graphics animated images. Comparisons made with the LZ algorithm indicate that the decompression time using our algorithm is faster than that using the LZ algorithm. Once the data are in memory, a relatively simple and fast transformation is applied to uncompress the file.

Clinical validation of a novel diagnostic HIV-2 total nucleic acid qualitative assay using the Abbott m2000 platform: Implications for complementary HIV-2 nucleic acid testing for the CDC 4th generation HIV diagnostic testing algorithm.

PubMed

Chang, Ming; Wong, Audrey J S; Raugi, Dana N; Smith, Robert A; Seilie, Annette M; Ortega, Jose P; Bogusz, Kyle M; Sall, Fatima; Ba, Selly; Seydi, Moussa; Gottlieb, Geoffrey S; Coombs, Robert W

2017-01-01

The 2014 CDC 4th generation HIV screening algorithm includes an orthogonal immunoassay to confirm and discriminate HIV-1 and HIV-2 antibodies. Additional nucleic acid testing (NAT) is recommended to resolve indeterminate or undifferentiated HIV seroreactivity. HIV-2 NAT requires a second-line assay to detect HIV-2 total nucleic acid (TNA) in patients' blood cells, as a third of untreated patients have undetectable plasma HIV-2 RNA. To validate a qualitative HIV-2 TNA assay using peripheral blood mononuclear cells (PBMC) from HIV-2-infected Senegalese study participants. We evaluated the assay precision, sensitivity, specificity, and diagnostic performance of an HIV-2 TNA assay. Matched plasma and PBMC samples were collected from 25 HIV-1, 30 HIV-2, 8 HIV-1/-2 dual-seropositive and 25 HIV seronegative individuals. Diagnostic performance was evaluated by comparing the outcome of the TNA assay to the results obtained by the 4th generation HIV screening and confirmatory immunoassays. All PBMC from 30 HIV-2 seropositive participants tested positive for HIV-2 TNA including 23 patients with undetectable plasma RNA. Of the 30 matched plasma specimens, one was HIV non-reactive. Samples from 50 non-HIV-2 infected individuals were confirmed as non-reactive for HIV-2 Ab and negative for HIV-2 TNA. The agreement between HIV-2 TNA and the combined immunoassay results was 98.8% (79/80). Furthermore, HIV-2 TNA was detected in 7 of 8 PBMC specimens from HIV-1/HIV-2 dual-seropositive participants. Our TNA assay detected HIV-2 DNA/RNA in PBMC from serologically HIV-2 reactive, HIV indeterminate or HIV undifferentiated individuals with undetectable plasma RNA, and is suitable for confirming HIV-2 infection in the HIV testing algorithm. Copyright © 2016 Elsevier B.V. All rights reserved.

Efficient RNA structure comparison algorithms.

PubMed

Arslan, Abdullah N; Anandan, Jithendar; Fry, Eric; Monschke, Keith; Ganneboina, Nitin; Bowerman, Jason

2017-12-01

Recently proposed relative addressing-based ([Formula: see text]) RNA secondary structure representation has important features by which an RNA structure database can be stored into a suffix array. A fast substructure search algorithm has been proposed based on binary search on this suffix array. Using this substructure search algorithm, we present a fast algorithm that finds the largest common substructure of given multiple RNA structures in [Formula: see text] format. The multiple RNA structure comparison problem is NP-hard in its general formulation. We introduced a new problem for comparing multiple RNA structures. This problem has more strict similarity definition and objective, and we propose an algorithm that solves this problem efficiently. We also develop another comparison algorithm that iteratively calls this algorithm to locate nonoverlapping large common substructures in compared RNAs. With the new resulting tools, we improved the RNASSAC website (linked from http://faculty.tamuc.edu/aarslan ). This website now also includes two drawing tools: one specialized for preparing RNA substructures that can be used as input by the search tool, and another one for automatically drawing the entire RNA structure from a given structure sequence.

An algorithmic framework for multiobjective optimization.

PubMed

Ganesan, T; Elamvazuthi, I; Shaari, Ku Zilati Ku; Vasant, P

2013-01-01

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization.

Testing an earthquake prediction algorithm

USGS Publications Warehouse

Kossobokov, V.G.; Healy, J.H.; Dewey, J.W.

1997-01-01

A test to evaluate earthquake prediction algorithms is being applied to a Russian algorithm known as M8. The M8 algorithm makes intermediate term predictions for earthquakes to occur in a large circle, based on integral counts of transient seismicity in the circle. In a retroactive prediction for the period January 1, 1985 to July 1, 1991 the algorithm as configured for the forward test would have predicted eight of ten strong earthquakes in the test area. A null hypothesis, based on random assignment of predictions, predicts eight earthquakes in 2.87% of the trials. The forward test began July 1, 1991 and will run through December 31, 1997. As of July 1, 1995, the algorithm had forward predicted five out of nine earthquakes in the test area, which success ratio would have been achieved in 53% of random trials with the null hypothesis.

Advancements to the planogram frequency–distance rebinning algorithm

PubMed Central

Champley, Kyle M; Raylman, Raymond R; Kinahan, Paul E

2010-01-01

In this paper we consider the task of image reconstruction in positron emission tomography (PET) with the planogram frequency–distance rebinning (PFDR) algorithm. The PFDR algorithm is a rebinning algorithm for PET systems with panel detectors. The algorithm is derived in the planogram coordinate system which is a native data format for PET systems with panel detectors. A rebinning algorithm averages over the redundant four-dimensional set of PET data to produce a three-dimensional set of data. Images can be reconstructed from this rebinned three-dimensional set of data. This process enables one to reconstruct PET images more quickly than reconstructing directly from the four-dimensional PET data. The PFDR algorithm is an approximate rebinning algorithm. We show that implementing the PFDR algorithm followed by the (ramp) filtered backprojection (FBP) algorithm in linogram coordinates from multiple views reconstructs a filtered version of our image. We develop an explicit formula for this filter which can be used to achieve exact reconstruction by means of a modified FBP algorithm applied to the stack of rebinned linograms and can also be used to quantify the errors introduced by the PFDR algorithm. This filter is similar to the filter in the planogram filtered backprojection algorithm derived by Brasse et al. The planogram filtered backprojection and exact reconstruction with the PFDR algorithm require complete projections which can be completed with a reprojection algorithm. The PFDR algorithm is similar to the rebinning algorithm developed by Kao et al. By expressing the PFDR algorithm in detector coordinates, we provide a comparative analysis between the two algorithms. Numerical experiments using both simulated data and measured data from a positron emission mammography/tomography (PEM/PET) system are performed. Images are reconstructed by PFDR+FBP (PFDR followed by 2D FBP reconstruction), PFDRX (PFDR followed by the modified FBP algorithm for exact

A Comparison of Three Curve Intersection Algorithms

NASA Technical Reports Server (NTRS)

Sederberg, T. W.; Parry, S. R.

1985-01-01

An empirical comparison is made between three algorithms for computing the points of intersection of two planar Bezier curves. The algorithms compared are: the well known Bezier subdivision algorithm, which is discussed in Lane 80; a subdivision algorithm based on interval analysis due to Koparkar and Mudur; and an algorithm due to Sederberg, Anderson and Goldman which reduces the problem to one of finding the roots of a univariate polynomial. The details of these three algorithms are presented in their respective references.

One-dimensional swarm algorithm packaging

NASA Astrophysics Data System (ADS)

Lebedev, Boris K.; Lebedev, Oleg B.; Lebedeva, Ekaterina O.

2018-05-01

The paper considers an algorithm for solving the problem of onedimensional packaging based on the adaptive behavior model of an ant colony. The key role in the development of the ant algorithm is the choice of representation (interpretation) of the solution. The structure of the solution search graph, the procedure for finding solutions on the graph, the methods of deposition and evaporation of pheromone are described. Unlike the canonical paradigm of an ant algorithm, an ant on the solution search graph generates sets of elements distributed across blocks. Experimental studies were conducted on IBM PC. Compared with the existing algorithms, the results are improved.

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

Turning Points in Qualitative Research: Tying Knots in a Handkerchief. Crossroads in Qualitative Inquiry Series.

ERIC Educational Resources Information Center

Lincoln, Yvonna S., Ed.; Denzin, Norman K., Ed.

The chapters of this volume traces the changes in the discipline of qualitative inquiry over the last five decades. The collection serves as a textbook for training scholars in the history and trajectory of qualitative research. The chapters of part 1, The Revolution of Representation: Feminist and Race/Ethnic Studies Discourses, are: (1) Situated…

QCCM Center for Quantum Algorithms

DTIC Science & Technology

2008-10-17

algorithms (e.g., quantum walks and adiabatic computing ), as well as theoretical advances relating algorithms to physical implementations (e.g...Park, NC 27709-2211 15. SUBJECT TERMS Quantum algorithms, quantum computing , fault-tolerant error correction Richard Cleve MITACS East Academic...0511200 Algebraic results on quantum automata A. Ambainis, M. Beaudry, M. Golovkins, A. Kikusts, M. Mercer, D. Thrien Theory of Computing Systems 39(2006

Qualitative and quantitative reasoning about thermodynamics

NASA Technical Reports Server (NTRS)

Skorstad, Gordon; Forbus, Ken

1989-01-01

One goal of qualitative physics is to capture the tacit knowledge of engineers and scientists. It is shown how Qualitative Process theory can be used to express concepts of engineering thermodynamics. In particular, it is shown how to integrate qualitative and quantitative knowledge to solve textbook problems involving thermodynamic cycles, such as gas turbine plants and steam power plants. These ideas were implemented in a program called SCHISM. Its analysis of a sample textbook problem is described and plans for future work are discussed.

One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms.

PubMed

Andersson, Richard; Larsson, Linnea; Holmqvist, Kenneth; Stridh, Martin; Nyström, Marcus

2017-04-01

Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9):2484-2493,2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties.

New directions in qualitative research in psychology.

PubMed

Demuth, Carolin

2015-06-01

Qualitative Research gains increasing popularity in the field of Psychology. With the renewed interest, there are, however, also some risks related to the overhomogenization and increasing standardization of qualitative methods. This special issue is dedicated to clarify some of the existing misconceptions of qualitative research and to discuss its potentials for the field of psychology in light of recent endeavors to overcome paradigmatic battles and a re-orientation to the specifities of psychology. The issue comprises a discussion from workshop on the future of qualitative research in psychology organized at Aalborg University, and several contributions that resulted from it.

Driver Distraction Using Visual-Based Sensors and Algorithms.

PubMed

Fernández, Alberto; Usamentiaga, Rubén; Carús, Juan Luis; Casado, Rubén

2016-10-28

Driver distraction, defined as the diversion of attention away from activities critical for safe driving toward a competing activity, is increasingly recognized as a significant source of injuries and fatalities on the roadway. Additionally, the trend towards increasing the use of in-vehicle information systems is critical because they induce visual, biomechanical and cognitive distraction and may affect driving performance in qualitatively different ways. Non-intrusive methods are strongly preferred for monitoring distraction, and vision-based systems have appeared to be attractive for both drivers and researchers. Biomechanical, visual and cognitive distractions are the most commonly detected types in video-based algorithms. Many distraction detection systems only use a single visual cue and therefore, they may be easily disturbed when occlusion or illumination changes appear. Moreover, the combination of these visual cues is a key and challenging aspect in the development of robust distraction detection systems. These visual cues can be extracted mainly by using face monitoring systems but they should be completed with more visual cues (e.g., hands or body information) or even, distraction detection from specific actions (e.g., phone usage). Additionally, these algorithms should be included in an embedded device or system inside a car. This is not a trivial task and several requirements must be taken into account: reliability, real-time performance, low cost, small size, low power consumption, flexibility and short time-to-market. The key points for the development and implementation of sensors to carry out the detection of distraction will also be reviewed. This paper shows a review of the role of computer vision technology applied to the development of monitoring systems to detect distraction. Some key points considered as both future work and challenges ahead yet to be solved will also be addressed.

Driver Distraction Using Visual-Based Sensors and Algorithms

PubMed Central

Fernández, Alberto; Usamentiaga, Rubén; Carús, Juan Luis; Casado, Rubén

2016-01-01

Driver distraction, defined as the diversion of attention away from activities critical for safe driving toward a competing activity, is increasingly recognized as a significant source of injuries and fatalities on the roadway. Additionally, the trend towards increasing the use of in-vehicle information systems is critical because they induce visual, biomechanical and cognitive distraction and may affect driving performance in qualitatively different ways. Non-intrusive methods are strongly preferred for monitoring distraction, and vision-based systems have appeared to be attractive for both drivers and researchers. Biomechanical, visual and cognitive distractions are the most commonly detected types in video-based algorithms. Many distraction detection systems only use a single visual cue and therefore, they may be easily disturbed when occlusion or illumination changes appear. Moreover, the combination of these visual cues is a key and challenging aspect in the development of robust distraction detection systems. These visual cues can be extracted mainly by using face monitoring systems but they should be completed with more visual cues (e.g., hands or body information) or even, distraction detection from specific actions (e.g., phone usage). Additionally, these algorithms should be included in an embedded device or system inside a car. This is not a trivial task and several requirements must be taken into account: reliability, real-time performance, low cost, small size, low power consumption, flexibility and short time-to-market. The key points for the development and implementation of sensors to carry out the detection of distraction will also be reviewed. This paper shows a review of the role of computer vision technology applied to the development of monitoring systems to detect distraction. Some key points considered as both future work and challenges ahead yet to be solved will also be addressed. PMID:27801822

Principles of qualitative analysis in the chromatographic context.

PubMed

Valcárcel, M; Cárdenas, S; Simonet, B M; Carrillo-Carrión, C

2007-07-27

This article presents the state of the art of qualitative analysis in the framework of the chromatographic analysis. After establishing the differences between two main classes of qualitative analysis (analyte identification and sample classification/qualification) the particularities of instrumental qualitative analysis are commented on. Qualitative chromatographic analysis for sample classification/qualification through the so-called chromatographic fingerprint (for complex samples) or the volatiles profile (through the direct coupling headspace-mass spectrometry using the chromatograph as interface) is discussed. Next, more technical exposition of the qualitative chromatographic information is presented supported by a variety of representative examples.

Dialog on a country path: the qualitative research journey.

PubMed

Sorrell, Jeanne M; Cangelosi, Pamela R; Dinkins, Christine S

2014-03-01

There is little information in the literature describing how students learn qualitative research. This article describes an approach to learning that is based on the pedagogical approach of Dinkins' Socratic-Hermeneutic Shared Inquiry. This approach integrates shared dialog as an essential aspect of learning. The qualitative pedagogy described in this article focused on three questions: What is knowing in qualitative research? How do we come to know qualitative research? What can we do with qualitative research? Students learned the basics of qualitative research within a context that fostered interpretive inquiry. In this way, the course framework mirrored the combination of interviewing, storytelling, and journeying toward understanding that constitute qualitative research. © 2013.

Achieving trustworthiness in qualitative research: a pan-paradigmatic perspective.

PubMed

Williams, Elizabeth Nutt; Morrow, Susan L

2009-07-01

In this article, as two researchers from different traditions in qualitative research (consensual qualitative research and grounded theory), the authors present their shared views on the critical elements of trustworthiness in qualitative data. In addition to making specific recommendations about the integrity of data, the balance between participant meaning and researcher interpretation, and clear communication and application of the findings, they identify ways in which these issues are difficult to negotiate within and across different qualitative approaches. The authors present examples from various qualitative studies, emphasize the need for a shared language to reduce confusion between qualitative traditions and with researchers from a more strictly quantitative orientation, and recommend particular approaches to establishing trustworthiness in qualitative research.

QPSO-Based Adaptive DNA Computing Algorithm

PubMed Central

Karakose, Mehmet; Cigdem, Ugur

2013-01-01

DNA (deoxyribonucleic acid) computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm. PMID:23935409

Algorithmic Mechanism Design of Evolutionary Computation.

PubMed

Pei, Yan

2015-01-01

We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.

Algorithmic Mechanism Design of Evolutionary Computation

PubMed Central

2015-01-01

We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm. PMID:26257777

Firefly Mating Algorithm for Continuous Optimization Problems.

PubMed

Ritthipakdee, Amarita; Thammano, Arit; Premasathian, Nol; Jitkongchuen, Duangjai

2017-01-01

This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA), for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i) the mutual attraction between males and females causes them to mate and (ii) fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones) against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima.

Firefly Mating Algorithm for Continuous Optimization Problems

PubMed Central

Ritthipakdee, Amarita; Premasathian, Nol; Jitkongchuen, Duangjai

2017-01-01

This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA), for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i) the mutual attraction between males and females causes them to mate and (ii) fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones) against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima. PMID:28808442

An Algorithmic Framework for Multiobjective Optimization

PubMed Central

Ganesan, T.; Elamvazuthi, I.; Shaari, Ku Zilati Ku; Vasant, P.

2013-01-01

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization. PMID:24470795

The Rational Hybrid Monte Carlo algorithm

NASA Astrophysics Data System (ADS)

Clark, Michael

2006-12-01

The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.

Integrating Qualitative and Quantitative Research in Organizations.

DTIC Science & Technology

1981-07-01

Qualitative Researcher Qualitative research using the traditional case study was the most popular method during the early empirical investigations of...what is now known as qualitative methods (Van Maanen, 1979). Some researchers have recently argued that restricting case studies to exploratory work... phenomenological approaches at the subjective end of the continuum. A few researchers have suggested ways in which quantitative and

Power of automated algorithms for combining time-line follow-back and urine drug screening test results in stimulant-abuse clinical trials.

PubMed

Oden, Neal L; VanVeldhuisen, Paul C; Wakim, Paul G; Trivedi, Madhukar H; Somoza, Eugene; Lewis, Daniel

2011-09-01

In clinical trials of treatment for stimulant abuse, researchers commonly record both Time-Line Follow-Back (TLFB) self-reports and urine drug screen (UDS) results. To compare the power of self-report, qualitative (use vs. no use) UDS assessment, and various algorithms to generate self-report-UDS composite measures to detect treatment differences via t-test in simulated clinical trial data. We performed Monte Carlo simulations patterned in part on real data to model self-report reliability, UDS errors, dropout, informatively missing UDS reports, incomplete adherence to a urine donation schedule, temporal correlation of drug use, number of days in the study period, number of patients per arm, and distribution of drug-use probabilities. Investigated algorithms include maximum likelihood and Bayesian estimates, self-report alone, UDS alone, and several simple modifications of self-report (referred to here as ELCON algorithms) which eliminate perceived contradictions between it and UDS. Among the algorithms investigated, simple ELCON algorithms gave rise to the most powerful t-tests to detect mean group differences in stimulant drug use. Further investigation is needed to determine if simple, naïve procedures such as the ELCON algorithms are optimal for comparing clinical study treatment arms. But researchers who currently require an automated algorithm in scenarios similar to those simulated for combining TLFB and UDS to test group differences in stimulant use should consider one of the ELCON algorithms. This analysis continues a line of inquiry which could determine how best to measure outpatient stimulant use in clinical trials (NIDA. NIDA Monograph-57: Self-Report Methods of Estimating Drug Abuse: Meeting Current Challenges to Validity. NTIS PB 88248083. Bethesda, MD: National Institutes of Health, 1985; NIDA. NIDA Research Monograph 73: Urine Testing for Drugs of Abuse. NTIS PB 89151971. Bethesda, MD: National Institutes of Health, 1987; NIDA. NIDA Research

Remote sensing imagery classification using multi-objective gravitational search algorithm

NASA Astrophysics Data System (ADS)

Zhang, Aizhu; Sun, Genyun; Wang, Zhenjie

2016-10-01

Simultaneous optimization of different validity measures can capture different data characteristics of remote sensing imagery (RSI) and thereby achieving high quality classification results. In this paper, two conflicting cluster validity indices, the Xie-Beni (XB) index and the fuzzy C-means (FCM) (Jm) measure, are integrated with a diversity-enhanced and memory-based multi-objective gravitational search algorithm (DMMOGSA) to present a novel multi-objective optimization based RSI classification method. In this method, the Gabor filter method is firstly implemented to extract texture features of RSI. Then, the texture features are syncretized with the spectral features to construct the spatial-spectral feature space/set of the RSI. Afterwards, cluster of the spectral-spatial feature set is carried out on the basis of the proposed method. To be specific, cluster centers are randomly generated initially. After that, the cluster centers are updated and optimized adaptively by employing the DMMOGSA. Accordingly, a set of non-dominated cluster centers are obtained. Therefore, numbers of image classification results of RSI are produced and users can pick up the most promising one according to their problem requirements. To quantitatively and qualitatively validate the effectiveness of the proposed method, the proposed classification method was applied to classifier two aerial high-resolution remote sensing imageries. The obtained classification results are compared with that produced by two single cluster validity index based and two state-of-the-art multi-objective optimization algorithms based classification results. Comparison results show that the proposed method can achieve more accurate RSI classification.

Understanding Participatory Action Research: A Qualitative Research Methodology Option

ERIC Educational Resources Information Center

MacDonald, Cathy

2012-01-01

Participatory Action Research (PAR) is a qualitative research methodology option that requires further understanding and consideration. PAR is considered democratic, equitable, liberating, and life-enhancing qualitative inquiry that remains distinct from other qualitative methodologies (Kach & Kralik, 2006). Using PAR, qualitative features of an…

Algorithms for accelerated convergence of adaptive PCA.

PubMed

Chatterjee, C; Kang, Z; Roychowdhury, V P

2000-01-01

We derive and discuss new adaptive algorithms for principal component analysis (PCA) that are shown to converge faster than the traditional PCA algorithms due to Oja, Sanger, and Xu. It is well known that traditional PCA algorithms that are derived by using gradient descent on an objective function are slow to converge. Furthermore, the convergence of these algorithms depends on appropriate choices of the gain sequences. Since online applications demand faster convergence and an automatic selection of gains, we present new adaptive algorithms to solve these problems. We first present an unconstrained objective function, which can be minimized to obtain the principal components. We derive adaptive algorithms from this objective function by using: 1) gradient descent; 2) steepest descent; 3) conjugate direction; and 4) Newton-Raphson methods. Although gradient descent produces Xu's LMSER algorithm, the steepest descent, conjugate direction, and Newton-Raphson methods produce new adaptive algorithms for PCA. We also provide a discussion on the landscape of the objective function, and present a global convergence proof of the adaptive gradient descent PCA algorithm using stochastic approximation theory. Extensive experiments with stationary and nonstationary multidimensional Gaussian sequences show faster convergence of the new algorithms over the traditional gradient descent methods.We also compare the steepest descent adaptive algorithm with state-of-the-art methods on stationary and nonstationary sequences.

[The relevance of qualitative techniques in biomedical research].

PubMed

de Camargo, Kenneth Rochel

2008-01-01

On observing how qualitative and quantitative studies are reported in the biomedical literature it becomes evident that, besides the virtual absence of the former, they are presented in different ways. Authors of qualitative studies seem to need almost invariably to explain why they choose a qualitative approach whereas that does not occur in quantitative studies. This paper takes Ludwik Fleck's comparative epistemology as a means of exploring those differences empirically, illustrating on the basis of two studies dealing with different aspects of biomedical practices how qualitative methods can elucidate a variety of questions pertaining to this field. The paper concludes presenting some structural characteristics of the biomedical field which on one hand, would not be explored properly without employing qualitative methods and, on the other hand, can help understanding the little value given to qualitative techniques in this area.

Building Interdisciplinary Qualitative Research Networks: Reflections on Qualitative Research Group (QRG) at the University of Manitoba

ERIC Educational Resources Information Center

Roger, Kerstin Stieber; Halas, Gayle

2012-01-01

As qualitative research methodologies continue to evolve and develop, both students and experienced researchers are showing greater interest in learning about and developing new approaches. To meet this need, faculty at the University of Manitoba created the Qualitative Research Group (QRG), a community of practice that utilizes experiential…

Multimodal Estimation of Distribution Algorithms.

PubMed

Yang, Qiang; Chen, Wei-Neng; Li, Yun; Chen, C L Philip; Xu, Xiang-Min; Zhang, Jun

2016-02-15

Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima.

Spaceborne SAR Imaging Algorithm for Coherence Optimized.

PubMed

Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun

2016-01-01

This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application.

Spaceborne SAR Imaging Algorithm for Coherence Optimized

PubMed Central

Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun

2016-01-01

This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446

Multi-object Detection and Discrimination Algorithms

DTIC Science & Technology

2015-03-26

with  an   algorithm  similar  to  a  depth-­‐first   search .   This  stage  of  the   algorithm  is  O(CN).  From...Multi-object Detection and Discrimination Algorithms This document contains an overview of research and work performed and published at the University...of Florida from October 1, 2009 to October 31, 2013 pertaining to proposal 57306CS: Multi-object Detection and Discrimination Algorithms

QRS Detection Algorithm for Telehealth Electrocardiogram Recordings.

PubMed

Khamis, Heba; Weiss, Robert; Xie, Yang; Chang, Chan-Wei; Lovell, Nigel H; Redmond, Stephen J

2016-07-01

QRS detection algorithms are needed to analyze electrocardiogram (ECG) recordings generated in telehealth environments. However, the numerous published QRS detectors focus on clean clinical data. Here, a "UNSW" QRS detection algorithm is described that is suitable for clinical ECG and also poorer quality telehealth ECG. The UNSW algorithm generates a feature signal containing information about ECG amplitude and derivative, which is filtered according to its frequency content and an adaptive threshold is applied. The algorithm was tested on clinical and telehealth ECG and the QRS detection performance is compared to the Pan-Tompkins (PT) and Gutiérrez-Rivas (GR) algorithm. For the MIT-BIH Arrhythmia database (virtually artifact free, clinical ECG), the overall sensitivity (Se) and positive predictivity (+P) of the UNSW algorithm was >99%, which was comparable to PT and GR. When applied to the MIT-BIH noise stress test database (clinical ECG with added calibrated noise) after artifact masking, all three algorithms had overall Se >99%, and the UNSW algorithm had higher +P (98%, p < 0.05) than PT and GR. For 250 telehealth ECG records (unsupervised recordings; dry metal electrodes), the UNSW algorithm had 98% Se and 95% +P which was superior to PT (+P: p < 0.001) and GR (Se and +P: p < 0.001). This is the first study to describe a QRS detection algorithm for telehealth data and evaluate it on clinical and telehealth ECG with superior results to published algorithms. The UNSW algorithm could be used to manage increasing telehealth ECG analysis workloads.

A pipelined FPGA implementation of an encryption algorithm based on genetic algorithm

NASA Astrophysics Data System (ADS)

Thirer, Nonel

2013-05-01

With the evolution of digital data storage and exchange, it is essential to protect the confidential information from every unauthorized access. High performance encryption algorithms were developed and implemented by software and hardware. Also many methods to attack the cipher text were developed. In the last years, the genetic algorithm has gained much interest in cryptanalysis of cipher texts and also in encryption ciphers. This paper analyses the possibility to use the genetic algorithm as a multiple key sequence generator for an AES (Advanced Encryption Standard) cryptographic system, and also to use a three stages pipeline (with four main blocks: Input data, AES Core, Key generator, Output data) to provide a fast encryption and storage/transmission of a large amount of data.

Conflict-Aware Scheduling Algorithm

NASA Technical Reports Server (NTRS)

Wang, Yeou-Fang; Borden, Chester

2006-01-01

conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.

Qualitative Research and Its Place in Psychological Science

ERIC Educational Resources Information Center

Madill, Anna; Gough, Brendan

2008-01-01

In discussing the place of diverse qualitative research within psychological science, the authors highlight the potential permeability of the quantitative-qualitative boundary and identify different ways of increasing communication between researchers specializing in different methods. Explicating diversity within qualitative research is…

One improved LSB steganography algorithm

NASA Astrophysics Data System (ADS)

Song, Bing; Zhang, Zhi-hong

2013-03-01

It is easy to be detected by X2 and RS steganalysis with high accuracy that using LSB algorithm to hide information in digital image. We started by selecting information embedded location and modifying the information embedded method, combined with sub-affine transformation and matrix coding method, improved the LSB algorithm and a new LSB algorithm was proposed. Experimental results show that the improved one can resist the X2 and RS steganalysis effectively.

An algorithm for longitudinal registration of PET/CT images acquired during neoadjuvant chemotherapy in breast cancer: preliminary results.

PubMed

Li, Xia; Abramson, Richard G; Arlinghaus, Lori R; Chakravarthy, Anuradha Bapsi; Abramson, Vandana; Mayer, Ingrid; Farley, Jaime; Delbeke, Dominique; Yankeelov, Thomas E

2012-11-16

By providing estimates of tumor glucose metabolism, 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) can potentially characterize the response of breast tumors to treatment. To assess therapy response, serial measurements of FDG-PET parameters (derived from static and/or dynamic images) can be obtained at different time points during the course of treatment. However, most studies track the changes in average parameter values obtained from the whole tumor, thereby discarding all spatial information manifested in tumor heterogeneity. Here, we propose a method whereby serially acquired FDG-PET breast data sets can be spatially co-registered to enable the spatial comparison of parameter maps at the voxel level. The goal is to optimally register normal tissues while simultaneously preventing tumor distortion. In order to accomplish this, we constructed a PET support device to enable PET/CT imaging of the breasts of ten patients in the prone position and applied a mutual information-based rigid body registration followed by a non-rigid registration. The non-rigid registration algorithm extended the adaptive bases algorithm (ABA) by incorporating a tumor volume-preserving constraint, which computed the Jacobian determinant over the tumor regions as outlined on the PET/CT images, into the cost function. We tested this approach on ten breast cancer patients undergoing neoadjuvant chemotherapy. By both qualitative and quantitative evaluation, our constrained algorithm yielded significantly less tumor distortion than the unconstrained algorithm: considering the tumor volume determined from standard uptake value maps, the post-registration median tumor volume changes, and the 25th and 75th quantiles were 3.42% (0%, 13.39%) and 16.93% (9.21%, 49.93%) for the constrained and unconstrained algorithms, respectively (p = 0.002), while the bending energy (a measure of the smoothness of the deformation) was 0.0015 (0.0005, 0.012) and 0.017 (0.005, 0

Qualitative science policy.

PubMed

Mitcham, Carl

2007-12-01

Qualitative research struggles against a tide of quantitative methods. To assist in this struggle, it is useful to consider the historical and philosophical origins of quantitative methods as well as criticisms that have been raised against them. Although these criticisms have often been restricted to discussions in the philosophy of science, they have become increasingly prominent in debates regarding science policy. This article thus reviews current science policy debates concerning scientific autonomy and the linear model of science-society relationships. Then, having considered the multiple meanings of quality, it argues for a science policy reassessment of quantitative research, for deeper engagements between science policy and the social sciences, and finally, for a more explicit alliance between science policy and qualitative methods.

Integrating Algorithm Visualization Video into a First-Year Algorithm and Data Structure Course

ERIC Educational Resources Information Center

Crescenzi, Pilu; Malizia, Alessio; Verri, M. Cecilia; Diaz, Paloma; Aedo, Ignacio

2012-01-01

In this paper we describe the results that we have obtained while integrating algorithm visualization (AV) movies (strongly tightened with the other teaching material), within a first-year undergraduate course on algorithms and data structures. Our experimental results seem to support the hypothesis that making these movies available significantly…

QUAGOL: a guide for qualitative data analysis.

PubMed

Dierckx de Casterlé, Bernadette; Gastmans, Chris; Bryon, Els; Denier, Yvonne

2012-03-01

Data analysis is a complex and contested part of the qualitative research process, which has received limited theoretical attention. Researchers are often in need of useful instructions or guidelines on how to analyze the mass of qualitative data, but face the lack of clear guidance for using particular analytic methods. The aim of this paper is to propose and discuss the Qualitative Analysis Guide of Leuven (QUAGOL), a guide that was developed in order to be able to truly capture the rich insights of qualitative interview data. The article describes six major problems researchers are often struggling with during the process of qualitative data analysis. Consequently, the QUAGOL is proposed as a guide to facilitate the process of analysis. Challenges emerged and lessons learned from own extensive experiences with qualitative data analysis within the Grounded Theory Approach, as well as from those of other researchers (as described in the literature), were discussed and recommendations were presented. Strengths and pitfalls of the proposed method were discussed in detail. The Qualitative Analysis Guide of Leuven (QUAGOL) offers a comprehensive method to guide the process of qualitative data analysis. The process consists of two parts, each consisting of five stages. The method is systematic but not rigid. It is characterized by iterative processes of digging deeper, constantly moving between the various stages of the process. As such, it aims to stimulate the researcher's intuition and creativity as optimal as possible. The QUAGOL guide is a theory and practice-based guide that supports and facilitates the process of analysis of qualitative interview data. Although the method can facilitate the process of analysis, it cannot guarantee automatic quality. The skills of the researcher and the quality of the research team remain the most crucial components of a successful process of analysis. Additionally, the importance of constantly moving between the various stages

Firefly Algorithm, Lévy Flights and Global Optimization

NASA Astrophysics Data System (ADS)

Yang, Xin-She

Nature-inspired algorithms such as Particle Swarm Optimization and Firefly Algorithm are among the most powerful algorithms for optimization. In this paper, we intend to formulate a new metaheuristic algorithm by combining Lévy flights with the search strategy via the Firefly Algorithm. Numerical studies and results suggest that the proposed Lévy-flight firefly algorithm is superior to existing metaheuristic algorithms. Finally implications for further research and wider applications will be discussed.

A novel algorithm for Bluetooth ECG.

PubMed

Pandya, Utpal T; Desai, Uday B

2012-11-01

In wireless transmission of ECG, data latency will be significant when battery power level and data transmission distance are not maintained. In applications like home monitoring or personalized care, to overcome the joint effect of previous issues of wireless transmission and other ECG measurement noises, a novel filtering strategy is required. Here, a novel algorithm, identified as peak rejection adaptive sampling modified moving average (PRASMMA) algorithm for wireless ECG is introduced. This algorithm first removes error in bit pattern of received data if occurred in wireless transmission and then removes baseline drift. Afterward, a modified moving average is implemented except in the region of each QRS complexes. The algorithm also sets its filtering parameters according to different sampling rate selected for acquisition of signals. To demonstrate the work, a prototyped Bluetooth-based ECG module is used to capture ECG with different sampling rate and in different position of patient. This module transmits ECG wirelessly to Bluetooth-enabled devices where the PRASMMA algorithm is applied on captured ECG. The performance of PRASMMA algorithm is compared with moving average and S-Golay algorithms visually as well as numerically. The results show that the PRASMMA algorithm can significantly improve the ECG reconstruction by efficiently removing the noise and its use can be extended to any parameters where peaks are importance for diagnostic purpose.

Qualitative Evaluation.

ERIC Educational Resources Information Center

Stone, James C., Ed.; James, Raymond A., Ed.

1981-01-01

"Qualitative evaluation" is the theme of this issue of the California Journal of Teacher Education. Ralph Tyler states that evaluation is essentially descriptive, and using numbers does not solve basic problems. Martha Elin Vernazza examines the issue of objectivity in history and its implications for evaluation. She posits that the…

Comparison of Snow Mass Estimates from a Prototype Passive Microwave Snow Algorithm, a Revised Algorithm and a Snow Depth Climatology

NASA Technical Reports Server (NTRS)

Foster, J. L.; Chang, A. T. C.; Hall, D. K.

1997-01-01

While it is recognized that no single snow algorithm is capable of producing accurate global estimates of snow depth, for research purposes it is useful to test an algorithm's performance in different climatic areas in order to see how it responds to a variety of snow conditions. This study is one of the first to develop separate passive microwave snow algorithms for North America and Eurasia by including parameters that consider the effects of variations in forest cover and crystal size on microwave brightness temperature. A new algorithm (GSFC 1996) is compared to a prototype algorithm (Chang et al., 1987) and to a snow depth climatology (SDC), which for this study is considered to be a standard reference or baseline. It is shown that the GSFC 1996 algorithm compares much more favorably to the SDC than does the Chang et al. (1987) algorithm. For example, in North America in February there is a 15% difference between the GSFC 198-96 Algorithm and the SDC, but with the Chang et al. (1987) algorithm the difference is greater than 50%. In Eurasia, also in February, there is only a 1.3% difference between the GSFC 1996 algorithm and the SDC, whereas with the Chang et al. (1987) algorithm the difference is about 20%. As expected, differences tend to be less when the snow cover extent is greater, particularly for Eurasia. The GSFC 1996 algorithm performs better in North America in each month than dose the Chang et al. (1987) algorithm. This is also the case in Eurasia, except in April and May when the Chang et al.(1987) algorithms is in closer accord to the SDC than is GSFC 1996 algorithm.

Noise-enhanced clustering and competitive learning algorithms.

PubMed

Osoba, Osonde; Kosko, Bart

2013-01-01

Noise can provably speed up convergence in many centroid-based clustering algorithms. This includes the popular k-means clustering algorithm. The clustering noise benefit follows from the general noise benefit for the expectation-maximization algorithm because many clustering algorithms are special cases of the expectation-maximization algorithm. Simulations show that noise also speeds up convergence in stochastic unsupervised competitive learning, supervised competitive learning, and differential competitive learning. Copyright © 2012 Elsevier Ltd. All rights reserved.

Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy.

PubMed

Gibbons, Chris; Richards, Suzanne; Valderas, Jose Maria; Campbell, John

2017-03-15

Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor's activity for the purposes of quality assurance, safety, and continuing professional development. The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors' professional performance in the United Kingdom. We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians' colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to "popular" (recall=.97), "innovator" (recall=.98), and "respected" (recall=.87) codes and was lower for the "interpersonal" (recall=.80) and "professional" (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as "respected," "professional," and "interpersonal" related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P<.05). Scores did not vary between doctors who were rated as popular or innovative and those who were not rated at all (P>.05). Machine learning

Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy

PubMed Central

2017-01-01

Background Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing professional development. Objective The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors’ professional performance in the United Kingdom. Methods We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians’ colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Results Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to “popular” (recall=.97), “innovator” (recall=.98), and “respected” (recall=.87) codes and was lower for the “interpersonal” (recall=.80) and “professional” (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as “respected,” “professional,” and “interpersonal” related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P<.05). Scores did not vary between doctors who were rated as popular or

Fast algorithm of adaptive Fourier series

NASA Astrophysics Data System (ADS)

Gao, You; Ku, Min; Qian, Tao

2018-05-01

Adaptive Fourier decomposition (AFD, precisely 1-D AFD or Core-AFD) was originated for the goal of positive frequency representations of signals. It achieved the goal and at the same time offered fast decompositions of signals. There then arose several types of AFDs. AFD merged with the greedy algorithm idea, and in particular, motivated the so-called pre-orthogonal greedy algorithm (Pre-OGA) that was proven to be the most efficient greedy algorithm. The cost of the advantages of the AFD type decompositions is, however, the high computational complexity due to the involvement of maximal selections of the dictionary parameters. The present paper offers one formulation of the 1-D AFD algorithm by building the FFT algorithm into it. Accordingly, the algorithm complexity is reduced, from the original $\\mathcal{O}(M N^2)$ to $\\mathcal{O}(M N\\log_2 N)$, where $N$ denotes the number of the discretization points on the unit circle and $M$ denotes the number of points in $[0,1)$. This greatly enhances the applicability of AFD. Experiments are carried out to show the high efficiency of the proposed algorithm.

Examining Data Repository Guidelines for Qualitative Data Sharing.

PubMed

Antes, Alison L; Walsh, Heidi A; Strait, Michelle; Hudson-Vitale, Cynthia R; DuBois, James M

2018-02-01

Qualitative data provide rich information on research questions in diverse fields. Recent calls for increased transparency and openness in research emphasize data sharing. However, qualitative data sharing has yet to become the norm internationally and is particularly uncommon in the United States. Guidance for archiving and secondary use of qualitative data is required for progress in this regard. In this study, we review the benefits and concerns associated with qualitative data sharing and then describe the results of a content analysis of guidelines from international repositories that archive qualitative data. A minority of repositories provide qualitative data sharing guidelines. Of the guidelines available, there is substantial variation in whether specific topics are addressed. Some topics, such as removing direct identifiers, are consistently addressed, while others, such as providing an anonymization log, are not. We discuss the implications of our study for education, best practices, and future research.

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

NASA Astrophysics Data System (ADS)

Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing

2015-08-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).

Using Alternative Multiplication Algorithms to "Offload" Cognition

ERIC Educational Resources Information Center

Jazby, Dan; Pearn, Cath

2015-01-01

When viewed through a lens of embedded cognition, algorithms may enable aspects of the cognitive work of multi-digit multiplication to be "offloaded" to the environmental structure created by an algorithm. This study analyses four multiplication algorithms by viewing different algorithms as enabling cognitive work to be distributed…

Bracketing as a skill in conducting unstructured qualitative interviews.

PubMed

Sorsa, Minna Anneli; Kiikkala, Irma; Åstedt-Kurki, Päivi

2015-03-01

To provide an overview of bracketing as a skill in unstructured qualitative research interviews. Researchers affect the qualitative research process. Bracketing in descriptive phenomenology entails researchers setting aside their pre-understanding and acting non-judgementally. In interpretative phenomenology, previous knowledge is used intentionally to create new understanding. A literature search of bracketing in phenomenology and qualitative research. This is a methodology paper examining the researchers' impact in creating data in creating data in qualitative research. Self-knowledge, sensitivity and reflexivity of the researcher enable bracketing. Skilled and experienced researchers are needed to use bracketing in unstructured qualitative research interviews. Bracketing adds scientific rigour and validity to any qualitative study.

Distilling the Verification Process for Prognostics Algorithms

NASA Technical Reports Server (NTRS)

Roychoudhury, Indranil; Saxena, Abhinav; Celaya, Jose R.; Goebel, Kai

2013-01-01

The goal of prognostics and health management (PHM) systems is to ensure system safety, and reduce downtime and maintenance costs. It is important that a PHM system is verified and validated before it can be successfully deployed. Prognostics algorithms are integral parts of PHM systems. This paper investigates a systematic process of verification of such prognostics algorithms. To this end, first, this paper distinguishes between technology maturation and product development. Then, the paper describes the verification process for a prognostics algorithm as it moves up to higher maturity levels. This process is shown to be an iterative process where verification activities are interleaved with validation activities at each maturation level. In this work, we adopt the concept of technology readiness levels (TRLs) to represent the different maturity levels of a prognostics algorithm. It is shown that at each TRL, the verification of a prognostics algorithm depends on verifying the different components of the algorithm according to the requirements laid out by the PHM system that adopts this prognostics algorithm. Finally, using simplified examples, the systematic process for verifying a prognostics algorithm is demonstrated as the prognostics algorithm moves up TRLs.

Hybrid employment recommendation algorithm based on Spark

NASA Astrophysics Data System (ADS)

Li, Zuoquan; Lin, Yubei; Zhang, Xingming

2017-08-01

Aiming at the real-time application of collaborative filtering employment recommendation algorithm (CF), a clustering collaborative filtering recommendation algorithm (CCF) is developed, which applies hierarchical clustering to CF and narrows the query range of neighbour items. In addition, to solve the cold-start problem of content-based recommendation algorithm (CB), a content-based algorithm with users’ information (CBUI) is introduced for job recommendation. Furthermore, a hybrid recommendation algorithm (HRA) which combines CCF and CBUI algorithms is proposed, and implemented on Spark platform. The experimental results show that HRA can overcome the problems of cold start and data sparsity, and achieve good recommendation accuracy and scalability for employment recommendation.

Categorizing Variations of Student-Implemented Sorting Algorithms

ERIC Educational Resources Information Center

Taherkhani, Ahmad; Korhonen, Ari; Malmi, Lauri

2012-01-01

In this study, we examined freshmen students' sorting algorithm implementations in data structures and algorithms' course in two phases: at the beginning of the course before the students received any instruction on sorting algorithms, and after taking a lecture on sorting algorithms. The analysis revealed that many students have insufficient…

Project resource reallocation algorithm

NASA Technical Reports Server (NTRS)

Myers, J. E.

1981-01-01

A methodology for adjusting baseline cost estimates according to project schedule changes is described. An algorithm which performs a linear expansion or contraction of the baseline project resource distribution in proportion to the project schedule expansion or contraction is presented. Input to the algorithm consists of the deck of cards (PACE input data) prepared for the baseline project schedule as well as a specification of the nature of the baseline schedule change. Output of the algorithm is a new deck of cards with all work breakdown structure block and element of cost estimates redistributed for the new project schedule. This new deck can be processed through PACE to produce a detailed cost estimate for the new schedule.

Algorithm Estimates Microwave Water-Vapor Delay

NASA Technical Reports Server (NTRS)

Robinson, Steven E.

1989-01-01

Accuracy equals or exceeds conventional linear algorithms. "Profile" algorithm improved algorithm using water-vapor-radiometer data to produce estimates of microwave delays caused by water vapor in troposphere. Does not require site-specific and weather-dependent empirical parameters other than standard meteorological data, latitude, and altitude for use in conjunction with published standard atmospheric data. Basic premise of profile algorithm, wet-path delay approximated closely by solution to simplified version of nonlinear delay problem and generated numerically from each radiometer observation and simultaneous meteorological data.

Decoding algorithm for vortex communications receiver

NASA Astrophysics Data System (ADS)

Kupferman, Judy; Arnon, Shlomi

2018-01-01

Vortex light beams can provide a tremendous alphabet for encoding information. We derive a symbol decoding algorithm for a direct detection matrix detector vortex beam receiver using Laguerre Gauss (LG) modes, and develop a mathematical model of symbol error rate (SER) for this receiver. We compare SER as a function of signal to noise ratio (SNR) for our algorithm and for the Pearson correlation algorithm. To our knowledge, this is the first comprehensive treatment of a decoding algorithm of a matrix detector for an LG receiver.

What can acute medicine learn from qualitative methods?

PubMed

Heasman, Brett; Reader, Tom W

2015-10-01

The contribution of qualitative methods to evidence-based medicine is growing, with qualitative studies increasingly used to examine patient experience and unsafe organizational cultures. The present review considers qualitative research recently conducted on teamwork and organizational culture in the ICU and also other acute domains. Qualitative studies have highlighted the importance of interpersonal and social aspects of healthcare on managing and responding to patient care needs. Clear/consistent communication, compassion, and trust underpin successful patient-physician interactions, with improved patient experiences linked to patient safety and clinical effectiveness across a wide range of measures and outcomes. Across multidisciplinary teams, good communication facilitates shared understanding, decision-making and coordinated action, reducing patient risk in the process. Qualitative methods highlight the complex nature of risk management in hospital wards, which is highly contextualized to the demands and resources available, and influenced by multilayered social contexts. In addition to augmenting quantitative research, qualitative investigations enable the investigation of questions on social behaviour that are beyond the scope of quantitative assessment alone. To develop improved patient-centred care, health professionals should therefore consider integrating qualitative procedures into their existing assessments of patient/staff satisfaction.

A new bio-inspired optimisation algorithm: Bird Swarm Algorithm

NASA Astrophysics Data System (ADS)

Meng, Xian-Bing; Gao, X. Z.; Lu, Lihua; Liu, Yu; Zhang, Hengzhen

2016-07-01

A new bio-inspired algorithm, namely Bird Swarm Algorithm (BSA), is proposed for solving optimisation applications. BSA is based on the swarm intelligence extracted from the social behaviours and social interactions in bird swarms. Birds mainly have three kinds of behaviours: foraging behaviour, vigilance behaviour and flight behaviour. Birds may forage for food and escape from the predators by the social interactions to obtain a high chance of survival. By modelling these social behaviours, social interactions and the related swarm intelligence, four search strategies associated with five simplified rules are formulated in BSA. Simulations and comparisons based on eighteen benchmark problems demonstrate the effectiveness, superiority and stability of BSA. Some proposals for future research about BSA are also discussed.

Selecting materialized views using random algorithm

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Hao, Zhongxiao; Liu, Chi

2007-04-01

The data warehouse is a repository of information collected from multiple possibly heterogeneous autonomous distributed databases. The information stored at the data warehouse is in form of views referred to as materialized views. The selection of the materialized views is one of the most important decisions in designing a data warehouse. Materialized views are stored in the data warehouse for the purpose of efficiently implementing on-line analytical processing queries. The first issue for the user to consider is query response time. So in this paper, we develop algorithms to select a set of views to materialize in data warehouse in order to minimize the total view maintenance cost under the constraint of a given query response time. We call it query_cost view_ selection problem. First, cost graph and cost model of query_cost view_ selection problem are presented. Second, the methods for selecting materialized views by using random algorithms are presented. The genetic algorithm is applied to the materialized views selection problem. But with the development of genetic process, the legal solution produced become more and more difficult, so a lot of solutions are eliminated and producing time of the solutions is lengthened in genetic algorithm. Therefore, improved algorithm has been presented in this paper, which is the combination of simulated annealing algorithm and genetic algorithm for the purpose of solving the query cost view selection problem. Finally, in order to test the function and efficiency of our algorithms experiment simulation is adopted. The experiments show that the given methods can provide near-optimal solutions in limited time and works better in practical cases. Randomized algorithms will become invaluable tools for data warehouse evolution.

Efficient Approximation Algorithms for Weighted $b$-Matching

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khan, Arif; Pothen, Alex; Mostofa Ali Patwary, Md.

2016-01-01

We describe a half-approximation algorithm, b-Suitor, for computing a b-Matching of maximum weight in a graph with weights on the edges. b-Matching is a generalization of the well-known Matching problem in graphs, where the objective is to choose a subset of M edges in the graph such that at most a specified number b(v) of edges in M are incident on each vertex v. Subject to this restriction we maximize the sum of the weights of the edges in M. We prove that the b-Suitor algorithm computes the same b-Matching as the one obtained by the greedy algorithm for themore » problem. We implement the algorithm on serial and shared-memory parallel processors, and compare its performance against a collection of approximation algorithms that have been proposed for the Matching problem. Our results show that the b-Suitor algorithm outperforms the Greedy and Locally Dominant edge algorithms by one to two orders of magnitude on a serial processor. The b-Suitor algorithm has a high degree of concurrency, and it scales well up to 240 threads on a shared memory multiprocessor. The b-Suitor algorithm outperforms the Locally Dominant edge algorithm by a factor of fourteen on 16 cores of an Intel Xeon multiprocessor.« less

[An improved algorithm for electrohysterogram envelope extraction].

PubMed

Lu, Yaosheng; Pan, Jie; Chen, Zhaoxia; Chen, Zhaoxia

2017-02-01

Extraction uterine contraction signal from abdominal uterine electromyogram(EMG) signal is considered as the most promising method to replace the traditional tocodynamometer(TOCO) for detecting uterine contractions activity. The traditional root mean square(RMS) algorithm has only some limited values in canceling the impulsive noise. In our study, an improved algorithm for uterine EMG envelope extraction was proposed to overcome the problem. Firstly, in our experiment, zero-crossing detection method was used to separate the burst of uterine electrical activity from the raw uterine EMG signal. After processing the separated signals by employing two filtering windows which have different width, we used the traditional RMS algorithm to extract uterus EMG envelope. To assess the performance of the algorithm, the improved algorithm was compared with two existing intensity of uterine electromyogram(IEMG) extraction algorithms. The results showed that the improved algorithm was better than the traditional ones in eliminating impulsive noise present in the uterine EMG signal. The measurement sensitivity and positive predictive value(PPV) of the improved algorithm were 0.952 and 0.922, respectively, which were not only significantly higher than the corresponding values(0.859 and 0.847) of the first comparison algorithm, but also higher than the values(0.928 and 0.877) of the second comparison algorithm. Thus the new method is reliable and effective.

Qualitative Research Designs: Selection and Implementation

ERIC Educational Resources Information Center

Creswell, John W.; Hanson, William E.; Plano Clark, Vicki L.; Morales, Alejandro

2007-01-01

Counseling psychologists face many approaches from which to choose when they conduct a qualitative research study. This article focuses on the processes of selecting, contrasting, and implementing five different qualitative approaches. Based on an extended example related to test interpretation by counselors, clients, and communities, this article…