ProbCD: enrichment analysis accounting for categorization uncertainty.

PubMed

Vêncio, Ricardo Z N; Shmulevich, Ilya

2007-10-12

As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test. We developed an open-source R-based software to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: http://xerad.systemsbiology.net/ProbCD/. We present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation.

Chi-square-based scoring function for categorization of MEDLINE citations.

PubMed

Kastrin, A; Peterlin, B; Hristovski, D

2010-01-01

Text categorization has been used in biomedical informatics for identifying documents containing relevant topics of interest. We developed a simple method that uses a chi-square-based scoring function to determine the likelihood of MEDLINE citations containing genetic relevant topic. Our procedure requires construction of a genetic and a nongenetic domain document corpus. We used MeSH descriptors assigned to MEDLINE citations for this categorization task. We compared frequencies of MeSH descriptors between two corpora applying chi-square test. A MeSH descriptor was considered to be a positive indicator if its relative observed frequency in the genetic domain corpus was greater than its relative observed frequency in the nongenetic domain corpus. The output of the proposed method is a list of scores for all the citations, with the highest score given to those citations containing MeSH descriptors typical for the genetic domain. Validation was done on a set of 734 manually annotated MEDLINE citations. It achieved predictive accuracy of 0.87 with 0.69 recall and 0.64 precision. We evaluated the method by comparing it to three machine-learning algorithms (support vector machines, decision trees, naïve Bayes). Although the differences were not statistically significantly different, results showed that our chi-square scoring performs as good as compared machine-learning algorithms. We suggest that the chi-square scoring is an effective solution to help categorize MEDLINE citations. The algorithm is implemented in the BITOLA literature-based discovery support system as a preprocessor for gene symbol disambiguation process.

Financial time series analysis based on information categorization method

NASA Astrophysics Data System (ADS)

Tian, Qiang; Shang, Pengjian; Feng, Guochen

2014-12-01

The paper mainly applies the information categorization method to analyze the financial time series. The method is used to examine the similarity of different sequences by calculating the distances between them. We apply this method to quantify the similarity of different stock markets. And we report the results of similarity in US and Chinese stock markets in periods 1991-1998 (before the Asian currency crisis), 1999-2006 (after the Asian currency crisis and before the global financial crisis), and 2007-2013 (during and after global financial crisis) by using this method. The results show the difference of similarity between different stock markets in different time periods and the similarity of the two stock markets become larger after these two crises. Also we acquire the results of similarity of 10 stock indices in three areas; it means the method can distinguish different areas' markets from the phylogenetic trees. The results show that we can get satisfactory information from financial markets by this method. The information categorization method can not only be used in physiologic time series, but also in financial time series.

Infant categorization.

PubMed

Rakison, David H; Yermolayeva, Yevdokiya

2010-11-01

In this article, we review the principal findings on infant categorization from the last 30 years. The review focuses on behaviorally based experiments with visual preference, habituation, object examining, sequential touching, and inductive generalization procedures. We propose that although this research has helped to elucidate the 'what' and 'when' of infant categorization, it has failed to clarify the mechanisms that underpin this behavior and the development of concepts. We outline a number of reasons for why the field has failed in this regard, most notably because of the context-specific nature of infant categorization and a lack of ground rules in interpreting data. We conclude by suggesting that one remedy for this issue is for infant categorization researchers to adopt more of an interdisciplinary approach by incorporating imaging and computational methods into their current methodological arsenal. WIREs Cogn Sci 2010 1 894-905 For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.

Students creative thinking skills in solving two dimensional arithmetic series through research-based learning

NASA Astrophysics Data System (ADS)

Tohir, M.; Abidin, Z.; Dafik; Hobri

2018-04-01

Arithmetics is one of the topics in Mathematics, which deals with logic and detailed process upon generalizing formula. Creativity and flexibility are needed in generalizing formula of arithmetics series. This research aimed at analyzing students creative thinking skills in generalizing arithmetic series. The triangulation method and research-based learning was used in this research. The subjects were students of the Master Program of Mathematics Education in Faculty of Teacher Training and Education at Jember University. The data was collected by giving assignments to the students. The data collection was done by giving open problem-solving task and documentation study to the students to arrange generalization pattern based on the dependent function formula i and the function depend on i and j. Then, the students finished the next problem-solving task to construct arithmetic generalization patterns based on the function formula which depends on i and i + n and the sum formula of functions dependent on i and j of the arithmetic compiled. The data analysis techniques operative in this study was Miles and Huberman analysis model. Based on the result of data analysis on task 1, the levels of students creative thinking skill were classified as follows; 22,22% of the students categorized as “not creative” 38.89% of the students categorized as “less creative” category; 22.22% of the students categorized as “sufficiently creative” and 16.67% of the students categorized as “creative”. By contrast, the results of data analysis on task 2 found that the levels of students creative thinking skills were classified as follows; 22.22% of the students categorized as “sufficiently creative”, 44.44% of the students categorized as “creative” and 33.33% of the students categorized as “very creative”. This analysis result can set the basis for teaching references and actualizing a better teaching model in order to increase students creative thinking skills.

Gaussian-based routines to impute categorical variables in health surveys.

PubMed

Yucel, Recai M; He, Yulei; Zaslavsky, Alan M

2011-12-20

The multivariate normal (MVN) distribution is arguably the most popular parametric model used in imputation and is available in most software packages (e.g., SAS PROC MI, R package norm). When it is applied to categorical variables as an approximation, practitioners often either apply simple rounding techniques for ordinal variables or create a distinct 'missing' category and/or disregard the nominal variable from the imputation phase. All of these practices can potentially lead to biased and/or uninterpretable inferences. In this work, we develop a new rounding methodology calibrated to preserve observed distributions to multiply impute missing categorical covariates. The major attractiveness of this method is its flexibility to use any 'working' imputation software, particularly those based on MVN, allowing practitioners to obtain usable imputations with small biases. A simulation study demonstrates the clear advantage of the proposed method in rounding ordinal variables and, in some scenarios, its plausibility in imputing nominal variables. We illustrate our methods on a widely used National Survey of Children with Special Health Care Needs where incomplete values on race posed a valid threat on inferences pertaining to disparities. Copyright © 2011 John Wiley & Sons, Ltd.

Comparison of Marine Spatial Planning Methods in Madagascar Demonstrates Value of Alternative Approaches

PubMed Central

Allnutt, Thomas F.; McClanahan, Timothy R.; Andréfouët, Serge; Baker, Merrill; Lagabrielle, Erwann; McClennen, Caleb; Rakotomanjaka, Andry J. M.; Tianarisoa, Tantely F.; Watson, Reg; Kremen, Claire

2012-01-01

The Government of Madagascar plans to increase marine protected area coverage by over one million hectares. To assist this process, we compare four methods for marine spatial planning of Madagascar's west coast. Input data for each method was drawn from the same variables: fishing pressure, exposure to climate change, and biodiversity (habitats, species distributions, biological richness, and biodiversity value). The first method compares visual color classifications of primary variables, the second uses binary combinations of these variables to produce a categorical classification of management actions, the third is a target-based optimization using Marxan, and the fourth is conservation ranking with Zonation. We present results from each method, and compare the latter three approaches for spatial coverage, biodiversity representation, fishing cost and persistence probability. All results included large areas in the north, central, and southern parts of western Madagascar. Achieving 30% representation targets with Marxan required twice the fish catch loss than the categorical method. The categorical classification and Zonation do not consider targets for conservation features. However, when we reduced Marxan targets to 16.3%, matching the representation level of the “strict protection” class of the categorical result, the methods show similar catch losses. The management category portfolio has complete coverage, and presents several management recommendations including strict protection. Zonation produces rapid conservation rankings across large, diverse datasets. Marxan is useful for identifying strict protected areas that meet representation targets, and minimize exposure probabilities for conservation features at low economic cost. We show that methods based on Zonation and a simple combination of variables can produce results comparable to Marxan for species representation and catch losses, demonstrating the value of comparing alternative approaches during initial stages of the planning process. Choosing an appropriate approach ultimately depends on scientific and political factors including representation targets, likelihood of adoption, and persistence goals. PMID:22359534

Comparison of marine spatial planning methods in Madagascar demonstrates value of alternative approaches.

PubMed

Allnutt, Thomas F; McClanahan, Timothy R; Andréfouët, Serge; Baker, Merrill; Lagabrielle, Erwann; McClennen, Caleb; Rakotomanjaka, Andry J M; Tianarisoa, Tantely F; Watson, Reg; Kremen, Claire

2012-01-01

The Government of Madagascar plans to increase marine protected area coverage by over one million hectares. To assist this process, we compare four methods for marine spatial planning of Madagascar's west coast. Input data for each method was drawn from the same variables: fishing pressure, exposure to climate change, and biodiversity (habitats, species distributions, biological richness, and biodiversity value). The first method compares visual color classifications of primary variables, the second uses binary combinations of these variables to produce a categorical classification of management actions, the third is a target-based optimization using Marxan, and the fourth is conservation ranking with Zonation. We present results from each method, and compare the latter three approaches for spatial coverage, biodiversity representation, fishing cost and persistence probability. All results included large areas in the north, central, and southern parts of western Madagascar. Achieving 30% representation targets with Marxan required twice the fish catch loss than the categorical method. The categorical classification and Zonation do not consider targets for conservation features. However, when we reduced Marxan targets to 16.3%, matching the representation level of the "strict protection" class of the categorical result, the methods show similar catch losses. The management category portfolio has complete coverage, and presents several management recommendations including strict protection. Zonation produces rapid conservation rankings across large, diverse datasets. Marxan is useful for identifying strict protected areas that meet representation targets, and minimize exposure probabilities for conservation features at low economic cost. We show that methods based on Zonation and a simple combination of variables can produce results comparable to Marxan for species representation and catch losses, demonstrating the value of comparing alternative approaches during initial stages of the planning process. Choosing an appropriate approach ultimately depends on scientific and political factors including representation targets, likelihood of adoption, and persistence goals.

The Necessity of Machine Learning and Epistemology in the Development of Categorization Theories: A Case Study in Prototype-Exemplar Debate

NASA Astrophysics Data System (ADS)

Gagliardi, Francesco

In the present paper we discuss some aspects of the development of categorization theories concerning cognitive psychology and machine learning. We consider the thirty-year debate between prototype-theory and exemplar-theory in the studies of cognitive psychology regarding the categorization processes. We propose this debate is ill-posed, because it neglects some theoretical and empirical results of machine learning about the bias-variance theorem and the existence of some instance-based classifiers which can embed models subsuming both prototype and exemplar theories. Moreover this debate lies on a epistemological error of pursuing a, so called, experimentum crucis. Then we present how an interdisciplinary approach, based on synthetic method for cognitive modelling, can be useful to progress both the fields of cognitive psychology and machine learning.

Unsupervised categorization method of graphemes on handwritten manuscripts: application to style recognition

NASA Astrophysics Data System (ADS)

Daher, H.; Gaceb, D.; Eglin, V.; Bres, S.; Vincent, N.

2012-01-01

We present in this paper a feature selection and weighting method for medieval handwriting images that relies on codebooks of shapes of small strokes of characters (graphemes that are issued from the decomposition of manuscripts). These codebooks are important to simplify the automation of the analysis, the manuscripts transcription and the recognition of styles or writers. Our approach provides a precise features weighting by genetic algorithms and a highperformance methodology for the categorization of the shapes of graphemes by using graph coloring into codebooks which are applied in turn on CBIR (Content Based Image Retrieval) in a mixed handwriting database containing different pages from different writers, periods of the history and quality. We show how the coupling of these two mechanisms 'features weighting - graphemes classification' can offer a better separation of the forms to be categorized by exploiting their grapho-morphological, their density and their significant orientations particularities.

A novel toxicogenomics-based approach to categorize (non-)genotoxic carcinogens.

PubMed

Schaap, Mirjam M; Wackers, Paul F K; Zwart, Edwin P; Huijskens, Ilse; Jonker, Martijs J; Hendriks, Giel; Breit, Timo M; van Steeg, Harry; van de Water, Bob; Luijten, Mirjam

2015-12-01

Alternative methods to detect non-genotoxic carcinogens are urgently needed, as this class of carcinogens goes undetected in the current testing strategy for carcinogenicity under REACH. A complicating factor is that non-genotoxic carcinogens act through several distinctive modes of action, which makes prediction of their carcinogenic property difficult. We have recently demonstrated that gene expression profiling in primary mouse hepatocytes is a useful approach to categorize non-genotoxic carcinogens according to their modes of action. In the current study, we improved the methods used for analysis and added mouse embryonic stem cells as a second in vitro test system, because of their features complementary to hepatocytes. Our approach involved an unsupervised analysis based on the 30 most significantly up- and down-regulated genes per chemical. Mouse embryonic stem cells and primary mouse hepatocytes were exposed to a selected set of chemicals and subsequently subjected to gene expression profiling. We focused on non-genotoxic carcinogens, but also included genotoxic carcinogens and non-carcinogens to test the robustness of this approach. Application of the optimized comparison approach resulted in improved categorization of non-genotoxic carcinogens. Mouse embryonic stem cells were a useful addition, especially for genotoxic substances, but also for detection of non-genotoxic carcinogens that went undetected by primary hepatocytes. The approach presented here is an important step forward to categorize chemicals, especially those that are carcinogenic.

Motivated social categorization: fundamental motives enhance people's sensitivity to basic social categories.

PubMed

Maner, Jon K; Miller, Saul L; Moss, Justin H; Leo, Jennifer L; Plant, E Ashby

2012-07-01

This article presents an evolutionary framework for identifying the characteristics people use to categorize members of their social world. Findings suggest that fundamental social motives lead people to implicitly categorize social targets based on whether those targets display goal-relevant phenotypic traits. A mate-search prime caused participants to categorize opposite-sex targets (but not same-sex targets) based on their level of physical attractiveness (Experiment 1). A mate-guarding prime interacted with relationship investment, causing participants to categorize same-sex targets (but not opposite-sex targets) based on their physical attractiveness (Experiment 2). A self-protection prime interacted with chronic beliefs about danger, increasing participants' tendency to categorize targets based on their racial group membership (Black or White; Experiment 3). This work demonstrates that people categorize others based on whether they display goal-relevant characteristics reflecting high levels of perceived desirability or threat. Social categorization is guided by fundamental evolved motives designed to enhance adaptive social outcomes. PsycINFO Database Record (c) 2012 APA, all rights reserved

Analysis of students’ creative thinking level in problem solving based on national council of teachers of mathematics

NASA Astrophysics Data System (ADS)

Hobri; Suharto; Rifqi Naja, Ahmad

2018-04-01

This research aims to determine students’ creative thinking level in problem solving based on NCTM in function subject. The research type is descriptive with qualitative approach. Data collection methods which were used are test and interview. Creative thinking level in problem solving based on NCTM indicators consists of (1) Make mathematical model from a contextual problem and solve the problem, (2) Solve problem using various possible alternatives, (3) Find new alternative(s) to solve the problem, (4) Determine the most efficient and effective alternative for that problem, (5) Review and correct mistake(s) on the process of problem solving. Result of the research showed that 10 students categorized in very satisfying level, 23 students categorized in satisfying level and 1 students categorized in less satisfying level. Students in very satisfying level meet all indicators, students in satisfying level meet first, second, fourth, and fifth indicator, while students in less satisfying level only meet first and fifth indicator.

Transitional Leadership: Leadership During Times of Transition, Key Principles, and Considerations for Success.

PubMed

Norbash, Alexander

2017-06-01

To suggest a methodical approach for refining transitional management abilities, including empowerment of a growing leader, leading in an unfamiliar organization or leading in an organization that is changing. Management approaches based on the body of work dealing with leadership studies and transitions and dealing with leadership during times of transition and change management were consolidated and categorized. Transitional leaders can benefit from effective leadership training including defining and prospectively accruing necessary experiences and skills; strengthening information gathering skills; effectively self-assessing; valuing and implementing mentoring; formulating strategy; and communicating. A categorical approach to transitional leadership may be implemented through a systems-based and methodical approach to gaining the definable, and distinct sets of skills and abilities necessary for transitional leadership success. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Adhesives: Test Method, Group Assignment, and Categorization Guide for High-Loading Rate Applications - History and Rationale

DTIC Science & Technology

2017-04-20

Categorization Guide for High -Loading- Rate Applications – History and Rationale by Robert Jensen, David Flanagan, Daniel DeSchepper, and Charles...Adhesives: Test Method, Group Assignment, and Categorization Guide for High -Loading- Rate Applications – History and Rationale by Robert Jensen...Categorization Guide for High - Loading-Rate Applications – History and Rationale 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6

Clustering Multivariate Time Series Using Hidden Markov Models

PubMed Central

Ghassempour, Shima; Girosi, Federico; Maeder, Anthony

2014-01-01

In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs), where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers. PMID:24662996

Social Work Science and Knowledge Utilization

ERIC Educational Resources Information Center

Marsh, Jeanne C.; Reed, Martena

2016-01-01

Objective: This article advances understanding of social work science by examining the content and methods of highly utilized or cited journal articles in social work. Methods: A data base of the 100 most frequently cited articles from 79 social work journals was coded and categorized into three primary domains: content, research versus…

Clustering "N" Objects into "K" Groups under Optimal Scaling of Variables.

ERIC Educational Resources Information Center

van Buuren, Stef; Heiser, Willem J.

1989-01-01

A method based on homogeneity analysis (multiple correspondence analysis or multiple scaling) is proposed to reduce many categorical variables to one variable with "k" categories. The method is a generalization of the sum of squared distances cluster analysis problem to the case of mixed measurement level variables. (SLD)

Low-Threshold Active Teaching Methods for Mathematic Instruction

ERIC Educational Resources Information Center

Marotta, Sebastian M.; Hargis, Jace

2011-01-01

In this article, we present a large list of low-threshold active teaching methods categorized so the instructor can efficiently access and target the deployment of conceptually based lessons. The categories include teaching strategies for lecture on large and small class sizes; student action individually, in pairs, and groups; games; interaction…

Space vehicle engine and heat shield environment review. Volume 1: Engineering analysis

NASA Technical Reports Server (NTRS)

Mcanelly, W. B.; Young, C. T. K.

1973-01-01

Methods for predicting the base heating characteristics of a multiple rocket engine installation are discussed. The environmental data is applied to the design of adequate protection system for the engine components. The methods for predicting the base region thermal environment are categorized as: (1) scale model testing, (2) extrapolation of previous and related flight test results, and (3) semiempirical analytical techniques.

Creative Interactive Teaching: Case Method & Other Techniques. Selected Papers of the International Conference on Case Methods Research & Application (16th, Caceres, Spain, 1999).

ERIC Educational Resources Information Center

Klein, Hans E., Ed.

This book presents a selection of papers from the international, interdisciplinary conference of the World Association for Case Method Research & Application. Papers are categorized into seven areas: (1) "International Case Studies" (e.g., event-based entrepreneurship, case studies on consumer complaints, and strategic quality…

Categorizing document by fuzzy C-Means and K-nearest neighbors approach

NASA Astrophysics Data System (ADS)

Priandini, Novita; Zaman, Badrus; Purwanti, Endah

2017-08-01

Increasing of technology had made categorizing documents become important. It caused by increasing of number of documents itself. Managing some documents by categorizing is one of Information Retrieval application, because it involve text mining on its process. Whereas, categorization technique could be done both Fuzzy C-Means (FCM) and K-Nearest Neighbors (KNN) method. This experiment would consolidate both methods. The aim of the experiment is increasing performance of document categorize. First, FCM is in order to clustering training documents. Second, KNN is in order to categorize testing document until the output of categorization is shown. Result of the experiment is 14 testing documents retrieve relevantly to its category. Meanwhile 6 of 20 testing documents retrieve irrelevant to its category. Result of system evaluation shows that both precision and recall are 0,7.

Memory, reasoning, and categorization: parallels and common mechanisms

PubMed Central

Hayes, Brett K.; Heit, Evan; Rotello, Caren M.

2014-01-01

Traditionally, memory, reasoning, and categorization have been treated as separate components of human cognition. We challenge this distinction, arguing that there is broad scope for crossover between the methods and theories developed for each task. The links between memory and reasoning are illustrated in a review of two lines of research. The first takes theoretical ideas (two-process accounts) and methodological tools (signal detection analysis, receiver operating characteristic curves) from memory research and applies them to important issues in reasoning research: relations between induction and deduction, and the belief bias effect. The second line of research introduces a task in which subjects make either memory or reasoning judgments for the same set of stimuli. Other than broader generalization for reasoning than memory, the results were similar for the two tasks, across a variety of experimental stimuli and manipulations. It was possible to simultaneously explain performance on both tasks within a single cognitive architecture, based on exemplar-based comparisons of similarity. The final sections explore evidence for empirical and processing links between inductive reasoning and categorization and between categorization and recognition. An important implication is that progress in all three of these fields will be expedited by further investigation of the many commonalities between these tasks. PMID:24987380

Memory, reasoning, and categorization: parallels and common mechanisms.

PubMed

Hayes, Brett K; Heit, Evan; Rotello, Caren M

2014-01-01

Traditionally, memory, reasoning, and categorization have been treated as separate components of human cognition. We challenge this distinction, arguing that there is broad scope for crossover between the methods and theories developed for each task. The links between memory and reasoning are illustrated in a review of two lines of research. The first takes theoretical ideas (two-process accounts) and methodological tools (signal detection analysis, receiver operating characteristic curves) from memory research and applies them to important issues in reasoning research: relations between induction and deduction, and the belief bias effect. The second line of research introduces a task in which subjects make either memory or reasoning judgments for the same set of stimuli. Other than broader generalization for reasoning than memory, the results were similar for the two tasks, across a variety of experimental stimuli and manipulations. It was possible to simultaneously explain performance on both tasks within a single cognitive architecture, based on exemplar-based comparisons of similarity. The final sections explore evidence for empirical and processing links between inductive reasoning and categorization and between categorization and recognition. An important implication is that progress in all three of these fields will be expedited by further investigation of the many commonalities between these tasks.

Identifying Wrist Fracture Patients with High Accuracy by Automatic Categorization of X-ray Reports

PubMed Central

de Bruijn, Berry; Cranney, Ann; O’Donnell, Siobhan; Martin, Joel D.; Forster, Alan J.

2006-01-01

The authors performed this study to determine the accuracy of several text classification methods to categorize wrist x-ray reports. We randomly sampled 751 textual wrist x-ray reports. Two expert reviewers rated the presence (n = 301) or absence (n = 450) of an acute fracture of wrist. We developed two information retrieval (IR) text classification methods and a machine learning method using a support vector machine (TC-1). In cross-validation on the derivation set (n = 493), TC-1 outperformed the two IR based methods and six benchmark classifiers, including Naive Bayes and a Neural Network. In the validation set (n = 258), TC-1 demonstrated consistent performance with 93.8% accuracy; 95.5% sensitivity; 92.9% specificity; and 87.5% positive predictive value. TC-1 was easy to implement and superior in performance to the other classification methods. PMID:16929046

Adolescent Male Conduct-Disordered Patients in Substance Use Disorder Treatment: Examining the "Limited Prosocial Emotions" Specifier.

PubMed

Sakai, Joseph T; Mikulich-Gilbertson, Susan K; Young, Susan E; Rhee, Soo Hyun; McWilliams, Shannon K; Dunn, Robin; Salomonsen-Sautel, Stacy; Thurstone, Christian; Hopfer, Christian J

2016-01-01

To our knowledge, this is the first study to examine the DSM-5-defined conduct disorder (CD) with limited prosocial emotions (LPE) among adolescents in substance use disorder (SUD) treatment, despite the high rates of CD in this population. We tested previously published methods of LPE categorization in a sample of male conduct-disordered patients in SUD treatment (n=196). CD with LPE patients did not demonstrate a distinct pattern in terms of demographics or co-morbidity regardless of the categorization method utilized. In conclusion, LPE, as operationalized here, does not identify a distinct subgroup of patients based on psychiatric comorbidity, SUD diagnoses, or demographics.

Human Pose Estimation from Monocular Images: A Comprehensive Survey

PubMed Central

Gong, Wenjuan; Zhang, Xuena; Gonzàlez, Jordi; Sobral, Andrews; Bouwmans, Thierry; Tu, Changhe; Zahzah, El-hadi

2016-01-01

Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation can be found in the literature, but they focus on a certain category; for example, model-based approaches or human motion analysis, etc. As far as we know, an overall review of this problem domain has yet to be provided. Furthermore, recent advancements based on deep learning have brought novel algorithms for this problem. In this paper, a comprehensive survey of human pose estimation from monocular images is carried out including milestone works and recent advancements. Based on one standard pipeline for the solution of computer vision problems, this survey splits the problem into several modules: feature extraction and description, human body models, and modeling methods. Problem modeling methods are approached based on two means of categorization in this survey. One way to categorize includes top-down and bottom-up methods, and another way includes generative and discriminative methods. Considering the fact that one direct application of human pose estimation is to provide initialization for automatic video surveillance, there are additional sections for motion-related methods in all modules: motion features, motion models, and motion-based methods. Finally, the paper also collects 26 publicly available data sets for validation and provides error measurement methods that are frequently used. PMID:27898003

Mode of Action (MOA) Assignment Classifications for Ecotoxicology: Evaluation of Available Methods

EPA Science Inventory

There are various structure-based classification schemes to categorize chemicals based on mode of action (MOA) which have been applied for both eco and human toxicology. With increasing calls to assess 1000s of chemicals, some of which have little available information other tha...

LSHSIM: A Locality Sensitive Hashing based method for multiple-point geostatistics

NASA Astrophysics Data System (ADS)

Moura, Pedro; Laber, Eduardo; Lopes, Hélio; Mesejo, Daniel; Pavanelli, Lucas; Jardim, João; Thiesen, Francisco; Pujol, Gabriel

2017-10-01

Reservoir modeling is a very important task that permits the representation of a geological region of interest, so as to generate a considerable number of possible scenarios. Since its inception, many methodologies have been proposed and, in the last two decades, multiple-point geostatistics (MPS) has been the dominant one. This methodology is strongly based on the concept of training image (TI) and the use of its characteristics, which are called patterns. In this paper, we propose a new MPS method that combines the application of a technique called Locality Sensitive Hashing (LSH), which permits to accelerate the search for patterns similar to a target one, with a Run-Length Encoding (RLE) compression technique that speeds up the calculation of the Hamming similarity. Experiments with both categorical and continuous images show that LSHSIM is computationally efficient and produce good quality realizations. In particular, for categorical data, the results suggest that LSHSIM is faster than MS-CCSIM, one of the state-of-the-art methods.

Feature selection methods for big data bioinformatics: A survey from the search perspective.

PubMed

Wang, Lipo; Wang, Yaoli; Chang, Qing

2016-12-01

This paper surveys main principles of feature selection and their recent applications in big data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and embedded approaches to feature selection, we formulate feature selection as a combinatorial optimization or search problem and categorize feature selection methods into exhaustive search, heuristic search, and hybrid methods, where heuristic search methods may further be categorized into those with or without data-distilled feature ranking measures. Copyright © 2016 Elsevier Inc. All rights reserved.

Projected 1981 exposure estimates using iterative proportional fitting

DOT National Transportation Integrated Search

1985-10-01

1981 VMT estimates categorized by eight driver, vehicle, and environmental : variables are produced. These 1981 estimates are produced using analytical : methods developed in a previous report. The estimates are based on 1977 : NPTS data (the latest ...

A measure of association for ordered categorical data in population-based studies

PubMed Central

Nelson, Kerrie P; Edwards, Don

2016-01-01

Ordinal classification scales are commonly used to define a patient’s disease status in screening and diagnostic tests such as mammography. Challenges arise in agreement studies when evaluating the association between many raters’ classifications of patients’ disease or health status when an ordered categorical scale is used. In this paper, we describe a population-based approach and chance-corrected measure of association to evaluate the strength of relationship between multiple raters’ ordinal classifications where any number of raters can be accommodated. In contrast to Shrout and Fleiss’ intraclass correlation coefficient, the proposed measure of association is invariant with respect to changes in disease prevalence. We demonstrate how unique characteristics of individual raters can be explored using random effects. Simulation studies are conducted to demonstrate the properties of the proposed method under varying assumptions. The methods are applied to two large-scale agreement studies of breast cancer screening and prostate cancer severity. PMID:27184590

48 CFR 11.107 - Solicitation provision.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Institute of Standards and Technology using the categorical reporting method. Agencies that manage their... manage their specifications centrally use the categorical method of reporting. Agency regulations...

48 CFR 11.107 - Solicitation provision.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Institute of Standards and Technology using the categorical reporting method. Agencies that manage their... manage their specifications centrally use the categorical method of reporting. Agency regulations...

48 CFR 11.107 - Solicitation provision.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Institute of Standards and Technology using the categorical reporting method. Agencies that manage their... manage their specifications centrally use the categorical method of reporting. Agency regulations...

48 CFR 11.107 - Solicitation provision.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Institute of Standards and Technology using the categorical reporting method. Agencies that manage their... manage their specifications centrally use the categorical method of reporting. Agency regulations...

Automatic categorization of anatomical landmark-local appearances based on diffeomorphic demons and spectral clustering for constructing detector ensembles.

PubMed

Hanaoka, Shouhei; Masutani, Yoshitaka; Nemoto, Mitsutaka; Nomura, Yukihiro; Yoshikawa, Takeharu; Hayashi, Naoto; Ohtomo, Kuni

2012-01-01

A method for categorizing landmark-local appearances extracted from computed tomography (CT) datasets is presented. Anatomical landmarks in the human body inevitably have inter-individual variations that cause difficulty in automatic landmark detection processes. The goal of this study is to categorize subjects (i.e., training datasets) according to local shape variations of such a landmark so that each subgroup has less shape variation and thus the machine learning of each landmark detector is much easier. The similarity between each subject pair is measured based on the non-rigid registration result between them. These similarities are used by the spectral clustering process. After the clustering, all training datasets in each cluster, as well as synthesized intermediate images calculated from all subject-pairs in the cluster, are used to train the corresponding subgroup detector. All of these trained detectors compose a detector ensemble to detect the target landmark. Evaluation with clinical CT datasets showed great improvement in the detection performance.

The neural basis for novel semantic categorization.

PubMed

Koenig, Phyllis; Smith, Edward E; Glosser, Guila; DeVita, Chris; Moore, Peachie; McMillan, Corey; Gee, Jim; Grossman, Murray

2005-01-15

We monitored regional cerebral activity with BOLD fMRI during acquisition of a novel semantic category and subsequent categorization of test stimuli by a rule-based strategy or a similarity-based strategy. We observed different patterns of activation in direct comparisons of rule- and similarity-based categorization. During rule-based category acquisition, subjects recruited anterior cingulate, thalamic, and parietal regions to support selective attention to perceptual features, and left inferior frontal cortex to helps maintain rules in working memory. Subsequent rule-based categorization revealed anterior cingulate and parietal activation while judging stimuli whose conformity with the rules was readily apparent, and left inferior frontal recruitment during judgments of stimuli whose conformity was less apparent. By comparison, similarity-based category acquisition showed recruitment of anterior prefrontal and posterior cingulate regions, presumably to support successful retrieval of previously encountered exemplars from long-term memory, and bilateral temporal-parietal activation for perceptual feature integration. Subsequent similarity-based categorization revealed temporal-parietal, posterior cingulate, and anterior prefrontal activation. These findings suggest that large-scale networks support relatively distinct categorization processes during the acquisition and judgment of semantic category knowledge.

Assessment of Spectral and Temporal Resolution in Cochlear Implant Users Using Psychoacoustic Discrimination and Speech Cue Categorization.

PubMed

Winn, Matthew B; Won, Jong Ho; Moon, Il Joon

This study was conducted to measure auditory perception by cochlear implant users in the spectral and temporal domains, using tests of either categorization (using speech-based cues) or discrimination (using conventional psychoacoustic tests). The authors hypothesized that traditional nonlinguistic tests assessing spectral and temporal auditory resolution would correspond to speech-based measures assessing specific aspects of phonetic categorization assumed to depend on spectral and temporal auditory resolution. The authors further hypothesized that speech-based categorization performance would ultimately be a superior predictor of speech recognition performance, because of the fundamental nature of speech recognition as categorization. Nineteen cochlear implant listeners and 10 listeners with normal hearing participated in a suite of tasks that included spectral ripple discrimination, temporal modulation detection, and syllable categorization, which was split into a spectral cue-based task (targeting the /ba/-/da/ contrast) and a timing cue-based task (targeting the /b/-/p/ and /d/-/t/ contrasts). Speech sounds were manipulated to contain specific spectral or temporal modulations (formant transitions or voice onset time, respectively) that could be categorized. Categorization responses were quantified using logistic regression to assess perceptual sensitivity to acoustic phonetic cues. Word recognition testing was also conducted for cochlear implant listeners. Cochlear implant users were generally less successful at utilizing both spectral and temporal cues for categorization compared with listeners with normal hearing. For the cochlear implant listener group, spectral ripple discrimination was significantly correlated with the categorization of formant transitions; both were correlated with better word recognition. Temporal modulation detection using 100- and 10-Hz-modulated noise was not correlated either with the cochlear implant subjects' categorization of voice onset time or with word recognition. Word recognition was correlated more closely with categorization of the controlled speech cues than with performance on the psychophysical discrimination tasks. When evaluating people with cochlear implants, controlled speech-based stimuli are feasible to use in tests of auditory cue categorization, to complement traditional measures of auditory discrimination. Stimuli based on specific speech cues correspond to counterpart nonlinguistic measures of discrimination, but potentially show better correspondence with speech perception more generally. The ubiquity of the spectral (formant transition) and temporal (voice onset time) stimulus dimensions across languages highlights the potential to use this testing approach even in cases where English is not the native language.

Assessment of spectral and temporal resolution in cochlear implant users using psychoacoustic discrimination and speech cue categorization

PubMed Central

Winn, Matthew B.; Won, Jong Ho; Moon, Il Joon

2016-01-01

Objectives This study was conducted to measure auditory perception by cochlear implant users in the spectral and temporal domains, using tests of either categorization (using speech-based cues) or discrimination (using conventional psychoacoustic tests). We hypothesized that traditional nonlinguistic tests assessing spectral and temporal auditory resolution would correspond to speech-based measures assessing specific aspects of phonetic categorization assumed to depend on spectral and temporal auditory resolution. We further hypothesized that speech-based categorization performance would ultimately be a superior predictor of speech recognition performance, because of the fundamental nature of speech recognition as categorization. Design Nineteen CI listeners and 10 listeners with normal hearing (NH) participated in a suite of tasks that included spectral ripple discrimination (SRD), temporal modulation detection (TMD), and syllable categorization, which was split into a spectral-cue-based task (targeting the /ba/-/da/ contrast) and a timing-cue-based task (targeting the /b/-/p/ and /d/-/t/ contrasts). Speech sounds were manipulated in order to contain specific spectral or temporal modulations (formant transitions or voice onset time, respectively) that could be categorized. Categorization responses were quantified using logistic regression in order to assess perceptual sensitivity to acoustic phonetic cues. Word recognition testing was also conducted for CI listeners. Results CI users were generally less successful at utilizing both spectral and temporal cues for categorization compared to listeners with normal hearing. For the CI listener group, SRD was significantly correlated with the categorization of formant transitions; both were correlated with better word recognition. TMD using 100 Hz and 10 Hz modulated noise was not correlated with the CI subjects’ categorization of VOT, nor with word recognition. Word recognition was correlated more closely with categorization of the controlled speech cues than with performance on the psychophysical discrimination tasks. Conclusions When evaluating people with cochlear implants, controlled speech-based stimuli are feasible to use in tests of auditory cue categorization, to complement traditional measures of auditory discrimination. Stimuli based on specific speech cues correspond to counterpart non-linguistic measures of discrimination, but potentially show better correspondence with speech perception more generally. The ubiquity of the spectral (formant transition) and temporal (VOT) stimulus dimensions across languages highlights the potential to use this testing approach even in cases where English is not the native language. PMID:27438871

Assessment of forward head posture in females: observational and photogrammetry methods.

PubMed

Salahzadeh, Zahra; Maroufi, Nader; Ahmadi, Amir; Behtash, Hamid; Razmjoo, Arash; Gohari, Mahmoud; Parnianpour, Mohamad

2014-01-01

There are different methods to assess forward head posture (FHP) but the accuracy and discrimination ability of these methods are not clear. Here, we want to compare three postural angles for FHP assessment and also study the discrimination accuracy of three photogrammetric methods to differentiate groups categorized based on observational method. All Seventy-eight healthy female participants (23 ± 2.63 years), were classified into three groups: moderate-severe FHP, slight FHP and non FHP based on observational postural assessment rules. Applying three photogrammetric methods - craniovertebral angle, head title angle and head position angle - to measure FHP objectively. One - way ANOVA test showed a significant difference in three categorized group's craniovertebral angle (P< 0.05, F=83.07). There was no dramatic difference in head tilt angle and head position angle methods in three groups. According to Linear Discriminate Analysis (LDA) results, the canonical discriminant function (Wilks'Lambda) was 0.311 for craniovertebral angle with 79.5% of cross-validated grouped cases correctly classified. Our results showed that, craniovertebral angle method may discriminate the females with moderate-severe and non FHP more accurate than head position angle and head tilt angle. The photogrammetric method had excellent inter and intra rater reliability to assess the head and cervical posture.

An overview on the emerging area of identification, characterization, and assessment of health apps.

PubMed

Paglialonga, Alessia; Lugo, Alessandra; Santoro, Eugenio

2018-05-28

The need to characterize and assess health apps has inspired a significant amount of research in the past years, in search for methods able to provide potential app users with relevant, meaningful knowledge. This article presents an overview of the recent literature in this field and categorizes - by discussing some specific examples - the various methodologies introduced so far for the identification, characterization, and assessment of health apps. Specifically, this article outlines the most significant web-based resources for app identification, relevant frameworks for descriptive characterization of apps' features, and a number of methods for the assessment of quality along its various components (e.g., evidence base, trustworthiness, privacy, or user engagement). The development of methods to characterize the apps' features and to assess their quality is important to define benchmarks and minimum requirements. Similarly, such methods are important to categorize potential risks and challenges in the field so that risks can be minimized, whenever possible, by design. Understanding methods to assess apps is key to raise the standards of quality of health apps on the market, towards the final goal of delivering apps that are built on the pillars of evidence-base, reliability, long-term effectiveness, and user-oriented quality. Copyright © 2018. Published by Elsevier Inc.

The Research of Tax Text Categorization based on Rough Set

NASA Astrophysics Data System (ADS)

Liu, Bin; Xu, Guang; Xu, Qian; Zhang, Nan

To solve the problem of effective of categorization of text data in taxation system, the paper analyses the text data and the size calculation of key issues first, then designs text categorization based on rough set model.

Inquiry-based problem solving in introductory physics

NASA Astrophysics Data System (ADS)

Koleci, Carolann

What makes problem solving in physics difficult? How do students solve physics problems, and how does this compare to an expert physicist's strategy? Over the past twenty years, physics education research has revealed several differences between novice and expert problem solving. The work of Chi, Feltovich, and Glaser demonstrates that novices tend to categorize problems based on surface features, while experts categorize according to theory, principles, or concepts1. If there are differences between how problems are categorized, then are there differences between how physics problems are solved? Learning more about the problem solving process, including how students like to learn and what is most effective, requires both qualitative and quantitative analysis. In an effort to learn how novices and experts solve introductory electricity problems, a series of in-depth interviews were conducted, transcribed, and analyzed, using both qualitative and quantitative methods. One-way ANOVA tests were performed in order to learn if there are any significant problem solving differences between: (a) novices and experts, (b) genders, (c) students who like to answer questions in class and those who don't, (d) students who like to ask questions in class and those who don't, (e) students employing an interrogative approach to problem solving and those who don't, and (f) those who like physics and those who dislike it. The results of both the qualitative and quantitative methods reveal that inquiry-based problem solving is prevalent among novices and experts, and frequently leads to the correct physics. These findings serve as impetus for the third dimension of this work: the development of Choose Your Own Adventure Physics(c) (CYOAP), an innovative teaching tool in physics which encourages inquiry-based problem solving. 1Chi, M., P. Feltovich, R. Glaser, "Categorization and Representation of Physics Problems by Experts and Novices", Cognitive Science, 5, 121--152 (1981).

NICE: A Computational Solution to Close the Gap from Colour Perception to Colour Categorization

PubMed Central

Parraga, C. Alejandro; Akbarinia, Arash

2016-01-01

The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms. PMID:26954691

NICE: A Computational Solution to Close the Gap from Colour Perception to Colour Categorization.

PubMed

Parraga, C Alejandro; Akbarinia, Arash

2016-01-01

The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms.

Target-Based Maintenance of Privacy Preserving Association Rules

ERIC Educational Resources Information Center

Ahluwalia, Madhu V.

2011-01-01

In the context of association rule mining, the state-of-the-art in privacy preserving data mining provides solutions for categorical and Boolean association rules but not for quantitative association rules. This research fills this gap by describing a method based on discrete wavelet transform (DWT) to protect input data privacy while preserving…

System for pathology categorization and retrieval in chest radiographs

NASA Astrophysics Data System (ADS)

Avni, Uri; Greenspan, Hayit; Konen, Eli; Sharon, Michal; Goldberger, Jacob

2011-03-01

In this paper we present an overview of a system we have been developing for the past several years for efficient image categorization and retrieval in large radiograph archives. The methodology is based on local patch representation of the image content, using a bag of visual words approach and similarity-based categorization with a kernel based SVM classifier. We show an application to pathology-level categorization of chest x-ray data, the most popular examination in radiology. Our study deals with pathology detection and identification of individual pathologies including right and left pleural effusion, enlarged heart and cases of enlarged mediastinum. The input from a radiologist provided a global label for the entire image (healthy/pathology), and the categorization was conducted on the entire image, with no need for segmentation algorithms or any geometrical rules. An automatic diagnostic-level categorization, even on such an elementary level as healthy vs pathological, provides a useful tool for radiologists on this popular and important examination. This is a first step towards similarity-based categorization, which has a major clinical implications for computer-assisted diagnostics.

The Proposal Auto-Categorizer and Manager for Time Allocation Review at the Space Telescope Science Institute

NASA Astrophysics Data System (ADS)

Strolger, Louis-Gregory; Porter, Sophia; Lagerstrom, Jill; Weissman, Sarah; Reid, I. Neill; Garcia, Michael

2017-04-01

The Proposal Auto-Categorizer and Manager (PACMan) tool was written to respond to concerns about subjective flaws and potential biases in some aspects of the proposal review process for time allocation for the Hubble Space Telescope (HST), and to partially alleviate some of the anticipated additional workload from the James Webb Space Telescope (JWST) proposal review. PACMan is essentially a mixed-method Naive Bayesian spam filtering routine, with multiple pools representing scientific categories, that utilizes the Robinson method for combining token (or word) probabilities. PACMan was trained to make similar programmatic decisions in science category sorting, panelist selection, and proposal-to-panelists assignments to those made by individuals and committees in the Science Policies Group (SPG) at the Space Telescope Science Institute. Based on training from the previous cycle’s proposals, at an average of 87%, PACMan made the same science category assignments for proposals in Cycle 24 as the SPG. Tests for similar science categorizations, based on training using proposals from additional cycles, show that this accuracy can be further improved, to the > 95 % level. This tool will be used to augment or replace key functions in the Time Allocation Committee review processes in future HST and JWST cycles.

Discriminating Simulated Vocal Tremor Source Using Amplitude Modulation Spectra

PubMed Central

Carbonell, Kathy M.; Lester, Rosemary A.; Story, Brad H.; Lotto, Andrew J.

2014-01-01

Objectives/Hypothesis Sources of vocal tremor are difficult to categorize perceptually and acoustically. This paper describes a preliminary attempt to discriminate vocal tremor sources through the use of spectral measures of the amplitude envelope. The hypothesis is that different vocal tremor sources are associated with distinct patterns of acoustic amplitude modulations. Study Design Statistical categorization methods (discriminant function analysis) were used to discriminate signals from simulated vocal tremor with different sources using only acoustic measures derived from the amplitude envelopes. Methods Simulations of vocal tremor were created by modulating parameters of a vocal fold model corresponding to oscillations of respiratory driving pressure (respiratory tremor), degree of vocal fold adduction (adductory tremor) and fundamental frequency of vocal fold vibration (F0 tremor). The acoustic measures were based on spectral analyses of the amplitude envelope computed across the entire signal and within select frequency bands. Results The signals could be categorized (with accuracy well above chance) in terms of the simulated tremor source using only measures of the amplitude envelope spectrum even when multiple sources of tremor were included. Conclusions These results supply initial support for an amplitude-envelope based approach to identify the source of vocal tremor and provide further evidence for the rich information about talker characteristics present in the temporal structure of the amplitude envelope. PMID:25532813

Potential Information Loss Due to Categorization of Minimum Inhibitory Concentration Frequency Distributions.

PubMed

Mazloom, Reza; Jaberi-Douraki, Majid; Comer, Jeffrey R; Volkova, Victoriya

2018-01-01

A bacterial isolate's susceptibility to antimicrobial is expressed as the lowest drug concentration inhibiting its visible growth, termed minimum inhibitory concentration (MIC). The susceptibilities of isolates from a host population at a particular time vary, with isolates with specific MICs present at different frequencies. Currently, for either clinical or monitoring purposes, an isolate is most often categorized as Susceptible, Intermediate, or Resistant to the antimicrobial by comparing its MIC to a breakpoint value. Such data categorizations are known in statistics to cause information loss compared to analyzing the underlying frequency distributions. The U.S. National Antimicrobial Resistance Monitoring System (NARMS) includes foodborne bacteria at the food animal processing and retail product points. The breakpoints used to interpret the MIC values for foodborne bacteria are those relevant to clinical treatments by the antimicrobials in humans in whom the isolates were to cause infection. However, conceptually different objectives arise when inference is sought concerning changes in susceptibility/resistance across isolates of a bacterial species in host populations among different sampling points or times. For the NARMS 1996-2013 data for animal processing and retail, we determined the fraction of comparisons of susceptibility/resistance to 44 antimicrobial drugs of twelve classes of a bacterial species in a given animal host or product population where there was a significant change in the MIC frequency distributions between consecutive years or the two sampling points, while the categorization-based analyses concluded no change. The categorization-based analyses missed significant changes in 54% of the year-to-year comparisons and in 71% of the slaughter-to-retail within-year comparisons. Hence, analyses using the breakpoint-based categorizations of the MIC data may miss significant developments in the resistance distributions between the sampling points or times. Methods considering the MIC frequency distributions in their entirety may be superior for epidemiological analyses of resistance dynamics in populations.

Rule-Based Category Learning in Children: The Role of Age and Executive Functioning

PubMed Central

Rabi, Rahel; Minda, John Paul

2014-01-01

Rule-based category learning was examined in 4–11 year-olds and adults. Participants were asked to learn a set of novel perceptual categories in a classification learning task. Categorization performance improved with age, with younger children showing the strongest rule-based deficit relative to older children and adults. Model-based analyses provided insight regarding the type of strategy being used to solve the categorization task, demonstrating that the use of the task appropriate strategy increased with age. When children and adults who identified the correct categorization rule were compared, the performance deficit was no longer evident. Executive functions were also measured. While both working memory and inhibitory control were related to rule-based categorization and improved with age, working memory specifically was found to marginally mediate the age-related improvements in categorization. When analyses focused only on the sample of children, results showed that working memory ability and inhibitory control were associated with categorization performance and strategy use. The current findings track changes in categorization performance across childhood, demonstrating at which points performance begins to mature and resemble that of adults. Additionally, findings highlight the potential role that working memory and inhibitory control may play in rule-based category learning. PMID:24489658

Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease.

PubMed

Taguchi, Y-h; Iwadate, Mitsuo; Umeyama, Hideaki

2015-04-30

Feature extraction (FE) is difficult, particularly if there are more features than samples, as small sample numbers often result in biased outcomes or overfitting. Furthermore, multiple sample classes often complicate FE because evaluating performance, which is usual in supervised FE, is generally harder than the two-class problem. Developing sample classification independent unsupervised methods would solve many of these problems. Two principal component analysis (PCA)-based FE, specifically, variational Bayes PCA (VBPCA) was extended to perform unsupervised FE, and together with conventional PCA (CPCA)-based unsupervised FE, were tested as sample classification independent unsupervised FE methods. VBPCA- and CPCA-based unsupervised FE both performed well when applied to simulated data, and a posttraumatic stress disorder (PTSD)-mediated heart disease data set that had multiple categorical class observations in mRNA/microRNA expression of stressed mouse heart. A critical set of PTSD miRNAs/mRNAs were identified that show aberrant expression between treatment and control samples, and significant, negative correlation with one another. Moreover, greater stability and biological feasibility than conventional supervised FE was also demonstrated. Based on the results obtained, in silico drug discovery was performed as translational validation of the methods. Our two proposed unsupervised FE methods (CPCA- and VBPCA-based) worked well on simulated data, and outperformed two conventional supervised FE methods on a real data set. Thus, these two methods have suggested equivalence for FE on categorical multiclass data sets, with potential translational utility for in silico drug discovery.

Bootstrap imputation with a disease probability model minimized bias from misclassification due to administrative database codes.

PubMed

van Walraven, Carl

2017-04-01

Diagnostic codes used in administrative databases cause bias due to misclassification of patient disease status. It is unclear which methods minimize this bias. Serum creatinine measures were used to determine severe renal failure status in 50,074 hospitalized patients. The true prevalence of severe renal failure and its association with covariates were measured. These were compared to results for which renal failure status was determined using surrogate measures including the following: (1) diagnostic codes; (2) categorization of probability estimates of renal failure determined from a previously validated model; or (3) bootstrap methods imputation of disease status using model-derived probability estimates. Bias in estimates of severe renal failure prevalence and its association with covariates were minimal when bootstrap methods were used to impute renal failure status from model-based probability estimates. In contrast, biases were extensive when renal failure status was determined using codes or methods in which model-based condition probability was categorized. Bias due to misclassification from inaccurate diagnostic codes can be minimized using bootstrap methods to impute condition status using multivariable model-derived probability estimates. Copyright © 2017 Elsevier Inc. All rights reserved.

Meta-analytical synthesis of regression coefficients under different categorization scheme of continuous covariates.

PubMed

Yoneoka, Daisuke; Henmi, Masayuki

2017-11-30

Recently, the number of clinical prediction models sharing the same regression task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these regression models have not been sufficiently studied, particularly in meta-analysis settings where only regression coefficients are available. One of the difficulties lies in the differences between the categorization schemes of continuous covariates across different studies. In general, categorization methods using cutoff values are study specific across available models, even if they focus on the same covariates of interest. Differences in the categorization of covariates could lead to serious bias in the estimated regression coefficients and thus in subsequent syntheses. To tackle this issue, we developed synthesis methods for linear regression models with different categorization schemes of covariates. A 2-step approach to aggregate the regression coefficient estimates is proposed. The first step is to estimate the joint distribution of covariates by introducing a latent sampling distribution, which uses one set of individual participant data to estimate the marginal distribution of covariates with categorization. The second step is to use a nonlinear mixed-effects model with correction terms for the bias due to categorization to estimate the overall regression coefficients. Especially in terms of precision, numerical simulations show that our approach outperforms conventional methods, which only use studies with common covariates or ignore the differences between categorization schemes. The method developed in this study is also applied to a series of WHO epidemiologic studies on white blood cell counts. Copyright © 2017 John Wiley & Sons, Ltd.

An efficient scheme for automatic web pages categorization using the support vector machine

NASA Astrophysics Data System (ADS)

Bhalla, Vinod Kumar; Kumar, Neeraj

2016-07-01

In the past few years, with an evolution of the Internet and related technologies, the number of the Internet users grows exponentially. These users demand access to relevant web pages from the Internet within fraction of seconds. To achieve this goal, there is a requirement of an efficient categorization of web page contents. Manual categorization of these billions of web pages to achieve high accuracy is a challenging task. Most of the existing techniques reported in the literature are semi-automatic. Using these techniques, higher level of accuracy cannot be achieved. To achieve these goals, this paper proposes an automatic web pages categorization into the domain category. The proposed scheme is based on the identification of specific and relevant features of the web pages. In the proposed scheme, first extraction and evaluation of features are done followed by filtering the feature set for categorization of domain web pages. A feature extraction tool based on the HTML document object model of the web page is developed in the proposed scheme. Feature extraction and weight assignment are based on the collection of domain-specific keyword list developed by considering various domain pages. Moreover, the keyword list is reduced on the basis of ids of keywords in keyword list. Also, stemming of keywords and tag text is done to achieve a higher accuracy. An extensive feature set is generated to develop a robust classification technique. The proposed scheme was evaluated using a machine learning method in combination with feature extraction and statistical analysis using support vector machine kernel as the classification tool. The results obtained confirm the effectiveness of the proposed scheme in terms of its accuracy in different categories of web pages.

Out of sight, out of mind: Categorization learning and normal aging.

PubMed

Schenk, Sabrina; Minda, John P; Lech, Robert K; Suchan, Boris

2016-10-01

The present combined EEG and eye tracking study examined the process of categorization learning at different age ranges and aimed to investigate to which degree categorization learning is mediated by visual attention and perceptual strategies. Seventeen young subjects and ten elderly subjects had to perform a visual categorization task with two abstract categories. Each category consisted of prototypical stimuli and an exception. The categorization of prototypical stimuli was learned very early during the experiment, while the learning of exceptions was delayed. The categorization of exceptions was accompanied by higher P150, P250 and P300 amplitudes. In contrast to younger subjects, elderly subjects had problems in the categorization of exceptions, but showed an intact categorization performance for prototypical stimuli. Moreover, elderly subjects showed higher fixation rates for important stimulus features and higher P150 amplitudes, which were positively correlated with the categorization performances. These results indicate that elderly subjects compensate for cognitive decline through enhanced perceptual and attentional processing of individual stimulus features. Additionally, a computational approach has been applied and showed a transition away from purely abstraction-based learning to an exemplar-based learning in the middle block for both groups. However, the calculated models provide a better fit for younger subjects than for elderly subjects. The current study demonstrates that human categorization learning is based on early abstraction-based processing followed by an exemplar-memorization stage. This strategy combination facilitates the learning of real world categories with a nuanced category structure. In addition, the present study suggests that categorization learning is affected by normal aging and modulated by perceptual processing and visual attention. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Categorization Model for Educational Values of the History of Mathematics. An Empirical Study

NASA Astrophysics Data System (ADS)

Wang, Xiao-qin; Qi, Chun-yan; Wang, Ke

2017-11-01

There is not a clear consensus on the categorization framework of the educational values of the history of mathematics. By analyzing 20 Chinese teaching cases on integrating the history of mathematics into mathematics teaching based on the relevant literature, this study examined a new categorization framework of the educational values of the history of mathematics by combining the objectives of high school mathematics curriculum in China. This framework includes six dimensions: the harmony of knowledge, the beauty of ideas or methods, the pleasure of inquiries, the improvement of capabilities, the charm of cultures, and the availability of moral education. The results show that this framework better explained the all-educational values of the history of mathematics that all teaching cases showed. Therefore, the framework can guide teachers to better integrate the history of mathematics into teaching.

Diamond like carbon coatings: Categorization by atomic number density

NASA Technical Reports Server (NTRS)

Angus, John C.

1986-01-01

Dense diamond-like hydrocarbon films grown at the NASA Lewis Research Center by radio frequency self bias discharge and by direct ion beam deposition were studied. A new method for categorizing hydrocarbons based on their atomic number density and elemental composition was developed and applied to the diamond-like hydrocarbon films. It was shown that the diamond-like hydrocarbon films are an entirely new class of hydrocarbons with atomic number densities lying between those of single crystal diamond and adamantanes. In addition, a major review article on these new materials was completed in cooperation with NASA Lewis Research Center personnel.

Acne severity grading: determining essential clinical components and features using a Delphi consensus.

PubMed

Tan, Jerry; Wolfe, Barat; Weiss, Jonathan; Stein-Gold, Linda; Bikowski, Joseph; Del Rosso, James; Webster, Guy F; Lucky, Anne; Thiboutot, Diane; Wilkin, Jonathan; Leyden, James; Chren, Mary-Margaret

2012-08-01

There are multiple global scales for acne severity grading but no singular standard. Our objective was to determine the essential clinical components (content items) and features (property-related items) for an acne global grading scale for use in research and clinical practice using an iterative method, the Delphi process. Ten acne experts were invited to participate in a Web-based Delphi survey comprising 3 iterative rounds of questions. In round 1, the experts identified the following clinical components (primary acne lesions, number of lesions, extent, regional involvement, secondary lesions, and patient experiences) and features (clinimetric properties, ease of use, categorization of severity based on photographs or text, and acceptance by all stakeholders). In round 2, consensus for inclusion in the scale was established for primary lesions, number, sites, and extent; as well as clinimetric properties and ease of use. In round 3, consensus for inclusion was further established for categorization and acceptance. Patient experiences were excluded and no consensus was achieved for secondary lesions. The Delphi panel consisted solely of the United States (U.S.)-based acne experts. Using an established method for achieving consensus, experts in acne vulgaris concluded that an ideal acne global grading scale would comprise the essential clinical components of primary acne lesions, their quantity, extent, and facial and extrafacial sites of involvement; with features of clinimetric properties, categorization, efficiency, and acceptance. Copyright © 2011 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

Multiple systems of category learning.

PubMed

Smith, Edward E; Grossman, Murray

2008-01-01

We review neuropsychological and neuroimaging evidence for the existence of three qualitatively different categorization systems. These categorization systems are themselves based on three distinct memory systems: working memory (WM), explicit long-term memory (explicit LTM), and implicit long-term memory (implicit LTM). We first contrast categorization based on WM with that based on explicit LTM, where the former typically involves applying rules to a test item and the latter involves determining the similarity between stored exemplars or prototypes and a test item. Neuroimaging studies show differences between brain activity in normal participants as a function of whether they are instructed to categorize novel test items by rule or by similarity to known category members. Rule instructions typically lead to more activation in frontal or parietal areas, associated with WM and selective attention, whereas similarity instructions may activate parietal areas associated with the integration of perceptual features. Studies with neurological patients in the same paradigms provide converging evidence, e.g., patients with Alzheimer's disease, who have damage in prefrontal regions, are more impaired with rule than similarity instructions. Our second contrast is between categorization based on explicit LTM with that based on implicit LTM. Neuropsychological studies with patients with medial-temporal lobe damage show that patients are impaired on tasks requiring explicit LTM, but perform relatively normally on an implicit categorization task. Neuroimaging studies provide converging evidence: whereas explicit categorization is mediated by activation in numerous frontal and parietal areas, implicit categorization is mediated by a deactivation in posterior cortex.

Ontology-Based Learner Categorization through Case Based Reasoning and Fuzzy Logic

ERIC Educational Resources Information Center

Sarwar, Sohail; García-Castro, Raul; Qayyum, Zia Ul; Safyan, Muhammad; Munir, Rana Faisal

2017-01-01

Learner categorization has a pivotal role in making e-learning systems a success. However, learner characteristics exploited at abstract level of granularity by contemporary techniques cannot categorize the learners effectively. In this paper, an architecture of e-learning framework has been presented that exploits the machine learning based…

Categorizing Drugs and Drug-Taking: A More Meaningful Approach.

ERIC Educational Resources Information Center

Gold, Robert S.; Duncan, David F.

This document reviews various definitions of the nature and classification of drugs. Difficulties with existing categorizations which use such bases as clinical utility, molecular structure, effects on the central nervous system, legality, and hazard potential are disucssed. A more meaningful categorization based on the availability and sources of…

Multinomial mixture model with heterogeneous classification probabilities

USGS Publications Warehouse

Holland, M.D.; Gray, B.R.

2011-01-01

Royle and Link (Ecology 86(9):2505-2512, 2005) proposed an analytical method that allowed estimation of multinomial distribution parameters and classification probabilities from categorical data measured with error. While useful, we demonstrate algebraically and by simulations that this method yields biased multinomial parameter estimates when the probabilities of correct category classifications vary among sampling units. We address this shortcoming by treating these probabilities as logit-normal random variables within a Bayesian framework. We use Markov chain Monte Carlo to compute Bayes estimates from a simulated sample from the posterior distribution. Based on simulations, this elaborated Royle-Link model yields nearly unbiased estimates of multinomial and correct classification probability estimates when classification probabilities are allowed to vary according to the normal distribution on the logit scale or according to the Beta distribution. The method is illustrated using categorical submersed aquatic vegetation data. ?? 2010 Springer Science+Business Media, LLC.

Instance-based categorization: automatic versus intentional forms of retrieval.

PubMed

Neal, A; Hesketh, B; Andrews, S

1995-03-01

Two experiments are reported which attempt to disentangle the relative contribution of intentional and automatic forms of retrieval to instance-based categorization. A financial decision-making task was used in which subjects had to decide whether a bank would approve loans for a series of applicants. Experiment 1 found that categorization was sensitive to instance-specific knowledge, even when subjects had practiced using a simple rule. L. L. Jacoby's (1991) process-dissociation procedure was adapted for use in Experiment 2 to infer the relative contribution of intentional and automatic retrieval processes to categorization decisions. The results provided (1) strong evidence that intentional retrieval processes influence categorization, and (2) some preliminary evidence suggesting that automatic retrieval processes may also contribute to categorization decisions.

Fine-grained visual marine vessel classification for coastal surveillance and defense applications

NASA Astrophysics Data System (ADS)

Solmaz, Berkan; Gundogdu, Erhan; Karaman, Kaan; Yücesoy, Veysel; Koç, Aykut

2017-10-01

The need for capabilities of automated visual content analysis has substantially increased due to presence of large number of images captured by surveillance cameras. With a focus on development of practical methods for extracting effective visual data representations, deep neural network based representations have received great attention due to their success in visual categorization of generic images. For fine-grained image categorization, a closely related yet a more challenging research problem compared to generic image categorization due to high visual similarities within subgroups, diverse applications were developed such as classifying images of vehicles, birds, food and plants. Here, we propose the use of deep neural network based representations for categorizing and identifying marine vessels for defense and security applications. First, we gather a large number of marine vessel images via online sources grouping them into four coarse categories; naval, civil, commercial and service vessels. Next, we subgroup naval vessels into fine categories such as corvettes, frigates and submarines. For distinguishing images, we extract state-of-the-art deep visual representations and train support-vector-machines. Furthermore, we fine tune deep representations for marine vessel images. Experiments address two scenarios, classification and verification of naval marine vessels. Classification experiment aims coarse categorization, as well as learning models of fine categories. Verification experiment embroils identification of specific naval vessels by revealing if a pair of images belongs to identical marine vessels by the help of learnt deep representations. Obtaining promising performance, we believe these presented capabilities would be essential components of future coastal and on-board surveillance systems.

Self-Directed Adult Learning: A Critical Paradigm Revisited.

ERIC Educational Resources Information Center

Caffarella, Rosemary S.; O'Donnell, Judith M.

1987-01-01

Seeks to analyze and categorize both data-based and conceptual articles on self-directed learning. Covers (1) verification studies, (2) nature of the method, (3) nature of the learner, (4) nature of the philosophical position, and (5) policy. Suggests future research topics. (Author/CH)

Three Reading Comprehension Strategies: TELLS, Story Mapping, and QARs.

ERIC Educational Resources Information Center

Sorrell, Adrian L.

1990-01-01

Three reading comprehension strategies are presented to assist learning-disabled students: an advance organizer technique called "TELLS Fact or Fiction" used before reading a passage, a schema-based technique called "Story Mapping" used while reading, and a postreading method of categorizing questions called…

Experimental Fuels Facility Re-categorization Based on Facility Segmentation

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

Reiss, Troy P.; Andrus, Jason

The Experimental Fuels Facility (EFF) (MFC-794) at the Materials and Fuels Complex (MFC) located on the Idaho National Laboratory (INL) Site was originally constructed to provide controlled-access, indoor storage for radiological contaminated equipment. Use of the facility was expanded to provide a controlled environment for repairing contaminated equipment and characterizing, repackaging, and treating waste. The EFF facility is also used for research and development services, including fuel fabrication. EFF was originally categorized as a LTHC-3 radiological facility based on facility operations and facility radiological inventories. Newly planned program activities identified the need to receive quantities of fissionable materials in excessmore » of the single parameter subcritical limit in ANSI/ANS-8.1, “Nuclear Criticality Safety in Operations with Fissionable Materials Outside Reactors” (identified as “criticality list” quantities in DOE-STD-1027-92, “Hazard Categorization and Accident Analysis Techniques for Compliance with DOE Order 5480.23, Nuclear Safety Analysis Reports,” Attachment 1, Table A.1). Since the proposed inventory of fissionable materials inside EFF may be greater than the single parameter sub-critical limit of 700 g of U-235 equivalent, the initial re-categorization is Hazard Category (HC) 2 based upon a potential criticality hazard. This paper details the facility hazard categorization performed for the EFF. The categorization was necessary to determine (a) the need for further safety analysis in accordance with LWP-10802, “INL Facility Categorization,” and (b) compliance with 10 Code of Federal Regulations (CFR) 830, Subpart B, “Safety Basis Requirements.” Based on the segmentation argument presented in this paper, the final hazard categorization for the facility is LTHC-3. Department of Energy Idaho (DOE-ID) approval of the final hazard categorization determined by this hazard assessment document (HAD) was required per the DOE-ID Supplemental Guidance for DOE-STD-1027-92 based on the proposed downgrade of the initial facility categorization of Hazard Category 2.« less

Memory Training for Older Adults with Low Education: Mental Images versus Categorization

ERIC Educational Resources Information Center

da Silva, Henrique Salmazo; Yassuda, Monica Sanches

2009-01-01

This study aimed to describe the benefits of memory training for older adults with low education. Twenty-nine healthy older adults with zero to two years of formal education participated. Sixteen participants received training based on categorization (categorization group = CATG) and 13 received training based on mental images (imagery…

Model-based Clustering of Categorical Time Series with Multinomial Logit Classification

NASA Astrophysics Data System (ADS)

Frühwirth-Schnatter, Sylvia; Pamminger, Christoph; Winter-Ebmer, Rudolf; Weber, Andrea

2010-09-01

A common problem in many areas of applied statistics is to identify groups of similar time series in a panel of time series. However, distance-based clustering methods cannot easily be extended to time series data, where an appropriate distance-measure is rather difficult to define, particularly for discrete-valued time series. Markov chain clustering, proposed by Pamminger and Frühwirth-Schnatter [6], is an approach for clustering discrete-valued time series obtained by observing a categorical variable with several states. This model-based clustering method is based on finite mixtures of first-order time-homogeneous Markov chain models. In order to further explain group membership we present an extension to the approach of Pamminger and Frühwirth-Schnatter [6] by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule by using a multinomial logit model. The parameters are estimated for a fixed number of clusters within a Bayesian framework using an Markov chain Monte Carlo (MCMC) sampling scheme representing a (full) Gibbs-type sampler which involves only draws from standard distributions. Finally, an application to a panel of Austrian wage mobility data is presented which leads to an interesting segmentation of the Austrian labour market.

Categorization of Quantum Mechanics Problems by Professors and Students

ERIC Educational Resources Information Center

Lin, Shih-Yin; Singh, Chandralekha

2010-01-01

We discuss the categorization of 20 quantum mechanics problems by physics professors and undergraduate students from two honours-level quantum mechanics courses. Professors and students were asked to categorize the problems based upon similarity of solution. We also had individual discussions with professors who categorized the problems. Faculty…

Effects of categorization method, regression type, and variable distribution on the inflation of Type-I error rate when categorizing a confounding variable.

PubMed

Barnwell-Ménard, Jean-Louis; Li, Qing; Cohen, Alan A

2015-03-15

The loss of signal associated with categorizing a continuous variable is well known, and previous studies have demonstrated that this can lead to an inflation of Type-I error when the categorized variable is a confounder in a regression analysis estimating the effect of an exposure on an outcome. However, it is not known how the Type-I error may vary under different circumstances, including logistic versus linear regression, different distributions of the confounder, and different categorization methods. Here, we analytically quantified the effect of categorization and then performed a series of 9600 Monte Carlo simulations to estimate the Type-I error inflation associated with categorization of a confounder under different regression scenarios. We show that Type-I error is unacceptably high (>10% in most scenarios and often 100%). The only exception was when the variable categorized was a continuous mixture proxy for a genuinely dichotomous latent variable, where both the continuous proxy and the categorized variable are error-ridden proxies for the dichotomous latent variable. As expected, error inflation was also higher with larger sample size, fewer categories, and stronger associations between the confounder and the exposure or outcome. We provide online tools that can help researchers estimate the potential error inflation and understand how serious a problem this is. Copyright © 2014 John Wiley & Sons, Ltd.

LDA boost classification: boosting by topics

NASA Astrophysics Data System (ADS)

Lei, La; Qiao, Guo; Qimin, Cao; Qitao, Li

2012-12-01

AdaBoost is an efficacious classification algorithm especially in text categorization (TC) tasks. The methodology of setting up a classifier committee and voting on the documents for classification can achieve high categorization precision. However, traditional Vector Space Model can easily lead to the curse of dimensionality and feature sparsity problems; so it affects classification performance seriously. This article proposed a novel classification algorithm called LDABoost based on boosting ideology which uses Latent Dirichlet Allocation (LDA) to modeling the feature space. Instead of using words or phrase, LDABoost use latent topics as the features. In this way, the feature dimension is significantly reduced. Improved Naïve Bayes (NB) is designed as the weaker classifier which keeps the efficiency advantage of classic NB algorithm and has higher precision. Moreover, a two-stage iterative weighted method called Cute Integration in this article is proposed for improving the accuracy by integrating weak classifiers into strong classifier in a more rational way. Mutual Information is used as metrics of weights allocation. The voting information and the categorization decision made by basis classifiers are fully utilized for generating the strong classifier. Experimental results reveals LDABoost making categorization in a low-dimensional space, it has higher accuracy than traditional AdaBoost algorithms and many other classic classification algorithms. Moreover, its runtime consumption is lower than different versions of AdaBoost, TC algorithms based on support vector machine and Neural Networks.

Endangered Fish Species in Kansas: Historic vs Contemporary Distribution

EPA Science Inventory

Background/Question/Methods Kansas state has more freshwater fish species than other states in the west and northern US. Based on recent count, more than 140 fishes have been documented in Kansas rivers. And at least five are categorized as endangered species in Kansas (and thre...

Using Categorization of Problems as an Instructional Tool to Help Introductory Students Learn Physics

ERIC Educational Resources Information Center

Mason, Andrew; Singh, Chandralekha

2016-01-01

The ability to categorize problems based upon underlying principles, rather than contexts, is considered a hallmark of expertise in physics problem solving. With inspiration from a classic study by Chi, Feltovich, and Glaser, we compared the categorization of 25 introductory mechanics problems based upon similarity of solution by students in large…

77 FR 11536 - Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-27

... Categorization of Chemicals Causing Allergic Contact Dermatitis: Availability of Federal Agency Responses AGENCY... lymph node assay (LLNA) for potency categorization of chemicals causing allergic contact dermatitis (ACD... Local Lymph Node Assay for Potency Categorization of Chemicals Causing Allergic Contact Dermatitis in...

Initial assessment of facial nerve paralysis based on motion analysis using an optical flow method.

PubMed

Samsudin, Wan Syahirah W; Sundaraj, Kenneth; Ahmad, Amirozi; Salleh, Hasriah

2016-01-01

An initial assessment method that can classify as well as categorize the severity of paralysis into one of six levels according to the House-Brackmann (HB) system based on facial landmarks motion using an Optical Flow (OF) algorithm is proposed. The desired landmarks were obtained from the video recordings of 5 normal and 3 Bell's Palsy subjects and tracked using the Kanade-Lucas-Tomasi (KLT) method. A new scoring system based on the motion analysis using area measurement is proposed. This scoring system uses the individual scores from the facial exercises and grades the paralysis based on the HB system. The proposed method has obtained promising results and may play a pivotal role towards improved rehabilitation programs for patients.

Assets as a Socioeconomic Status Index: Categorical Principal Components Analysis vs. Latent Class Analysis.

PubMed

Sartipi, Majid; Nedjat, Saharnaz; Mansournia, Mohammad Ali; Baigi, Vali; Fotouhi, Akbar

2016-11-01

Some variables like Socioeconomic Status (SES) cannot be directly measured, instead, so-called 'latent variables' are measured indirectly through calculating tangible items. There are different methods for measuring latent variables such as data reduction methods e.g. Principal Components Analysis (PCA) and Latent Class Analysis (LCA). The purpose of our study was to measure assets index- as a representative of SES- through two methods of Non-Linear PCA (NLPCA) and LCA, and to compare them for choosing the most appropriate model. This was a cross sectional study in which 1995 respondents filled the questionnaires about their assets in Tehran. The data were analyzed by SPSS 19 (CATPCA command) and SAS 9.2 (PROC LCA command) to estimate their socioeconomic status. The results were compared based on the Intra-class Correlation Coefficient (ICC). The 6 derived classes from LCA based on BIC, were highly consistent with the 6 classes from CATPCA (Categorical PCA) (ICC = 0.87, 95%CI: 0.86 - 0.88). There is no gold standard to measure SES. Therefore, it is not possible to definitely say that a specific method is better than another one. LCA is a complicated method that presents detailed information about latent variables and required one assumption (local independency), while NLPCA is a simple method, which requires more assumptions. Generally, NLPCA seems to be an acceptable method of analysis because of its simplicity and high agreement with LCA.

Pseudolongitudinal Investigation on Chinese Students' Categorization of Kinematics and Mechanics Problems

ERIC Educational Resources Information Center

Zhu, Guangtian; Wang, Jue

2017-01-01

Students' categorization of physics problems reflects their expertise in problem solving. We conducted a pseudolongitudinal study to investigate the development of students' categorization ability. Over 250 Chinese students from grade 10 to grade 12 were asked to categorize 20 problems of kinematics and mechanics into suitable categories based on…

Nonlinear dynamics based digital logic and circuits.

PubMed

Kia, Behnam; Lindner, John F; Ditto, William L

2015-01-01

We discuss the role and importance of dynamics in the brain and biological neural networks and argue that dynamics is one of the main missing elements in conventional Boolean logic and circuits. We summarize a simple dynamics based computing method, and categorize different techniques that we have introduced to realize logic, functionality, and programmability. We discuss the role and importance of coupled dynamics in networks of biological excitable cells, and then review our simple coupled dynamics based method for computing. In this paper, for the first time, we show how dynamics can be used and programmed to implement computation in any given base, including but not limited to base two.

Groups for Parents with Intellectual Disabilities: A Qualitative Analysis of Experiences

ERIC Educational Resources Information Center

Gustavsson, Marie; Starke, Mikaela

2017-01-01

Background: Parents with intellectual disabilities (IDs) are often socially isolated and need support. Materials and Methods: This qualitative study is based on participant observations of a group for parents with with intellectual disabilities. Data were categorized and interpreted in the framework of social capital and symbolic interactionism.…

An Examination of Strategy Implementation during Abstract Nonlinguistic Category Learning in Aphasia

ERIC Educational Resources Information Center

Vallila-Rohter, Sofia; Kiran, Swathi

2015-01-01

Purpose: Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Method: Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases…

Oppositional Defiant Disorder in Adults with ADHD

ERIC Educational Resources Information Center

Reimherr, Frederick W.; Marchant, Barrie K.; Olsen, John L.; Wender, Paul H.; Robison, Reid J.

2013-01-01

Objective: Oppositional defiant disorder (ODD) is the most common comorbid condition in childhood ADHD. This trial was prospectively designed to explore ODD symptoms in ADHD adults. Method: A total of 86 patients in this placebo-controlled, double-blind trial of methylphenidate transdermal system (MTS) were categorized based on the presence of ODD…

The Latent Structure of Child Depression: A Taxometric Analysis

ERIC Educational Resources Information Center

Richey, J. Anthony; Schmidt, Norman B.; Lonigan, Christopher J.; Phillips, Beth M.; Catanzaro, Salvatore J.; Laurent, Jeff; Gerhardstein, Rebecca R.; Kotov, Roman

2009-01-01

Background: The current study examined the categorical versus continuous nature of child and adolescent depression among three samples of children and adolescents ranging from 5 to 19 years. Methods: Depression was measured using the Children's Depression Inventory (CDI). Indicators derived from the CDI were based on factor analytic research on…

Cluster Analysis of Minnesota School Districts. A Research Report.

ERIC Educational Resources Information Center

Cleary, James

The term "cluster analysis" refers to a set of statistical methods that classify entities with similar profiles of scores on a number of measured dimensions, in order to create empirically based typologies. A 1980 Minnesota House Research Report employed cluster analysis to categorize school districts according to their relative mixtures…

Flexible categorization of relative stimulus strength by the optic tectum

PubMed Central

Mysore, Shreesh P.; Knudsen, Eric I.

2011-01-01

Categorization is the process by which the brain segregates continuously variable stimuli into discrete groups. We report that patterns of neural population activity in the owl optic tectum (OT) categorize stimuli based on their relative strengths into “strongest” versus “other”. The category boundary shifts adaptively to track changes in the absolute strength of the strongest stimulus. This population-wide categorization is mediated by the responses of a small subset of neurons. Our data constitute the first direct demonstration of an explicit categorization of stimuli by a neural network based on relative stimulus strength or salience. The finding of categorization by the population code relaxes constraints on the properties of downstream decoders that might read out the location of the strongest stimulus. These results indicate that the ensemble neural code in the OT could mediate bottom-up stimulus selection for gaze and attention, a form of stimulus categorization in which the category boundary often shifts within hundreds of milliseconds. PMID:21613487

Clustering Categorical Data Using Community Detection Techniques

PubMed Central

2017-01-01

With the advent of the k-modes algorithm, the toolbox for clustering categorical data has an efficient tool that scales linearly in the number of data items. However, random initialization of cluster centers in k-modes makes it hard to reach a good clustering without resorting to many trials. Recently proposed methods for better initialization are deterministic and reduce the clustering cost considerably. A variety of initialization methods differ in how the heuristics chooses the set of initial centers. In this paper, we address the clustering problem for categorical data from the perspective of community detection. Instead of initializing k modes and running several iterations, our scheme, CD-Clustering, builds an unweighted graph and detects highly cohesive groups of nodes using a fast community detection technique. The top-k detected communities by size will define the k modes. Evaluation on ten real categorical datasets shows that our method outperforms the existing initialization methods for k-modes in terms of accuracy, precision, and recall in most of the cases. PMID:29430249

A Novel Artificial Bee Colony Based Clustering Algorithm for Categorical Data

PubMed Central

2015-01-01

Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data. PMID:25993469

A novel artificial bee colony based clustering algorithm for categorical data.

PubMed

Ji, Jinchao; Pang, Wei; Zheng, Yanlin; Wang, Zhe; Ma, Zhiqiang

2015-01-01

Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data.

Same-gender distractors are not so easy to reject: ERP evidence of gender categorization.

PubMed

Rakić, Tamara; Steffens, Melanie C; Wiese, Holger

2018-05-07

Social categorization appears to be an automatic process that occurs during person perception. Understanding social categorization better is important because mere categorization can lead to stereotype activation and, in turn, to discrimination. In the present study we used a novel approach to examine event-related potentials (ERPs) of gender categorization in the "Who said what?" memory paradigm, thus allowing for a more in-depth understanding of the specific mechanisms underlying identity versus categorization processing. After observing video clips showing a "discussion" among female and male targets, participants were shown individual statements, each accompanied by one of the discussants' faces. While we measured ERPs, participants had to decide whether or not a given statement had previously been made by the person with the accompanying face. In same-person trials, statements were paired with the correct person, whereas in the distractor trials, either a same-gender or a different-gender distractor was shown. As expected, participants were able to reject different-gender distractors faster than same-gender distractors, and they were more likely to falsely choose yes for a same-gender than for a different-gender distractor. Both findings indicate gender-based categorization. ERPs, analyzed in a 300- to 400-ms time window at occipito-temporal channels, indicated more negative amplitudes for yes responses both for the same person and for same-gender distractors, relative to different-gender distractors. Overall, these results show gender-based categorization even when the task was to assess the identifying information in a gender-neutral context. These findings are interpreted as showing that gender categorization occurs automatically during person perception, but later than race- or age-based categorization.

The potential of mangrove Avicennia marina and A. Alba from Nguling district, Pasuruan, East Java as an antioxidant

NASA Astrophysics Data System (ADS)

Iranawati, F.; Muhammad, F.; Fajri, H.; Kasitowati, R. D.; Arifin, S.

2018-04-01

Free radicals are highly reactive molecules due to unpaired electron in their outer orbital. Excess of free radicals inside human body as consequences of environmental exposure such cigarette smoke may lead to degenerative diseases such as diabetic, cancer etc. This negative effect can be limited by the utilization of natural antioxidant substances, especially produced from plant. Avicennia alba dan A. marina are mangrove species that widely distributed in Indonesia and are expected potential as antioxidant. The objective of this study is to evaluated Avicennia alba dan A. marina potency as antioxidant performed with DPPD (1,1-diphenyl-β-picryl hydrazyl) method. Leaf and bark of Avicennia alba dan A. marina were collected from Nguling District, Pasuruan, East Java. Results shows that based on 50% inhibition Concentration (IC50), Avicennia alba leaf were categorized had a very high antioxidant potential (IC50 14,85 ppm) whereas the bark were categorized had a weak antioxidant potential IC50 167,17 ppm). For A. marina, the leaf were categorized had a moderate antioxidant (IC50 123,23 ppm) whereas the bark were categorized had a weak antioxidant potential (IC50 198,15 ppm).

[Client centered psychotherapy].

PubMed

Werthmann, H V

1979-01-01

In the discussion concerning which psychotherapeutic methods should come under the auspices of the medical health system in West Germany, the question is raised regarding the client-centered therapy of Carl Rogers. Can it be considered a distinct psychotherapeutic method? A review of the scientific literature dealing with this method shows that it provides neither a theory of mental illness nor a theory of clinical application based on individual cases or specific neurotic disturbances, Therefore it should be categorized as a useful method of communication in the field of psychology and not as a therapeutic method for treating mental illness.

Mapcurves: a quantitative method for comparing categorical maps.

Treesearch

William W. Hargrove; M. Hoffman Forrest; Paul F. Hessburg

2006-01-01

We present Mapcurves, a quantitative goodness-of-fit (GOF) method that unambiguously shows the degree of spatial concordance between two or more categorical maps. Mapcurves graphically and quantitatively evaluate the degree of fit among any number of maps and quantify a GOF for each polygon, as well as the entire map. The Mapcurve method indicates a perfect fit even if...

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

PubMed Central

Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

2015-01-01

A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620

Fragment virtual screening based on Bayesian categorization for discovering novel VEGFR-2 scaffolds.

PubMed

Zhang, Yanmin; Jiao, Yu; Xiong, Xiao; Liu, Haichun; Ran, Ting; Xu, Jinxing; Lu, Shuai; Xu, Anyang; Pan, Jing; Qiao, Xin; Shi, Zhihao; Lu, Tao; Chen, Yadong

2015-11-01

The discovery of novel scaffolds against a specific target has long been one of the most significant but challengeable goals in discovering lead compounds. A scaffold that binds in important regions of the active pocket is more favorable as a starting point because scaffolds generally possess greater optimization possibilities. However, due to the lack of sufficient chemical space diversity of the databases and the ineffectiveness of the screening methods, it still remains a great challenge to discover novel active scaffolds. Since the strengths and weaknesses of both fragment-based drug design and traditional virtual screening (VS), we proposed a fragment VS concept based on Bayesian categorization for the discovery of novel scaffolds. This work investigated the proposal through an application on VEGFR-2 target. Firstly, scaffold and structural diversity of chemical space for 10 compound databases were explicitly evaluated. Simultaneously, a robust Bayesian classification model was constructed for screening not only compound databases but also their corresponding fragment databases. Although analysis of the scaffold diversity demonstrated a very unevenly distribution of scaffolds over molecules, results showed that our Bayesian model behaved better in screening fragments than molecules. Through a literature retrospective research, several generated fragments with relatively high Bayesian scores indeed exhibit VEGFR-2 biological activity, which strongly proved the effectiveness of fragment VS based on Bayesian categorization models. This investigation of Bayesian-based fragment VS can further emphasize the necessity for enrichment of compound databases employed in lead discovery by amplifying the diversity of databases with novel structures.

Ataques de nervios in Puerto Rico: culture-bound syndrome or popular illness?

PubMed

Guarnaccia, P J

1993-04-01

Ataque de nervious is a popular illness category among Puerto Ricans and other Latinos written about in anthropological and psychiatric literature for over thirty years. This paper discusses the issue of categorizing ataque de nervios as a "culture-bound syndrome" using data from the first community-based study of this phenomena using epidemiological methods. The paper summarizes the social and psychological correlates of ataques de nervios and provides a preliminary overview of the situations which provoke ataques and the symptoms people experience. The paper critically examines the use of the "culture-bound syndrome" framework analyzing ataques de nervios and suggests that the term "popular illness" is a more effective label for categorizing this syndrome.

To Sum or Not to Sum: Taxometric Analysis with Ordered Categorical Assessment Items

ERIC Educational Resources Information Center

Walters, Glenn D.; Ruscio, John

2009-01-01

Meehl's taxometric method has been shown to differentiate between categorical and dimensional data, but there are many ways to implement taxometric procedures. When analyzing the ordered categorical data typically provided by assessment instruments, summing items to form input indicators has been a popular practice for more than 20 years. A Monte…

Parametric embedding for class visualization.

PubMed

Iwata, Tomoharu; Saito, Kazumi; Ueda, Naonori; Stromsten, Sean; Griffiths, Thomas L; Tenenbaum, Joshua B

2007-09-01

We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.

Maintaining forest diversity in a changing climate: A geophysical approach

Treesearch

Mark Anderson; Nels Johnson; Scott Bearer

2014-01-01

Forest conservationists need a method to conserve the maximum amount of biological diversity while allowing species and communities to rearrange in response to a continually changing climate. Here, we develop such an approach for northeastern North America. First we characterize and categorize forest blocks based on their geology, landforms, and elevation zones. Next,...

Auditory Processing Disorder and Auditory/Language Interventions: An Evidence-Based Systematic Review

ERIC Educational Resources Information Center

Fey, Marc E.; Richard, Gail J.; Geffner, Donna; Kamhi, Alan G.; Medwetsky, Larry; Paul, Diane; Ross-Swain, Deborah; Wallach, Geraldine P.; Frymark, Tobi; Schooling, Tracy

2011-01-01

Purpose: In this systematic review, the peer-reviewed literature on the efficacy of interventions for school-age children with auditory processing disorder (APD) is critically evaluated. Method: Searches of 28 electronic databases yielded 25 studies for analysis. These studies were categorized by research phase (e.g., exploratory, efficacy) and…

TOXCAST, A TOOL FOR CATEGORIZATION AND PRIORITIZATION OF CHEMICAL HAZARD BASED ON MULTI-DIMENSIONAL INFORMATION DOMAINS

EPA Science Inventory

Across several EPA Program Offices (e.g., OPPTS, OW, OAR), there is a clear need to develop strategies and methods to screen large numbers of chemicals for potential toxicity, and to use the resulting information to prioritize the use of testing resources towards those entities a...

Supporting Learner-Centered ICT Integration: The Influence of Collaborative and Needs-Based Professional Development

ERIC Educational Resources Information Center

MacDonald, Ronald

2009-01-01

A mixed-method study was carried out to investigate how teacher attitude and professional development influence learner-centered Information Communication Technology (ICT) integration. A questionnaire, interviews and observations were used to gather data in a school district in Nova Scotia, Canada. Teacher data were categorized by grade level,…

Bayesian data fusion for spatial prediction of categorical variables in environmental sciences

NASA Astrophysics Data System (ADS)

Gengler, Sarah; Bogaert, Patrick

2014-12-01

First developed to predict continuous variables, Bayesian Maximum Entropy (BME) has become a complete framework in the context of space-time prediction since it has been extended to predict categorical variables and mixed random fields. This method proposes solutions to combine several sources of data whatever the nature of the information. However, the various attempts that were made for adapting the BME methodology to categorical variables and mixed random fields faced some limitations, as a high computational burden. The main objective of this paper is to overcome this limitation by generalizing the Bayesian Data Fusion (BDF) theoretical framework to categorical variables, which is somehow a simplification of the BME method through the convenient conditional independence hypothesis. The BDF methodology for categorical variables is first described and then applied to a practical case study: the estimation of soil drainage classes using a soil map and point observations in the sandy area of Flanders around the city of Mechelen (Belgium). The BDF approach is compared to BME along with more classical approaches, as Indicator CoKringing (ICK) and logistic regression. Estimators are compared using various indicators, namely the Percentage of Correctly Classified locations (PCC) and the Average Highest Probability (AHP). Although BDF methodology for categorical variables is somehow a simplification of BME approach, both methods lead to similar results and have strong advantages compared to ICK and logistic regression.

Metadata from data: identifying holidays from anesthesia data.

PubMed

Starnes, Joseph R; Wanderer, Jonathan P; Ehrenfeld, Jesse M

2015-05-01

The increasingly large databases available to researchers necessitate high-quality metadata that is not always available. We describe a method for generating this metadata independently. Cluster analysis and expectation-maximization were used to separate days into holidays/weekends and regular workdays using anesthesia data from Vanderbilt University Medical Center from 2004 to 2014. This classification was then used to describe differences between the two sets of days over time. We evaluated 3802 days and correctly categorized 3797 based on anesthesia case time (representing an error rate of 0.13%). Use of other metrics for categorization, such as billed anesthesia hours and number of anesthesia cases per day, led to similar results. Analysis of the two categories showed that surgical volume increased more quickly with time for non-holidays than holidays (p < 0.001). We were able to successfully generate metadata from data by distinguishing holidays based on anesthesia data. This data can then be used for economic analysis and scheduling purposes. It is possible that the method can be expanded to similar bimodal and multimodal variables.

Anterior Temporal Lobe Morphometry Predicts Categorization Ability.

PubMed

Garcin, Béatrice; Urbanski, Marika; Thiebaut de Schotten, Michel; Levy, Richard; Volle, Emmanuelle

2018-01-01

Categorization is the mental operation by which the brain classifies objects and events. It is classically assessed using semantic and non-semantic matching or sorting tasks. These tasks show a high variability in performance across healthy controls and the cerebral bases supporting this variability remain unknown. In this study we performed a voxel-based morphometry study to explore the relationships between semantic and shape categorization tasks and brain morphometric differences in 50 controls. We found significant correlation between categorization performance and the volume of the gray matter in the right anterior middle and inferior temporal gyri. Semantic categorization tasks were associated with more rostral temporal regions than shape categorization tasks. A significant relationship was also shown between white matter volume in the right temporal lobe and performance in the semantic tasks. Tractography revealed that this white matter region involved several projection and association fibers, including the arcuate fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, and inferior longitudinal fasciculus. These results suggest that categorization abilities are supported by the anterior portion of the right temporal lobe and its interaction with other areas.

Council for Exceptional Children: Standards for Evidence-Based Practices in Special Education

ERIC Educational Resources Information Center

TEACHING Exceptional Children, 2014

2014-01-01

In this article, the "Council for Exceptional Children (CEC)" presents Standards for Evidence-Based Practices in Special Education. The statement presents an approach for categorizing the evidence base of practices in special education. The quality indicators and the criteria for categorizing the evidence base of special education…

Photonic integrated circuits based on silica and polymer PLC

NASA Astrophysics Data System (ADS)

Izuhara, T.; Fujita, J.; Gerhardt, R.; Sui, B.; Lin, W.; Grek, B.

2013-03-01

Various methods of hybrid integration of photonic circuits are discussed focusing on merits and challenges. Material platforms discussed in this report are mainly polymer and silica. We categorize the hybridization methods using silica and polymer waveguides into two types, chip-to-chip and on-chip integration. General reviews of these hybridization technologies from the past works are reviewed. An example for each method is discussed in details. We also discuss current status of our silica PLC hybrid integration technology.

Category's analysis and operational project capacity method of transformation in design

NASA Astrophysics Data System (ADS)

Obednina, S. V.; Bystrova, T. Y.

2015-10-01

The method of transformation is attracting widespread interest in fields such contemporary design. However, in theory of design little attention has been paid to a categorical status of the term "transformation". This paper presents the conceptual analysis of transformation based on the theory of form employed in the influential essays by Aristotle and Thomas Aquinas. In the present work the transformation as a method of shaping design has been explored as well as potential application of this term in design has been demonstrated.

The Role of Simulation in Microsurgical Training.

PubMed

Evgeniou, Evgenios; Walker, Harriet; Gujral, Sameer

Simulation has been established as an integral part of microsurgical training. The aim of this study was to assess and categorize the various simulation models in relation to the complexity of the microsurgical skill being taught and analyze the assessment methods commonly employed in microsurgical simulation training. Numerous courses have been established using simulation models. These models can be categorized, according to the level of complexity of the skill being taught, into basic, intermediate, and advanced. Microsurgical simulation training should be assessed using validated assessment methods. Assessment methods vary significantly from subjective expert opinions to self-assessment questionnaires and validated global rating scales. The appropriate assessment method should carefully be chosen based on the simulation modality. Simulation models should be validated, and a model with appropriate fidelity should be chosen according to the microsurgical skill being taught. Assessment should move from traditional simple subjective evaluations of trainee performance to validated tools. Future studies should assess the transferability of skills gained during simulation training to the real-life setting. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

The time course of explicit and implicit categorization.

PubMed

Smith, J David; Zakrzewski, Alexandria C; Herberger, Eric R; Boomer, Joseph; Roeder, Jessica L; Ashby, F Gregory; Church, Barbara A

2015-10-01

Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization.

Power of an Adaptive Trial Design for Endovascular Stroke Studies: Simulations Using IMS (Interventional Management of Stroke) III Data.

PubMed

Lansberg, Maarten G; Bhat, Ninad S; Yeatts, Sharon D; Palesch, Yuko Y; Broderick, Joseph P; Albers, Gregory W; Lai, Tze L; Lavori, Philip W

2016-12-01

Adaptive trial designs that allow enrichment of the study population through subgroup selection can increase the chance of a positive trial when there is a differential treatment effect among patient subgroups. The goal of this study is to illustrate the potential benefit of adaptive subgroup selection in endovascular stroke studies. We simulated the performance of a trial design with adaptive subgroup selection and compared it with that of a traditional design. Outcome data were based on 90-day modified Rankin Scale scores, observed in IMS III (Interventional Management of Stroke III), among patients with a vessel occlusion on baseline computed tomographic angiography (n=382). Patients were categorized based on 2 methods: (1) according to location of the arterial occlusive lesion and onset-to-randomization time and (2) according to onset-to-randomization time alone. The power to demonstrate a treatment benefit was based on 10 000 trial simulations for each design. The treatment effect was relatively homogeneous across categories when patients were categorized based on arterial occlusive lesion and time. Consequently, the adaptive design had similar power (47%) compared with the fixed trial design (45%). There was a differential treatment effect when patients were categorized based on time alone, resulting in greater power with the adaptive design (82%) than with the fixed design (57%). These simulations, based on real-world patient data, indicate that adaptive subgroup selection has merit in endovascular stroke trials as it substantially increases power when the treatment effect differs among subgroups in a predicted pattern. © 2016 American Heart Association, Inc.

MULTIVARIATE ANALYSES (CONONICAL CORRELATION AND PARTIAL LEAST SQUARE, PLS) TO MODEL AND ASSESS THE ASSOCIATION OF LANDSCAPE METRICS TO SURFACE WATER CHEMICAL AND BIOLOGICAL PROPERTIES USING SAVANNAH RIVER BASIN DATA.

EPA Science Inventory

Many multivariate methods are used in describing and predicting relation; each has its unique usage of categorical and non-categorical data. In multivariate analysis of variance (MANOVA), many response variables (y's) are related to many independent variables that are categorical...

Functionally engineered nanosized particles in pharmaceutics: improved oral delivery of poorly water-soluble drugs.

PubMed

Ozeki, Tetsuya; Tagami, Tatsuaki

2013-01-01

The development of drug nanoparticles has attracted substantial attention because of their potential to improve the dissolution rate and oral availability of poorly water-soluble drugs. This review summarizes the recent articles that discussed nanoparticle-based oral drug delivery systems. The preparation methods were categorized as top-down and bottom-up methods, which are common methods for preparing drug nanoparticles. In addition, methods of handling drug nanoparticles (e.g., one-step preparation of nanocomposites which are microparticles containing drug nanoparticles) were introduced for the effective preservation of drug nanoparticles. The carrier-based preparation of drug nanoparticles was also introduced as a potentially promising oral drug delivery system.

Potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection

NASA Astrophysics Data System (ADS)

Kawata, Y.; Niki, N.; Ohmatsu, H.; Satake, M.; Kusumoto, M.; Tsuchida, T.; Aokage, K.; Eguchi, K.; Kaneko, M.; Moriyama, N.

2014-03-01

In this work, we investigate a potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection. The elucidation of the subcategorization of a pulmonary nodule type in CT images is an important preliminary step towards developing the nodule managements that are specific to each patient. We categorize lung cancers by analyzing volumetric distributions of CT values within lung cancers via a topic model such as latent Dirichlet allocation. Through applying our scheme to 3D CT images of nonsmall- cell lung cancer (maximum lesion size of 3 cm) , we demonstrate the potential usefulness of the topic model-based categorization of lung cancers as quantitative CT biomarkers.

Comparison of public peak detection algorithms for MALDI mass spectrometry data analysis.

PubMed

Yang, Chao; He, Zengyou; Yu, Weichuan

2009-01-06

In mass spectrometry (MS) based proteomic data analysis, peak detection is an essential step for subsequent analysis. Recently, there has been significant progress in the development of various peak detection algorithms. However, neither a comprehensive survey nor an experimental comparison of these algorithms is yet available. The main objective of this paper is to provide such a survey and to compare the performance of single spectrum based peak detection methods. In general, we can decompose a peak detection procedure into three consequent parts: smoothing, baseline correction and peak finding. We first categorize existing peak detection algorithms according to the techniques used in different phases. Such a categorization reveals the differences and similarities among existing peak detection algorithms. Then, we choose five typical peak detection algorithms to conduct a comprehensive experimental study using both simulation data and real MALDI MS data. The results of comparison show that the continuous wavelet-based algorithm provides the best average performance.

Similar Task Features Shape Judgment and Categorization Processes

ERIC Educational Resources Information Center

Hoffmann, Janina A.; von Helversen, Bettina; Rieskamp, Jörg

2016-01-01

The distinction between similarity-based and rule-based strategies has instigated a large body of research in categorization and judgment. Within both domains, the task characteristics guiding strategy shifts are increasingly well documented. Across domains, past research has observed shifts from rule-based strategies in judgment to…

[Clinical application of "categorization by analogy" in acupuncture for pain syndromes].

PubMed

Chen, Xiaojun

2018-03-12

The"categorization by analogy"is one of the most primitive thinking methods for ancient people to explore the world, which has exerted far-reaching impact on the origin and development of TCM. With examples of Sanjian (LI 3) for neck pain, Chize (LU 5) for low back pain and Chengshan (BL 57) for dysmenorrhea, the clinical application of"categorization by analogy"in acupuncture for pain syndromes was discussed, hoping more acupuncturists will pay attention to the guiding role of"categorization by analogy"in acupuncture clinical treatment.

Categorical and dimensional psychopathology in Dutch and US offspring of parents with bipolar disorder: A preliminary cross-national comparison✩

PubMed Central

Mesman, Esther; Birmaher, Boris B.; Goldstein, Benjamin I.; Goldstein, Tina; Derks, Eske M.; Vleeschouwer, Marloes; Hickey, Mary Beth; Axelson, David; Monk, Kelly; Diler, Rasim; Hafeman, Danella; Sakolsky, Dara J.; Reichart, Catrien G.; Wals, Marjolein; Verhulst, Frank C.; Nolen, Willem A.; Hillegers, Manon H.J.

2017-01-01

Objective Accumulating evidence suggests cross-national differences in adults with bipolar disorder (BD), but also in the susceptibility of their offspring (bipolar offspring). This study aims to explore and clarify cross-national variation in the prevalence of categorical and dimensional psychopathology between bipolar offspring in the US and The Netherlands. Methods We compared levels of psychopathology in offspring of the Pittsburgh Bipolar Offspring Study (n=224) and the Dutch Bipolar Offspring Study (n=136) (age 10–18). Categorical psychopathology was ascertained through interviews using the Schedule for Affective Disorders and Schizophrenia for School Age Children (K-SADS-PL), dimensional psychopathology by parental reports using the Child Behavior Checklist (CBCL). Results Higher rates of categorical psychopathology were observed in the US versus the Dutch samples (66% versus 44%). We found no differences in the overall prevalence of mood disorders, including BD-I or -II, but more comorbidity in mood disorders in US versus Dutch offspring (80% versus 34%). The strongest predictors of categorical psychopathology were maternal BD (OR: 1.72, p<.05), older age of the offspring (OR: 1.19, p<.05), and country of origin (US; OR: 2.17, p<.001). Regarding comorbidity, only country of origin (OR: 7.84, p<.001) was a significant predictor. In general, we found no differences in dimensional psychopathology based on CBCL reports. Limitations Preliminary measure of inter-site reliability. Conclusions We found cross-national differences in prevalence of categorical diagnoses of non-mood disorders in bipolar offspring, but not in mood disorder diagnoses nor in parent-reported dimensional psychopathology. Cross-national variation was only partially explained by between-sample differences. Cultural and methodological explanations for these findings warrant further study. PMID:27423424

Consumer psychology: categorization, inferences, affect, and persuasion.

PubMed

Loken, Barbara

2006-01-01

This chapter reviews research on consumer psychology with emphasis on the topics of categorization, inferences, affect, and persuasion. The chapter reviews theory-based empirical research during the period 1994-2004. Research on categorization includes empirical research on brand categories, goals as organizing frameworks and motivational bases for judgments, and self-based processing. Research on inferences includes numerous types of inferences that are cognitively and/or experienced based. Research on affect includes the effects of mood on processing and cognitive and noncognitive bases for attitudes and intentions. Research on persuasion focuses heavily on the moderating role of elaboration and dual-process models, and includes research on attitude strength responses, advertising responses, and negative versus positive evaluative dimensions.

Beyond Correctness: Development and Validation of Concept-Based Categorical Scoring Rubrics for Diagnostic Purposes

ERIC Educational Resources Information Center

Arieli-Attali, Meirav; Liu, Ying

2016-01-01

Diagnostic assessment approaches intend to provide fine-grained reports of what students know and can do, focusing on their areas of strengths and weaknesses. However, current application of such diagnostic approaches is limited by the scoring method for item responses; important diagnostic information, such as type of errors and strategy use is…

A reappraisal of the uncanny valley: categorical perception or frequency-based sensitization?

PubMed Central

Burleigh, Tyler J.; Schoenherr, Jordan R.

2015-01-01

The uncanny valley (UCV) hypothesis describes a non-linear relationship between perceived human-likeness and affective response. The “uncanny valley” refers to an intermediate level of human-likeness that is associated with strong negative affect. Recent studies have suggested that the uncanny valley might result from the categorical perception of human-like stimuli during identification. When presented with stimuli sharing human-like traits, participants attempt to segment the continuum in “human” and “non-human” categories. Due to the ambiguity of stimuli located at a category boundary, categorization difficulty gives rise to a strong, negative affective response. Importantly, researchers who have studied the UCV in terms of categorical perception have focused on categorization responses rather than affective ratings. In the present study, we examined whether the negative affect associated with the UCV might be explained in terms of an individual's degree of exposure to stimuli. In two experiments, we tested a frequency-based model against a categorical perception model using a category-learning paradigm. We manipulated the frequency of exemplars that were presented to participants from two categories during a training phase. We then examined categorization and affective responses functions, as well as the relationship between categorization and affective responses. Supporting previous findings, categorization responses suggested that participants acquired novel category structures that reflected a category boundary. These category structures appeared to influence affective ratings of eeriness. Crucially, participants' ratings of eeriness were additionally affected by exemplar frequency. Taken together, these findings suggest that the UCV is determined by both categorical properties as well as the frequency of individual exemplars retained in memory. PMID:25653623

Performance of Velicer's Minimum Average Partial Factor Retention Method with Categorical Variables

ERIC Educational Resources Information Center

Garrido, Luis E.; Abad, Francisco J.; Ponsoda, Vicente

2011-01-01

Despite strong evidence supporting the use of Velicer's minimum average partial (MAP) method to establish the dimensionality of continuous variables, little is known about its performance with categorical data. Seeking to fill this void, the current study takes an in-depth look at the performance of the MAP procedure in the presence of…

Assessing the suitability of fractional polynomial methods in health services research: a perspective on the categorization epidemic.

PubMed

Williams, Jennifer Stewart

2011-07-01

To show how fractional polynomial methods can usefully replace the practice of arbitrarily categorizing data in epidemiology and health services research. A health service setting is used to illustrate a structured and transparent way of representing non-linear data without arbitrary grouping. When age is a regressor its effects on an outcome will be interpreted differently depending upon the placing of cutpoints or the use of a polynomial transformation. Although it is common practice, categorization comes at a cost. Information is lost, and accuracy and statistical power reduced, leading to spurious statistical interpretation of the data. The fractional polynomial method is widely supported by statistical software programs, and deserves greater attention and use.

The Time Course of Explicit and Implicit Categorization

PubMed Central

Zakrzewski, Alexandria C.; Herberger, Eric; Boomer, Joseph; Roeder, Jessica; Ashby, F. Gregory; Church, Barbara A.

2015-01-01

Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization. PMID:26025556

Expert system for web based collaborative CAE

NASA Astrophysics Data System (ADS)

Hou, Liang; Lin, Zusheng

2006-11-01

An expert system for web based collaborative CAE was developed based on knowledge engineering, relational database and commercial FEA (Finite element analysis) software. The architecture of the system was illustrated. In this system, the experts' experiences, theories and typical examples and other related knowledge, which will be used in the stage of pre-process in FEA, were categorized into analysis process and object knowledge. Then, the integrated knowledge model based on object-oriented method and rule based method was described. The integrated reasoning process based on CBR (case based reasoning) and rule based reasoning was presented. Finally, the analysis process of this expert system in web based CAE application was illustrated, and an analysis example of a machine tool's column was illustrated to prove the validity of the system.

When Can Categorical Variables Be Treated as Continuous? A Comparison of Robust Continuous and Categorical SEM Estimation Methods under Suboptimal Conditions

ERIC Educational Resources Information Center

Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria

2012-01-01

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

Automated defect spatial signature analysis for semiconductor manufacturing process

DOEpatents

Tobin, Jr., Kenneth W.; Gleason, Shaun S.; Karnowski, Thomas P.; Sari-Sarraf, Hamed

1999-01-01

An apparatus and method for performing automated defect spatial signature alysis on a data set representing defect coordinates and wafer processing information includes categorizing data from the data set into a plurality of high level categories, classifying the categorized data contained in each high level category into user-labeled signature events, and correlating the categorized, classified signature events to a present or incipient anomalous process condition.

Accelerating simulation for the multiple-point statistics algorithm using vector quantization

NASA Astrophysics Data System (ADS)

Zuo, Chen; Pan, Zhibin; Liang, Hao

2018-03-01

Multiple-point statistics (MPS) is a prominent algorithm to simulate categorical variables based on a sequential simulation procedure. Assuming training images (TIs) as prior conceptual models, MPS extracts patterns from TIs using a template and records their occurrences in a database. However, complex patterns increase the size of the database and require considerable time to retrieve the desired elements. In order to speed up simulation and improve simulation quality over state-of-the-art MPS methods, we propose an accelerating simulation for MPS using vector quantization (VQ), called VQ-MPS. First, a variable representation is presented to make categorical variables applicable for vector quantization. Second, we adopt a tree-structured VQ to compress the database so that stationary simulations are realized. Finally, a transformed template and classified VQ are used to address nonstationarity. A two-dimensional (2D) stationary channelized reservoir image is used to validate the proposed VQ-MPS. In comparison with several existing MPS programs, our method exhibits significantly better performance in terms of computational time, pattern reproductions, and spatial uncertainty. Further demonstrations consist of a 2D four facies simulation, two 2D nonstationary channel simulations, and a three-dimensional (3D) rock simulation. The results reveal that our proposed method is also capable of solving multifacies, nonstationarity, and 3D simulations based on 2D TIs.

Categorical perception of facial expressions in individuals with non-clinical social anxiety.

PubMed

Qiu, Fanghui; Han, Mingxiu; Zhai, Yu; Jia, Shiwei

2018-03-01

According to the well-established categorical perception (CP) of facial expressions, we decode complicated expression signals into simplified categories to facilitate expression processing. Expression processing deficits have been widely described in social anxiety (SA), but it remains to be investigated whether CP of expressions are affected by SA. The present study examined whether individuals with SA had an interpretation bias when processing ambiguous expressions and whether the sensitivity of their CP was affected by their SA. Sixty-four participants (high SA, 30; low SA, 34) were selected from 658 undergraduates using the Interaction Anxiousness Scale (IAS). With the CP paradigm, specifically with the analysis method of the logistic function model, we derived the categorical boundaries (reflecting interpretation bias) and slopes (reflecting sensitivity of CP) of both high- and low-SA groups while recognizing angry-fearful, happy-angry, and happy-fearful expression continua. Based on a comparison of the categorical boundaries and slopes between the high- and low-SA groups, the results showed that the categorical boundaries between the two groups were not different for any of the three continua, which means that the SA does not affect the interpretation bias for any of the three continua. The slopes for the high-SA group were flatter than those for the low-SA group for both the angry-fearful and happy-angry continua, indicating that the high-SA group is insensitive to the subtle changes that occur from angry to fearful faces and from happy to angry faces. Since participants were selected from a sample of undergraduates based on their IAS scores, the results cannot be directly generalized to individuals with clinical SA disorder. The study indicates that SA does not affect interpretation biases in the processing of anger, fear, and happiness, but does modulate the sensitivity of individuals' CP when anger appears. High-SA individuals perceive angry expressions in a less categorical manner than the low-SA group, but no such difference was found in the perception of happy or fearful expressions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Supply chain value creation methodology under BSC approach

NASA Astrophysics Data System (ADS)

Golrizgashti, Seyedehfatemeh

2014-06-01

The objective of this paper is proposing a developed balanced scorecard approach to measure supply chain performance with the aim of creating more value in manufacturing and business operations. The most important metrics have been selected based on experts' opinion acquired by in-depth interviews focused on creating more value for stakeholders. Using factor analysis method, a survey research has been used to categorize selected metrics into balanced scorecard perspectives. The result identifies the intensity of correlation between perspectives and cause-and-effect chains among them using statistical method based on a real case study in home appliance manufacturing industries.

Information categorization approach to literary authorship disputes

NASA Astrophysics Data System (ADS)

Yang, Albert C.-C.; Peng, C.-K.; Yien, H.-W.; Goldberger, Ary L.

2003-11-01

Scientific analysis of the linguistic styles of different authors has generated considerable interest. We present a generic approach to measuring the similarity of two symbolic sequences that requires minimal background knowledge about a given human language. Our analysis is based on word rank order-frequency statistics and phylogenetic tree construction. We demonstrate the applicability of this method to historic authorship questions related to the classic Chinese novel “The Dream of the Red Chamber,” to the plays of William Shakespeare, and to the Federalist papers. This method may also provide a simple approach to other large databases based on their information content.

Structuring Clinical Workflows for Diabetes Care

PubMed Central

Lasierra, N.; Oberbichler, S.; Toma, I.; Fensel, A.; Hoerbst, A.

2014-01-01

Summary Background Electronic health records (EHRs) play an important role in the treatment of chronic diseases such as diabetes mellitus. Although the interoperability and selected functionality of EHRs are already addressed by a number of standards and best practices, such as IHE or HL7, the majority of these systems are still monolithic from a user-functionality perspective. The purpose of the OntoHealth project is to foster a functionally flexible, standards-based use of EHRs to support clinical routine task execution by means of workflow patterns and to shift the present EHR usage to a more comprehensive integration concerning complete clinical workflows. Objectives The goal of this paper is, first, to introduce the basic architecture of the proposed OntoHealth project and, second, to present selected functional needs and a functional categorization regarding workflow-based interactions with EHRs in the domain of diabetes. Methods A systematic literature review regarding attributes of workflows in the domain of diabetes was conducted. Eligible references were gathered and analyzed using a qualitative content analysis. Subsequently, a functional workflow categorization was derived from diabetes-specific raw data together with existing general workflow patterns. Results This paper presents the design of the architecture as well as a categorization model which makes it possible to describe the components or building blocks within clinical workflows. The results of our study lead us to identify basic building blocks, named as actions, decisions, and data elements, which allow the composition of clinical workflows within five identified contexts. Conclusions The categorization model allows for a description of the components or building blocks of clinical workflows from a functional view. PMID:25024765

SELF-BLM: Prediction of drug-target interactions via self-training SVM.

PubMed

Keum, Jongsoo; Nam, Hojung

2017-01-01

Predicting drug-target interactions is important for the development of novel drugs and the repositioning of drugs. To predict such interactions, there are a number of methods based on drug and target protein similarity. Although these methods, such as the bipartite local model (BLM), show promise, they often categorize unknown interactions as negative interaction. Therefore, these methods are not ideal for finding potential drug-target interactions that have not yet been validated as positive interactions. Thus, here we propose a method that integrates machine learning techniques, such as self-training support vector machine (SVM) and BLM, to develop a self-training bipartite local model (SELF-BLM) that facilitates the identification of potential interactions. The method first categorizes unlabeled interactions and negative interactions among unknown interactions using a clustering method. Then, using the BLM method and self-training SVM, the unlabeled interactions are self-trained and final local classification models are constructed. When applied to four classes of proteins that include enzymes, G-protein coupled receptors (GPCRs), ion channels, and nuclear receptors, SELF-BLM showed the best performance for predicting not only known interactions but also potential interactions in three protein classes compare to other related studies. The implemented software and supporting data are available at https://github.com/GIST-CSBL/SELF-BLM.

A Review on Human Activity Recognition Using Vision-Based Method.

PubMed

Zhang, Shugang; Wei, Zhiqiang; Nie, Jie; Huang, Lei; Wang, Shuang; Li, Zhen

2017-01-01

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research.

A Review on Human Activity Recognition Using Vision-Based Method

PubMed Central

Nie, Jie

2017-01-01

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research. PMID:29065585

On the Agreement between Manual and Automated Methods for Single-Trial Detection and Estimation of Features from Event-Related Potentials

PubMed Central

Biurrun Manresa, José A.; Arguissain, Federico G.; Medina Redondo, David E.; Mørch, Carsten D.; Andersen, Ole K.

2015-01-01

The agreement between humans and algorithms on whether an event-related potential (ERP) is present or not and the level of variation in the estimated values of its relevant features are largely unknown. Thus, the aim of this study was to determine the categorical and quantitative agreement between manual and automated methods for single-trial detection and estimation of ERP features. To this end, ERPs were elicited in sixteen healthy volunteers using electrical stimulation at graded intensities below and above the nociceptive withdrawal reflex threshold. Presence/absence of an ERP peak (categorical outcome) and its amplitude and latency (quantitative outcome) in each single-trial were evaluated independently by two human observers and two automated algorithms taken from existing literature. Categorical agreement was assessed using percentage positive and negative agreement and Cohen’s κ, whereas quantitative agreement was evaluated using Bland-Altman analysis and the coefficient of variation. Typical values for the categorical agreement between manual and automated methods were derived, as well as reference values for the average and maximum differences that can be expected if one method is used instead of the others. Results showed that the human observers presented the highest categorical and quantitative agreement, and there were significantly large differences between detection and estimation of quantitative features among methods. In conclusion, substantial care should be taken in the selection of the detection/estimation approach, since factors like stimulation intensity and expected number of trials with/without response can play a significant role in the outcome of a study. PMID:26258532

Principle-Based Inferences in Young Children's Categorization: Revisiting the Impact of Function on the Naming of Artifacts.

ERIC Educational Resources Information Center

Nelson, Deborah G. Kemler

1995-01-01

Three studies investigated the influence of principle-based inferences and unprincipled similarity relations on new category learning by three- to six-year-old children. Results indicated that categorization into newly learned categories may activate self-initiated, principle-based reasoning in young children, suggesting that spontaneous…

Velocity-based motion categorization by pigeons.

PubMed

Cook, Robert G; Beale, Kevin; Koban, Angie

2011-04-01

To examine if animals could learn action-like categorizations in a manner similar to noun-based categories, eight pigeons were trained to categorize rates of object motion. Testing 40 different objects in a go/no-go discrimination, pigeons were first trained to discriminate between fast and slow rates of object rotation around their central y-axis. They easily learned this velocity discrimination and transferred it to novel objects and rates. This discrimination also transferred to novel types of motions including the other two axes of rotation and two new translations around the display. Comparable tests with rapid and slow changes in the objects' size, color, and shape failed to support comparable transfer. This difference in discrimination transfer between motion-based and property-based changes suggests the pigeons had learned motion concept rather than one based on change per se. The results provide evidence that pigeons can acquire an understanding of motion-based actions, at least with regard to the property of object velocity. This may be similar to our use of verbs and adverbs to categorize different classes of behavior or motion (e.g., walking, jogging, or running slow vs. fast).

Creative Digital Worksheet Base on Mobile Learning

NASA Astrophysics Data System (ADS)

Wibawa, S. C.; Cholifah, R.; Utami, A. W.; Nurhidayat, A. I.

2018-01-01

The student is required to understand and act in the classroom and it is very important for selecting the media learning to determine the learning outcome. An instructional media is needed to help students achieve the best learning outcome. The objectives of this study are (1) to make Android-based student worksheet, (2) to know the students’ response on Android-based student worksheet in multimedia subject, (3) to determine the student result using Android-based student worksheet. The method used was Research and Development (R&D) using post-test-only in controlled quasi-experimental group design. The subjects of the study were 2 classes, a control class and an experimental class. The results showed (1) Android-based student worksheet was categorized very good as percentage of 85%; (2) the students’ responses was categorized very good as percentage of 86.42%; (3) the experimental class results were better than control class. The average result on cognitive tests on the experimental class was 89.97 and on control class was 78.31; whether the average result on psychomotor test on the experimental class was 89.90 and on the control class was 79.83. In conclusion, student result using Android-based student worksheet was better than those without it.

Estimation of Lithological Classification in Taipei Basin: A Bayesian Maximum Entropy Method

NASA Astrophysics Data System (ADS)

Wu, Meng-Ting; Lin, Yuan-Chien; Yu, Hwa-Lung

2015-04-01

In environmental or other scientific applications, we must have a certain understanding of geological lithological composition. Because of restrictions of real conditions, only limited amount of data can be acquired. To find out the lithological distribution in the study area, many spatial statistical methods used to estimate the lithological composition on unsampled points or grids. This study applied the Bayesian Maximum Entropy (BME method), which is an emerging method of the geological spatiotemporal statistics field. The BME method can identify the spatiotemporal correlation of the data, and combine not only the hard data but the soft data to improve estimation. The data of lithological classification is discrete categorical data. Therefore, this research applied Categorical BME to establish a complete three-dimensional Lithological estimation model. Apply the limited hard data from the cores and the soft data generated from the geological dating data and the virtual wells to estimate the three-dimensional lithological classification in Taipei Basin. Keywords: Categorical Bayesian Maximum Entropy method, Lithological Classification, Hydrogeological Setting

Using Configural Frequency Analysis as a Person-Centered Analytic Approach with Categorical Data

ERIC Educational Resources Information Center

Stemmler, Mark; Heine, Jörg-Henrik

2017-01-01

Configural frequency analysis and log-linear modeling are presented as person-centered analytic approaches for the analysis of categorical or categorized data in multi-way contingency tables. Person-centered developmental psychology, based on the holistic interactionistic perspective of the Stockholm working group around David Magnusson and Lars…

Experience-Based and On-Line Categorization of Objects in Early Infancy

ERIC Educational Resources Information Center

Bornstein, Marc H.; Mash, Clay

2010-01-01

What processes do infants employ in categorizing? Infants might categorize on line as they encounter category-related entities; alternatively, infants might depend on prior experience with entities in formulating categories. These alternatives were tested in forty-four 5-month-olds. Infants who were familiarized in the laboratory with a category…

A Regional Categorization for “New-Type Urbanization” in China

PubMed Central

Fang, Chuanglin; Ma, Haitao; Wang, Jing

2015-01-01

Regional differences in the character of urbanization in China are substantial. The promotion of what has been termed “new-type urbanization” cannot, as a result of these regional differences, be expected to follow a universal approach—rather, such a development must objectively adhere to locational and category-specific principles and adopt differentiated urbanization development models. Regional categorization is often used in geography, but is rarely deployed in research addressing human and social problems relating to urbanization. In March 2014, China published the National New-type Urbanization Plan (2014–2020), which calls for the scientific and reasonable planning of “new-type urbanization,” and appropriate regional categorizations are urgently needed in order to guide this reform. Responding to this challenge, this research engaged in the design of a “dominantly quantitative analysis, qualitatively supplemented” method in order to divide China into 5 main regions and 47 sub-regions in terms of new-type urbanization. The paper discusses the features and key problems of each region. This study introduces a new method for regional categorization, thereby remedying the lack of regional categorization in relation to “new-type urbanization” in China, and ultimately promoting the development of regional categorization in the humanities as a valuable reference for healthy and sustainable Chinese urbanization. PMID:26237405

A Regional Categorization for "New-Type Urbanization" in China.

PubMed

Fang, Chuanglin; Ma, Haitao; Wang, Jing

2015-01-01

Regional differences in the character of urbanization in China are substantial. The promotion of what has been termed "new-type urbanization" cannot, as a result of these regional differences, be expected to follow a universal approach--rather, such a development must objectively adhere to locational and category-specific principles and adopt differentiated urbanization development models. Regional categorization is often used in geography, but is rarely deployed in research addressing human and social problems relating to urbanization. In March 2014, China published the National New-type Urbanization Plan (2014-2020), which calls for the scientific and reasonable planning of "new-type urbanization," and appropriate regional categorizations are urgently needed in order to guide this reform. Responding to this challenge, this research engaged in the design of a "dominantly quantitative analysis, qualitatively supplemented" method in order to divide China into 5 main regions and 47 sub-regions in terms of new-type urbanization. The paper discusses the features and key problems of each region. This study introduces a new method for regional categorization, thereby remedying the lack of regional categorization in relation to "new-type urbanization" in China, and ultimately promoting the development of regional categorization in the humanities as a valuable reference for healthy and sustainable Chinese urbanization.

Taxonomic and ad hoc categorization within the two cerebral hemispheres.

PubMed

Shen, Yeshayahu; Aharoni, Bat-El; Mashal, Nira

2015-01-01

A typicality effect refers to categorization which is performed more quickly or more accurately for typical than for atypical members of a given category. Previous studies reported a typicality effect for category members presented in the left visual field/right hemisphere (RH), suggesting that the RH applies a similarity-based categorization strategy. However, findings regarding the typicality effect within the left hemisphere (LH) are less conclusive. The current study tested the pattern of typicality effects within each hemisphere for both taxonomic and ad hoc categories, using words presented to the left or right visual fields. Experiment 1 tested typical and atypical members of taxonomic categories as well as non-members, and Experiment 2 tested typical and atypical members of ad hoc categories as well as non-members. The results revealed a typicality effect in both hemispheres and in both types of categories. Furthermore, the RH categorized atypical stimuli more accurately than did the LH. Our findings suggest that both hemispheres rely on a similarity-based categorization strategy, but the coarse semantic coding of the RH seems to facilitate the categorization of atypical members.

Image categorization for marketing purposes

NASA Astrophysics Data System (ADS)

Almishari, Mishari I.; Lee, Haengju; Gnanasambandam, Nathan

2011-03-01

Images meant for marketing and promotional purposes (i.e. coupons) represent a basic component in incentivizing customers to visit shopping outlets and purchase discounted commodities. They also help department stores in attracting more customers and potentially, speeding up their cash flow. While coupons are available from various sources - print, web, etc. categorizing these monetary instruments is a benefit to the users. We are interested in an automatic categorizer system that aggregates these coupons from different sources (web, digital coupons, paper coupons, etc) and assigns a type to each of these coupons in an efficient manner. While there are several dimensions to this problem, in this paper we study the problem of accurately categorizing/classifying the coupons. We propose and evaluate four different techniques for categorizing the coupons namely, word-based model, n-gram-based model, externally weighing model, weight decaying model which take advantage of known machine learning algorithms. We evaluate these techniques and they achieve high accuracies in the range of 73.1% to 93.2%. We provide various examples of accuracy optimizations that can be performed and show a progressive increase in categorization accuracy for our test dataset.

Rapid analysis method for the determination of 14C specific activity in irradiated graphite

PubMed Central

Remeikis, Vidmantas; Lagzdina, Elena; Garbaras, Andrius; Gudelis, Arūnas; Garankin, Jevgenij; Juodis, Laurynas; Duškesas, Grigorijus; Lingis, Danielius; Abdulajev, Vladimir; Plukis, Artūras

2018-01-01

14C is one of the limiting radionuclides used in the categorization of radioactive graphite waste; this categorization is crucial in selecting the appropriate graphite treatment/disposal method. We propose a rapid analysis method for 14C specific activity determination in small graphite samples in the 1–100 μg range. The method applies an oxidation procedure to the sample, which extracts 14C from the different carbonaceous matrices in a controlled manner. Because this method enables fast online measurement and 14C specific activity evaluation, it can be especially useful for characterizing 14C in irradiated graphite when dismantling graphite moderator and reflector parts, or when sorting radioactive graphite waste from decommissioned nuclear power plants. The proposed rapid method is based on graphite combustion and the subsequent measurement of both CO2 and 14C, using a commercial elemental analyser and the semiconductor detector, respectively. The method was verified using the liquid scintillation counting (LSC) technique. The uncertainty of this rapid method is within the acceptable range for radioactive waste characterization purposes. The 14C specific activity determination procedure proposed in this study takes approximately ten minutes, comparing favorably to the more complicated and time consuming LSC method. This method can be potentially used to radiologically characterize radioactive waste or used in biomedical applications when dealing with the specific activity determination of 14C in the sample. PMID:29370233

Rapid analysis method for the determination of 14C specific activity in irradiated graphite.

PubMed

Remeikis, Vidmantas; Lagzdina, Elena; Garbaras, Andrius; Gudelis, Arūnas; Garankin, Jevgenij; Plukienė, Rita; Juodis, Laurynas; Duškesas, Grigorijus; Lingis, Danielius; Abdulajev, Vladimir; Plukis, Artūras

2018-01-01

14C is one of the limiting radionuclides used in the categorization of radioactive graphite waste; this categorization is crucial in selecting the appropriate graphite treatment/disposal method. We propose a rapid analysis method for 14C specific activity determination in small graphite samples in the 1-100 μg range. The method applies an oxidation procedure to the sample, which extracts 14C from the different carbonaceous matrices in a controlled manner. Because this method enables fast online measurement and 14C specific activity evaluation, it can be especially useful for characterizing 14C in irradiated graphite when dismantling graphite moderator and reflector parts, or when sorting radioactive graphite waste from decommissioned nuclear power plants. The proposed rapid method is based on graphite combustion and the subsequent measurement of both CO2 and 14C, using a commercial elemental analyser and the semiconductor detector, respectively. The method was verified using the liquid scintillation counting (LSC) technique. The uncertainty of this rapid method is within the acceptable range for radioactive waste characterization purposes. The 14C specific activity determination procedure proposed in this study takes approximately ten minutes, comparing favorably to the more complicated and time consuming LSC method. This method can be potentially used to radiologically characterize radioactive waste or used in biomedical applications when dealing with the specific activity determination of 14C in the sample.

Evaluation of model-based seasonal streamflow and water allocation forecasts for the Elqui Valley, Chile

NASA Astrophysics Data System (ADS)

Delorit, Justin; Cristian Gonzalez Ortuya, Edmundo; Block, Paul

2017-09-01

In many semi-arid regions, multisectoral demands often stress available water supplies. Such is the case in the Elqui River valley of northern Chile, which draws on a limited-capacity reservoir to allocate 25 000 water rights. Delayed infrastructure investment forces water managers to address demand-based allocation strategies, particularly in dry years, which are realized through reductions in the volume associated with each water right. Skillful season-ahead streamflow forecasts have the potential to inform managers with an indication of future conditions to guide reservoir allocations. This work evaluates season-ahead statistical prediction models of October-January (growing season) streamflow at multiple lead times associated with manager and user decision points, and links predictions with a reservoir allocation tool. Skillful results (streamflow forecasts outperform climatology) are produced for short lead times (1 September: ranked probability skill score (RPSS) of 0.31, categorical hit skill score of 61 %). At longer lead times, climatological skill exceeds forecast skill due to fewer observations of precipitation. However, coupling the 1 September statistical forecast model with a sea surface temperature phase and strength statistical model allows for equally skillful categorical streamflow forecasts to be produced for a 1 May lead, triggered for 60 % of years (1950-2015), suggesting forecasts need not be strictly deterministic to be useful for water rights holders. An early (1 May) categorical indication of expected conditions is reinforced with a deterministic forecast (1 September) as more observations of local variables become available. The reservoir allocation model is skillful at the 1 September lead (categorical hit skill score of 53 %); skill improves to 79 % when categorical allocation prediction certainty exceeds 80 %. This result implies that allocation efficiency may improve when forecasts are integrated into reservoir decision frameworks. The methods applied here advance the understanding of the mechanisms and timing responsible for moisture transport to the Elqui Valley and provide a unique application of streamflow forecasting in the prediction of water right allocations.

The learning of aquaponics practice in university

NASA Astrophysics Data System (ADS)

Agustina, T. W.; Rustaman, N. Y.; Riandi; Purwianingsih, W.

2018-05-01

This study aims to obtain a description of the perfomance capabilities of aquaponic technology and the assessment of product and packaging of harvest kale. The aquaponic practice used a STREAM (Science Technology Religion Art Matematics) approach. The method was explanatory sequential mixed method. The research was conducted on one class of Biology Education students in 6th semester. The sample was chosen purposively with 49 students. The study instruments are student worksheet, observation sheet, rubric performance and product assessment, interview sheet and field notes. The indicator of performance rubrics on the manufacture of aquaponic technology consisted of the product rubric, cultivation criteria and packing method of kale. The interview rubric is in the form of student constraints on the manufacture of aquaponics. Based on the results, most students have performance in designing technology that is categorized as enough up to good. Almost all students produce a very good kale harvest. Most of the students produce kale packaging products that are categorized as enough. The implications of this research are the learning of aquaponic with the STREAM approach can equip student’s performance and product capabilities.

Image analysis for skeletal evaluation of carpal bones

NASA Astrophysics Data System (ADS)

Ko, Chien-Chuan; Mao, Chi-Wu; Lin, Chi-Jen; Sun, Yung-Nien

1995-04-01

The assessment of bone age is an important field to the pediatric radiology. It provides very important information for treatment and prediction of skeletal growth in a developing child. So far, various computerized algorithms for automatically assessing the skeletal growth have been reported. Most of these methods made attempt to analyze the phalangeal growth. The most fundamental step in these automatic measurement methods is the image segmentation that extracts bones from soft-tissue and background. These automatic segmentation methods of hand radiographs can roughly be categorized into two main approaches that are edge and region based methods. This paper presents a region-based carpal-bone segmentation approach. It is organized into four stages: contrast enhancement, moment-preserving thresholding, morphological processing, and region-growing labeling.

Attention Deficit/Hyperactivity Disorder in Children and Adolescents with Autism Spectrum Disorder: Symptom or Syndrome?

ERIC Educational Resources Information Center

Sinzig, Judith; Walter, Daniel; Doepfner, Manfred

2009-01-01

Objective: This study aims to evaluate ADHD-like symptoms in children with autism spectrum disorder (ASD) based on single-item analysis, as well as the comparison of two ASD subsamples of children with ADHD (ASD+) and without ADHD (ASD-). Methods: Participants are 83 children with ASD. Dimensional and categorical aspects of ADHD are evaluated…

Indian Education Policies in Five Northwest Region States. Issues & Answers. REL 2009-081

ERIC Educational Resources Information Center

Smiley, Richard; Sather, Susan

2009-01-01

In this comprehensive effort to study Indian education policies, the report categorizes the policies of five Northwest Region states based on 13 key policies identified in the literature and describes the legal methods used to adopt them, such as statutes, regulations, and executive orders. The study found that six of the key policies had been…

Generalizing a Categorization of Students' Interpretations of Linear Kinematics Graphs

ERIC Educational Resources Information Center

Bollen, Laurens; De Cock, Mieke; Zuza, Kristina; Guisasola, Jenaro; van Kampen, Paul

2016-01-01

We have investigated whether and how a categorization of responses to questions on linear distance-time graphs, based on a study of Irish students enrolled in an algebra-based course, could be adopted and adapted to responses from students enrolled in calculus-based physics courses at universities in Flanders, Belgium (KU Leuven) and the Basque…

Robust and Blind 3D Mesh Watermarking in Spatial Domain Based on Faces Categorization and Sorting

NASA Astrophysics Data System (ADS)

Molaei, Amir Masoud; Ebrahimnezhad, Hossein; Sedaaghi, Mohammad Hossein

2016-06-01

In this paper, a 3D watermarking algorithm in spatial domain is presented with blind detection. In the proposed method, a negligible visual distortion is observed in host model. Initially, a preprocessing is applied on the 3D model to make it robust against geometric transformation attacks. Then, a number of triangle faces are determined as mark triangles using a novel systematic approach in which faces are categorized and sorted robustly. In order to enhance the capability of information retrieval by attacks, block watermarks are encoded using Reed-Solomon block error-correcting code before embedding into the mark triangles. Next, the encoded watermarks are embedded in spherical coordinates. The proposed method is robust against additive noise, mesh smoothing and quantization attacks. Also, it is stout next to geometric transformation, vertices and faces reordering attacks. Moreover, the proposed algorithm is designed so that it is robust against the cropping attack. Simulation results confirm that the watermarked models confront very low distortion if the control parameters are selected properly. Comparison with other methods demonstrates that the proposed method has good performance against the mesh smoothing attacks.

Wearable accelerometry-based technology capable of assessing functional activities in neurological populations in community settings: a systematic review

PubMed Central

2014-01-01

Background Integrating rehabilitation services through wearable systems has the potential to accurately assess the type, intensity, duration, and quality of movement necessary for procuring key outcome measures. Objectives This review aims to explore wearable accelerometry-based technology (ABT) capable of assessing mobility-related functional activities intended for rehabilitation purposes in community settings for neurological populations. In this review, we focus on the accuracy of ABT-based methods, types of outcome measures, and the implementation of ABT in non-clinical settings for rehabilitation purposes. Data sources Cochrane, PubMed, Web of Knowledge, EMBASE, and IEEE Xplore. The search strategy covered three main areas, namely wearable technology, rehabilitation, and setting. Study selection Potentially relevant studies were categorized as systems either evaluating methods or outcome parameters. Methods Methodological qualities of studies were assessed by two customized checklists, depending on their categorization and rated independently by three blinded reviewers. Results Twelve studies involving ABT met the eligibility criteria, of which three studies were identified as having implemented ABT for rehabilitation purposes in non-clinical settings. From the twelve studies, seven studies achieved high methodological quality scores. These studies were not only capable of assessing the type, quantity, and quality measures of functional activities, but could also distinguish healthy from non-healthy subjects and/or address disease severity levels. Conclusion While many studies support ABT’s potential for telerehabilitation, few actually utilized it to assess mobility-related functional activities outside laboratory settings. To generate more appropriate outcome measures, there is a clear need to translate research findings and novel methods into practice. PMID:24625308

Computer Aided Ballistic Orbit Classification Around Small Bodies

NASA Astrophysics Data System (ADS)

Villac, Benjamin F.; Anderson, Rodney L.; Pini, Alex J.

2016-09-01

Orbital dynamics around small bodies are as varied as the shapes and dynamical states of these bodies. While various classes of orbits have been analyzed in detail, the global overview of relevant ballistic orbits at particular bodies is not easily computed or organized. Yet, correctly categorizing these orbits will ease their future use in the overall trajectory design process. This paper overviews methods that have been used to organize orbits, focusing on periodic orbits in particular, and introduces new methods based on clustering approaches.

Categorization of the trophic status of a hydroelectric power plant reservoir in the Brazilian Amazon by statistical analyses and fuzzy approaches.

PubMed

da Costa Lobato, Tarcísio; Hauser-Davis, Rachel Ann; de Oliveira, Terezinha Ferreira; Maciel, Marinalva Cardoso; Tavares, Maria Regina Madruga; da Silveira, Antônio Morais; Saraiva, Augusto Cesar Fonseca

2015-02-15

The Amazon area has been increasingly suffering from anthropogenic impacts, especially due to the construction of hydroelectric power plant reservoirs. The analysis and categorization of the trophic status of these reservoirs are of interest to indicate man-made changes in the environment. In this context, the present study aimed to categorize the trophic status of a hydroelectric power plant reservoir located in the Brazilian Amazon by constructing a novel Water Quality Index (WQI) and Trophic State Index (TSI) for the reservoir using major ion concentrations and physico-chemical water parameters determined in the area and taking into account the sampling locations and the local hydrological regimes. After applying statistical analyses (factor analysis and cluster analysis) and establishing a rule base of a fuzzy system to these indicators, the results obtained by the proposed method were then compared to the generally applied Carlson and a modified Lamparelli trophic state index (TSI), specific for trophic regions. The categorization of the trophic status by the proposed fuzzy method was shown to be more reliable, since it takes into account the specificities of the study area, while the Carlson and Lamparelli TSI do not, and, thus, tend to over or underestimate the trophic status of these ecosystems. The statistical techniques proposed and applied in the present study, are, therefore, relevant in cases of environmental management and policy decision-making processes, aiding in the identification of the ecological status of water bodies. With this, it is possible to identify which factors should be further investigated and/or adjusted in order to attempt the recovery of degraded water bodies. Copyright © 2014 Elsevier B.V. All rights reserved.

Categorizing entities by common role.

PubMed

Goldwater, Micah B; Markman, Arthur B

2011-04-01

Many categories group together entities that play a common role across situations. For example, guest and host refer to complementary roles in visiting situations and, thus, are role-governed categories (A. B. Markman & Stilwell, Journal of Experiment & Theoretical Artificial Intelligence, 13, 329-358, 2001). However, categorizing an entity by role is one of many possible classification strategies. This article examines factors that promote role-governed categorization over thematic-relation-based categorization (Lin & Murphy, Journal of Experimental Psychology: General, 130, 3-28, 2001). In Experiments 1a and 1b, we demonstrate that the use of novel category labels facilitates role-governed categorization. In Experiments 2a and 2b, we demonstrate that analogical comparison facilitates role-governed categorization. In Experiments 1b and 2b, we show that these facilitatory factors induce a general sensitivity to role information, as opposed to only promoting role-governed categorization on an item-by-item basis.

A Categorization Model for Educational Values of the History of Mathematics: An Empirical Study

ERIC Educational Resources Information Center

Wang, Xiao-qin; Qi, Chun-yan; Wang, Ke

2017-01-01

There is not a clear consensus on the categorization framework of the educational values of the history of mathematics. By analyzing 20 Chinese teaching cases on integrating the history of mathematics into mathematics teaching based on the relevant literature, this study examined a new categorization framework of the educational values of the…

A Population-Based Survival Assessment of Categorizing Level III and IV Rural Hospitals as Trauma Centers

ERIC Educational Resources Information Center

Arthur, Melanie; Newgard, Craig D.; Mullins, Richard J.; Diggs, Brian S.; Stone, Judith V.; Adams, Annette L.; Hedges, Jerris R.

2009-01-01

Context: Patients injured in rural areas are hypothesized to have improved outcomes if statewide trauma systems categorize rural hospitals as Level III and IV trauma centers, though evidence to support this belief is sparse. Purpose: To determine if there is improved survival among injured patients hospitalized in states that categorize rural…

The role of edge-based and surface-based information in natural scene categorization: Evidence from behavior and event-related potentials.

PubMed

Fu, Qiufang; Liu, Yong-Jin; Dienes, Zoltan; Wu, Jianhui; Chen, Wenfeng; Fu, Xiaolan

2016-07-01

A fundamental question in vision research is whether visual recognition is determined by edge-based information (e.g., edge, line, and conjunction) or surface-based information (e.g., color, brightness, and texture). To investigate this question, we manipulated the stimulus onset asynchrony (SOA) between the scene and the mask in a backward masking task of natural scene categorization. The behavioral results showed that correct classification was higher for line-drawings than for color photographs when the SOA was 13ms, but lower when the SOA was longer. The ERP results revealed that most latencies of early components were shorter for the line-drawings than for the color photographs, and the latencies gradually increased with the SOA for the color photographs but not for the line-drawings. The results provide new evidence that edge-based information is the primary determinant of natural scene categorization, receiving priority processing; by contrast, surface information takes longer to facilitate natural scene categorization. Copyright © 2016 Elsevier Inc. All rights reserved.

A nearest neighbor approach for automated transporter prediction and categorization from protein sequences.

PubMed

Li, Haiquan; Dai, Xinbin; Zhao, Xuechun

2008-05-01

Membrane transport proteins play a crucial role in the import and export of ions, small molecules or macromolecules across biological membranes. Currently, there are a limited number of published computational tools which enable the systematic discovery and categorization of transporters prior to costly experimental validation. To approach this problem, we utilized a nearest neighbor method which seamlessly integrates homologous search and topological analysis into a machine-learning framework. Our approach satisfactorily distinguished 484 transporter families in the Transporter Classification Database, a curated and representative database for transporters. A five-fold cross-validation on the database achieved a positive classification rate of 72.3% on average. Furthermore, this method successfully detected transporters in seven model and four non-model organisms, ranging from archaean to mammalian species. A preliminary literature-based validation has cross-validated 65.8% of our predictions on the 11 organisms, including 55.9% of our predictions overlapping with 83.6% of the predicted transporters in TransportDB.

Interpolation of Regional Groundwater Quality Parameters With Categorical and Real-Valued Secondary Information in the State of Baden-Württemberg, Germany

NASA Astrophysics Data System (ADS)

Haslauer, C. P.; Allmendinger, M.; Gnann, S.; Heisserer, T.; Bárdossy, A.

2017-12-01

The basic problem of geostatistics is to estimate the primary variable (e.g. groundwater quality, nitrate) at an un-sampled location based on point measurements at locations in the vicinity. Typically, models are being used that describe the spatial dependence based on the geometry of the observation network. This presentation demonstrates methods that take the following properties additionally into account: the statistical distribution of the measurements, a different degree of dependence in different quantiles, censored measurements, the composition of categorical additional information in the neighbourhood (exhaustive secondary information), and the spatial dependence of a dependent secondary variable, possibly measured with a different observation network (non-exhaustive secondary data). Two modelling approaches are demonstrated individually and combined: The non-stationarity in the marginal distribution is accounted for by locally mixed distribution functions that depend on the composition of the categorical variable in the neighbourhood of each interpolation location. This methodology is currently being implemented for operational use at the environmental state agency of Baden-Württemberg. An alternative to co-Kriging in copula space with an arbitrary number of secondary parameters is presented: The method performs better than traditional techniques if the primary variable is undersampled and does not produce erroneous negative estimates. Even more, the quality of the uncertainty estimates is much improved. The worth of the secondary information is thoroughly evaluated. The improved geostatistical hydrogeological models are being analyzed using measurements of a large observation network ( 2500 measurement locations) in the state of Baden-Württemberg ( 36.000 km2). Typical groundwater quality parameters such as nitrate, chloride, barium, antrazine, and desethylatrazine are being assessed, cross-validated, and compared with traditional geostatistical methods. The secondary information of land use is available on a 30m x 30m raster. We show that the presented methods are not only better estimators (e.g. in the sense of an average quadratic error), but exhibit a much more realistic structure of the uncertainty and hence are improvements compared to existing methods.

Bosniak classification system: a prospective comparison of CT, contrast-enhanced US, and MR for categorizing complex renal cystic masses.

PubMed

Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens; Hørlyck, Arne; Osther, Palle Jörn Sloth

2016-11-01

Background The Bosniak classification was originally based on computed tomographic (CT) findings. Magnetic resonance (MR) and contrast-enhanced ultrasonography (CEUS) imaging may demonstrate findings that are not depicted at CT, and there may not always be a clear correlation between the findings at MR and CEUS imaging and those at CT. Purpose To compare diagnostic accuracy of MR, CEUS, and CT when categorizing complex renal cystic masses according to the Bosniak classification. Material and Methods From February 2011 to June 2012, 46 complex renal cysts were prospectively evaluated by three readers. Each mass was categorized according to the Bosniak classification and CT was chosen as gold standard. Kappa was calculated for diagnostic accuracy and data was compared with pathological results. Results CT images found 27 BII, six BIIF, seven BIII, and six BIV. Forty-three cysts could be characterized by CEUS, 79% were in agreement with CT (κ = 0.86). Five BII lesions were upgraded to BIIF and four lesions were categorized lower with CEUS. Forty-one lesions were examined with MR; 78% were in agreement with CT (κ = 0.91). Three BII lesions were upgraded to BIIF and six lesions were categorized one category lower. Pathologic correlation in six lesions revealed four malignant and two benign lesions. Conclusion CEUS and MR both up- and downgraded renal cysts compared to CT, and until these non-radiation modalities have been refined and adjusted, CT should remain the gold standard of the Bosniak classification.

Expert and novice categorization of introductory physics problems

NASA Astrophysics Data System (ADS)

Wolf, Steven Frederick

Since it was first published 30 years ago, Chi et al.'s seminal paper on expert and novice categorization of introductory problems led to a plethora of follow-up studies within and outside of the area of physics [Chi et al. Cognitive Science 5, 121 -- 152 (1981)]. These studies frequently encompass "card-sorting" exercises whereby the participants group problems. The study firmly established the paradigm that novices categorize physics problems by "surface features" (e.g. "incline," "pendulum," "projectile motion,"... ), while experts use "deep structure" (e.g. "energy conservation," "Newton 2,"... ). While this technique certainly allows insights into problem solving approaches, simple descriptive statistics more often than not fail to find significant differences between experts and novices. In most experiments, the clean-cut outcome of the original study cannot be reproduced. Given the widespread implications of the original study, the frequent failure to reproduce its findings warrants a closer look. We developed a less subjective statistical analysis method for the card sorting outcome and studied how the "successful" outcome of the experiment depends on the choice of the original card set. Thus, in a first step, we are moving beyond descriptive statistics, and develop a novel microscopic approach that takes into account the individual identity of the cards and uses graph theory and models to visualize, analyze, and interpret problem categorization experiments. These graphs are compared macroscopically, using standard graph theoretic statistics, and microscopically, using a distance metric that we have developed. This macroscopic sorting behavior is described using our Cognitive Categorization Model. The microscopic comparison allows us to visualize our sorters using Principal Components Analysis and compare the expert sorters to the novice sorters as a group. In the second step, we ask the question: Which properties of problems are most important in problem sets that discriminate experts from novices in a measurable way? We are describing a method to characterize problems along several dimensions, and then study the effectiveness of differently composed problem sets in differentiating experts from novices, using our analysis method. Both components of our study are based on an extensive experiment using a large problem set, which known physics experts and novices categorized according to the original experimental protocol. Both the size of the card set and the size of the sorter pool were larger than in comparable experiments. Based on our analysis method, we find that most of the variation in sorting outcome is not due to the sorter being an expert versus a novice, but rather due to an independent characteristic that we named "stacker" versus "spreader." The fact that the expert-novice distinction only accounts for a smaller amount of the variation may partly explain the frequent null-results when conducting these experiments. In order to study how the outcome depends on the original problem set, our problem set needed to be large so that we could determine how well experts and novices could be discriminated by considering both small subsets using a Monte Carlo approach and larger subsets using Simulated Annealing. This computationally intense study relied on our objective analysis method, as the large combinatorics did not allow for manual analysis of the outcomes from the subsets. We found that the number of questions required to accurately classify experts and novices could be surprisingly small so long as the problem set was carefully crafted to be composed of problems with particular pedagogical and contextual features. In order to discriminate experts from novices in a categorization task, it is important that the problem sets carefully consider three problem properties: The chapters that problems are in (the problems need to be from a wide spectrum of chapters to allow for the original "deep structure" categorization), the processes required to solve the problems (the problems must required different solving strategies), and the difficulty of the problems (the problems must be "easy"). In other words, for the experiment to be "successful," the card set needs to be carefully "rigged" across three property dimensions.

View subspaces for indexing and retrieval of 3D models

NASA Astrophysics Data System (ADS)

Dutagaci, Helin; Godil, Afzal; Sankur, Bülent; Yemez, Yücel

2010-02-01

View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithms.

Open-access programs for injury categorization using ICD-9 or ICD-10.

PubMed

Clark, David E; Black, Adam W; Skavdahl, David H; Hallagan, Lee D

2018-04-09

The article introduces Programs for Injury Categorization, using the International Classification of Diseases (ICD) and R statistical software (ICDPIC-R). Starting with ICD-8, methods have been described to map injury diagnosis codes to severity scores, especially the Abbreviated Injury Scale (AIS) and Injury Severity Score (ISS). ICDPIC was originally developed for this purpose using Stata, and ICDPIC-R is an open-access update that accepts both ICD-9 and ICD-10 codes. Data were obtained from the National Trauma Data Bank (NTDB), Admission Year 2015. ICDPIC-R derives CDC injury mechanism categories and an approximate ISS ("RISS") from either ICD-9 or ICD-10 codes. For ICD-9-coded cases, RISS is derived similar to the Stata package (with some improvements reflecting user feedback). For ICD-10-coded cases, RISS may be calculated in several ways: The "GEM" methods convert ICD-10 to ICD-9 (using General Equivalence Mapping tables from CMS) and then calculate ISS with options similar to the Stata package; a "ROCmax" method calculates RISS directly from ICD-10 codes, based on diagnosis-specific mortality in the NTDB, maximizing the C-statistic for predicting NTDB mortality while attempting to minimize the difference between RISS and ISS submitted by NTDB registrars (ISSAIS). Findings were validated using data from the National Inpatient Survey (NIS, 2015). NTDB contained 917,865 cases, of which 86,878 had valid ICD-10 injury codes. For a random 100,000 ICD-9-coded cases in NTDB, RISS using the GEM methods was nearly identical to ISS calculated by the Stata version, which has been previously validated. For ICD-10-coded cases in NTDB, categorized ISS using any version of RISS was similar to ISSAIS; for both NTDB and NIS cases, increasing ISS was associated with increasing mortality. Prediction of NTDB mortality was associated with C-statistics of 0.81 for ISSAIS, 0.75 for RISS using the GEM methods, and 0.85 for RISS using the ROCmax method; prediction of NIS mortality was associated with C-statistics of 0.75-0.76 for RISS using the GEM methods, and 0.78 for RISS using the ROCmax method. Instructions are provided for accessing ICDPIC-R at no cost. The ideal methods of injury categorization and injury severity scoring involve trained personnel with access to injured persons or their medical records. ICDPIC-R may be a useful substitute when this ideal cannot be obtained.

Detecting and Categorizing Fleeting Emotions in Faces

PubMed Central

Sweeny, Timothy D.; Suzuki, Satoru; Grabowecky, Marcia; Paller, Ken A.

2013-01-01

Expressions of emotion are often brief, providing only fleeting images from which to base important social judgments. We sought to characterize the sensitivity and mechanisms of emotion detection and expression categorization when exposure to faces is very brief, and to determine whether these processes dissociate. Observers viewed 2 backward-masked facial expressions in quick succession, 1 neutral and the other emotional (happy, fearful, or angry), in a 2-interval forced-choice task. On each trial, observers attempted to detect the emotional expression (emotion detection) and to classify the expression (expression categorization). Above-chance emotion detection was possible with extremely brief exposures of 10 ms and was most accurate for happy expressions. We compared categorization among expressions using a d′ analysis, and found that categorization was usually above chance for angry versus happy and fearful versus happy, but consistently poor for fearful versus angry expressions. Fearful versus angry categorization was poor even when only negative emotions (fearful, angry, or disgusted) were used, suggesting that this categorization is poor independent of decision context. Inverting faces impaired angry versus happy categorization, but not emotion detection, suggesting that information from facial features is used differently for emotion detection and expression categorizations. Emotion detection often occurred without expression categorization, and expression categorization sometimes occurred without emotion detection. These results are consistent with the notion that emotion detection and expression categorization involve separate mechanisms. PMID:22866885

Concurrent and convergent validity of the mobility- and multidimensional-hierarchical disability categorization models with physical performance in community older adults.

PubMed

Hu, Ming-Hsia; Yeh, Chih-Jun; Chen, Tou-Rong; Wang, Ching-Yi

2014-01-01

A valid, time-efficient and easy-to-use instrument is important for busy clinical settings, large scale surveys, or community screening use. The purpose of this study was to validate the mobility hierarchical disability categorization model (an abbreviated model) by investigating its concurrent validity with the multidimensional hierarchical disability categorization model (a comprehensive model) and triangulating both models with physical performance measures in older adults. 604 community-dwelling older adults of at least 60 years in age volunteered to participate. Self-reported function on mobility, instrumental activities of daily living (IADL) and activities of daily living (ADL) domains were recorded and then the disability status determined based on both the multidimensional hierarchical categorization model and the mobility hierarchical categorization model. The physical performance measures, consisting of grip strength and usual and fastest gait speeds (UGS, FGS), were collected on the same day. Both categorization models showed high correlation (γs = 0.92, p < 0.001) and agreement (kappa = 0.61, p < 0.0001). Physical performance measures demonstrated significant different group means among the disability subgroups based on both categorization models. The results of multiple regression analysis indicated that both models individually explain similar amount of variance on all physical performances, with adjustments for age, sex, and number of comorbidities. Our results found that the mobility hierarchical disability categorization model is a valid and time efficient tool for large survey or screening use.

Task switching in rhesus macaques (Macaca mulatta) and tufted capuchin monkeys (Cebus apella) during computerized categorization tasks.

PubMed

Smith, Travis R; Beran, Michael J

2018-05-31

The present experiments extended to monkeys a previously used abstract categorization procedure (Castro & Wasserman, 2016) where pigeons had categorized arrays of clipart icons based upon two task rules: the number of clipart objects in the array or the variability of objects in the array. Experiment 1 replicated Castro and Wasserman by using capuchin monkeys and rhesus monkeys and reported that monkeys' performances were similar to pigeons' in terms of acquisition, pattern of errors, and the absence of switch costs. Furthermore, monkeys' insensitivity to the added irrelevant information suggested that an associative (rather than rule-based) categorization mechanism was dominant. Experiment 2 was conducted to include categorization cue reversals to determine (a) whether the monkeys would quickly adapt to the reversals and inhibit interference from a prereversal task rule (consistent with a rule-based mechanism) and (b) whether the latency to make a response prior to a correct or incorrect outcome was informative about the presence of a cognitive mechanism. The cue reassignment produced profound and long-lasting performance deficits, and a long reacquisition phase suggested the involvement of associative learning processes; however, monkeys also displayed longer latencies to choose prior to correct responses on challenging trials, suggesting the involvement of nonassociative processes. Together these performances suggest a mix of associative and cognitive-control processes governing monkey categorization judgments. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A note on power and sample size calculations for the Kruskal-Wallis test for ordered categorical data.

PubMed

Fan, Chunpeng; Zhang, Donghui

2012-01-01

Although the Kruskal-Wallis test has been widely used to analyze ordered categorical data, power and sample size methods for this test have been investigated to a much lesser extent when the underlying multinomial distributions are unknown. This article generalizes the power and sample size procedures proposed by Fan et al. ( 2011 ) for continuous data to ordered categorical data, when estimates from a pilot study are used in the place of knowledge of the true underlying distribution. Simulations show that the proposed power and sample size formulas perform well. A myelin oligodendrocyte glycoprotein (MOG) induced experimental autoimmunce encephalomyelitis (EAE) mouse study is used to demonstrate the application of the methods.

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

NASA Astrophysics Data System (ADS)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

Language and thought in Bilinguals: The Case of Grammatical Number and Nonverbal Classification Preferences

ERIC Educational Resources Information Center

Athanasopoulos, Panos; Kasai, Chise

2008-01-01

Recent research shows that speakers of languages with obligatory plural marking (English) preferentially categorize objects based on common shape, whereas speakers of nonplural-marking classifier languages (Yucatec and Japanese) preferentially categorize objects based on common material. The current study extends that investigation to the domain…

Appraisal and standardization of curvilinear velocity (VCL) cut-off values for CASA analysis of Japanese quail (Coturnix japonica) sperm.

PubMed

Farooq, U; Malecki, I A; Mahmood, M; Martin, G B

2017-06-01

One of the basic steps in objective analysis of sperm motility is the subdivision of a motile sperm population into slow, medium and rapid categories based on their velocity. However, for CASA analysis of quail sperm, the velocity values for categorization of slow, medium and rapid sperm have not yet been standardized. To identify the cut-off values of "velocity curvilinear" (VCL) for quail sperm categorization, we captured and analysed 22,300 tracks of quail sperm using SCA ® -CASA. The median and mean VCL values were 85 and 97 μm/s. To define the VCL cut-off values, we used two methods. In the first, we identified the upper (rapid sperm) and lower (slow sperm) cut-off values using: (i) median VCL ± 25% or ± 50% or ± 75% of median VCL value; (ii) first and third quartile values of VCL data (i.e. 25% cut-off setting); and (iii) 33% and 66% of VCL data. Among these settings, sperm categories and their corresponding motility characteristics recorded using the "25%" setting (i.e. slow ≤36 ≤ medium ≤154 ≤ rapid) were found the most realistic and coherent with male ranking by fertility. In the second method, we calculated heteroscedasticity in the total VCL data using PCA and the two-step clustering method. With this approach, the mean of the high and low clusters was 165 and 51 μm/s, respectively. Together, the mean from two methods suggested that, for SCA ® -CASA categorization of quail sperm, sperm should be classed as "rapid" at VCL ≥160 μm/s and "slow" at VCL ≤45 μm/s. © 2017 Blackwell Verlag GmbH.

Rapid methods for the detection of foodborne bacterial pathogens: principles, applications, advantages and limitations

PubMed Central

Law, Jodi Woan-Fei; Ab Mutalib, Nurul-Syakima; Chan, Kok-Gan; Lee, Learn-Han

2015-01-01

The incidence of foodborne diseases has increased over the years and resulted in major public health problem globally. Foodborne pathogens can be found in various foods and it is important to detect foodborne pathogens to provide safe food supply and to prevent foodborne diseases. The conventional methods used to detect foodborne pathogen are time consuming and laborious. Hence, a variety of methods have been developed for rapid detection of foodborne pathogens as it is required in many food analyses. Rapid detection methods can be categorized into nucleic acid-based, biosensor-based and immunological-based methods. This review emphasizes on the principles and application of recent rapid methods for the detection of foodborne bacterial pathogens. Detection methods included are simple polymerase chain reaction (PCR), multiplex PCR, real-time PCR, nucleic acid sequence-based amplification (NASBA), loop-mediated isothermal amplification (LAMP) and oligonucleotide DNA microarray which classified as nucleic acid-based methods; optical, electrochemical and mass-based biosensors which classified as biosensor-based methods; enzyme-linked immunosorbent assay (ELISA) and lateral flow immunoassay which classified as immunological-based methods. In general, rapid detection methods are generally time-efficient, sensitive, specific and labor-saving. The developments of rapid detection methods are vital in prevention and treatment of foodborne diseases. PMID:25628612

Consensus categorization of cheese based on water activity and pH-A rational approach to systemizing cheese diversity.

PubMed

Trmčić, A; Ralyea, R; Meunier-Goddik, L; Donnelly, C; Glass, K; D'Amico, D; Meredith, E; Kehler, M; Tranchina, N; McCue, C; Wiedmann, M

2017-01-01

Development of science-based interventions in raw milk cheese production is challenging due to the large diversity of production procedures and final products. Without an agreed upon categorization scheme, science-based food safety evaluations and validation of preventive controls would have to be completed separately on each individual cheese product, which is not feasible considering the large diversity of products and the typically small scale of production. Thus, a need exists to systematically group raw milk cheeses into logically agreed upon categories to be used for food safety evaluations. This paper proposes and outlines one such categorization scheme that provides for 30 general categories of cheese. As a base for this systematization and categorization of raw milk cheese, we used Table B of the US Food and Drug Administration's 2013 Food Code, which represents the interaction of pH and water activity for control of vegetative cells and spores in non-heat-treated food. Building on this table, we defined a set of more granular pH and water activity categories to better represent the pH and water activity range of different raw milk cheeses. The resulting categorization scheme was effectively validated using pH and water activity values determined for 273 different cheese samples collected in the marketplace throughout New York State, indicating the distribution of commercially available cheeses among the categories proposed here. This consensus categorization of cheese provides a foundation for a feasible approach to developing science-based solutions to assure compliance of the cheese processors with food safety regulations, such as those required by the US Food Safety Modernization Act. The key purpose of the cheese categorization proposed here is to facilitate product assessment for food safety risks and provide scientifically validated guidance on effective interventions for general cheese categories. Once preventive controls for a given category have been defined, these categories would represent safe havens for cheesemakers, which would allow cheesemakers to safely and legally produce raw milk cheeses that meet appropriate science-based safety requirements (e.g., risk to human health equivalent to pasteurized milk cheeses). Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Different brain activations between own- and other-race face categorization: an fMRI study using group independent component analysis

NASA Astrophysics Data System (ADS)

Wei, Wenjuan; Liu, Jiangang; Dai, Ruwei; Feng, Lu; Li, Ling; Tian, Jie

2014-03-01

Previous behavioral research has proved that individuals process own- and other-race faces differently. One well-known effect is the other-race effect (ORE), which indicates that individuals categorize other-race faces more accurately and faster than own-race faces. The existed functional magnetic resonance imaging (fMRI) studies of the other-race effect mainly focused on the racial prejudice and the socio-affective differences towards own- and other-race face. In the present fMRI study, we adopted a race-categorization task to determine the activation level differences between categorizing own- and other-race faces. Thirty one Chinese participants who live in China with Chinese as the majority and who had no direct contact with Caucasian individual were recruited in the present study. We used the group independent component analysis (ICA), which is a method of blind source signal separation that has proven to be promising for analysis of fMRI data. We separated the entail data into 56 components which is estimated based on one subject using the Minimal Description Length (MDL) criteria. The components sorted based on the multiple linear regression temporal sorting criteria, and the fit regression parameters were used in performing statistical test to evaluate the task-relatedness of the components. The one way anova was performed to test the significance of the component time course in different conditions. Our result showed that the areas, which coordinates is similar to the right FFA coordinates that previous studies reported, were greater activated for own-race faces than other-race faces, while the precuneus showed greater activation for other-race faces than own-race faces.

Effects of gross motor function and manual function levels on performance-based ADL motor skills of children with spastic cerebral palsy.

PubMed

Park, Myoung-Ok

2017-02-01

[Purpose] The purpose of this study was to determine effects of Gross Motor Function Classification System and Manual Ability Classification System levels on performance-based motor skills of children with spastic cerebral palsy. [Subjects and Methods] Twenty-three children with cerebral palsy were included. The Assessment of Motor and Process Skills was used to evaluate performance-based motor skills in daily life. Gross motor function was assessed using Gross Motor Function Classification Systems, and manual function was measured using the Manual Ability Classification System. [Results] Motor skills in daily activities were significantly different on Gross Motor Function Classification System level and Manual Ability Classification System level. According to the results of multiple regression analysis, children categorized as Gross Motor Function Classification System level III scored lower in terms of performance based motor skills than Gross Motor Function Classification System level I children. Also, when analyzed with respect to Manual Ability Classification System level, level II was lower than level I, and level III was lower than level II in terms of performance based motor skills. [Conclusion] The results of this study indicate that performance-based motor skills differ among children categorized based on Gross Motor Function Classification System and Manual Ability Classification System levels of cerebral palsy.

The Role of Age and Executive Function in Auditory Category Learning

PubMed Central

Reetzke, Rachel; Maddox, W. Todd; Chandrasekaran, Bharath

2015-01-01

Auditory categorization is a natural and adaptive process that allows for the organization of high-dimensional, continuous acoustic information into discrete representations. Studies in the visual domain have identified a rule-based learning system that learns and reasons via a hypothesis-testing process that requires working memory and executive attention. The rule-based learning system in vision shows a protracted development, reflecting the influence of maturing prefrontal function on visual categorization. The aim of the current study is two-fold: (a) to examine the developmental trajectory of rule-based auditory category learning from childhood through adolescence, into early adulthood; and (b) to examine the extent to which individual differences in rule-based category learning relate to individual differences in executive function. Sixty participants with normal hearing, 20 children (age range, 7–12), 21 adolescents (age range, 13–19), and 19 young adults (age range, 20–23), learned to categorize novel dynamic ripple sounds using trial-by-trial feedback. The spectrotemporally modulated ripple sounds are considered the auditory equivalent of the well-studied Gabor patches in the visual domain. Results revealed that auditory categorization accuracy improved with age, with young adults outperforming children and adolescents. Computational modeling analyses indicated that the use of the task-optimal strategy (i.e. a conjunctive rule-based learning strategy) improved with age. Notably, individual differences in executive flexibility significantly predicted auditory category learning success. The current findings demonstrate a protracted development of rule-based auditory categorization. The results further suggest that executive flexibility coupled with perceptual processes play important roles in successful rule-based auditory category learning. PMID:26491987

A 2-year study of patient safety competency assessment in 29 clinical laboratories.

PubMed

Reed, Robyn C; Kim, Sara; Farquharson, Kara; Astion, Michael L

2008-06-01

Competency assessment is critical for laboratory operations and is mandated by the Clinical Laboratory Improvement Amendments of 1988. However, no previous reports describe methods for assessing competency in patient safety. We developed and implemented a Web-based tool to assess performance of 875 laboratory staff from 29 laboratories in patient safety. Question categories included workplace culture, categorizing error, prioritization of patient safety interventions, strength of specific interventions, and general patient safety concepts. The mean score was 85.0%, with individual scores ranging from 56% to 100% and scores by category from 81.3% to 88.6%. Of the most difficult questions (<72% correct), 6 were about intervention strength, 3 about categorizing error, 1 about workplace culture, and 1 about prioritization of interventions. Of the 13 questions about intervention strength, 6 (46%) were in the lowest quartile, suggesting that this may be a difficult topic for laboratory technologists. Computer-based competency assessments help laboratories identify topics for continuing education in patient safety.

ASSOCIATIVE CONCEPT LEARNING IN ANIMALS

PubMed Central

Zentall, Thomas R.; Wasserman, Edward A.; Urcuioli, Peter J.

2014-01-01

Nonhuman animals show evidence for three types of concept learning: perceptual or similarity-based in which objects/stimuli are categorized based on physical similarity; relational in which one object/stimulus is categorized relative to another (e.g., same/different); and associative in which arbitrary stimuli become interchangeable with one another by virtue of a common association with another stimulus, outcome, or response. In this article, we focus on various methods for establishing associative concepts in nonhuman animals and evaluate data documenting the development of associative classes of stimuli. We also examine the nature of the common within-class representation of samples that have been associated with the same reinforced comparison response (i.e., many-to-one matching) by describing manipulations for distinguishing possible representations. Associative concepts provide one foundation for human language such that spoken and written words and the objects they represent become members of a class of interchangeable stimuli. The mechanisms of associative concept learning and the behavioral flexibility it allows, however, are also evident in the adaptive behaviors of animals lacking language. PMID:24170540

Decision Making Analysis: Critical Factors-Based Methodology

DTIC Science & Technology

2010-04-01

the pitfalls associated with current wargaming methods such as assuming a western view of rational values in decision - making regardless of the cultures...Utilization theory slightly expands the rational decision making model as it states that “actors try to maximize their expected utility by weighing the...items to categorize the decision - making behavior of political leaders which tend to demonstrate either a rational or cognitive leaning. Leaders

Similarity relations in visual search predict rapid visual categorization

PubMed Central

Mohan, Krithika; Arun, S. P.

2012-01-01

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

Improved analytical methods for microarray-based genome-composition analysis

PubMed Central

Kim, Charles C; Joyce, Elizabeth A; Chan, Kaman; Falkow, Stanley

2002-01-01

Background Whereas genome sequencing has given us high-resolution pictures of many different species of bacteria, microarrays provide a means of obtaining information on genome composition for many strains of a given species. Genome-composition analysis using microarrays, or 'genomotyping', can be used to categorize genes into 'present' and 'divergent' categories based on the level of hybridization signal. This typically involves selecting a signal value that is used as a cutoff to discriminate present (high signal) and divergent (low signal) genes. Current methodology uses empirical determination of cutoffs for classification into these categories, but this methodology is subject to several problems that can result in the misclassification of many genes. Results We describe a method that depends on the shape of the signal-ratio distribution and does not require empirical determination of a cutoff. Moreover, the cutoff is determined on an array-to-array basis, accounting for variation in strain composition and hybridization quality. The algorithm also provides an estimate of the probability that any given gene is present, which provides a measure of confidence in the categorical assignments. Conclusions Many genes previously classified as present using static methods are in fact divergent on the basis of microarray signal; this is corrected by our algorithm. We have reassigned hundreds of genes from previous genomotyping studies of Helicobacter pylori and Campylobacter jejuni strains, and expect that the algorithm should be widely applicable to genomotyping data. PMID:12429064

Intersectionality and risk for ischemic heart disease in Sweden: Categorical and anti-categorical approaches.

PubMed

Wemrell, Maria; Mulinari, Shai; Merlo, Juan

2017-03-01

Intersectionality theory can contribute to epidemiology and public health by furthering understanding of power dynamics driving production of health disparities, and increasing knowledge about heterogeneities within, and overlap between, social categories. Drawing on McCall, we relate the first of these potential contributions to categorical intersectionality and the second to anti-categorical intersectionality. Both approaches are used in study of risk of ischemic heart disease (IHD), based on register data on 3.6 million adults residing in Sweden by 2010, followed for three years. Categorical intersectionality is here coupled with between-group differences in average risk calculation, as we use intersectional categorizations while estimating odds ratios through logistic regressions. The anti-categorical approach is operationalized through measurement of discriminatory accuracy (DA), i.e., capacity to accurately categorize individuals with or without a certain outcome, through computation of the area under the curve (AUC). Our results show substantial differences in average risk between intersectional groupings. The DA of social categorizations is found to be low, however, due to outcome variability within and overlap between categories. We argue that measures of DA should be used for proper interpretation of differences in average risk between social (or any other) categories. Tension between average between-group risk and the DA of categorizations, which can be related to categorical and anti-categorical intersectional analyses, should be made explicit and discussed to a larger degree in epidemiology and public health. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Learning and transfer of category knowledge in an indirect categorization task.

PubMed

Helie, Sebastien; Ashby, F Gregory

2012-05-01

Knowledge representations acquired during category learning experiments are 'tuned' to the task goal. A useful paradigm to study category representations is indirect category learning. In the present article, we propose a new indirect categorization task called the "same"-"different" categorization task. The same-different categorization task is a regular same-different task, but the question asked to the participants is about the stimulus category membership instead of stimulus identity. Experiment 1 explores the possibility of indirectly learning rule-based and information-integration category structures using the new paradigm. The results suggest that there is little learning about the category structures resulting from an indirect categorization task unless the categories can be separated by a one-dimensional rule. Experiment 2 explores whether a category representation learned indirectly can be used in a direct classification task (and vice versa). The results suggest that previous categorical knowledge acquired during a direct classification task can be expressed in the same-different categorization task only when the categories can be separated by a rule that is easily verbalized. Implications of these results for categorization research are discussed.

The Consequences of Providing Drinkers with Blood Alcohol Concentration Information on Assessments of Alcohol Impairment and Drunk-Driving Risk*

PubMed Central

JOHNSON, MARK B.; VOAS, ROBERT B.; KELLEY-BAKER, TARA; FURR-HOLDEN, C. DEBRA M.

2009-01-01

Objective We examined the effect of providing drinkers with blood alcohol concentration (BAC) information on subjective assessments of alcohol impairment and drunk-driving risk. Method We sampled 959 drinking participants from a natural drinking environment and asked them to self-administer a personal saliva-based alcohol test. Participants then were asked to rate their alcohol impairment and to indicate whether they could drive legally under one of four BAC feedback conditions (assigned at random): (1) control condition (no BAC feedback provided before the ratings); (2) categorical BAC information (low, high, and highest risk) from the saliva test; (3) categorical BAC information corroborated by a calibrated police breath alcohol analyzer; and (4) precise (three-digit) BAC information from the breath alcohol analyzer. Results Both control participants and participants who received precise BAC feedback gave subjective impairment ratings that correlated with actual BACs. For participants who received categorical BAC information from the saliva test, subjective impairment did not correlate with the actual BAC. Providing drinkers with BAC information, however, did help them predict more accurately if their BAC was higher than the legal BAC driving limit. Conclusions Although BAC information can influence drinkers’ assessments of alcohol impairment and drunk-driving risk, there is no strong evidence that personal saliva-based alcohol tests are particularly useful. PMID:18612570

Research priorities in Italian diabetes nursing care: findings from a Delphi study.

PubMed

Palese, A; Gentilini, S; Lo Grasso, G; Branca, M T; Chiandetti, R; Mansutti, I

2015-01-01

Defining a set of research priorities for diabetes nursing care in the Italian context. A two-step study design based on a modified Delphi technique was undertaken in 2013. In the first stage of research, five systematic reviews of literature were performed. Among them 865 recommendations in diabetes nursing care emerged, and 217 (25.1%) were categorized at level IV or lower, thus based on a lack of knowledge and therefore a potential research area. Homogeneous recommendations among the 217 emerged and were categorized by two researchers independently: 96 final recommendations were identified and transformed into items embodied into a questionnaire. A Likert scale ranging from 1 (very low) to 5 (very high) was used to collect the consensus regarding priority. For that purpose a sample of 200 nurses was randomly considered. Potential participants were invited to cooperate via email through a letter reporting aims and methods. In the first round 85 nurses participated; in the third and final round, only 13 nurses took part. Participants have identified 14 research priorities categorized into three main areas: 1) education strategies' effectiveness (n=7); 2) models of care delivery and advanced nursing education effectiveness (n=4); and 3) in specific clinical issues (n=3). More research on patient education and on models of care delivery and advanced nursing education should be included in any future Italian agenda.

Recent developments in detection and enumeration of waterborne bacteria: a retrospective minireview.

PubMed

Deshmukh, Rehan A; Joshi, Kopal; Bhand, Sunil; Roy, Utpal

2016-12-01

Waterborne diseases have emerged as global health problems and their rapid and sensitive detection in environmental water samples is of great importance. Bacterial identification and enumeration in water samples is significant as it helps to maintain safe drinking water for public consumption. Culture-based methods are laborious, time-consuming, and yield false-positive results, whereas viable but nonculturable (VBNCs) microorganisms cannot be recovered. Hence, numerous methods have been developed for rapid detection and quantification of waterborne pathogenic bacteria in water. These rapid methods can be classified into nucleic acid-based, immunology-based, and biosensor-based detection methods. This review summarizes the principle and current state of rapid methods for the monitoring and detection of waterborne bacterial pathogens. Rapid methods outlined are polymerase chain reaction (PCR), digital droplet PCR, real-time PCR, multiplex PCR, DNA microarray, Next-generation sequencing (pyrosequencing, Illumina technology and genomics), and fluorescence in situ hybridization that are categorized as nucleic acid-based methods. Enzyme-linked immunosorbent assay (ELISA) and immunofluorescence are classified into immunology-based methods. Optical, electrochemical, and mass-based biosensors are grouped into biosensor-based methods. Overall, these methods are sensitive, specific, time-effective, and important in prevention and diagnosis of waterborne bacterial diseases. © 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Potential of bioethanol as a chemical building block for biorefineries: preliminary sustainability assessment of 12 bioethanol-based products.

PubMed

Posada, John A; Patel, Akshay D; Roes, Alexander; Blok, Kornelis; Faaij, André P C; Patel, Martin K

2013-05-01

The aim of this study is to present and apply a quick screening method and to identify the most promising bioethanol derivatives using an early-stage sustainability assessment method that compares a bioethanol-based conversion route to its respective petrochemical counterpart. The method combines, by means of a multi-criteria approach, quantitative and qualitative proxy indicators describing economic, environmental, health and safety and operational aspects. Of twelve derivatives considered, five were categorized as favorable (diethyl ether, 1,3-butadiene, ethyl acetate, propylene and ethylene), two as promising (acetaldehyde and ethylene oxide) and five as unfavorable derivatives (acetic acid, n-butanol, isobutylene, hydrogen and acetone) for an integrated biorefinery concept. Copyright © 2012 Elsevier Ltd. All rights reserved.

Gold-standard evaluation of a folksonomy-based ontology learning model

NASA Astrophysics Data System (ADS)

Djuana, E.

2018-03-01

Folksonomy, as one result of collaborative tagging process, has been acknowledged for its potential in improving categorization and searching of web resources. However, folksonomy contains ambiguities such as synonymy and polysemy as well as different abstractions or generality problem. To maximize its potential, some methods for associating tags of folksonomy with semantics and structural relationships have been proposed such as using ontology learning method. This paper evaluates our previous work in ontology learning according to gold-standard evaluation approach in comparison to a notable state-of-the-art work and several baselines. The results show that our method is comparable to the state-of the art work which further validate our approach as has been previously validated using task-based evaluation approach.

Neural Connectivity Evidence for a Categorical-Dimensional Hybrid Model of Autism Spectrum Disorder.

PubMed

Elton, Amanda; Di Martino, Adriana; Hazlett, Heather Cody; Gao, Wei

2016-07-15

Autism spectrum disorder (ASD) encompasses a complex manifestation of symptoms that include deficits in social interaction and repetitive or stereotyped interests and behaviors. In keeping with the increasing recognition of the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate the neural mechanisms of ASD symptoms based on the functional connectivity of four known neural networks (i.e., default mode network, dorsal attention network, salience network, and executive control network). We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state functional magnetic resonance imaging data sets from 90 boys with ASD and 95 typically developing boys. This data set also included the Social Responsiveness Scale as a dimensional measure of ASD traits. Seed-based functional connectivity was paired with linear regression to identify functional connectivity abnormalities associated with categorical effects of ASD diagnosis, dimensional effects of ASD-like behaviors, and their interaction. Our results revealed the existence of dimensional mechanisms of ASD uniquely affecting each network based on the presence of connectivity-behavioral relationships; these were independent of diagnostic category. However, we also found evidence of categorical differences (i.e., diagnostic group differences) in connectivity strength for each network as well as categorical differences in connectivity-behavioral relationships (i.e., diagnosis-by-behavior interactions), supporting the coexistence of categorical mechanisms of ASD. Our findings support a hybrid model for ASD characterization that includes a combination of categorical and dimensional brain mechanisms and provide a novel understanding of the neural underpinnings of ASD. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Categorization by Schema Relations and Perceptual Similarity in 5-Year-Olds and Adults: A Study in Vision and in Audition

ERIC Educational Resources Information Center

Berger, Carole; Donnadieu, Sophie

2006-01-01

This research explores the way in which young children (5 years of age) and adults use perceptual and conceptual cues for categorizing objects processed by vision or by audition. Three experiments were carried out using forced-choice categorization tasks that allowed responses based on taxonomic relations (e.g., vehicles) or on schema category…

The cross-category effect: mere social categorization is sufficient to elicit an own-group bias in face recognition.

PubMed

Bernstein, Michael J; Young, Steven G; Hugenberg, Kurt

2007-08-01

Although the cross-race effect (CRE) is a well-established phenomenon, both perceptual-expertise and social-categorization models have been proposed to explain the effect. The two studies reported here investigated the extent to which categorizing other people as in-group versus out-group members is sufficient to elicit a pattern of face recognition analogous to that of the CRE, even when perceptual expertise with the stimuli is held constant. In Study 1, targets were categorized as members of real-life in-groups and out-groups (based on university affiliation), whereas in Study 2, targets were categorized into experimentally created minimal groups. In both studies, recognition performance was better for targets categorized as in-group members, despite the fact that perceptual expertise was equivalent for in-group and out-group faces. These results suggest that social-cognitive mechanisms of in-group and out-group categorization are sufficient to elicit performance differences for in-group and out-group face recognition.

Proposal for a new categorization of aseptic processing facilities based on risk assessment scores.

PubMed

Katayama, Hirohito; Toda, Atsushi; Tokunaga, Yuji; Katoh, Shigeo

2008-01-01

Risk assessment of aseptic processing facilities was performed using two published risk assessment tools. Calculated risk scores were compared with experimental test results, including environmental monitoring and media fill run results, in three different types of facilities. The two risk assessment tools used gave a generally similar outcome. However, depending on the tool used, variations were observed in the relative scores between the facilities. For the facility yielding the lowest risk scores, the corresponding experimental test results showed no contamination, indicating that these ordinal testing methods are insufficient to evaluate this kind of facility. A conventional facility having acceptable aseptic processing lines gave relatively high risk scores. The facility showing a rather high risk score demonstrated the usefulness of conventional microbiological test methods. Considering the significant gaps observed in calculated risk scores and in the ordinal microbiological test results between advanced and conventional facilities, we propose a facility categorization based on risk assessment. The most important risk factor in aseptic processing is human intervention. When human intervention is eliminated from the process by advanced hardware design, the aseptic processing facility can be classified into a new risk category that is better suited for assuring sterility based on a new set of criteria rather than on currently used microbiological analysis. To fully benefit from advanced technologies, we propose three risk categories for these aseptic facilities.

Developmentally invariant dissociations in children's true and false memories: not all relatedness is created equal.

PubMed

Howe, Mark L

2006-01-01

The role of categorical versus associative relations in 5-, 7-, and 11-year-old children's true and false memories was examined using the Deese-Roediger-McDermott (DRM) paradigm and categorized lists of pictures or words with or without category labels as primes. For true items, recall increased with age and categorized lists were better recalled than DRM lists. For false items, recall increased with age except for picture lists, there were no differences between categorized and DRM lists and no effect of priming, and there were fewer false memories for pictures than words. Like adults, children's false memories are based on associative not thematic relations, whereas their veridical memories depend on both. This new, developmentally invariant dissociation is consistent with knowledge- and resource-based models of memory development.

Detection of heavy metal by paper-based microfluidics.

PubMed

Lin, Yang; Gritsenko, Dmitry; Feng, Shaolong; Teh, Yi Chen; Lu, Xiaonan; Xu, Jie

2016-09-15

Heavy metal pollution has shown great threat to the environment and public health worldwide. Current methods for the detection of heavy metals require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Various microfluidic paper-based analytical devices have been developed recently as simple, cheap and disposable alternatives to conventional ones for on-site detection of heavy metals. In this review, we first summarize current development of paper-based analytical devices and discuss the selection of paper substrates, methods of device fabrication, and relevant theories in these devices. We then compare and categorize recent reports on detection of heavy metals using paper-based microfluidic devices on the basis of various detection mechanisms, such as colorimetric, fluorescent, and electrochemical methods. To finalize, the future development and trend in this field are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Interferometric architectures based All-Optical logic design methods and their implementations

NASA Astrophysics Data System (ADS)

Singh, Karamdeep; Kaur, Gurmeet

2015-06-01

All-Optical Signal Processing is an emerging technology which can avoid costly Optical-electronic-optical (O-E-O) conversions which are usually compulsory in traditional Electronic Signal Processing systems, thus greatly enhancing operating bit rate with some added advantages such as electro-magnetic interference immunity and low power consumption etc. In order to implement complex signal processing tasks All-Optical logic gates are required as backbone elements. This review describes the advances in the field of All-Optical logic design methods based on interferometric architectures such as Mach-Zehnder Interferometer (MZI), Sagnac Interferometers and Ultrafast Non-Linear Interferometer (UNI). All-Optical logic implementations for realization of arithmetic and signal processing applications based on each interferometric arrangement are also presented in a categorized manner.

Measuring Vocational Preferences: Ranking versus Categorical Rating Procedures.

ERIC Educational Resources Information Center

Carifio, James

1978-01-01

Describes a study to compare the relative validities of ranking v categorical rating procedures for obtaining student vocational preference data in exploratory program assignment situations. Students indicated their vocational program preferences from career clusters, and the frequency of wrong assignments made by each method was analyzed. (MF)

Categorical Variables in Multiple Regression: Some Cautions.

ERIC Educational Resources Information Center

O'Grady, Kevin E.; Medoff, Deborah R.

1988-01-01

Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)

Perceptual and categorical decision making: goal-relevant representation of two domains at different levels of abstraction.

PubMed

Shankar, Swetha; Kayser, Andrew S

2017-06-01

To date it has been unclear whether perceptual decision making and rule-based categorization reflect activation of similar cognitive processes and brain regions. On one hand, both map potentially ambiguous stimuli to a smaller set of motor responses. On the other hand, decisions about perceptual salience typically concern concrete sensory representations derived from a noisy stimulus, while categorization is typically conceptualized as an abstract decision about membership in a potentially arbitrary set. Previous work has primarily examined these types of decisions in isolation. Here we independently varied salience in both the perceptual and categorical domains in a random dot-motion framework by manipulating dot-motion coherence and motion direction relative to a category boundary, respectively. Behavioral and modeling results suggest that categorical (more abstract) information, which is more relevant to subjects' decisions, is weighted more strongly than perceptual (more concrete) information, although they also have significant interactive effects on choice. Within the brain, BOLD activity within frontal regions strongly differentiated categorical salience and weakly differentiated perceptual salience; however, the interaction between these two factors activated similar frontoparietal brain networks. Notably, explicitly evaluating feature interactions revealed a frontal-parietal dissociation: parietal activity varied strongly with both features, but frontal activity varied with the combined strength of the information that defined the motor response. Together, these data demonstrate that frontal regions are driven by decision-relevant features and argue that perceptual decisions and rule-based categorization reflect similar cognitive processes and activate similar brain networks to the extent that they define decision-relevant stimulus-response mappings. NEW & NOTEWORTHY Here we study the behavioral and neural dynamics of perceptual categorization when decision information varies in multiple domains at different levels of abstraction. Behavioral and modeling results suggest that categorical (more abstract) information is weighted more strongly than perceptual (more concrete) information but that perceptual and categorical domains interact to influence decisions. Frontoparietal brain activity during categorization flexibly represents decision-relevant features and highlights significant dissociations in frontal and parietal activity during decision making. Copyright © 2017 the American Physiological Society.

Perceptual and categorical decision making: goal-relevant representation of two domains at different levels of abstraction

PubMed Central

Kayser, Andrew S.

2017-01-01

To date it has been unclear whether perceptual decision making and rule-based categorization reflect activation of similar cognitive processes and brain regions. On one hand, both map potentially ambiguous stimuli to a smaller set of motor responses. On the other hand, decisions about perceptual salience typically concern concrete sensory representations derived from a noisy stimulus, while categorization is typically conceptualized as an abstract decision about membership in a potentially arbitrary set. Previous work has primarily examined these types of decisions in isolation. Here we independently varied salience in both the perceptual and categorical domains in a random dot-motion framework by manipulating dot-motion coherence and motion direction relative to a category boundary, respectively. Behavioral and modeling results suggest that categorical (more abstract) information, which is more relevant to subjects’ decisions, is weighted more strongly than perceptual (more concrete) information, although they also have significant interactive effects on choice. Within the brain, BOLD activity within frontal regions strongly differentiated categorical salience and weakly differentiated perceptual salience; however, the interaction between these two factors activated similar frontoparietal brain networks. Notably, explicitly evaluating feature interactions revealed a frontal-parietal dissociation: parietal activity varied strongly with both features, but frontal activity varied with the combined strength of the information that defined the motor response. Together, these data demonstrate that frontal regions are driven by decision-relevant features and argue that perceptual decisions and rule-based categorization reflect similar cognitive processes and activate similar brain networks to the extent that they define decision-relevant stimulus-response mappings. NEW & NOTEWORTHY Here we study the behavioral and neural dynamics of perceptual categorization when decision information varies in multiple domains at different levels of abstraction. Behavioral and modeling results suggest that categorical (more abstract) information is weighted more strongly than perceptual (more concrete) information but that perceptual and categorical domains interact to influence decisions. Frontoparietal brain activity during categorization flexibly represents decision-relevant features and highlights significant dissociations in frontal and parietal activity during decision making. PMID:28250149

Test Statistics and Confidence Intervals to Establish Noninferiority between Treatments with Ordinal Categorical Data.

PubMed

Zhang, Fanghong; Miyaoka, Etsuo; Huang, Fuping; Tanaka, Yutaka

2015-01-01

The problem for establishing noninferiority is discussed between a new treatment and a standard (control) treatment with ordinal categorical data. A measure of treatment effect is used and a method of specifying noninferiority margin for the measure is provided. Two Z-type test statistics are proposed where the estimation of variance is constructed under the shifted null hypothesis using U-statistics. Furthermore, the confidence interval and the sample size formula are given based on the proposed test statistics. The proposed procedure is applied to a dataset from a clinical trial. A simulation study is conducted to compare the performance of the proposed test statistics with that of the existing ones, and the results show that the proposed test statistics are better in terms of the deviation from nominal level and the power.

The kappa statistic in rehabilitation research: an examination.

PubMed

Tooth, Leigh R; Ottenbacher, Kenneth J

2004-08-01

The number and sophistication of statistical procedures reported in medical rehabilitation research is increasing. Application of the principles and methods associated with evidence-based practice has contributed to the need for rehabilitation practitioners to understand quantitative methods in published articles. Outcomes measurement and determination of reliability are areas that have experienced rapid change during the past decade. In this study, distinctions between reliability and agreement are examined. Information is presented on analytical approaches for addressing reliability and agreement with the focus on the application of the kappa statistic. The following assumptions are discussed: (1) kappa should be used with data measured on a categorical scale, (2) the patients or objects categorized should be independent, and (3) the observers or raters must make their measurement decisions and judgments independently. Several issues related to using kappa in measurement studies are described, including use of weighted kappa, methods of reporting kappa, the effect of bias and prevalence on kappa, and sample size and power requirements for kappa. The kappa statistic is useful for assessing agreement among raters, and it is being used more frequently in rehabilitation research. Correct interpretation of the kappa statistic depends on meeting the required assumptions and accurate reporting.

A psychophysical imaging method evidencing auditory cue extraction during speech perception: a group analysis of auditory classification images.

PubMed

Varnet, Léo; Knoblauch, Kenneth; Serniclaes, Willy; Meunier, Fanny; Hoen, Michel

2015-01-01

Although there is a large consensus regarding the involvement of specific acoustic cues in speech perception, the precise mechanisms underlying the transformation from continuous acoustical properties into discrete perceptual units remains undetermined. This gap in knowledge is partially due to the lack of a turnkey solution for isolating critical speech cues from natural stimuli. In this paper, we describe a psychoacoustic imaging method known as the Auditory Classification Image technique that allows experimenters to estimate the relative importance of time-frequency regions in categorizing natural speech utterances in noise. Importantly, this technique enables the testing of hypotheses on the listening strategies of participants at the group level. We exemplify this approach by identifying the acoustic cues involved in da/ga categorization with two phonetic contexts, Al- or Ar-. The application of Auditory Classification Images to our group of 16 participants revealed significant critical regions on the second and third formant onsets, as predicted by the literature, as well as an unexpected temporal cue on the first formant. Finally, through a cluster-based nonparametric test, we demonstrate that this method is sufficiently sensitive to detect fine modifications of the classification strategies between different utterances of the same phoneme.

Crowd density estimation based on convolutional neural networks with mixed pooling

NASA Astrophysics Data System (ADS)

Zhang, Li; Zheng, Hong; Zhang, Ying; Zhang, Dongming

2017-09-01

Crowd density estimation is an important topic in the fields of machine learning and video surveillance. Existing methods do not provide satisfactory classification accuracy; moreover, they have difficulty in adapting to complex scenes. Therefore, we propose a method based on convolutional neural networks (CNNs). The proposed method improves performance of crowd density estimation in two key ways. First, we propose a feature pooling method named mixed pooling to regularize the CNNs. It replaces deterministic pooling operations with a parameter that, by studying the algorithm, could combine the conventional max pooling with average pooling methods. Second, we present a classification strategy, in which an image is divided into two cells and respectively categorized. The proposed approach was evaluated on three datasets: two ground truth image sequences and the University of California, San Diego, anomaly detection dataset. The results demonstrate that the proposed approach performs more effectively and easily than other methods.

Visual Categorization of Natural Movies by Rats

PubMed Central

Vinken, Kasper; Vermaercke, Ben

2014-01-01

Visual categorization of complex, natural stimuli has been studied for some time in human and nonhuman primates. Recent interest in the rodent as a model for visual perception, including higher-level functional specialization, leads to the question of how rodents would perform on a categorization task using natural stimuli. To answer this question, rats were trained in a two-alternative forced choice task to discriminate movies containing rats from movies containing other objects and from scrambled movies (ordinate-level categorization). Subsequently, transfer to novel, previously unseen stimuli was tested, followed by a series of control probes. The results show that the animals are capable of acquiring a decision rule by abstracting common features from natural movies to generalize categorization to new stimuli. Control probes demonstrate that they did not use single low-level features, such as motion energy or (local) luminance. Significant generalization was even present with stationary snapshots from untrained movies. The variability within and between training and test stimuli, the complexity of natural movies, and the control experiments and analyses all suggest that a more high-level rule based on more complex stimulus features than local luminance-based cues was used to classify the novel stimuli. In conclusion, natural stimuli can be used to probe ordinate-level categorization in rats. PMID:25100598

Color names, color categories, and color-cued visual search: Sometimes, color perception is not categorical

PubMed Central

Brown, Angela M; Lindsey, Delwin T; Guckes, Kevin M

2011-01-01

The relation between colors and their names is a classic case-study for investigating the Sapir-Whorf hypothesis that categorical perception is imposed on perception by language. Here, we investigate the Sapir-Whorf prediction that visual search for a green target presented among blue distractors (or vice versa) should be faster than search for a green target presented among distractors of a different color of green (or for a blue target among different blue distractors). Gilbert, Regier, Kay & Ivry (2006) reported that this Sapir-Whorf effect is restricted to the right visual field (RVF), because the major brain language centers are in the left cerebral hemisphere. We found no categorical effect at the Green|Blue color boundary, and no categorical effect restricted to the RVF. Scaling of perceived color differences by Maximum Likelihood Difference Scaling (MLDS) also showed no categorical effect, including no effect specific to the RVF. Two models fit the data: a color difference model based on MLDS and a standard opponent-colors model of color discrimination based on the spectral sensitivities of the cones. Neither of these models, nor any of our data, suggested categorical perception of colors at the Green|Blue boundary, in either visual field. PMID:21980188

Dyslexia Limits the Ability to Categorize Talker Dialect

ERIC Educational Resources Information Center

Long, Gayle Beam; Fox, Robert Allen; Jacewicz, Ewa

2016-01-01

Purpose: The purpose of this study was to determine whether the underlying phonological impairment in dyslexia is associated with a deficit in categorizing regional dialects. Method: Twenty adults with dyslexia, 20 school-age children with dyslexia, and 40 corresponding control listeners with average reading ability listened to sentences produced…

Categorization = Decision Making + Generalization

PubMed Central

Seger, Carol A; Peterson, Erik J.

2013-01-01

We rarely, if ever, repeatedly encounter exactly the same situation. This makes generalization crucial for real world decision making. We argue that categorization, the study of generalizable representations, is a type of decision making, and that categorization learning research would benefit from approaches developed to study the neuroscience of decision making. Similarly, methods developed to examine generalization and learning within the field of categorization may enhance decision making research. We first discuss perceptual information processing and integration, with an emphasis on accumulator models. We then examine learning the value of different decision making choices via experience, emphasizing reinforcement learning modeling approaches. Next we discuss how value is combined with other factors in decision making, emphasizing the effects of uncertainty. Finally, we describe how a final decision is selected via thresholding processes implemented by the basal ganglia and related regions. We also consider how memory related functions in the hippocampus may be integrated with decision making mechanisms and contribute to categorization. PMID:23548891

How many infants are temperamentally difficult? Comparing norms from the Revised Infant Temperament Questionnaire to a population sample of UK infants.

PubMed

Chong, Shiau Yun; Chittleborough, Catherine R; Gregory, Tess; Lynch, John W; Smithers, Lisa G

2015-08-01

The original norms for the Revised Infant Temperament Questionnaire (RITQ) were published in 1978 and were based on a small sample from the US. The aim of this study is to compare temperament scores from the original RITQ against scores from a large population-based cohort of infants from the UK. This study consists of 10,937 infants from the Avon Longitudinal Study of Parents and Children (ALSPAC) born between April 1991 and December 1992 in the southwest of England. Infant temperament at 6 months of age was reported by parents using the adapted RITQ. Responses were scored according to the RITQ manual and then categorized into temperament groups (easy, intermediate low, intermediate high, and difficult) using either the RITQ norms or norms derived from the data. The scores for each temperament subscale and the proportion of children in each temperament group were compared across the two methods. Subscale scores for the ALSPAC sample were higher (more "difficult") than the RITQ norms for rhythmicity, approach, adaptability, intensity, and distractibility. When RITQ norms were applied, 24% infants were categorized as difficult and 25% as easy, compared with 15% difficult and 38% easy when ALSPAC norms were used. There are discrepancies between RITQ norms and the ALSPAC norms which resulted in differences in the distribution of temperament groups. There is a need to re-examine RITQ norms and categorization for use in primary care practice and contemporary population-based studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Wearable accelerometry-based technology capable of assessing functional activities in neurological populations in community settings: a systematic review.

PubMed

Steins, Dax; Dawes, Helen; Esser, Patrick; Collett, Johnny

2014-03-13

Integrating rehabilitation services through wearable systems has the potential to accurately assess the type, intensity, duration, and quality of movement necessary for procuring key outcome measures. This review aims to explore wearable accelerometry-based technology (ABT) capable of assessing mobility-related functional activities intended for rehabilitation purposes in community settings for neurological populations. In this review, we focus on the accuracy of ABT-based methods, types of outcome measures, and the implementation of ABT in non-clinical settings for rehabilitation purposes. Cochrane, PubMed, Web of Knowledge, EMBASE, and IEEE Xplore. The search strategy covered three main areas, namely wearable technology, rehabilitation, and setting. Potentially relevant studies were categorized as systems either evaluating methods or outcome parameters. Methodological qualities of studies were assessed by two customized checklists, depending on their categorization and rated independently by three blinded reviewers. Twelve studies involving ABT met the eligibility criteria, of which three studies were identified as having implemented ABT for rehabilitation purposes in non-clinical settings. From the twelve studies, seven studies achieved high methodological quality scores. These studies were not only capable of assessing the type, quantity, and quality measures of functional activities, but could also distinguish healthy from non-healthy subjects and/or address disease severity levels. While many studies support ABT's potential for telerehabilitation, few actually utilized it to assess mobility-related functional activities outside laboratory settings. To generate more appropriate outcome measures, there is a clear need to translate research findings and novel methods into practice.

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

PubMed Central

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

2014-01-01

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

Cluster categorization of urban roads to optimize their noise monitoring.

PubMed

Zambon, G; Benocci, R; Brambilla, G

2016-01-01

Road traffic in urban areas is recognized to be associated with urban mobility and public health, and it is often the main source of noise pollution. Lately, noise maps have been considered a powerful tool to estimate the population exposure to environmental noise, but they need to be validated by measured noise data. The project Dynamic Acoustic Mapping (DYNAMAP), co-funded in the framework of the LIFE 2013 program, is aimed to develop a statistically based method to optimize the choice and the number of monitoring sites and to automate the noise mapping update using the data retrieved from a low-cost monitoring network. Indeed, the first objective should improve the spatial sampling based on the legislative road classification, as this classification is mainly based on the geometrical characteristics of the road, rather than its noise emission. The present paper describes the statistical approach of the methodology under development and the results of its preliminary application to a limited sample of roads in the city of Milan. The resulting categorization of roads, based on clustering the 24-h hourly L Aeqh, looks promising to optimize the spatial sampling of noise monitoring toward a description of the noise pollution due to complex urban road networks more efficient than that based on the legislative road classification.

Categorization and reasoning among tree experts: do all roads lead to Rome?

PubMed

Medin, D L; Lynch, E B; Coley, J D; Atran, S

1997-02-01

To what degree do conceptual systems reflect universal patterns of featural covariation in the world (similarity) or universal organizing principles of mind, and to what degree do they reflect specific goals, theories, and beliefs of the categorizer? This question was addressed in experiments concerned with categorization and reasoning among different types of tree experts (e.g., taxonomists, landscape workers, parks maintenance personnel). The results show an intriguing pattern of similarities and differences. Differences in sorting between taxonomists and maintenance workers reflect differences in weighting of morphological features. Landscape workers, in contrast, sort trees into goal-derived categories based on utilitarian concerns. These sorting patterns carry over into category-based reasoning for the taxonomists and maintenance personnel but not the landscape workers. These generalizations interact with taxonomic rank and suggest that the genus (or folk generic) level is relatively and in some cases absolutely privileged. Implications of these findings for theories of categorization are discussed.

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization.

PubMed

Brand, John; Johnson, Aaron P

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization

PubMed Central

Brand, John; Johnson, Aaron P.

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks. PMID:25520675

Robust Identification of Alzheimer's Disease subtypes based on cortical atrophy patterns.

PubMed

Park, Jong-Yun; Na, Han Kyu; Kim, Sungsoo; Kim, Hyunwook; Kim, Hee Jin; Seo, Sang Won; Na, Duk L; Han, Cheol E; Seong, Joon-Kyung

2017-03-09

Accumulating evidence suggests that Alzheimer's disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar atrophy patterns using the Louvain method for modular organization extraction. We applied our method to AD patients recruited at Samsung Medical Center and externally validated our method by using the AD Neuroimaging Initiative (ADNI) dataset. Our method categorized very mild AD into three clinically distinct subtypes with high reproducibility (>90%); the parietal-predominant (P), medial temporal-predominant (MT), and diffuse (D) atrophy subtype. The P subtype showed the worst clinical presentation throughout the cognitive domains, while the MT and D subtypes exhibited relatively mild presentation. The MT subtype revealed more impaired language and executive function compared to the D subtype.

Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns

NASA Astrophysics Data System (ADS)

Park, Jong-Yun; Na, Han Kyu; Kim, Sungsoo; Kim, Hyunwook; Kim, Hee Jin; Seo, Sang Won; Na, Duk L.; Han, Cheol E.; Seong, Joon-Kyung; Weiner, Michael; Aisen, Paul; Petersen, Ronald; Jack, Clifford R.; Jagust, William; Trojanowki, John Q.; Toga, Arthur W.; Beckett, Laurel; Green, Robert C.; Saykin, Andrew J.; Morris, John; Shaw, Leslie M.; Liu, Enchi; Montine, Tom; Thomas, Ronald G.; Donohue, Michael; Walter, Sarah; Gessert, Devon; Sather, Tamie; Jiminez, Gus; Harvey, Danielle; Bernstein, Matthew; Fox, Nick; Thompson, Paul; Schuff, Norbert; Decarli, Charles; Borowski, Bret; Gunter, Jeff; Senjem, Matt; Vemuri, Prashanthi; Jones, David; Kantarci, Kejal; Ward, Chad; Koeppe, Robert A.; Foster, Norm; Reiman, Eric M.; Chen, Kewei; Mathis, Chet; Landau, Susan; Cairns, Nigel J.; Householder, Erin; Taylor Reinwald, Lisa; Lee, Virginia; Korecka, Magdalena; Figurski, Michal; Crawford, Karen; Neu, Scott; Foroud, Tatiana M.; Potkin, Steven G.; Shen, Li; Kelley, Faber; Kim, Sungeun; Nho, Kwangsik; Kachaturian, Zaven; Frank, Richard; Snyder, Peter J.; Molchan, Susan; Kaye, Jeffrey; Quinn, Joseph; Lind, Betty; Carter, Raina; Dolen, Sara; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Brewer, James; Vanderswag, Helen; Fleisher, Adam; Heidebrink, Judith L.; Lord, Joanne L.; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Doody, Rachelle S.; Villanueva Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Ances, Beau; Carroll, Maria; Leon, Sue; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Grossman, Hillel; Mitsis, Effie; de Toledo-Morrell, Leyla; Shah, Raj C.; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Albert, Marilyn; Onyike, Chiadi; D'Agostino, Daniel, II; Kielb, Stephanie; Galvin, James E.; Pogorelec, Dana M.; Cerbone, Brittany; Michel, Christina A.; Rusinek, Henry; de Leon, Mony J.; Glodzik, Lidia; de Santi, Susan; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Wong, Terence Z.; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Smith, Charles D.; Jicha, Greg; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Lopez, Oscar L.; Oakley, Maryann; Simpson, Donna M.; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Mulnard, Ruth A.; Thai, Gaby; Mc Adams Ortiz, Catherine; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Diaz Arrastia, Ramon; King, Richard; Weiner, Myron; Martin Cook, Kristen; Devous, Michael; Levey, Allan I.; Lah, James J.; Cellar, Janet S.; Burns, Jeffrey M.; Anderson, Heather S.; Swerdlow, Russell H.; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H. S.; Lu, Po H.; Bartzokis, George; Graff Radford, Neill R.; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Farlow, Martin R.; Marie Hake, Ann; Matthews, Brandy R.; Herring, Scott; Hunt, Cynthia; van Dyck, Christopher H.; Carson, Richard E.; Macavoy, Martha G.; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Robin Hsiung, Ging Yuek; Feldman, Howard; Mudge, Benita; Assaly, Michele; Trost, Dick; Bernick, Charles; Munic, Donna; Kerwin, Diana; Marsel Mesulam, Marek; Lipowski, Kristine; Kuo Wu, Chuang; Johnson, Nancy; Sadowsky, Carl; Martinez, Walter; Villena, Teresa; Scott Turner, Raymond; Johnson, Kathleen; Reynolds, Brigid; Sperling, Reisa A.; Johnson, Keith A.; Marshall, Gad; Frey, Meghan; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Sabbagh, Marwan N.; Belden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Lynn Johnson, Patricia; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Hudson, Leon; Fletcher, Evan; Carmichael, Owen; Olichney, John; Kittur, Smita; Borrie, Michael; Lee, T. Y.; Bartha, Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Scharre, Douglas W.; Kataki, Maria; Adeli, Anahita; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Santulli, Robert B.; Kitzmiller, Tamar J.; Schwartz, Eben S.; Sink, Kaycee M.; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J.; Miller, Bruce L.; Mintzer, Jacobo; Spicer, Kenneth; Bachman, David; Finger, Elizabether; Pasternak, Stephen; Rachinsky, Irina; Rogers, John; Kertesz, Andrew; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Schultz, Susan K.; Boles Ponto, Laura L.; Shim, Hyungsub; Smith, Karen Elizabeth; Relkin, Norman; Chaing, Gloria; Raudin, Lisa; Smith, Amanda; Fargher, Kristin; Raj, Balebail Ashok

2017-03-01

Accumulating evidence suggests that Alzheimer’s disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar atrophy patterns using the Louvain method for modular organization extraction. We applied our method to AD patients recruited at Samsung Medical Center and externally validated our method by using the AD Neuroimaging Initiative (ADNI) dataset. Our method categorized very mild AD into three clinically distinct subtypes with high reproducibility (>90%) the parietal-predominant (P), medial temporal-predominant (MT), and diffuse (D) atrophy subtype. The P subtype showed the worst clinical presentation throughout the cognitive domains, while the MT and D subtypes exhibited relatively mild presentation. The MT subtype revealed more impaired language and executive function compared to the D subtype.

Updating categorical soil maps using limited survey data by Bayesian Markov chain cosimulation.

PubMed

Li, Weidong; Zhang, Chuanrong; Dey, Dipak K; Willig, Michael R

2013-01-01

Updating categorical soil maps is necessary for providing current, higher-quality soil data to agricultural and environmental management but may not require a costly thorough field survey because latest legacy maps may only need limited corrections. This study suggests a Markov chain random field (MCRF) sequential cosimulation (Co-MCSS) method for updating categorical soil maps using limited survey data provided that qualified legacy maps are available. A case study using synthetic data demonstrates that Co-MCSS can appreciably improve simulation accuracy of soil types with both contributions from a legacy map and limited sample data. The method indicates the following characteristics: (1) if a soil type indicates no change in an update survey or it has been reclassified into another type that similarly evinces no change, it will be simply reproduced in the updated map; (2) if a soil type has changes in some places, it will be simulated with uncertainty quantified by occurrence probability maps; (3) if a soil type has no change in an area but evinces changes in other distant areas, it still can be captured in the area with unobvious uncertainty. We concluded that Co-MCSS might be a practical method for updating categorical soil maps with limited survey data.

Updating Categorical Soil Maps Using Limited Survey Data by Bayesian Markov Chain Cosimulation

PubMed Central

Dey, Dipak K.; Willig, Michael R.

2013-01-01

Updating categorical soil maps is necessary for providing current, higher-quality soil data to agricultural and environmental management but may not require a costly thorough field survey because latest legacy maps may only need limited corrections. This study suggests a Markov chain random field (MCRF) sequential cosimulation (Co-MCSS) method for updating categorical soil maps using limited survey data provided that qualified legacy maps are available. A case study using synthetic data demonstrates that Co-MCSS can appreciably improve simulation accuracy of soil types with both contributions from a legacy map and limited sample data. The method indicates the following characteristics: (1) if a soil type indicates no change in an update survey or it has been reclassified into another type that similarly evinces no change, it will be simply reproduced in the updated map; (2) if a soil type has changes in some places, it will be simulated with uncertainty quantified by occurrence probability maps; (3) if a soil type has no change in an area but evinces changes in other distant areas, it still can be captured in the area with unobvious uncertainty. We concluded that Co-MCSS might be a practical method for updating categorical soil maps with limited survey data. PMID:24027447

Symptom-based categorization of in-flight passenger medical incidents.

PubMed

Mahony, Paul H; Myers, Julia A; Larsen, Peter D; Powell, David M C; Griffiths, Robin F

2011-12-01

The majority of in-flight passenger medical events are managed by cabin crew. Our study aimed to evaluate the reliability of cabin crew reports of in-flight medical events and to develop a symptom-based categorization system. All cabin crew in-flight passenger medical incident reports for an airline over a 9-yr period were examined retrospectively. Validation of incident descriptions were undertaken on a sample of 162 cabin crew reports where medically trained persons' reports were available for comparison using a three Round Delphi technique and testing concordance using Cohen's Kappa. A hierarchical symptom-based categorization system was designed and validated. The rate was 159 incidents per 106 passengers carried, or 70.4/113.3 incidents per 106 revenue passenger kilometres/miles, respectively. Concordance between cabin crew and medical reports was 96%, with a high validity rating (mean 4.6 on a 1-5 scale) and high Cohen's Kappa (0.94). The most common in-flight medical events were transient loss of consciousness (41%), nausea/vomiting/diarrhea (19.5%), and breathing difficulty (16%). Cabin crew records provide reliable data regarding in-flight passenger medical incidents, complementary to diagnosis-based systems, and allow the use of currently underutilized data. The categorization system provides a means for tracking passenger medical incidents internationally and an evidence base for cabin crew first aid training.

A probabilistic model of cross-categorization.

PubMed

Shafto, Patrick; Kemp, Charles; Mansinghka, Vikash; Tenenbaum, Joshua B

2011-07-01

Most natural domains can be represented in multiple ways: we can categorize foods in terms of their nutritional content or social role, animals in terms of their taxonomic groupings or their ecological niches, and musical instruments in terms of their taxonomic categories or social uses. Previous approaches to modeling human categorization have largely ignored the problem of cross-categorization, focusing on learning just a single system of categories that explains all of the features. Cross-categorization presents a difficult problem: how can we infer categories without first knowing which features the categories are meant to explain? We present a novel model that suggests that human cross-categorization is a result of joint inference about multiple systems of categories and the features that they explain. We also formalize two commonly proposed alternative explanations for cross-categorization behavior: a features-first and an objects-first approach. The features-first approach suggests that cross-categorization is a consequence of attentional processes, where features are selected by an attentional mechanism first and categories are derived second. The objects-first approach suggests that cross-categorization is a consequence of repeated, sequential attempts to explain features, where categories are derived first, then features that are poorly explained are recategorized. We present two sets of simulations and experiments testing the models' predictions about human categorization. We find that an approach based on joint inference provides the best fit to human categorization behavior, and we suggest that a full account of human category learning will need to incorporate something akin to these capabilities. Copyright © 2011 Elsevier B.V. All rights reserved.

Error Discounting in Probabilistic Category Learning

PubMed Central

Craig, Stewart; Lewandowsky, Stephan; Little, Daniel R.

2011-01-01

Some current theories of probabilistic categorization assume that people gradually attenuate their learning in response to unavoidable error. However, existing evidence for this error discounting is sparse and open to alternative interpretations. We report two probabilistic-categorization experiments that investigated error discounting by shifting feedback probabilities to new values after different amounts of training. In both experiments, responding gradually became less responsive to errors, and learning was slowed for some time after the feedback shift. Both results are indicative of error discounting. Quantitative modeling of the data revealed that adding a mechanism for error discounting significantly improved the fits of an exemplar-based and a rule-based associative learning model, as well as of a recency-based model of categorization. We conclude that error discounting is an important component of probabilistic learning. PMID:21355666

The Bayesian Evaluation of Categorization Models: Comment on Wills and Pothos (2012)

ERIC Educational Resources Information Center

Vanpaemel, Wolf; Lee, Michael D.

2012-01-01

Wills and Pothos (2012) reviewed approaches to evaluating formal models of categorization, raising a series of worthwhile issues, challenges, and goals. Unfortunately, in discussing these issues and proposing solutions, Wills and Pothos (2012) did not consider Bayesian methods in any detail. This means not only that their review excludes a major…

Tests of the accuracy and speed of categorizing foods into child vs. professional categories using two methods of browsing with children.

USDA-ARS?s Scientific Manuscript database

This research tested whether children could categorize foods more accurately and speedily when presented with child-generated rather than professionally-generated food categories; and whether a graphically appealing browse procedure similar to the Apple, Inc, "cover flow" graphical user interface ac...

Psychophysical Boundary for Categorization of Voiced-Voiceless Stop Consonants in Native Japanese Speakers

ERIC Educational Resources Information Center

Tamura, Shunsuke; Ito, Kazuhito; Hirose, Nobuyuki; Mori, Shuji

2018-01-01

Purpose: The purpose of this study was to investigate the psychophysical boundary used for categorization of voiced-voiceless stop consonants in native Japanese speakers. Method: Twelve native Japanese speakers participated in the experiment. The stimuli were synthetic stop consonant-vowel stimuli varying in voice onset time (VOT) with…

Regression Methods for Categorical Dependent Variables: Effects on a Model of Student College Choice

ERIC Educational Resources Information Center

Rapp, Kelly E.

2012-01-01

The use of categorical dependent variables with the classical linear regression model (CLRM) violates many of the model's assumptions and may result in biased estimates (Long, 1997; O'Connell, Goldstein, Rogers, & Peng, 2008). Many dependent variables of interest to educational researchers (e.g., professorial rank, educational attainment) are…

Item Factor Analysis: Current Approaches and Future Directions

ERIC Educational Resources Information Center

Wirth, R. J.; Edwards, Michael C.

2007-01-01

The rationale underlying factor analysis applies to continuous and categorical variables alike; however, the models and estimation methods for continuous (i.e., interval or ratio scale) data are not appropriate for item-level data that are categorical in nature. The authors provide a targeted review and synthesis of the item factor analysis (IFA)…

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Detection and categorization of bacteria habitats using shallow linguistic analysis

PubMed Central

2015-01-01

Background Information regarding bacteria biotopes is important for several research areas including health sciences, microbiology, and food processing and preservation. One of the challenges for scientists in these domains is the huge amount of information buried in the text of electronic resources. Developing methods to automatically extract bacteria habitat relations from the text of these electronic resources is crucial for facilitating research in these areas. Methods We introduce a linguistically motivated rule-based approach for recognizing and normalizing names of bacteria habitats in biomedical text by using an ontology. Our approach is based on the shallow syntactic analysis of the text that include sentence segmentation, part-of-speech (POS) tagging, partial parsing, and lemmatization. In addition, we propose two methods for identifying bacteria habitat localization relations. The underlying assumption for the first method is that discourse changes with a new paragraph. Therefore, it operates on a paragraph-basis. The second method performs a more fine-grained analysis of the text and operates on a sentence-basis. We also develop a novel anaphora resolution method for bacteria coreferences and incorporate it with the sentence-based relation extraction approach. Results We participated in the Bacteria Biotope (BB) Task of the BioNLP Shared Task 2013. Our system (Boun) achieved the second best performance with 68% Slot Error Rate (SER) in Sub-task 1 (Entity Detection and Categorization), and ranked third with an F-score of 27% in Sub-task 2 (Localization Event Extraction). This paper reports the system that is implemented for the shared task, including the novel methods developed and the improvements obtained after the official evaluation. The extensions include the expansion of the OntoBiotope ontology using the training set for Sub-task 1, and the novel sentence-based relation extraction method incorporated with anaphora resolution for Sub-task 2. These extensions resulted in promising results for Sub-task 1 with a SER of 68%, and state-of-the-art performance for Sub-task 2 with an F-score of 53%. Conclusions Our results show that a linguistically-oriented approach based on the shallow syntactic analysis of the text is as effective as machine learning approaches for the detection and ontology-based normalization of habitat entities. Furthermore, the newly developed sentence-based relation extraction system with the anaphora resolution module significantly outperforms the paragraph-based one, as well as the other systems that participated in the BB Shared Task 2013. PMID:26201262

Global Infrasound Association Based on Probabilistic Clutter Categorization

NASA Astrophysics Data System (ADS)

Arora, Nimar; Mialle, Pierrick

2016-04-01

The IDC advances its methods and continuously improves its automatic system for the infrasound technology. The IDC focuses on enhancing the automatic system for the identification of valid signals and the optimization of the network detection threshold by identifying ways to refine signal characterization methodology and association criteria. An objective of this study is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the reviewed event bulletins. Indeed, a considerable number of signal detections are due to local clutter sources such as microbaroms, waterfalls, dams, gas flares, surf (ocean breaking waves) etc. These sources are either too diffuse or too local to form events. Worse still, the repetitive nature of this clutter leads to a large number of false event hypotheses due to the random matching of clutter at multiple stations. Previous studies, for example [1], have worked on categorization of clutter using long term trends on detection azimuth, frequency, and amplitude at each station. In this work we continue the same line of reasoning to build a probabilistic model of clutter that is used as part of NETVISA [2], a Bayesian approach to network processing. The resulting model is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] Infrasound categorization Towards a statistics based approach. J. Vergoz, P. Gaillard, A. Le Pichon, N. Brachet, and L. Ceranna. ITW 2011 [2] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013

A review on creatinine measurement techniques.

PubMed

Mohabbati-Kalejahi, Elham; Azimirad, Vahid; Bahrami, Manouchehr; Ganbari, Ahmad

2012-08-15

This paper reviews the entire recent global tendency for creatinine measurement. Creatinine biosensors involve complex relationships between biology and micro-mechatronics to which the blood is subjected. Comparison between new and old methods shows that new techniques (e.g. Molecular Imprinted Polymers based algorithms) are better than old methods (e.g. Elisa) in terms of stability and linear range. All methods and their details for serum, plasma, urine and blood samples are surveyed. They are categorized into five main algorithms: optical, electrochemical, impedometrical, Ion Selective Field-Effect Transistor (ISFET) based technique and chromatography. Response time, detection limit, linear range and selectivity of reported sensors are discussed. Potentiometric measurement technique has the lowest response time of 4-10 s and the lowest detection limit of 0.28 nmol L(-1) belongs to chromatographic technique. Comparison between various techniques of measurements indicates that the best selectivity belongs to MIP based and chromatographic techniques. Copyright © 2012 Elsevier B.V. All rights reserved.

Spatial generalised linear mixed models based on distances.

PubMed

Melo, Oscar O; Mateu, Jorge; Melo, Carlos E

2016-10-01

Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.

Cognitive load privileges memory-based over data-driven processing, not group-level over person-level processing.

PubMed

Skorich, Daniel P; Mavor, Kenneth I

2013-09-01

In the current paper, we argue that categorization and individuation, as traditionally discussed and as experimentally operationalized, are defined in terms of two confounded underlying dimensions: a person/group dimension and a memory-based/data-driven dimension. In a series of three experiments, we unconfound these dimensions and impose a cognitive load. Across the three experiments, two with laboratory-created targets and one with participants' friends as the target, we demonstrate that cognitive load privileges memory-based over data-driven processing, not group- over person-level processing. We discuss the results in terms of their implications for conceptualizations of the categorization/individuation distinction, for the equivalence of person and group processes, for the ultimate 'purpose' and meaningfulness of group-based perception and, fundamentally, for the process of categorization, broadly defined. © 2012 The British Psychological Society.

Visual categorization of natural movies by rats.

PubMed

Vinken, Kasper; Vermaercke, Ben; Op de Beeck, Hans P

2014-08-06

Visual categorization of complex, natural stimuli has been studied for some time in human and nonhuman primates. Recent interest in the rodent as a model for visual perception, including higher-level functional specialization, leads to the question of how rodents would perform on a categorization task using natural stimuli. To answer this question, rats were trained in a two-alternative forced choice task to discriminate movies containing rats from movies containing other objects and from scrambled movies (ordinate-level categorization). Subsequently, transfer to novel, previously unseen stimuli was tested, followed by a series of control probes. The results show that the animals are capable of acquiring a decision rule by abstracting common features from natural movies to generalize categorization to new stimuli. Control probes demonstrate that they did not use single low-level features, such as motion energy or (local) luminance. Significant generalization was even present with stationary snapshots from untrained movies. The variability within and between training and test stimuli, the complexity of natural movies, and the control experiments and analyses all suggest that a more high-level rule based on more complex stimulus features than local luminance-based cues was used to classify the novel stimuli. In conclusion, natural stimuli can be used to probe ordinate-level categorization in rats. Copyright © 2014 the authors 0270-6474/14/3410645-14$15.00/0.

[The triad configuration, humanist-existential-personal: a theoretical and methodological approach to psychiatric and mental health nursing].

PubMed

Vietta, E P

1995-01-01

The author establishes a research line based on a theoretical-methodological referential for the qualitative investigation of psychiatric nursing and mental health. Aspects of humanist and existential philosophies and personalism were evaluated integrating them in a unique perspective. In order to maintain the scientific method of research in this referential the categorization process which will be adopted in this kind of investigation was explained.

What information is necessary for speech categorization? Harnessing variability in the speech signal by integrating cues computed relative to expectations

PubMed Central

McMurray, Bob; Jongman, Allard

2012-01-01

Most theories of categorization emphasize how continuous perceptual information is mapped to categories. However, equally important is the informational assumptions of a model, the type of information subserving this mapping. This is crucial in speech perception where the signal is variable and context-dependent. This study assessed the informational assumptions of several models of speech categorization, in particular, the number of cues that are the basis of categorization and whether these cues represent the input veridically or have undergone compensation. We collected a corpus of 2880 fricative productions (Jongman, Wayland & Wong, 2000) spanning many talker- and vowel-contexts and measured 24 cues for each. A subset was also presented to listeners in an 8AFC phoneme categorization task. We then trained a common classification model based on logistic regression to categorize the fricative from the cue values, and manipulated the information in the training set to contrast 1) models based on a small number of invariant cues; 2) models using all cues without compensation, and 3) models in which cues underwent compensation for contextual factors. Compensation was modeled by Computing Cues Relative to Expectations (C-CuRE), a new approach to compensation that preserves fine-grained detail in the signal. Only the compensation model achieved a similar accuracy to listeners, and showed the same effects of context. Thus, even simple categorization metrics can overcome the variability in speech when sufficient information is available and compensation schemes like C-CuRE are employed. PMID:21417542

A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network

PubMed Central

Ahmed, Afaz Uddin; Tariqul Islam, Mohammad; Ismail, Mahamod; Kibria, Salehin; Arshad, Haslina

2014-01-01

An artificial neural network (ANN) and affinity propagation (AP) algorithm based user categorization technique is presented. The proposed algorithm is designed for closed access femtocell network. ANN is used for user classification process and AP algorithm is used to optimize the ANN training process. AP selects the best possible training samples for faster ANN training cycle. The users are distinguished by using the difference of received signal strength in a multielement femtocell device. A previously developed directive microstrip antenna is used to configure the femtocell device. Simulation results show that, for a particular house pattern, the categorization technique without AP algorithm takes 5 indoor users and 10 outdoor users to attain an error-free operation. While integrating AP algorithm with ANN, the system takes 60% less training samples reducing the training time up to 50%. This procedure makes the femtocell more effective for closed access operation. PMID:25133214

A novel user classification method for femtocell network by using affinity propagation algorithm and artificial neural network.

PubMed

Ahmed, Afaz Uddin; Islam, Mohammad Tariqul; Ismail, Mahamod; Kibria, Salehin; Arshad, Haslina

2014-01-01

An artificial neural network (ANN) and affinity propagation (AP) algorithm based user categorization technique is presented. The proposed algorithm is designed for closed access femtocell network. ANN is used for user classification process and AP algorithm is used to optimize the ANN training process. AP selects the best possible training samples for faster ANN training cycle. The users are distinguished by using the difference of received signal strength in a multielement femtocell device. A previously developed directive microstrip antenna is used to configure the femtocell device. Simulation results show that, for a particular house pattern, the categorization technique without AP algorithm takes 5 indoor users and 10 outdoor users to attain an error-free operation. While integrating AP algorithm with ANN, the system takes 60% less training samples reducing the training time up to 50%. This procedure makes the femtocell more effective for closed access operation.

Influence of internship toward entrepreneurship interest for mechanical engineering students

NASA Astrophysics Data System (ADS)

Sunyoto, Nugroho, Agus; Ulum, Miftakhul

2017-03-01

This study was aimed to determine the influence of internship toward students' entrepreneurship interest. Mechanical Engineering Education students from 2013 Batch who had the internship from Engineering Faculty at Semarang State University are the subject of this study. Data was collected through questionnaire and analyzed by simple regression analysis method. The internship subject score and entrepreneurship are categorized in very good level in which the average is 87.08% and 85.61%. However, the influence of internship toward students' interest is categorized in low level in which the average score is 7.9%. Internship section shall encourage students to study entrepreneurship aspects during the internship for entrepreneurship interest improvement and the students' preparation once they graduated. Description scoring standard is needed for scoring the students although they conduct their internship at different locations and companies. The students are highly recommended to conduct an an internship at entrepreneurship-based companies.

Toddlers' categorization of typical and scrambled dolls and cars.

PubMed

Heron, Michelle; Slaughter, Virginia

2008-09-01

Previous research has demonstrated discrimination of scrambled from typical human body shapes at 15-18 months of age [Slaughter, V., & Heron, M. (2004). Origins and early development of human body knowledge. Monographs of the Society for Research in Child Development, 69]. In the current study 18-, 24- and 30-month-old infants were presented with four typical and four scrambled dolls in a sequential touching procedure, to assess the development of explicit categorization of human body shapes. Infants were also presented with typical and scrambled cars, allowing comparison of infants' categorization of scrambled and typical exemplars in a different domain. Spontaneous comments regarding category membership were recorded. Girls categorized dolls and cars as typical or scrambled at 30 months, whereas boys only categorized the cars. Earliest categorization was for typical and scrambled cars, at 24 months, but only for boys. Language-based knowledge, coded from infants' comments, followed the same pattern. This suggests that human body knowledge does not have privileged status in infancy. Gender differences in performance are discussed.

Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual Categorization

PubMed Central

Sofer, Imri; Crouzet, Sébastien M.; Serre, Thomas

2015-01-01

Observers can rapidly perform a variety of visual tasks such as categorizing a scene as open, as outdoor, or as a beach. Although we know that different tasks are typically associated with systematic differences in behavioral responses, to date, little is known about the underlying mechanisms. Here, we implemented a single integrated paradigm that links perceptual processes with categorization processes. Using a large image database of natural scenes, we trained machine-learning classifiers to derive quantitative measures of task-specific perceptual discriminability based on the distance between individual images and different categorization boundaries. We showed that the resulting discriminability measure accurately predicts variations in behavioral responses across categorization tasks and stimulus sets. We further used the model to design an experiment, which challenged previous interpretations of the so-called “superordinate advantage.” Overall, our study suggests that observed differences in behavioral responses across rapid categorization tasks reflect natural variations in perceptual discriminability. PMID:26335683

Extending Intergroup Theorizing to the Instructional Context: Testing a Model of Teacher Communication Behaviors, Credibility, Group-Based Categorization, and Instructional Outcomes

ERIC Educational Resources Information Center

Hosek, Angela M.

2011-01-01

The purpose of this study was to determine how students' (N =348) perceptions of teachers' communication behaviors predicted the extent to which students believed they shared similar group-based categorizations with their teachers and how, if at all, these beliefs impacted instructional outcomes. This study was grounded in Social Identity Theory,…

Image analysis by integration of disparate information

NASA Technical Reports Server (NTRS)

Lemoigne, Jacqueline

1993-01-01

Image analysis often starts with some preliminary segmentation which provides a representation of the scene needed for further interpretation. Segmentation can be performed in several ways, which are categorized as pixel based, edge-based, and region-based. Each of these approaches are affected differently by various factors, and the final result may be improved by integrating several or all of these methods, thus taking advantage of their complementary nature. In this paper, we propose an approach that integrates pixel-based and edge-based results by utilizing an iterative relaxation technique. This approach has been implemented on a massively parallel computer and tested on some remotely sensed imagery from the Landsat-Thematic Mapper (TM) sensor.

Are all types of expertise created equal? Car experts use different spatial frequency scales for subordinate categorization of cars and faces.

PubMed

Harel, Assaf; Bentin, Shlomo

2013-01-01

A much-debated question in object recognition is whether expertise for faces and expertise for non-face objects utilize common perceptual information. We investigated this issue by assessing the diagnostic information required for different types of expertise. Specifically, we asked whether face categorization and expert car categorization at the subordinate level relies on the same spatial frequency (SF) scales. Fifteen car experts and fifteen novices performed a category verification task with spatially filtered images of faces, cars, and airplanes. Images were categorized based on their basic (e.g. "car") and subordinate level (e.g. "Japanese car") identity. The effect of expertise was not evident when objects were categorized at the basic level. However, when the car experts categorized faces and cars at the subordinate level, the two types of expertise required different kinds of SF information. Subordinate categorization of faces relied on low SFs more than on high SFs, whereas subordinate expert car categorization relied on high SFs more than on low SFs. These findings suggest that expertise in the recognition of objects and faces do not utilize the same type of information. Rather, different types of expertise require different types of diagnostic visual information.

Are All Types of Expertise Created Equal? Car Experts Use Different Spatial Frequency Scales for Subordinate Categorization of Cars and Faces

PubMed Central

Harel, Assaf; Bentin, Shlomo

2013-01-01

A much-debated question in object recognition is whether expertise for faces and expertise for non-face objects utilize common perceptual information. We investigated this issue by assessing the diagnostic information required for different types of expertise. Specifically, we asked whether face categorization and expert car categorization at the subordinate level relies on the same spatial frequency (SF) scales. Fifteen car experts and fifteen novices performed a category verification task with spatially filtered images of faces, cars, and airplanes. Images were categorized based on their basic (e.g. “car”) and subordinate level (e.g. “Japanese car”) identity. The effect of expertise was not evident when objects were categorized at the basic level. However, when the car experts categorized faces and cars at the subordinate level, the two types of expertise required different kinds of SF information. Subordinate categorization of faces relied on low SFs more than on high SFs, whereas subordinate expert car categorization relied on high SFs more than on low SFs. These findings suggest that expertise in the recognition of objects and faces do not utilize the same type of information. Rather, different types of expertise require different types of diagnostic visual information. PMID:23826188

Experiments on Supervised Learning Algorithms for Text Categorization

NASA Technical Reports Server (NTRS)

Namburu, Setu Madhavi; Tu, Haiying; Luo, Jianhui; Pattipati, Krishna R.

2005-01-01

Modern information society is facing the challenge of handling massive volume of online documents, news, intelligence reports, and so on. How to use the information accurately and in a timely manner becomes a major concern in many areas. While the general information may also include images and voice, we focus on the categorization of text data in this paper. We provide a brief overview of the information processing flow for text categorization, and discuss two supervised learning algorithms, viz., support vector machines (SVM) and partial least squares (PLS), which have been successfully applied in other domains, e.g., fault diagnosis [9]. While SVM has been well explored for binary classification and was reported as an efficient algorithm for text categorization, PLS has not yet been applied to text categorization. Our experiments are conducted on three data sets: Reuter's- 21578 dataset about corporate mergers and data acquisitions (ACQ), WebKB and the 20-Newsgroups. Results show that the performance of PLS is comparable to SVM in text categorization. A major drawback of SVM for multi-class categorization is that it requires a voting scheme based on the results of pair-wise classification. PLS does not have this drawback and could be a better candidate for multi-class text categorization.

Prototype Abstraction by Monkeys ("Macaca Mulatta")

ERIC Educational Resources Information Center

Smith, J. David; Redford, Joshua S.; Haas, Sarah M.

2008-01-01

The authors analyze the shape categorization of rhesus monkeys ("Macaca mulatta") and the role of prototype- and exemplar-based comparison processes in monkeys' category learning. Prototype and exemplar theories make contrasting predictions regarding performance on the Posner-Homa dot-distortion categorization task. Prototype theory--which…

Overdistribution illusions: Categorical judgments produce them, confidence ratings reduce them.

PubMed

Brainerd, C J; Nakamura, K; Reyna, V F; Holliday, R E

2017-01-01

Overdistribution is a form of memory distortion in which an event is remembered as belonging to too many episodic states, states that are logically or empirically incompatible with each other. We investigated a response formatting method of suppressing 2 basic types of overdistribution, disjunction and conjunction illusions, which parallel some classic illusions in the judgment and decision making literature. In this method, subjects respond to memory probes by rating their confidence that test cues belong to specific episodic states (e.g., presented on List 1, presented on List 2), rather than by making the usual categorical judgments about those states. The central prediction, which was derived from the task calibration principle of fuzzy-trace theory, was that confidence ratings should reduce overdistribution by diminishing subjects' reliance on noncompensatory gist memories. The data of 3 experiments agreed with that prediction. In Experiment 1, there were reliable disjunction illusions with categorical judgments but not with confidence ratings. In Experiment 2, both response formats produced reliable disjunction illusions, but those for confidence ratings were much smaller than those for categorical judgments. In Experiment 3, there were reliable conjunction illusions with categorical judgments but not with confidence ratings. Apropos of recent controversies over confidence-accuracy correlations in memory, such correlations were positive for hits, negative for correct rejections, and the 2 types of correlations were of equal magnitude. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Overdistribution Illusions: Categorical Judgments Produce Them, Confidence Ratings Reduce Them

PubMed Central

Brainerd, C. J.; Nakamura, K.; Reyna, V. F.; Holliday, R. E.

2017-01-01

Overdistribution is a form of memory distortion in which an event is remembered as belonging to too many episodic states, states that are logically or empirically incompatible with each other. We investigated a response formatting method of suppressing two basic types of overdistribution, disjunction and conjunction illusions, which parallel some classic illusions in the judgment and decision making literature. In this method, subjects respond to memory probes by rating their confidence that test cues belong to specific episodic states (e.g., presented on List 1, presented on List 2), rather than by making the usual categorical judgments about those states. The central prediction, which was derived from the task calibration principle of fuzzy-trace theory, was that confidence ratings should reduce overdistribution by diminishing subjects’ reliance on noncompensatory gist memories. The data of three experiments agreed with that prediction. In Experiment 1, there were reliable disjunction illusions with categorical judgments but not with confidence ratings. In Experiment 2, both response formats produced reliable disjunction illusions, but those for confidence ratings were much smaller than those for categorical judgments. In Experiment 3, there were reliable conjunction illusions with categorical judgments but not with confidence ratings. Apropos of recent controversies over confidence-accuracy correlations in memory, such correlations were positive for hits, negative for correct rejections, and the two types of correlations were of equal magnitude. PMID:28054811

Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys

ERIC Educational Resources Information Center

Si, Yajuan; Reiter, Jerome P.

2013-01-01

In many surveys, the data comprise a large number of categorical variables that suffer from item nonresponse. Standard methods for multiple imputation, like log-linear models or sequential regression imputation, can fail to capture complex dependencies and can be difficult to implement effectively in high dimensions. We present a fully Bayesian,…

Text Categorization for Multi-Page Documents: A Hybrid Naive Bayes HMM Approach.

ERIC Educational Resources Information Center

Frasconi, Paolo; Soda, Giovanni; Vullo, Alessandro

Text categorization is typically formulated as a concept learning problem where each instance is a single isolated document. This paper is interested in a more general formulation where documents are organized as page sequences, as naturally occurring in digital libraries of scanned books and magazines. The paper describes a method for classifying…

Emotions in "Black and White" or Shades of Gray? How We Think About Emotion Shapes Our Perception and Neural Representation of Emotion.

PubMed

Satpute, Ajay B; Nook, Erik C; Narayanan, Sandhya; Shu, Jocelyn; Weber, Jochen; Ochsner, Kevin N

2016-11-01

The demands of social life often require categorically judging whether someone's continuously varying facial movements express "calm" or "fear," or whether one's fluctuating internal states mean one feels "good" or "bad." In two studies, we asked whether this kind of categorical, "black and white," thinking can shape the perception and neural representation of emotion. Using psychometric and neuroimaging methods, we found that (a) across participants, judging emotions using a categorical, "black and white" scale relative to judging emotions using a continuous, "shades of gray," scale shifted subjective emotion perception thresholds; (b) these shifts corresponded with activity in brain regions previously associated with affective responding (i.e., the amygdala and ventral anterior insula); and (c) connectivity of these regions with the medial prefrontal cortex correlated with the magnitude of categorization-related shifts. These findings suggest that categorical thinking about emotions may actively shape the perception and neural representation of the emotions in question. © The Author(s) 2016.

Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis.

PubMed

Li, Bo; Tang, Jing; Yang, Qingxia; Cui, Xuejiao; Li, Shuang; Chen, Sijie; Cao, Quanxing; Xue, Weiwei; Chen, Na; Zhu, Feng

2016-12-13

In untargeted metabolomics analysis, several factors (e.g., unwanted experimental &biological variations and technical errors) may hamper the identification of differential metabolic features, which requires the data-driven normalization approaches before feature selection. So far, ≥16 normalization methods have been widely applied for processing the LC/MS based metabolomics data. However, the performance and the sample size dependence of those methods have not yet been exhaustively compared and no online tool for comparatively and comprehensively evaluating the performance of all 16 normalization methods has been provided. In this study, a comprehensive comparison on these methods was conducted. As a result, 16 methods were categorized into three groups based on their normalization performances across various sample sizes. The VSN, the Log Transformation and the PQN were identified as methods of the best normalization performance, while the Contrast consistently underperformed across all sub-datasets of different benchmark data. Moreover, an interactive web tool comprehensively evaluating the performance of 16 methods specifically for normalizing LC/MS based metabolomics data was constructed and hosted at http://server.idrb.cqu.edu.cn/MetaPre/. In summary, this study could serve as a useful guidance to the selection of suitable normalization methods in analyzing the LC/MS based metabolomics data.

Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis

PubMed Central

Li, Bo; Tang, Jing; Yang, Qingxia; Cui, Xuejiao; Li, Shuang; Chen, Sijie; Cao, Quanxing; Xue, Weiwei; Chen, Na; Zhu, Feng

2016-01-01

In untargeted metabolomics analysis, several factors (e.g., unwanted experimental & biological variations and technical errors) may hamper the identification of differential metabolic features, which requires the data-driven normalization approaches before feature selection. So far, ≥16 normalization methods have been widely applied for processing the LC/MS based metabolomics data. However, the performance and the sample size dependence of those methods have not yet been exhaustively compared and no online tool for comparatively and comprehensively evaluating the performance of all 16 normalization methods has been provided. In this study, a comprehensive comparison on these methods was conducted. As a result, 16 methods were categorized into three groups based on their normalization performances across various sample sizes. The VSN, the Log Transformation and the PQN were identified as methods of the best normalization performance, while the Contrast consistently underperformed across all sub-datasets of different benchmark data. Moreover, an interactive web tool comprehensively evaluating the performance of 16 methods specifically for normalizing LC/MS based metabolomics data was constructed and hosted at http://server.idrb.cqu.edu.cn/MetaPre/. In summary, this study could serve as a useful guidance to the selection of suitable normalization methods in analyzing the LC/MS based metabolomics data. PMID:27958387

Participatory Design in Gerontechnology: A Systematic Literature Review.

PubMed

Merkel, Sebastian; Kucharski, Alexander

2018-05-19

Participatory design (PD) is widely used within gerontechnology but there is no common understanding about which methods are used for what purposes. This review aims to examine what different forms of PD exist in the field of gerontechnology and how these can be categorized. We conducted a systematic literature review covering several databases. The search strategy was based on 3 elements: (1) participatory methods and approaches with (2) older persons aiming at developing (3) technology for older people. Our final review included 26 studies representing a variety of technologies designed/developed and methods/instruments applied. According to the technologies, the publications reviewed can be categorized in 3 groups: Studies that (1) use already existing technology with the aim to find new ways of use; (2) aim at creating new devices; (3) test and/or modify prototypes. The implementation of PD depends on the questions: Why a participatory approach is applied, who is involved as future user(s), when those future users are involved, and how they are incorporated into the innovation process. There are multiple ways, methods, and instruments to integrate users into the innovation process. Which methods should be applied, depends on the context. However, most studies do not evaluate if participatory approaches will lead to a better acceptance and/or use of the co-developed products. Therefore, participatory design should follow a comprehensive strategy, starting with the users' needs and ending with an evaluation if the applied methods have led to better results.

A conflict-based model of color categorical perception: evidence from a priming study.

PubMed

Hu, Zhonghua; Hanley, J Richard; Zhang, Ruiling; Liu, Qiang; Roberson, Debi

2014-10-01

Categorical perception (CP) of color manifests as faster or more accurate discrimination of two shades of color that straddle a category boundary (e.g., one blue and one green) than of two shades from within the same category (e.g., two different shades of green), even when the differences between the pairs of colors are equated according to some objective metric. The results of two experiments provide new evidence for a conflict-based account of this effect, in which CP is caused by competition between visual and verbal/categorical codes on within-category trials. According to this view, conflict arises because the verbal code indicates that the two colors are the same, whereas the visual code indicates that they are different. In Experiment 1, two shades from the same color category were discriminated significantly faster when the previous trial also comprised a pair of within-category colors than when the previous trial comprised a pair from two different color categories. Under the former circumstances, the CP effect disappeared. According to the conflict-based model, response conflict between visual and categorical codes during discrimination of within-category pairs produced an adjustment of cognitive control that reduced the weight given to the categorical code relative to the visual code on the subsequent trial. Consequently, responses on within-category trials were facilitated, and CP effects were reduced. The effectiveness of this conflict-based account was evaluated in comparison with an alternative view that CP reflects temporary warping of perceptual space at the boundaries between color categories.

Assessing Repetitive Negative Thinking Using Categorical and Transdiagnostic Approaches: A Comparison and Validation of Three Polish Language Adaptations of Self-Report Questionnaires.

PubMed

Kornacka, Monika; Buczny, Jacek; Layton, Rebekah L

2016-01-01

Repetitive negative thinking (RNT) is a transdiagnostic process involved in the risk, maintenance, and relapse of serious conditions including mood disorders, anxiety, eating disorders, and addictions. Processing mode theory provides a theoretical model to assess, research, and treat RNT using a transdiagnostic approach. Clinical researchers also often employ categorical approaches to RNT, including a focus on depressive rumination or worry, for similar purposes. Three widely used self-report questionnaires have been developed to assess these related constructs: the Ruminative Response Scale (RRS), the Perseverative Thinking Questionnaire (PTQ), and the Mini-Cambridge Exeter Repetitive Thought Scale (Mini-CERTS). Yet these scales have not previously been used in conjunction, despite useful theoretical distinctions only available in Mini-CERTS. The present validation of the methods in a Polish speaking population provides psychometric parameters estimates that contribute to current efforts to increase reliable replication of theoretical outcomes. Moreover, the following study aims to present particular characteristics and a comparison of the three methods. Although there has been some exploration of a categorical approach, the comparison of transdiagnostic methods is still lacking. These methods are particularly relevant for developing and evaluating theoretically based interventions like concreteness training, an emerging field of increasing interest, which can be used to address the maladaptive processing mode in RNT that can lead to depression and other disorders. Furthermore, the translation of these measures enables the examination of possible cross-cultural structural differences that may lead to important theoretical progress in the measurement and classification of RNT. The results support the theoretical hypothesis. As expected, the dimensions of brooding, general repetitive negative thinking, as well as abstract analytical thinking, can all be classified as unconstructive repetitive thinking. The particular characteristics of each scale and potential practical applications in clinical and research are discussed.

Curbing-The Metallic Mode In-between: An empirical study qualifying and categorizing restrained sounds known as Curbing based on audio perception, laryngostroboscopic imaging, acoustics, LTAS, and EGG.

PubMed

Thuesen, Mathias Aaen; McGlashan, Julian; Sadolin, Cathrine

2017-09-01

This study aims to study the categorization Curbing from the pedagogical method Complete Vocal Technique as a reduced metallic mode compared with the full metallic modes Overdrive and Edge by means of audio perception, laryngostroboscopic imaging, acoustics, long-term average spectrum (LTAS), and electroglottography (EGG). Twenty singers were recorded singing sustained vowels in a restrained character known as Curbing. Two studies were performed: (1) laryngostroboscopic examination using a videonasoendoscopic camera system and the Laryngostrobe program; and (2) simultaneous recording of EGG and acoustic signals using Speech Studio. Images were analyzed based on consensus agreement. Statistical analysis of acoustic, LTAS, and EGG parameters was undertaken using Student paired t tests. The reduced metallic singing mode Curbing has an identifiable laryngeal gesture. Curbing has a more open setting than Overdrive and Edge, with high visibility of the vocal folds, and the false folds giving a rectangular appearance. LTAS showed statistically significant differences between Curbing and the full metallic modes, with less energy across all spectra, yielding a high second and a low third harmonic. Statistically significant differences were identified on Max Qx, Average Qx, Shimmer+, Shimmer-, Shimmer dB, normalized noise energy, cepstral peak prominence, harmonics-to-noise ratio, and mean sound pressure level (P ≤ 0.05). Curbing as a voice production strategy is statistically significantly different from Overdrive and Edge, and can be categorized based on audio perception. This study demonstrates consistently different laryngeal gestures between Curbing and Overdrive and Edge, with high corresponding differences in LTAS, EGG and acoustic measures. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Metacognitive deficits in categorization tasks in a population with impaired inner speech.

PubMed

Langland-Hassan, Peter; Gauker, Christopher; Richardson, Michael J; Dietz, Aimee; Faries, Frank R

2017-11-01

This study examines the relation of language use to a person's ability to perform categorization tasks and to assess their own abilities in those categorization tasks. A silent rhyming task was used to confirm that a group of people with post-stroke aphasia (PWA) had corresponding covert language production (or "inner speech") impairments. The performance of the PWA was then compared to that of age- and education-matched healthy controls on three kinds of categorization tasks and on metacognitive self-assessments of their performance on those tasks. The PWA showed no deficits in their ability to categorize objects for any of the three trial types (visual, thematic, and categorial). However, on the categorial trials, their metacognitive assessments of whether they had categorized correctly were less reliable than those of the control group. The categorial trials were distinguished from the others by the fact that the categorization could not be based on some immediately perceptible feature or on the objects' being found together in a type of scenario or setting. This result offers preliminary evidence for a link between covert language use and a specific form of metacognition. Copyright © 2017 Elsevier B.V. All rights reserved.

Use of a validated algorithm to estimate the annual cost of effective biologic treatment for rheumatoid arthritis.

PubMed

Curtis, Jeffrey R; Schabert, Vernon F; Yeaw, Jason; Korn, Jonathan R; Quach, Caroleen; Harrison, David J; Yun, Huifeng; Joseph, George J; Collier, David

2014-08-01

To estimate biologic cost per effectively treated patient with rheumatoid arthritis (RA) using a claims-based algorithm for effectiveness. Patients with RA aged 18-63 years in the IMS PharMetrics Plus database were categorized as effectively treated if they met all six criteria: (1) a medication possession ratio ≥80% (subcutaneous) or at least as many infusions as specified in US labeling (intravenous); (2) no biologic dose increase; (3) no biologic switch; (4) no new non-biologic disease-modifying anti-rheumatic drug; (5) no new or increased oral glucocorticoid; and (6) ≤1 glucocorticoid injection. Biologic cost per effectively treated patient was defined as total cost of the index biologic (drug plus intravenous administration) divided by the number of patients categorized by the algorithm as effectively treated. Similar methods were used for the index biologic in the second year and for a second biologic after a switch. Rates that the index biologic was categorized as effective in the first year were 31.0% etanercept (2243/7247), 28.6% adalimumab (1426/4991), 28.6% abatacept (332/1160), 27.2% golimumab (71/261), and 20.2% infliximab (474/2352). Mean biologic cost per effectively treated patient, per the algorithm, was $50,141 etanercept, $53,386 golimumab, $56,942 adalimumab, $73,516 abatacept, and $114,089 infliximab. Biologic cost per effectively treated patient, using this algorithm, was lower for patients who continued the index biologic in the second year and higher after switching. When a claims-based algorithm was applied to a large commercial claims database, etanercept was categorized as the most effective and had the lowest estimated 1-year biologic cost per effectively treated patient. This proxy for effectiveness from claims databases was validated against a clinical effectiveness scale, but analyses of the second year or the year after a biologic switch were not included in the validation. Costs of other medications were not included in cost calculations.

Emergency Department Patient Perspectives on the Risk of Addiction to Prescription Opioids.

PubMed

Conrardy, Michael; Lank, Patrick; Cameron, Kenzie A; McConnell, Ryan; Chevrier, Alison; Sears, Jill; Ahlstrom, Eric; Wolf, Michael S; Courtney, D Mark; McCarthy, Danielle M

2016-01-01

To characterize emergency department (ED) patients' knowledge and beliefs about the addictive potential of opioids. Mixed methods analysis of data from a randomized controlled trial. Urban academic ED (>88,000 visits). One hundred and seventy four discharged ED patients prescribed hydrocodone-acetaminophen for acute pain. The study analyzed data collected from a randomized controlled trial investigating patients' knowledge of opioids. ED patients discharged with hydrocodone-acetaminophen completed an audio-recorded phone interview 4–7 days later. This analysis focuses on responses about addiction. Responses were categorized using content analysis; thematic analysis identified broad themes common across different categories. Participants' mean age was 45.5 years (SD, 14.8), 58.6% female, 50.6% white, and the majority had an orthopedic diagnosis (24.1% back pain, 52.3% other injuries). Responses were categorized first based on whether the patient believed that opioids could be addictive (categorized as: yes, 58.7%; no, 19.5%; depends, 17.2%; or do not know, 4.6%), and second based on whether or not the patient discussed his/her own experience with the medication (categorized as: personalized, 35.6%; or not personalized, 64.4%). Cohen's Kappa was 0.84 for all categories. Three themes emerged in the thematic analysis: theme 1) patients expect to “feel” addicted if they are addicted, theme 2) patients fear addiction, and theme 3) side effects affected patient views of addiction. In this sample, patients had misconceptions about opioid addiction. Some patients did not know opioids could be addictive, others underestimated their personal risk of addiction, and others overtly feared addiction and, therefore, risked inadequate pain management. Despite limited data, we recommend providers discuss opioid addiction with their patients. Published by Oxford University Press on behalf of the American Academy of Pain Medicine. 2016. This work is written by US Government employees and is in the public domain in the US.

Automatic Centerline Extraction of Coverd Roads by Surrounding Objects from High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Kamangir, H.; Momeni, M.; Satari, M.

2017-09-01

This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

NASA Technical Reports Server (NTRS)

Herskovits, Edward H.; Gerring, Joan P.

2003-01-01

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

Comparison of Meropenem MICs and Susceptibilities for Carbapenemase-Producing Klebsiella pneumoniae Isolates by Various Testing Methods▿

PubMed Central

Bulik, Catharine C.; Fauntleroy, Kathy A.; Jenkins, Stephen G.; Abuali, Mayssa; LaBombardi, Vincent J.; Nicolau, David P.; Kuti, Joseph L.

2010-01-01

We describe the levels of agreement between broth microdilution, Etest, Vitek 2, Sensititre, and MicroScan methods to accurately define the meropenem MIC and categorical interpretation of susceptibility against carbapenemase-producing Klebsiella pneumoniae (KPC). A total of 46 clinical K. pneumoniae isolates with KPC genotypes, all modified Hodge test and blaKPC positive, collected from two hospitals in NY were included. Results obtained by each method were compared with those from broth microdilution (the reference method), and agreement was assessed based on MICs and Clinical Laboratory Standards Institute (CLSI) interpretative criteria using 2010 susceptibility breakpoints. Based on broth microdilution, 0%, 2.2%, and 97.8% of the KPC isolates were classified as susceptible, intermediate, and resistant to meropenem, respectively. Results from MicroScan demonstrated the most agreement with those from broth microdilution, with 95.6% agreement based on the MIC and 2.2% classified as minor errors, and no major or very major errors. Etest demonstrated 82.6% agreement with broth microdilution MICs, a very major error rate of 2.2%, and a minor error rate of 2.2%. Vitek 2 MIC agreement was 30.4%, with a 23.9% very major error rate and a 39.1% minor error rate. Sensititre demonstrated MIC agreement for 26.1% of isolates, with a 3% very major error rate and a 26.1% minor error rate. Application of FDA breakpoints had little effect on minor error rates but increased very major error rates to 58.7% for Vitek 2 and Sensititre. Meropenem MIC results and categorical interpretations for carbapenemase-producing K. pneumoniae differ by methodology. Confirmation of testing results is encouraged when an accurate MIC is required for antibiotic dosing optimization. PMID:20484603

A genetic algorithm-based framework for wavelength selection on sample categorization.

PubMed

Anzanello, Michel J; Yamashita, Gabrielli; Marcelo, Marcelo; Fogliatto, Flávio S; Ortiz, Rafael S; Mariotti, Kristiane; Ferrão, Marco F

2017-08-01

In forensic and pharmaceutical scenarios, the application of chemometrics and optimization techniques has unveiled common and peculiar features of seized medicine and drug samples, helping investigative forces to track illegal operations. This paper proposes a novel framework aimed at identifying relevant subsets of attenuated total reflectance Fourier transform infrared (ATR-FTIR) wavelengths for classifying samples into two classes, for example authentic or forged categories in case of medicines, or salt or base form in cocaine analysis. In the first step of the framework, the ATR-FTIR spectra were partitioned into equidistant intervals and the k-nearest neighbour (KNN) classification technique was applied to each interval to insert samples into proper classes. In the next step, selected intervals were refined through the genetic algorithm (GA) by identifying a limited number of wavelengths from the intervals previously selected aimed at maximizing classification accuracy. When applied to Cialis®, Viagra®, and cocaine ATR-FTIR datasets, the proposed method substantially decreased the number of wavelengths needed to categorize, and increased the classification accuracy. From a practical perspective, the proposed method provides investigative forces with valuable information towards monitoring illegal production of drugs and medicines. In addition, focusing on a reduced subset of wavelengths allows the development of portable devices capable of testing the authenticity of samples during police checking events, avoiding the need for later laboratorial analyses and reducing equipment expenses. Theoretically, the proposed GA-based approach yields more refined solutions than the current methods relying on interval approaches, which tend to insert irrelevant wavelengths in the retained intervals. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The Sound of Voice: Voice-Based Categorization of Speakers’ Sexual Orientation within and across Languages

PubMed Central

Maass, Anne; Paladino, Maria Paola; Vespignani, Francesco; Eyssel, Friederike; Bentler, Dominik

2015-01-01

Empirical research had initially shown that English listeners are able to identify the speakers' sexual orientation based on voice cues alone. However, the accuracy of this voice-based categorization, as well as its generalizability to other languages (language-dependency) and to non-native speakers (language-specificity), has been questioned recently. Consequently, we address these open issues in 5 experiments: First, we tested whether Italian and German listeners are able to correctly identify sexual orientation of same-language male speakers. Then, participants of both nationalities listened to voice samples and rated the sexual orientation of both Italian and German male speakers. We found that listeners were unable to identify the speakers' sexual orientation correctly. However, speakers were consistently categorized as either heterosexual or gay on the basis of how they sounded. Moreover, a similar pattern of results emerged when listeners judged the sexual orientation of speakers of their own and of the foreign language. Overall, this research suggests that voice-based categorization of sexual orientation reflects the listeners' expectations of how gay voices sound rather than being an accurate detector of the speakers' actual sexual identity. Results are discussed with regard to accuracy, acoustic features of voices, language dependency and language specificity. PMID:26132820

The Sound of Voice: Voice-Based Categorization of Speakers' Sexual Orientation within and across Languages.

PubMed

Sulpizio, Simone; Fasoli, Fabio; Maass, Anne; Paladino, Maria Paola; Vespignani, Francesco; Eyssel, Friederike; Bentler, Dominik

2015-01-01

Empirical research had initially shown that English listeners are able to identify the speakers' sexual orientation based on voice cues alone. However, the accuracy of this voice-based categorization, as well as its generalizability to other languages (language-dependency) and to non-native speakers (language-specificity), has been questioned recently. Consequently, we address these open issues in 5 experiments: First, we tested whether Italian and German listeners are able to correctly identify sexual orientation of same-language male speakers. Then, participants of both nationalities listened to voice samples and rated the sexual orientation of both Italian and German male speakers. We found that listeners were unable to identify the speakers' sexual orientation correctly. However, speakers were consistently categorized as either heterosexual or gay on the basis of how they sounded. Moreover, a similar pattern of results emerged when listeners judged the sexual orientation of speakers of their own and of the foreign language. Overall, this research suggests that voice-based categorization of sexual orientation reflects the listeners' expectations of how gay voices sound rather than being an accurate detector of the speakers' actual sexual identity. Results are discussed with regard to accuracy, acoustic features of voices, language dependency and language specificity.

Ambiguity, logic, simplicity, and dynamics: Wittgensteinian evaluative criteria in peer review of quantitative research on categorization.

PubMed

Shimp, Charles P

2004-06-30

Research on categorization has changed over time, and some of these changes resemble how Wittgenstein's views changed from his Tractatus Logico-Philosophicus to his Philosophical Investigations. Wittgenstein initially focused on unambiguous, abstract, parsimonious, logical propositions and rules, and on independent, static, "atomic facts." This approach subsequently influenced the development of logical positivism and thereby may have indirectly influenced method and theory in research on categorization: much animal research on categorization has focused on learning simple, static, logical rules unambiguously interrelating small numbers of independent features. He later rejected logical simplicity and rigor and focused instead on Gestalt ideas about figure-ground reversals and context, the ambiguity of family resemblance, and the function of details of everyday language. Contemporary contextualism has been influenced by this latter position, some features of which appear in contemporary empirical research on categorization. These developmental changes are illustrated by research on avian local and global levels of visual perceptual analysis, categorization of rectangles and moving objects, and artificial grammar learning. Implications are described for peer review of quantitative theory in which ambiguity, logical rigor, simplicity, or dynamics are designed to play important roles.

NASA's human system risk management approach and its applicability to commercial spaceflight.

PubMed

Law, Jennifer; Mathers, Charles H; Fondy, Susan R E; Vanderploeg, James M; Kerstman, Eric L

2013-01-01

As planning continues for commercial spaceflight, attention is turned to NASA to assess whether its human system risk management approach can be applied to mitigate the risks associated with commercial suborbital and orbital flights. NASA uses a variety of methods to assess the risks to the human system based on their likelihood and consequences. In this article, we review these methods and categorize the risks in the system as "definite," "possible," or "least" concern for commercial spaceflight. As with career astronauts, these risks will be primarily mitigated by screening and environmental control. Despite its focus on long-duration exploration missions, NASA's human system risk management approach can serve as a preliminary knowledge base to help medical planners prepare for commercial spaceflights.

Inter-rater reliability of categorical versus continuous scoring of fish vitality: Does it affect the utility of the reflex action mortality predictor (RAMP) approach?

PubMed Central

Yochum, Noëlle; Kochzius, Marc; Ampe, Bart; Tuyttens, Frank A. M.

2017-01-01

Scoring reflex responsiveness and injury of aquatic organisms has gained popularity as predictors of discard survival. Given this method relies upon the individual interpretation of scoring criteria, an evaluation of its robustness is done here to test whether protocol-instructed, multiple raters with diverse backgrounds (research scientist, technician, and student) are able to produce similar or the same reflex and injury score for one of the same flatfish (European plaice, Pleuronectes platessa) after experiencing commercial fishing stressors. Inter-rater reliability for three raters was assessed by using a 3-point categorical scale (‘absent’, ‘weak’, ‘strong’) and a tagged visual analogue continuous scale (tVAS, a 10 cm bar split in three labelled sections: 0 for ‘absent’, ‘weak’, ‘moderate’, and ‘strong’) for six reflex responses, and a 4-point scale for four injury types. Plaice (n = 304) were sampled from 17 research beam-trawl deployments during four trips. Fleiss kappa (categorical scores) and intra-class correlation coefficients (ICC, continuous scores) indicated variable inter-rater agreement by reflex type (ranging between 0.55 and 0.88, and 67% and 91% for Fleiss kappa and ICC, respectively), with least agreement among raters on extent of injury (Fleiss kappa between 0.08 and 0.27). Despite differences among raters, which did not significantly influence the relationship between impairment and predicted survival, combining categorical reflex and injury scores always produced a close relationship of such vitality indices and observed delayed mortality. The use of the continuous scale did not improve fit of these models compared with using the reflex impairment index based on categorical scores. Given these findings, we recommend using a 3-point categorical over a continuous scale. We also determined that training rather than experience of raters minimised inter-rater differences. Our results suggest that cost-efficient reflex impairment and injury scoring may be considered a robust technique to evaluate lethal stress and damage of this flatfish species on-board commercial beam-trawl vessels. PMID:28704390

On a categorial aspect of knowledge representation

NASA Astrophysics Data System (ADS)

Tataj, Emanuel; Mulawka, Jan; Nieznański, Edward

Adequate representation of data is crucial for modeling any type of data. To faithfully present and describe the relevant section of the world it is necessary to select the method that can easily be implemented on a computer system which will help in further description allowing reasoning. The main objective of this contribution is to present methods of knowledge representation using categorial approach. Next to identify the main advantages for computer implementation. Categorical aspect of knowledge representation is considered in semantic networks realisation. Such method borrows already known metaphysics properties for data modeling process. The potential topics of further development of categorical semantic networks implementations are also underlined.

A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data.

PubMed

Nasejje, Justine B; Mwambi, Henry; Dheda, Keertan; Lesosky, Maia

2017-07-28

Random survival forest (RSF) models have been identified as alternative methods to the Cox proportional hazards model in analysing time-to-event data. These methods, however, have been criticised for the bias that results from favouring covariates with many split-points and hence conditional inference forests for time-to-event data have been suggested. Conditional inference forests (CIF) are known to correct the bias in RSF models by separating the procedure for the best covariate to split on from that of the best split point search for the selected covariate. In this study, we compare the random survival forest model to the conditional inference model (CIF) using twenty-two simulated time-to-event datasets. We also analysed two real time-to-event datasets. The first dataset is based on the survival of children under-five years of age in Uganda and it consists of categorical covariates with most of them having more than two levels (many split-points). The second dataset is based on the survival of patients with extremely drug resistant tuberculosis (XDR TB) which consists of mainly categorical covariates with two levels (few split-points). The study findings indicate that the conditional inference forest model is superior to random survival forest models in analysing time-to-event data that consists of covariates with many split-points based on the values of the bootstrap cross-validated estimates for integrated Brier scores. However, conditional inference forests perform comparably similar to random survival forests models in analysing time-to-event data consisting of covariates with fewer split-points. Although survival forests are promising methods in analysing time-to-event data, it is important to identify the best forest model for analysis based on the nature of covariates of the dataset in question.

A new service-oriented grid-based method for AIoT application and implementation

NASA Astrophysics Data System (ADS)

Zou, Yiqin; Quan, Li

2017-07-01

The traditional three-layer Internet of things (IoT) model, which includes physical perception layer, information transferring layer and service application layer, cannot express complexity and diversity in agricultural engineering area completely. It is hard to categorize, organize and manage the agricultural things with these three layers. Based on the above requirements, we propose a new service-oriented grid-based method to set up and build the agricultural IoT. Considering the heterogeneous, limitation, transparency and leveling attributes of agricultural things, we propose an abstract model for all agricultural resources. This model is service-oriented and expressed with Open Grid Services Architecture (OGSA). Information and data of agricultural things were described and encapsulated by using XML in this model. Every agricultural engineering application will provide service by enabling one application node in this service-oriented grid. Description of Web Service Resource Framework (WSRF)-based Agricultural Internet of Things (AIoT) and the encapsulation method were also discussed in this paper for resource management in this model.

Ontology-based structured cosine similarity in document summarization: with applications to mobile audio-based knowledge management.

PubMed

Yuan, Soe-Tsyr; Sun, Jerry

2005-10-01

Development of algorithms for automated text categorization in massive text document sets is an important research area of data mining and knowledge discovery. Most of the text-clustering methods were grounded in the term-based measurement of distance or similarity, ignoring the structure of the documents. In this paper, we present a novel method named structured cosine similarity (SCS) that furnishes document clustering with a new way of modeling on document summarization, considering the structure of the documents so as to improve the performance of document clustering in terms of quality, stability, and efficiency. This study was motivated by the problem of clustering speech documents (of no rich document features) attained from the wireless experience oral sharing conducted by mobile workforce of enterprises, fulfilling audio-based knowledge management. In other words, this problem aims to facilitate knowledge acquisition and sharing by speech. The evaluations also show fairly promising results on our method of structured cosine similarity.

Ageing airplane repair assessment program for Airbus A300

NASA Technical Reports Server (NTRS)

Gaillardon, J. M.; Schmidt, HANS-J.; Brandecker, B.

1992-01-01

This paper describes the current status of the repair categorization activities and includes all details about the methodologies developed for determination of the inspection program for the skin on pressurized fuselages. For inspection threshold determination two methods are defined based on fatigue life approach, a simplified and detailed method. The detailed method considers 15 different parameters to assess the influences of material, geometry, size location, aircraft usage, and workmanship on the fatigue life of the repair and the original structure. For definition of the inspection intervals a general method is developed which applies to all concerned repairs. For this the initial flaw concept is used by considering 6 parameters and the detectable flaw sizes depending on proposed nondestructive inspection methods. An alternative method is provided for small repairs allowing visual inspection with shorter intervals.

Correction of the significance level when attempting multiple transformations of an explanatory variable in generalized linear models

PubMed Central

2013-01-01

Background In statistical modeling, finding the most favorable coding for an exploratory quantitative variable involves many tests. This process involves multiple testing problems and requires the correction of the significance level. Methods For each coding, a test on the nullity of the coefficient associated with the new coded variable is computed. The selected coding corresponds to that associated with the largest statistical test (or equivalently the smallest pvalue). In the context of the Generalized Linear Model, Liquet and Commenges (Stat Probability Lett,71:33–38,2005) proposed an asymptotic correction of the significance level. This procedure, based on the score test, has been developed for dichotomous and Box-Cox transformations. In this paper, we suggest the use of resampling methods to estimate the significance level for categorical transformations with more than two levels and, by definition those that involve more than one parameter in the model. The categorical transformation is a more flexible way to explore the unknown shape of the effect between an explanatory and a dependent variable. Results The simulations we ran in this study showed good performances of the proposed methods. These methods were illustrated using the data from a study of the relationship between cholesterol and dementia. Conclusion The algorithms were implemented using R, and the associated CPMCGLM R package is available on the CRAN. PMID:23758852

Categorization-based stranger avoidance does not explain the uncanny valley effect.

PubMed

MacDorman, Karl F; Chattopadhyay, Debaleena

2017-04-01

The uncanny valley hypothesis predicts that an entity appearing almost human risks eliciting cold, eerie feelings in viewers. Categorization-based stranger avoidance theory identifies the cause of this feeling as categorizing the entity into a novel category. This explanation is doubtful because stranger is not a novel category in adults; infants do not avoid strangers while the category stranger remains novel; infants old enough to fear strangers prefer photographs of strangers to those more closely resembling a familiar person; and the uncanny valley's characteristic eeriness is seldom felt when meeting strangers. We repeated our original experiment with a more realistic 3D computer model and found no support for categorization-based stranger avoidance theory. By contrast, realism inconsistency theory explains cold, eerie feelings elicited by transitions between instances of two different, mutually exclusive categories, given that at least one category is anthropomorphic: Cold, eerie feelings are caused by prediction error from perceiving some features as features of the first category and other features as features of the second category. In principle, realism inconsistency theory can explain not only negative evaluations of transitions between real and computer modeled humans but also between different vertebrate species. Copyright © 2017 Elsevier B.V. All rights reserved.

Physician Dual Practice: A Descriptive Mapping Review of Literature.

PubMed

Moghri, Javad; Arab, Mohammad; Rashidian, Arash; Akbari Sari, Ali

2016-03-01

Physician dual practice is a common phenomenon in almost all countries throughout the world, which could potential impacts on access, equity and quality of services. This paper aims to review studies in physician dual practice and categorize them in order to their main objectives and purposes. Comprehensive literature searches were undertaken in order to obtain main papers and documents in the field of physician dual practice. Systematic searches in Medline and Embase from 1960 to 2013, and general searches in some popular search engines were carried out in this way. After that, descriptive mapping review methods were utilized to categorize eligible studies in this area. The searches obtained 404 titles, of which 81 full texts were assessed. Finally, 24 studies were eligible for inclusion in our review. These studies were categorized into four groups - "motivation and forces behind dual practice", "consequences of dual practice", "dual practice Policies and their impacts", and "other studies" - based on their main objectives. Our findings showed a dearth of scientifically reliable literature in some areas of dual practice, like the prevalence of the phenomenon, the real consequences of it, and the impacts of the implemented policy measures. Rigorous empirical and evaluative studies should be designed to detect the real consequences of DP and assess the effects of interventions and regulations, which governments have implemented in this field.

Global neural pattern similarity as a common basis for categorization and recognition memory.

PubMed

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

2014-05-28

Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. Copyright © 2014 the authors 0270-6474/14/347472-13$15.00/0.

Brain activity across the development of automatic categorization: A comparison of categorization tasks using multi-voxel pattern analysis

PubMed Central

Soto, Fabian A.; Waldschmidt, Jennifer G.; Helie, Sebastien; Ashby, F. Gregory

2013-01-01

Previous evidence suggests that relatively separate neural networks underlie initial learning of rule-based and information-integration categorization tasks. With the development of automaticity, categorization behavior in both tasks becomes increasingly similar and exclusively related to activity in cortical regions. The present study uses multi-voxel pattern analysis to directly compare the development of automaticity in different categorization tasks. Each of three groups of participants received extensive training in a different categorization task: either an information-integration task, or one of two rule-based tasks. Four training sessions were performed inside an MRI scanner. Three different analyses were performed on the imaging data from a number of regions of interest (ROIs). The common patterns analysis had the goal of revealing ROIs with similar patterns of activation across tasks. The unique patterns analysis had the goal of revealing ROIs with dissimilar patterns of activation across tasks. The representational similarity analysis aimed at exploring (1) the similarity of category representations across ROIs and (2) how those patterns of similarities compared across tasks. The results showed that common patterns of activation were present in motor areas and basal ganglia early in training, but only in the former later on. Unique patterns were found in a variety of cortical and subcortical areas early in training, but they were dramatically reduced with training. Finally, patterns of representational similarity between brain regions became increasingly similar across tasks with the development of automaticity. PMID:23333700

Uncertainties in land use data

NASA Astrophysics Data System (ADS)

Castilla, G.; Hay, G. J.

2006-11-01

This paper deals with the description and assessment of uncertainties in gridded land use data derived from Remote Sensing observations, in the context of hydrological studies. Land use is a categorical regionalised variable returning the main socio-economic role each location has, where the role is inferred from the pattern of occupation of land. There are two main uncertainties surrounding land use data, positional and categorical. This paper focuses on the second one, as the first one has in general less serious implications and is easier to tackle. The conventional method used to asess categorical uncertainty, the confusion matrix, is criticised in depth, the main critique being its inability to inform on a basic requirement to propagate uncertainty through distributed hydrological models, namely the spatial distribution of errors. Some existing alternative methods are reported, and finally the need for metadata is stressed as a more reliable means to assess the quality, and hence the uncertainty, of these data.

Changes in default mode network as automaticity develops in a categorization task.

PubMed

Shamloo, Farzin; Helie, Sebastien

2016-10-15

The default mode network (DMN) is a set of brain regions in which blood oxygen level dependent signal is suppressed during attentional focus on the external environment. Because automatic task processing requires less attention, development of automaticity in a rule-based categorization task may result in less deactivation and altered functional connectivity of the DMN when compared to the initial learning stage. We tested this hypothesis by re-analyzing functional magnetic resonance imaging data of participants trained in rule-based categorization for over 10,000 trials (Helie et al., 2010) [12,13]. The results show that some DMN regions are deactivated in initial training but not after automaticity has developed. There is also a significant decrease in DMN deactivation after extensive practice. Seed-based functional connectivity analyses with the precuneus, medial prefrontal cortex (two important DMN regions) and Brodmann area 6 (an important region in automatic categorization) were also performed. The results show increased functional connectivity with both DMN and non-DMN regions after the development of automaticity, and a decrease in functional connectivity between the medial prefrontal cortex and ventromedial orbitofrontal cortex. Together, these results further support the hypothesis of a strategy shift in automatic categorization and bridge the cognitive and neuroscientific conceptions of automaticity in showing that the reduced need for cognitive resources in automatic processing is accompanied by a disinhibition of the DMN and stronger functional connectivity between DMN and task-related brain regions. Copyright © 2016 Elsevier B.V. All rights reserved.

Categorical Perception of Mandarin Chinese Tones 1-2 and Tones 1-4: Effects of Aging and Signal Duration

ERIC Educational Resources Information Center

Wang, Yuxia; Yang, Xiaohu; Liu, Chang

2017-01-01

Purpose: The purpose of this study was to investigate the aging effect on the categorical perception of Mandarin Chinese tones with varied fundamental frequency (F0) contours and signal duration. Method: Both younger and older native Chinese listeners with normal hearing were recruited in 2 experiments--tone identification and tone discrimination…

Toward Increasing Professionalism in Public Relations: An Activity-Specific System for Categorizing Practitioners.

ERIC Educational Resources Information Center

Brownell, Mark A.; Niebauer, Walter E., Jr.

To develop a method of categorizing public relations practitioners according to a hierarchy of professionalism which would also identify what training is needed to raise those in lower levels to higher levels, a study surveyed 93 Iowa practitioners listed in the 1986-87 Public Relations Society of America Register Issue. Response rate was 66% and…

Logo image clustering based on advanced statistics

NASA Astrophysics Data System (ADS)

Wei, Yi; Kamel, Mohamed; He, Yiwei

2007-11-01

In recent years, there has been a growing interest in the research of image content description techniques. Among those, image clustering is one of the most frequently discussed topics. Similar to image recognition, image clustering is also a high-level representation technique. However it focuses on the coarse categorization rather than the accurate recognition. Based on wavelet transform (WT) and advanced statistics, the authors propose a novel approach that divides various shaped logo images into groups according to the external boundary of each logo image. Experimental results show that the presented method is accurate, fast and insensitive to defects.

Optimal Experimental Design for Model Discrimination

PubMed Central

Myung, Jay I.; Pitt, Mark A.

2009-01-01

Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it possible to determine these values, and thereby identify an optimal experimental design. After describing the method, it is demonstrated in two content areas in cognitive psychology in which models are highly competitive: retention (i.e., forgetting) and categorization. The optimal design is compared with the quality of designs used in the literature. The findings demonstrate that design optimization has the potential to increase the informativeness of the experimental method. PMID:19618983

Application and preventive maintenance of neurology medical equipment in isfahan alzahra hospital.

PubMed

Alikhani, Parivash; Vesal, Sahar; Kashefi, Parviz; Pour, Ramin Etamadi; Khorvash, Fariborz; Askari, Gholamreza; Meamar, Rokhsareh

2013-05-01

Nowadays Medical equipment plays an important role in the treatment and in the medical education. Using outdated preventive maintenance (PM) system may cause problems in the cutting edge medical equipment, Nervous system disease's equipment (In diagnosis and treatment) which are crucial for every medical center. Based on above facts we focused on nervous system treat units' equipment and informed the supervisors and their colleagues about the latest equipment maintenance status and promoted methodical and correct method to be used for medical equipment maintenance. This research is an analytical descriptive and has been done on the base information from a particular time to past. We gathered our required information of 2009 from Alzahra Medical Center. We divided this research info 2 main phases. In the first phase, we picked out Neurosurgery and Neourology diseases medical equipment (diagnosis and therapy equipment) and in the second phase, we need to implement a methodical PM for every equipment. Research has shown that there are 19nervous system equipment in Alzahra Medical center, categorized in diagnostic (13 pcs), therapeutic (4 pcs) and diagnostic-therapeutic (2 pcs). As we declare in methods part of this research, we categorized medical equipment in Food and Drug Administration (FDA) segmentation. Capital-scarce equipment: Magnetic resonance imaging, Eco Doppler, Kamalaarak ultrasonic surgical aspirator, Stereotactic, computed tomography-scan, euroendoscope/vital-scarce equipment: Coblation, Sonoco, vaterjet/scarce equipment: Transcranial color Doppler, electroencephalogram, electromyography, surgical microscope. Survey of application and preventive maintenance of neurology medical equipment in Isfahan Alzahra hospital show there is no P.M system. Implementing a complete P.M system for this medical center is crucial to preventing cause problems for these medical equipment and decreasing maintenance costs and gaining uptime. Researchers of this article have tried to provide PM, use of texts, web and experts.

Acoustic and Categorical Dissimilarity of Musical Timbre: Evidence from Asymmetries Between Acoustic and Chimeric Sounds

PubMed Central

Siedenburg, Kai; Jones-Mollerup, Kiray; McAdams, Stephen

2016-01-01

This paper investigates the role of acoustic and categorical information in timbre dissimilarity ratings. Using a Gammatone-filterbank-based sound transformation, we created tones that were rated as less familiar than recorded tones from orchestral instruments and that were harder to associate with an unambiguous sound source (Experiment 1). A subset of transformed tones, a set of orchestral recordings, and a mixed set were then rated on pairwise dissimilarity (Experiment 2A). We observed that recorded instrument timbres clustered into subsets that distinguished timbres according to acoustic and categorical properties. For the subset of cross-category comparisons in the mixed set, we observed asymmetries in the distribution of ratings, as well as a stark decay of inter-rater agreement. These effects were replicated in a more robust within-subjects design (Experiment 2B) and cannot be explained by acoustic factors alone. We finally introduced a novel model of timbre dissimilarity based on partial least-squares regression that compared the contributions of both acoustic and categorical timbre descriptors. The best model fit (R2 = 0.88) was achieved when both types of descriptors were taken into account. These findings are interpreted as evidence for an interplay of acoustic and categorical information in timbre dissimilarity perception. PMID:26779086

Categorization of fetal external findings in developmental toxicology studies by the Terminology Committee of the Japanese Teratology Society.

PubMed

Izumi, Yuko; Ooshima, Yojiro; Chihara, Kazuhiro; Fujiwara, Michio; Katsumata, Yoshihiro; Shiota, Kohei

2018-05-01

Categorization of fetal external findings in common laboratory animals, intended to make the agreement at Berlin Workshop in 2014 more practical, was proposed by the Terminology Committee of the Japanese Teratology Society at the Workshop in the 55th Japanese Teratology Society Annual Meeting in 2015. In the Workshop, 73 external findings, which had been categorized as "Gray zone" anomalies but not as "Malformation" or "Variation" in the 2014 Berlin Workshop, were discussed and classified as Malformation, "Non-structural abnormality," Variation, and "Not applicable." The proposal was based on the results of a survey conducted in 2014, where 20 facilities (including pharmaceutical, chemical, and pesticide companies and contract laboratories) and 2 selected expert teratologists in Japan were asked for their opinions on the categorization of these findings. Based on the discussion, Japanese Teratology Society members have agreed that 42 out of the 73 findings can be classified as Malformations (38), Non-structural abnormalities (3), Malformations/Non-structural abnormalities (1), and Variations (0), while the remaining 31 findings were recommended to be categorized as Not applicable for fetuses. The details of the classification are shown on the website of the Japanese Teratology Society (http://www.umin.ac.jp/cadb/External.pdf). © 2018 Japanese Teratology Society.

Modelling eye movements in a categorical search task

PubMed Central

Zelinsky, Gregory J.; Adeli, Hossein; Peng, Yifan; Samaras, Dimitris

2013-01-01

We introduce a model of eye movements during categorical search, the task of finding and recognizing categorically defined targets. It extends a previous model of eye movements during search (target acquisition model, TAM) by using distances from an support vector machine classification boundary to create probability maps indicating pixel-by-pixel evidence for the target category in search images. Other additions include functionality enabling target-absent searches, and a fixation-based blurring of the search images now based on a mapping between visual and collicular space. We tested this model on images from a previously conducted variable set-size (6/13/20) present/absent search experiment where participants searched for categorically defined teddy bear targets among random category distractors. The model not only captured target-present/absent set-size effects, but also accurately predicted for all conditions the numbers of fixations made prior to search judgements. It also predicted the percentages of first eye movements during search landing on targets, a conservative measure of search guidance. Effects of set size on false negative and false positive errors were also captured, but error rates in general were overestimated. We conclude that visual features discriminating a target category from non-targets can be learned and used to guide eye movements during categorical search. PMID:24018720

Basic-Level and Superordinate-like Categorical Representations in Early Infancy.

ERIC Educational Resources Information Center

Behl-Chadha, Gundeep

1996-01-01

Examined three- to four-month-old infants' ability to form perceptually based categorical representation in the domains of natural kinds and artifacts. By showing the availability of perceptually driven basic and superordinate-like representations in early infancy that closely correspond to adult conceptual categories, findings underscored the…

Relative Contribution of Perception/Cognition and Language on Spatial Categorization

ERIC Educational Resources Information Center

Choi, Soonja; Hattrup, Kate

2012-01-01

This study investigated the relative contribution of perception/cognition and language-specific semantics in nonverbal categorization of spatial relations. English and Korean speakers completed a video-based similarity judgment task involving containment, support, tight fit, and loose fit. Both perception/cognition and language served as resources…

Assessing Expertise in Introductory Physics Using Categorization Task

ERIC Educational Resources Information Center

Mason, Andrew; Singh, Chandralekha

2011-01-01

The ability to categorize problems based upon underlying principles, rather than surface features or contexts, is considered one of several proxy predictors of expertise in problem solving. With inspiration from the classic study by Chi, Feltovich, and Glaser, we assess the distribution of expertise among introductory physics students by asking…

Influence of Familiar Features on Diagnosis: Instantiated Features in an Applied Setting

ERIC Educational Resources Information Center

Dore, Kelly L.; Brooks, Lee R.; Weaver, Bruce; Norman, Geoffrey R.

2012-01-01

Medical diagnosis can be viewed as a categorization task. There are two mechanisms whereby humans make categorical judgments: "analytical reasoning," based on explicit consideration of features and "nonanalytical reasoning," an unconscious holistic process of matching against prior exemplars. However, there is evidence that prior experience can…

Identifying the Enemy: Social Categorization and National Security Policy

ERIC Educational Resources Information Center

Unsworth, Kristene

2010-01-01

This dissertation seeks to understand the interplay between informal articulations of social categories and formal instantiations of those categories in official language. Specifically, it explores the process of social categorization as it is used to identify threats to national security. The research employed a qualitative, document-based,…

Discourse Classification into Rhetorical Functions for AWE Feedback

ERIC Educational Resources Information Center

Cotos, Elena; Pendar, Nick

2016-01-01

This paper reports on the development of an analysis engine for the Research Writing Tutor (RWT), an AWE program designed to provide genre and discipline-specific feedback on the functional units of research article discourse. Unlike traditional NLP-based applications that categorize complete documents, the analyzer categorizes every sentence in…

Racial Prejudice in College Students: A Cross-Sectional Examination

ERIC Educational Resources Information Center

Gassner, Breanna; McGuigan, William

2014-01-01

Racial prejudice is based upon negative preconceived notions of select racial groups with the assumption that all members of a particular racial group can be categorized with the same negative characteristics. Social categorization allows for quick sorting of individuals into racial groups saturated with a common flavor. Allport's Principle of…

Webly-Supervised Fine-Grained Visual Categorization via Deep Domain Adaptation.

PubMed

Xu, Zhe; Huang, Shaoli; Zhang, Ya; Tao, Dacheng

2018-05-01

Learning visual representations from web data has recently attracted attention for object recognition. Previous studies have mainly focused on overcoming label noise and data bias and have shown promising results by learning directly from web data. However, we argue that it might be better to transfer knowledge from existing human labeling resources to improve performance at nearly no additional cost. In this paper, we propose a new semi-supervised method for learning via web data. Our method has the unique design of exploiting strong supervision, i.e., in addition to standard image-level labels, our method also utilizes detailed annotations including object bounding boxes and part landmarks. By transferring as much knowledge as possible from existing strongly supervised datasets to weakly supervised web images, our method can benefit from sophisticated object recognition algorithms and overcome several typical problems found in webly-supervised learning. We consider the problem of fine-grained visual categorization, in which existing training resources are scarce, as our main research objective. Comprehensive experimentation and extensive analysis demonstrate encouraging performance of the proposed approach, which, at the same time, delivers a new pipeline for fine-grained visual categorization that is likely to be highly effective for real-world applications.

Selective Influences of Precision and Power Grips on Speech Categorization.

PubMed

Tiainen, Mikko; Tiippana, Kaisa; Vainio, Martti; Peromaa, Tarja; Komeilipoor, Naeem; Vainio, Lari

2016-01-01

Recent studies have shown that articulatory gestures are systematically associated with specific manual grip actions. Here we show that executing such actions can influence performance on a speech-categorization task. Participants watched and/or listened to speech stimuli while executing either a power or a precision grip. Grip performance influenced the syllable categorization by increasing the proportion of responses of the syllable congruent with the executed grip (power grip-[ke] and precision grip-[te]). Two follow-up experiments indicated that the effect was based on action-induced bias in selecting the syllable.

Accuracy of gestalt perception of acute chest pain in predicting coronary artery disease

PubMed Central

das Virgens, Cláudio Marcelo Bittencourt; Lemos Jr, Laudenor; Noya-Rabelo, Márcia; Carvalhal, Manuela Campelo; Cerqueira Junior, Antônio Maurício dos Santos; Lopes, Fernanda Oliveira de Andrade; de Sá, Nicole Cruz; Suerdieck, Jéssica Gonzalez; de Souza, Thiago Menezes Barbosa; Correia, Vitor Calixto de Almeida; Sodré, Gabriella Sant'Ana; da Silva, André Barcelos; Alexandre, Felipe Kalil Beirão; Ferreira, Felipe Rodrigues Marques; Correia, Luís Cláudio Lemos

2017-01-01

AIM To test accuracy and reproducibility of gestalt to predict obstructive coronary artery disease (CAD) in patients with acute chest pain. METHODS We studied individuals who were consecutively admitted to our Chest Pain Unit. At admission, investigators performed a standardized interview and recorded 14 chest pain features. Based on these features, a cardiologist who was blind to other clinical characteristics made unstructured judgment of CAD probability, both numerically and categorically. As the reference standard for testing the accuracy of gestalt, angiography was required to rule-in CAD, while either angiography or non-invasive test could be used to rule-out. In order to assess reproducibility, a second cardiologist did the same procedure. RESULTS In a sample of 330 patients, the prevalence of obstructive CAD was 48%. Gestalt’s numerical probability was associated with CAD, but the area under the curve of 0.61 (95%CI: 0.55-0.67) indicated low level of accuracy. Accordingly, categorical definition of typical chest pain had a sensitivity of 48% (95%CI: 40%-55%) and specificity of 66% (95%CI: 59%-73%), yielding a negligible positive likelihood ratio of 1.4 (95%CI: 0.65-2.0) and negative likelihood ratio of 0.79 (95%CI: 0.62-1.02). Agreement between the two cardiologists was poor in the numerical classification (95% limits of agreement = -71% to 51%) and categorical definition of typical pain (Kappa = 0.29; 95%CI: 0.21-0.37). CONCLUSION Clinical judgment based on a combination of chest pain features is neither accurate nor reproducible in predicting obstructive CAD in the acute setting. PMID:28400920

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

PubMed

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

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

Methods of Implementation of Evidence-Based Stroke Care in Europe: European Implementation Score Collaboration.

PubMed

Di Carlo, Antonio; Pezzella, Francesca Romana; Fraser, Alec; Bovis, Francesca; Baeza, Juan; McKevitt, Chris; Boaz, Annette; Heuschmann, Peter; Wolfe, Charles D A; Inzitari, Domenico

2015-08-01

Differences in stroke care and outcomes reported in Europe may reflect different degrees of implementation of evidence-based interventions. We evaluated strategies for implementing research evidence into stroke care in 10 European countries. A questionnaire was developed and administered through face-to-face interviews with key informants. Implementation strategies were investigated considering 3 levels (macro, meso, and micro, eg, policy, organization, patients/professionals) identified by the framing analysis, and different settings (primary, hospital, and specialist) of stroke care. Similarities and differences among countries were evaluated using the categorical principal components analysis. Implementation methods reported by ≥7 countries included nonmandatory policies, public financial incentives, continuing professional education, distribution of educational material, educational meetings and campaigns, guidelines, opinion leaders', and stroke patients associations' activities. Audits were present in 6 countries at national level; national and regional regulations in 4 countries. Private financial incentives, reminders, and educational outreach visits were reported only in 2 countries. At national level, the first principal component of categorical principal components analysis separated England, France, Scotland, and Sweden, all with positive object scores, from the other countries. Belgium and Lithuania obtained the lowest scores. At regional level, England, France, Germany, Italy, and Sweden had positive scores in the first principal component, whereas Belgium, Lithuania, Poland, and Scotland showed negative scores. Spain was in an intermediate position. We developed a novel method to assess different domains of implementation in stroke care. Clear variations were observed among European countries. The new tool may be used elsewhere for future contributions. © 2015 American Heart Association, Inc.

Signal detection theory and methods for evaluating human performance in decision tasks

NASA Technical Reports Server (NTRS)

Obrien, Kevin; Feldman, Evan M.

1993-01-01

Signal Detection Theory (SDT) can be used to assess decision making performance in tasks that are not commonly thought of as perceptual. SDT takes into account both the sensitivity and biases in responding when explaining the detection of external events. In the standard SDT tasks, stimuli are selected in order to reveal the sensory capabilities of the observer. SDT can also be used to describe performance when decisions must be made as to the classification of easily and reliably sensed stimuli. Numbers are stimuli that are minimally affected by sensory processing and can belong to meaningful categories that overlap. Multiple studies have shown that the task of categorizing numbers from overlapping normal distributions produces performance predictable by SDT. These findings are particularly interesting in view of the similarity between the task of the categorizing numbers and that of determining the status of a mechanical system based on numerical values that represent sensor readings. Examples of the use of SDT to evaluate performance in decision tasks are reviewed. The methods and assumptions of SDT are shown to be effective in the measurement, evaluation, and prediction of human performance in such tasks.

Impact of pedagogical method on Brazilian dental students' waste management practice.

PubMed

Victorelli, Gabriela; Flório, Flávia Martão; Ramacciato, Juliana Cama; Motta, Rogério Heládio Lopes; de Souza Fonseca Silva, Almenara

2014-11-01

The purpose of this study was to conduct a qualitative analysis of waste management practices among a group of Brazilian dental students (n=64) before and after implementing two different pedagogical methods: 1) the students attended a two-hour lecture based on World Health Organization standards; and 2) the students applied the lessons learned in an organized group setting aimed toward raising their awareness about socioenvironmental issues related to waste. All eligible students participated, and the students' learning was evaluated through their answers to a series of essay questions, which were quantitatively measured. Afterwards, the impact of the pedagogical approaches was compared by means of qualitative categorization of wastes generated in clinical activities. Waste categorization was performed for a period of eight consecutive days, both before and thirty days after the pedagogical strategies. In the written evaluation, 80 to 90 percent of the students' answers were correct. The qualitative assessment revealed a high frequency of incorrect waste disposal with a significant increase of incorrect disposal inside general and infectious waste containers (p<0.05). Although the students' theoretical learning improved, it was not enough to change behaviors established by cultural values or to encourage the students to adequately segregate and package waste material.

A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.

PubMed

Brusco, Michael J; Shireman, Emilie; Steinley, Douglas

2017-09-01

The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A detailed transcript-level probe annotation reveals alternative splicing based microarray platform differences

PubMed Central

Lee, Joseph C; Stiles, David; Lu, Jun; Cam, Margaret C

2007-01-01

Background Microarrays are a popular tool used in experiments to measure gene expression levels. Improving the reproducibility of microarray results produced by different chips from various manufacturers is important to create comparable and combinable experimental results. Alternative splicing has been cited as a possible cause of differences in expression measurements across platforms, though no study to this point has been conducted to show its influence in cross-platform differences. Results Using probe sequence data, a new microarray probe/transcript annotation was created based on the AceView Aug05 release that allowed for the categorization of genes based on their expression measurements' susceptibility to alternative splicing differences across microarray platforms. Examining gene expression data from multiple platforms in light of the new categorization, genes unsusceptible to alternative splicing differences showed higher signal agreement than those genes most susceptible to alternative splicing differences. The analysis gave rise to a different probe-level visualization method that can highlight probe differences according to transcript specificity. Conclusion The results highlight the need for detailed probe annotation at the transcriptome level. The presence of alternative splicing within a given sample can affect gene expression measurements and is a contributing factor to overall technical differences across platforms. PMID:17708771

Cluster Correspondence Analysis.

PubMed

van de Velden, M; D'Enza, A Iodice; Palumbo, F

2017-03-01

A method is proposed that combines dimension reduction and cluster analysis for categorical data by simultaneously assigning individuals to clusters and optimal scaling values to categories in such a way that a single between variance maximization objective is achieved. In a unified framework, a brief review of alternative methods is provided and we show that the proposed method is equivalent to GROUPALS applied to categorical data. Performance of the methods is appraised by means of a simulation study. The results of the joint dimension reduction and clustering methods are compared with the so-called tandem approach, a sequential analysis of dimension reduction followed by cluster analysis. The tandem approach is conjectured to perform worse when variables are added that are unrelated to the cluster structure. Our simulation study confirms this conjecture. Moreover, the results of the simulation study indicate that the proposed method also consistently outperforms alternative joint dimension reduction and clustering methods.

From Tootsie Rolls to Composites: Assessing a Spectrum of Active Learning Activities in Engineering Mechanics

DTIC Science & Technology

2009-05-01

Appendix 9.1. Learning Styles & Pedagogical Theory Overview Educational theory plays a foundational role for the methodology and the development...of ALPs. We selected two methods to categorize student’s learning styles: (1) MBTI, (2) VARK, and five models of the learning process: (1) Kolb , (2... learning process which gives our work a more balanced foundation than may be possible if one bases their approach on one or two theories only, 2) our work

spMC: an R-package for 3D lithological reconstructions based on spatial Markov chains

NASA Astrophysics Data System (ADS)

Sartore, Luca; Fabbri, Paolo; Gaetan, Carlo

2016-09-01

The paper presents the spatial Markov Chains (spMC) R-package and a case study of subsoil simulation/prediction located in a plain site of Northeastern Italy. spMC is a quite complete collection of advanced methods for data inspection, besides spMC implements Markov Chain models to estimate experimental transition probabilities of categorical lithological data. Furthermore, simulation methods based on most known prediction methods (as indicator Kriging and CoKriging) were implemented in spMC package. Moreover, other more advanced methods are available for simulations, e.g. path methods and Bayesian procedures, that exploit the maximum entropy. Since the spMC package was developed for intensive geostatistical computations, part of the code is implemented for parallel computations via the OpenMP constructs. A final analysis of this computational efficiency compares the simulation/prediction algorithms by using different numbers of CPU cores, and considering the example data set of the case study included in the package.

Severity of alcohol use and problem behaviors among school-based youths in Puerto Rico

PubMed Central

Latimer, William W.; Rojas, Vanessa Cecilia; Mancha, Brent Edward

2009-01-01

Objectives The present study sought to: (a) categorize youths into groups based on their level of alcohol use and number of symptoms of alcohol abuse and dependence defined in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), and (b) examine whether these categories were associated with other problem behaviors in which youths engage (marijuana use, sexual intercourse, and having been arrested or having trouble with the law). Methods The study is based on a cross-sectional survey administered to 972 school-based youths from one middle school and one high school in San Juan, Puerto Rico. Youths were categorized based on their alcohol use and alcohol problems. These categories were then examined for associations with lifetime marijuana use, lifetime sexual intercourse, and having been arrested or having had trouble with the law in the past year. The original eight categories of alcohol use were collapsed into six categories based on the results. Results For virtually every group characterized by higher severity of alcohol use and alcohol problems, researchers found an increasing prevalence of marijuana use in their lifetimes, increasing odds of sexual intercourse in their lifetimes, and having had trouble with the law in the past year. Conclusions Knowing about variations in alcohol use and alcohol problems may be instrumental in measuring the degree to which youths may also be engaging in a range of other elevated risk behaviors and a progression to more serious forms of alcohol and drug use. PMID:18510792

Establishing seasonal and alert influenza thresholds in Cambodia using the WHO method: implications for effective utilization of influenza surveillance in the tropics and subtropics.

PubMed

Ly, Sovann; Arashiro, Takeshi; Ieng, Vanra; Tsuyuoka, Reiko; Parry, Amy; Horwood, Paul; Heng, Seng; Hamid, Sarah; Vandemaele, Katelijn; Chin, Savuth; Sar, Borann; Arima, Yuzo

2017-01-01

To establish seasonal and alert thresholds and transmission intensity categories for influenza to provide timely triggers for preventive measures or upscaling control measures in Cambodia. Using Cambodia's influenza-like illness (ILI) and laboratory-confirmed influenza surveillance data from 2009 to 2015, three parameters were assessed to monitor influenza activity: the proportion of ILI patients among all outpatients, proportion of ILI samples positive for influenza and the product of the two. With these parameters, four threshold levels (seasonal, moderate, high and alert) were established and transmission intensity was categorized based on a World Health Organization alignment method. Parameters were compared against their respective thresholds. Distinct seasonality was observed using the two parameters that incorporated laboratory data. Thresholds established using the composite parameter, combining syndromic and laboratory data, had the least number of false alarms in declaring season onset and were most useful in monitoring intensity. Unlike in temperate regions, the syndromic parameter was less useful in monitoring influenza activity or for setting thresholds. Influenza thresholds based on appropriate parameters have the potential to provide timely triggers for public health measures in a tropical country where monitoring and assessing influenza activity has been challenging. Based on these findings, the Ministry of Health plans to raise general awareness regarding influenza among the medical community and the general public. Our findings have important implications for countries in the tropics/subtropics and in resource-limited settings, and categorized transmission intensity can be used to assess severity of potential pandemic influenza as well as seasonal influenza.

A Review and Framework for Categorizing Current Research and Development in Health Related Geographical Information Systems (GIS) Studies

PubMed Central

Nøhr, C.; Sørensen, E. M.; Gudes, O.; Geraghty, E. M.; Shaw, N. T.; Bivona-Tellez, C.

2014-01-01

Summary Objectives The application of GIS in health science has increased over the last decade and new innovative application areas have emerged. This study reviews the literature and builds a framework to provide a conceptual overview of the domain, and to promote strategic planning for further research of GIS in health. Method The framework is based on literature from the library databases Scopus and Web of Science. The articles were identified based on keywords and initially selected for further study based on titles and abstracts. A grounded theory-inspired method was applied to categorize the selected articles in main focus areas. Subsequent frequency analysis was performed on the identified articles in areas of infectious and non-infectious diseases and continent of origin. Results A total of 865 articles were included. Four conceptual domains within GIS in health sciences comprise the framework: spatial analysis of disease, spatial analysis of health service planning, public health, health technologies and tools. Frequency analysis by disease status and location show that malaria and schistosomiasis are the most commonly analyzed infectious diseases where cancer and asthma are the most frequently analyzed non-infectious diseases. Across categories, articles from North America predominate, and in the category of spatial analysis of diseases an equal number of studies concern Asia. Conclusion Spatial analysis of diseases and health service planning are well-established research areas. The development of future technologies and new application areas for GIS and data-gathering technologies such as GPS, smartphones, remote sensing etc. will be nudging the research in GIS and health. PMID:25123730

External prognostic validations and comparisons of age- and gender-adjusted exercise capacity predictions.

PubMed

Kim, Esther S H; Ishwaran, Hemant; Blackstone, Eugene; Lauer, Michael S

2007-11-06

The purpose of this study was to externally validate the prognostic value of age- and gender-based nomograms and categorical definitions of impaired exercise capacity (EC). Exercise capacity predicts death, but its use in routine clinical practice is hampered by its close correlation with age and gender. For a median of 5 years, we followed 22,275 patients without known heart disease who underwent symptom-limited stress testing. Models for predicted or impaired EC were identified by literature search. Gender-specific multivariable proportional hazards models were constructed. Four methods were used to assess validity: Akaike Information Criterion (AIC), right-censored c-index in 100 out-of-bootstrap samples, the Nagelkerke Index R2, and calculation of calibration error in 100 bootstrap samples. There were 646 and 430 deaths in 13,098 men and 9,177 women, respectively. Of the 7 models tested in men, a model based on a Veterans Affairs cohort (predicted metabolic equivalents [METs] = 18 - [0.15 x age]) had the highest AIC and R2. In women, a model based on the St. James Take Heart Project (predicted METs = 14.7 - [0.13 x age]) performed best. Categorical definitions of fitness performed less well. Even after accounting for age and gender, there was still an important interaction with age, whereby predicted EC was a weaker predictor in older subjects (p for interaction <0.001 in men and 0.003 in women). Several methods describe EC accounting for age and gender-related differences, but their ability to predict mortality differ. Simple cutoff values fail to fully describe EC's strong predictive value.

Storytelling: a measure of anxiety in hospitalized children.

PubMed

Hudson, C J; Leeper, J D; Strickland, M P; Jessee, P

1987-01-01

This study investigates the use of storytelling as a method of measuring children's anxiety during hospitalization. Sixty-seven hospitalized children were asked to create stories about pictures they were shown. The stories were categorized as negative or positive in tone and, hence, the children were categorized as anxious or not anxious. Children who told negative stories displayed significantly more negative behaviors and showed significantly higher anxiety levels and poorer adjustment to hospitalization as measured by observational methods. The most anxious children were male, black, and rural. Implications for practitioners who work with children in medical settings are discussed.

ABC Analysis for Inventory Management: Bridging the Gap between Research and Classroom

ERIC Educational Resources Information Center

Ravinder, Handanhal; Misra, Ram B.

2014-01-01

ABC analysis is a well-established categorization technique based on the Pareto Principle for determining which items should get priority in the management of a company's inventory. In discussing this topic, today's operations management and supply chain textbooks focus on dollar volume as the sole criterion for performing the categorization. The…

Categorizing by Social Dimensions: A Developmental Basis for Stereotyping?

ERIC Educational Resources Information Center

Doyle, Anna-Beth; And Others

The use by 254 Canadian children of the dimensions of gender, language/ethnicity, and body type as bases of categorization was examined. A developmental approach was taken to see whether a sequence exists in the relative predominance of these dimensions; to examine the relation between the salience of these dimensions and cognitive developmental…

What We See Is What We Choose: Seers and Seekers with Diversity

ERIC Educational Resources Information Center

Srinivasan, Prasanna

2017-01-01

Educators are always reminded that the act of teaching and learning has to be purposeful and highly relevant to all individuals and groups within particular societies. However, societies are highly complex, and they are traversed by varied categorical groupings based on individual and group identities. Taylor contends that categorical identity…

Devices and tasks involved in the objective assessment of standing dynamic balancing - A systematic literature review.

PubMed

Petró, Bálint; Papachatzopoulou, Alexandra; Kiss, Rita M

2017-01-01

Static balancing assessment is often complemented with dynamic balancing tasks. Numerous dynamic balancing assessment methods have been developed in recent decades with their corresponding balancing devices and tasks. The aim of this systematic literature review is to identify and categorize existing objective methods of standing dynamic balancing ability assessment with an emphasis on the balancing devices and tasks being used. Three major scientific literature databases (Science Direct, Web of Science, PLoS ONE) and additional sources were used. Studies had to use a dynamic balancing device and a task described in detail. Evaluation had to be based on objectively measureable parameters. Functional tests without instrumentation evaluated exclusively by a clinician were excluded. A total of 63 articles were included. The data extracted during full-text assessment were: author and date; the balancing device with the balancing task and the measured parameters; the health conditions, size, age and sex of participant groups; and follow-up measurements. A variety of dynamic balancing assessment devices were identified and categorized as 1) Solid ground, 2) Balance board, 3) Rotating platform, 4) Horizontal translational platform, 5) Treadmill, 6) Computerized Dynamic Posturography, and 7) Other devices. The group discrimination ability of the methods was explored and the conclusions of the studies were briefly summarized. Due to the wide scope of this search, it provides an overview of balancing devices and do not represent the state-of-the-art of any single method. The identified dynamic balancing assessment methods are offered as a catalogue of candidate methods to complement static assessments used in studies involving postural control.

Word categorization from distributional information: frames confer more than the sum of their (Bigram) parts.

PubMed

Mintz, Toben H; Wang, Felix Hao; Li, Jia

2014-12-01

Grammatical categories, such as noun and verb, are the building blocks of syntactic structure and the components that govern the grammatical patterns of language. However, in many languages words are not explicitly marked with their category information, hence a critical part of acquiring a language is categorizing the words. Computational analyses of child-directed speech have shown that distributional information-information about how words pattern with one another in sentences-could be a useful source of initial category information. Yet questions remain as to whether learners use this kind of information, and if so, what kinds of distributional patterns facilitate categorization. In this paper we investigated how adults exposed to an artificial language use distributional information to categorize words. We compared training situations in which target words occurred in frames (i.e., surrounded by two words that frequently co-occur) against situations in which target words occurred in simpler bigram contexts (where an immediately adjacent word provides the context for categorization). We found that learners categorized words together when they occurred in similar frame contexts, but not when they occurred in similar bigram contexts. These findings are particularly relevant because they accord with computational investigations showing that frame contexts provide accurate category information cross-linguistically. We discuss these findings in the context of prior research on distribution-based categorization and the broader implications for the role of distributional categorization in language acquisition. Copyright © 2014 Elsevier Inc. All rights reserved.

Word Categorization From Distributional Information: Frames Confer More Than the Sum of Their (Bigram) Parts

PubMed Central

Mintz, Toben H.; Wang, Felix Hao; Li, Vivian Jia

2014-01-01

Grammatical categories, such as noun and verb, are the building blocks of syntactic structure and the components that govern the grammatical patterns of language. However, in many languages words are not explicitly marked with their category information, hence a critical part of acquiring a language is categorizing the words. Computational analyses of child-directed speech have shown that distributional information—information about how words pattern with one another in sentences—could be a useful source of initial category information. Yet questions remain as to whether learners use this kind of information, and if so, what kinds of distributional patterns facilitate categorization. In this paper we investigated how adults exposed to an artificial language use distributional information to categorize words. We compared training situations in which target words occurred in frames (i.e., surrounded by two words that frequently co-occur) against situations in which target words occurred in simpler bigram contexts (where an immediately adjacent word provides the context for categorization). We found that learners categorized words together when they occurred in similar frame contexts, but not when they occurred in similar bigram contexts. These findings are particularly relevant because they accord with computational investigations showing that frame contexts provide accurate category information cross-linguistically. We discuss these findings in the context of prior research on distribution-based categorization and the broader implications for the role of distributional categorization in language acquisition. PMID:25164244

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.

Welding-fume-induced transmission loss in tapered optical fibers

NASA Astrophysics Data System (ADS)

Yi, Ji-Haeng

2015-09-01

This paper presents a method for sensing welding fumes in real time. This method is based on the results of nanoparticle-induced optical-fiber loss experiments that show that the losses are determined by the nanoparticle density and the taper waist. The tapered fiber is obtained by applying heat radiated from hot quartz, and monitoring is done in real time. First, the durability of the tapered fiber during the welding process is proven. Then, the loss is categorized by using the sizes of welding fume particles. The sensitivity to welding fumes increases with increasing size of the particles; consequently, the dimension of the taper waist decreases.

Prediction of protein subcellular localization by weighted gene ontology terms.

PubMed

Chi, Sang-Mun

2010-08-27

We develop a new weighting approach of gene ontology (GO) terms for predicting protein subcellular localization. The weights of individual GO terms, corresponding to their contribution to the prediction algorithm, are determined by the term-weighting methods used in text categorization. We evaluate several term-weighting methods, which are based on inverse document frequency, information gain, gain ratio, odds ratio, and chi-square and its variants. Additionally, we propose a new term-weighting method based on the logarithmic transformation of chi-square. The proposed term-weighting method performs better than other term-weighting methods, and also outperforms state-of-the-art subcellular prediction methods. Our proposed method achieves 98.1%, 99.3%, 98.1%, 98.1%, and 95.9% overall accuracies for the animal BaCelLo independent dataset (IDS), fungal BaCelLo IDS, animal Höglund IDS, fungal Höglund IDS, and PLOC dataset, respectively. Furthermore, the close correlation between high-weighted GO terms and subcellular localizations suggests that our proposed method appropriately weights GO terms according to their relevance to the localizations. Copyright 2010 Elsevier Inc. All rights reserved.

Cerebellar tDCS Does Not Enhance Performance in an Implicit Categorization Learning Task.

PubMed

Verhage, Marie C; Avila, Eric O; Frens, Maarten A; Donchin, Opher; van der Geest, Jos N

2017-01-01

Background: Transcranial Direct Current Stimulation (tDCS) is a form of non-invasive electrical stimulation that changes neuronal excitability in a polarity and site-specific manner. In cognitive tasks related to prefrontal and cerebellar learning, cortical tDCS arguably facilitates learning, but the few studies investigating cerebellar tDCS, however, are inconsistent. Objective: We investigate the effect of cerebellar tDCS on performance of an implicit categorization learning task. Methods: Forty participants performed a computerized version of an implicit categorization learning task where squares had to be sorted into two categories, according to an unknown but fixed rule that integrated both the size and luminance of the square. Participants did one round of categorization to familiarize themselves with the task and to provide a baseline of performance. After that, 20 participants received anodal tDCS (20 min, 1.5 mA) over the right cerebellum, and 19 participants received sham stimulation and simultaneously started a second session of the categorization task using a new rule. Results: As expected, subjects performed better in the second session than in the first, baseline session, showing increased accuracy scores and reduced reaction times. Over trials, participants learned the categorization rule, improving their accuracy and reaction times. However, we observed no effect of anodal tDCS stimulation on overall performance or on learning, compared to sham stimulation. Conclusion: These results suggest that cerebellar tDCS does not modulate performance and learning on an implicit categorization task.

Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors

NASA Astrophysics Data System (ADS)

Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Santos-Filho, Osvaldo A.; Esposito, Emilio X.; Hopfinger, Anton J.; Tseng, Yufeng J.

2008-06-01

In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

Priming and the guidance by visual and categorical templates in visual search.

PubMed

Wilschut, Anna; Theeuwes, Jan; Olivers, Christian N L

2014-01-01

Visual search is thought to be guided by top-down templates that are held in visual working memory. Previous studies have shown that a search-guiding template can be rapidly and strongly implemented from a visual cue, whereas templates are less effective when based on categorical cues. Direct visual priming from cue to target may underlie this difference. In two experiments we first asked observers to remember two possible target colors. A postcue then indicated which of the two would be the relevant color. The task was to locate a briefly presented and masked target of the cued color among irrelevant distractor items. Experiment 1 showed that overall search accuracy improved more rapidly on the basis of a direct visual postcue that carried the target color, compared to a neutral postcue that pointed to the memorized color. However, selectivity toward the target feature, i.e., the extent to which observers searched selectively among items of the cued vs. uncued color, was found to be relatively unaffected by the presence of the visual signal. In Experiment 2 we compared search that was based on either visual or categorical information, but now controlled for direct visual priming. This resulted in no differences in overall performance nor selectivity. Altogether the results suggest that perceptual processing of visual search targets is facilitated by priming from visual cues, whereas attentional selectivity is enhanced by a working memory template that can formed from both visual and categorical input. Furthermore, if the priming is controlled for, categorical- and visual-based templates similarly enhance search guidance.

Inertial sensor-based methods in walking speed estimation: a systematic review.

PubMed

Yang, Shuozhi; Li, Qingguo

2012-01-01

Self-selected walking speed is an important measure of ambulation ability used in various clinical gait experiments. Inertial sensors, i.e., accelerometers and gyroscopes, have been gradually introduced to estimate walking speed. This research area has attracted a lot of attention for the past two decades, and the trend is continuing due to the improvement of performance and decrease in cost of the miniature inertial sensors. With the intention of understanding the state of the art of current development in this area, a systematic review on the exiting methods was done in the following electronic engines/databases: PubMed, ISI Web of Knowledge, SportDiscus and IEEE Xplore. Sixteen journal articles and papers in proceedings focusing on inertial sensor based walking speed estimation were fully reviewed. The existing methods were categorized by sensor specification, sensor attachment location, experimental design, and walking speed estimation algorithm.

Inertial Sensor-Based Methods in Walking Speed Estimation: A Systematic Review

PubMed Central

Yang, Shuozhi; Li, Qingguo

2012-01-01

Self-selected walking speed is an important measure of ambulation ability used in various clinical gait experiments. Inertial sensors, i.e., accelerometers and gyroscopes, have been gradually introduced to estimate walking speed. This research area has attracted a lot of attention for the past two decades, and the trend is continuing due to the improvement of performance and decrease in cost of the miniature inertial sensors. With the intention of understanding the state of the art of current development in this area, a systematic review on the exiting methods was done in the following electronic engines/databases: PubMed, ISI Web of Knowledge, SportDiscus and IEEE Xplore. Sixteen journal articles and papers in proceedings focusing on inertial sensor based walking speed estimation were fully reviewed. The existing methods were categorized by sensor specification, sensor attachment location, experimental design, and walking speed estimation algorithm. PMID:22778632

Active classifier selection for RGB-D object categorization using a Markov random field ensemble method

NASA Astrophysics Data System (ADS)

Durner, Maximilian; Márton, Zoltán.; Hillenbrand, Ulrich; Ali, Haider; Kleinsteuber, Martin

2017-03-01

In this work, a new ensemble method for the task of category recognition in different environments is presented. The focus is on service robotic perception in an open environment, where the robot's task is to recognize previously unseen objects of predefined categories, based on training on a public dataset. We propose an ensemble learning approach to be able to flexibly combine complementary sources of information (different state-of-the-art descriptors computed on color and depth images), based on a Markov Random Field (MRF). By exploiting its specific characteristics, the MRF ensemble method can also be executed as a Dynamic Classifier Selection (DCS) system. In the experiments, the committee- and topology-dependent performance boost of our ensemble is shown. Despite reduced computational costs and using less information, our strategy performs on the same level as common ensemble approaches. Finally, the impact of large differences between datasets is analyzed.

Estimation of group means when adjusting for covariates in generalized linear models.

PubMed

Qu, Yongming; Luo, Junxiang

2015-01-01

Generalized linear models are commonly used to analyze categorical data such as binary, count, and ordinal outcomes. Adjusting for important prognostic factors or baseline covariates in generalized linear models may improve the estimation efficiency. The model-based mean for a treatment group produced by most software packages estimates the response at the mean covariate, not the mean response for this treatment group for the studied population. Although this is not an issue for linear models, the model-based group mean estimates in generalized linear models could be seriously biased for the true group means. We propose a new method to estimate the group mean consistently with the corresponding variance estimation. Simulation showed the proposed method produces an unbiased estimator for the group means and provided the correct coverage probability. The proposed method was applied to analyze hypoglycemia data from clinical trials in diabetes. Copyright © 2014 John Wiley & Sons, Ltd.

Impact of feature saliency on visual category learning.

PubMed

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the 'essence' of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies.

Impact of feature saliency on visual category learning

PubMed Central

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the ‘essence’ of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies. PMID:25954220

Predictors of Salivary Fistulas in Patients Undergoing Salvage Total Laryngectomy

PubMed Central

Wang, Steven J.

2014-01-01

Background. Salivary fistula is a common complication after salvage total laryngectomy. Previous studies have not considered the number of layers of pharyngeal closure and have not classified fistulas according to severity. Our objective was to analyze our institutional experience with salvage total laryngectomy, categorize salivary fistulas based on severity, and study the effect of various pharyngeal closure techniques on fistula incidence. Methods. Retrospective analysis of 48 patients who underwent salvage total laryngectomy, comparing pharyngeal closure technique and use of a pectoralis major flap with regard to salivary fistula rate. Fistulas were categorized into major and minor fistulas based on whether operative intervention was required. Results. The major fistula rate was 18.8% (9/48) and the minor fistula rate was 29.2% (14/48). The overall (major plus minor) fistula rate was 47.9%. The overall fistula and major fistula rates decreased with increasing the number of closure layers and with use of a pectoralis major flap; however, these correlations did not reach statistical significance. Other than age, there were no clinicopathologic variables associated with salivary fistulas. Conclusion. For salvage total laryngectomies, increasing the number of closure layers or use of a pectoralis major flap may reduce the risk of salivary fistula. PMID:27355065

Negative Life Events, Social Support, and Self-Efficacy in Anxious Adolescents.

PubMed

Raknes, Solfrid; Pallesen, Ståle; Bjaastad, Jon Fauskanger; Wergeland, Gro Janne; Hoffart, Asle; Dyregrov, Kari; Håland, Åshild Tellefsen; Haugland, Bente Storm Mowatt

2017-01-01

Purpose To examine the prevalence and correlates of anxiety in a community sample of adolescents. Knowing the prevalence and characteristics of anxious adolescents is valuable to improve anxiety prevention strategies and interventions. Design Cross-sectional data about anxiety were collected via a school survey from a community sample of Norwegian adolescents aged 12-17 ( N = 1719). Methods Based on scores from the Spence Children's Anxiety Scale, the adolescents were categorized as not anxious or anxious. Logistic regression analysis was performed to access the impact of each factor on the likelihood that participants would report an elevated level of anxiety. Results A total of 22% of the adolescents were categorized as anxious. Female gender, experienced negative life events, low social support, and low self-efficacy were associated with elevated level of anxiety. Conclusions The high prevalence of anxiety in adolescents demonstrates the importance of improved prevention interventions targeting anxious adolescents. We argue that addressing is the responsibility of not only the individual adolescents and their families but also schools, school health services, and policy makers. School-based interventions that increase social support and self-efficacy would probably be particularly beneficial for anxious adolescents.

Screening tool to evaluate the vulnerability of down-gradient receptors to groundwater contaminants from uncapped landfills

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

Baker, Ronald J.; Reilly, Timothy J.; Lopez, Anthony

2015-09-15

Highlights: • A spreadsheet-based risk screening tool for groundwater affected by landfills is presented. • Domenico solute transport equations are used to estimate downgradient contaminant concentrations. • Landfills are categorized as presenting high, moderate or low risks. • Analysis of parameter sensitivity and examples of the method’s application are given. • The method has value to regulators and those considering redeveloping closed landfills. - Abstract: A screening tool for quantifying levels of concern for contaminants detected in monitoring wells on or near landfills to down-gradient receptors (streams, wetlands and residential lots) was developed and evaluated. The tool uses Quick Domenicomore » Multi-scenario (QDM), a spreadsheet implementation of Domenico-based solute transport, to estimate concentrations of contaminants reaching receptors under steady-state conditions from a constant-strength source. Unlike most other available Domenico-based model applications, QDM calculates the time for down-gradient contaminant concentrations to approach steady state and appropriate dispersivity values, and allows for up to fifty simulations on a single spreadsheet. Sensitivity of QDM solutions to critical model parameters was quantified. The screening tool uses QDM results to categorize landfills as having high, moderate and low levels of concern, based on contaminant concentrations reaching receptors relative to regulatory concentrations. The application of this tool was demonstrated by assessing levels of concern (as defined by the New Jersey Pinelands Commission) for thirty closed, uncapped landfills in the New Jersey Pinelands National Reserve, using historic water-quality data from monitoring wells on and near landfills and hydraulic parameters from regional flow models. Twelve of these landfills are categorized as having high levels of concern, indicating a need for further assessment. This tool is not a replacement for conventional numerically-based transport model or other available Domenico-based applications, but is suitable for quickly assessing the level of concern posed by a landfill or other contaminant point source before expensive and lengthy monitoring or remediation measures are taken. In addition to quantifying the level of concern using historic groundwater-monitoring data, the tool allows for archiving model scenarios and adding refinements as new data become available.« less

Explicit and implicit tasks for assessing hedonic-versus nutrition-based attitudes towards food in French children.

PubMed

Monnery-Patris, Sandrine; Marty, Lucile; Bayer, Frédéric; Nicklaus, Sophie; Chambaron, Stéphanie

2016-01-01

Attitudes are important precursors of behaviours. This study aims to compare the food attitudes (i.e., hedonic- and nutrition-based) of children using both an implicit pairing task and an explicit forced-choice categorization task suitable for the cognitive abilities of 5- to 11-year-olds. A dominance of hedonically driven attitudes was expected for all ages in the pairing task, designed to elicit affective and spontaneous answers, whereas a progressive emergence of nutrition-based attitudes was expected in the categorization task, designed to involve deliberate analyses of the costs/benefits of foods. An additional exploratory goal was to evaluate differences in the attitudes of normal and overweight children in both tasks. Children from 3 school levels (n = 194; mean age = 8.03 years) were individually tested on computers in their schools. They performed a pairing task in which the tendencies to associate foods with nutritional vs. culinary contexts were assessed. Next, they were asked to categorize each food into one of the following four categories: "yummy", "yucky" (i.e., hedonic categories), "makes you strong", or"makes you fat" (i.e., nutritional categories). The hedonic/culinary pairs were very frequently selected (81% on average), and this frequency significantly increased through school levels. In contrast, in the categorization task, a significant increase in nutrition-driven categorizations with school level was observed. Additional analyses revealed no differences in the food attitudes between the normal and overweight children in the pairing task, and a tendency towards lower hedonic categorizations among the overweight children. Culinary associations can reflect cultural learning in the French context where food pleasure is dominant. In contrast, the progressive emergence of cognitively driven attitudes with age may reflect the cognitive development of children who are more reasonable and influenced by social norms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Will a category cue attract you? Motor output reveals dynamic competition across person construal.

PubMed

Freeman, Jonathan B; Ambady, Nalini; Rule, Nicholas O; Johnson, Kerri L

2008-11-01

People use social categories to perceive others, extracting category cues to glean membership. Growing evidence for continuous dynamics in real-time cognition suggests, contrary to prevailing social psychological accounts, that person construal may involve dynamic competition between simultaneously active representations. To test this, the authors examined social categorization in real-time by streaming the x, y coordinates of hand movements as participants categorized typical and atypical faces by sex. Though judgments of atypical targets were largely accurate, online motor output exhibited a continuous spatial attraction toward the opposite sex category, indicating dynamic competition between multiple social category alternatives. The authors offer a dynamic continuity account of social categorization and provide converging evidence across categorizations of real male and female faces (containing a typical or an atypical sex-specifying cue) and categorizations of computer-generated male and female faces (with subtly morphed sex-typical or sex-atypical features). In 3 studies, online motor output revealed continuous dynamics underlying person construal, in which multiple simultaneously and partially active category representations gradually cascade into social categorical judgments. Such evidence is challenging for discrete stage-based accounts. (c) 2008 APA, all rights reserved

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database.

PubMed

Choi, Joon Yul; Yoo, Tae Keun; Seo, Jeong Gi; Kwak, Jiyong; Um, Terry Taewoong; Rim, Tyler Hyungtaek

2017-01-01

Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNet for an automated detection of multiple retinal diseases with fundus photographs involved in STructured Analysis of the REtina (STARE) database. Dataset was built by expanding data on 10 categories, including normal retina and nine retinal diseases. The optimal outcomes were acquired by using a random forest transfer learning based on VGG-19 architecture. The classification results depended greatly on the number of categories. As the number of categories increased, the performance of deep learning models was diminished. When all 10 categories were included, we obtained results with an accuracy of 30.5%, relative classifier information (RCI) of 0.052, and Cohen's kappa of 0.224. Considering three integrated normal, background diabetic retinopathy, and dry age-related macular degeneration, the multi-categorical classifier showed accuracy of 72.8%, 0.283 RCI, and 0.577 kappa. In addition, several ensemble classifiers enhanced the multi-categorical classification performance. The transfer learning incorporated with ensemble classifier of clustering and voting approach presented the best performance with accuracy of 36.7%, 0.053 RCI, and 0.225 kappa in the 10 retinal diseases classification problem. First, due to the small size of datasets, the deep learning techniques in this study were ineffective to be applied in clinics where numerous patients suffering from various types of retinal disorders visit for diagnosis and treatment. Second, we found that the transfer learning incorporated with ensemble classifiers can improve the classification performance in order to detect multi-categorical retinal diseases. Further studies should confirm the effectiveness of algorithms with large datasets obtained from hospitals.

Making predictions of mangrove deforestation: a comparison of two methods in Kenya.

PubMed

Rideout, Alasdair J R; Joshi, Neha P; Viergever, Karin M; Huxham, Mark; Briers, Robert A

2013-11-01

Deforestation of mangroves is of global concern given their importance for carbon storage, biogeochemical cycling and the provision of other ecosystem services, but the links between rates of loss and potential drivers or risk factors are rarely evaluated. Here, we identified key drivers of mangrove loss in Kenya and compared two different approaches to predicting risk. Risk factors tested included various possible predictors of anthropogenic deforestation, related to population, suitability for land use change and accessibility. Two approaches were taken to modelling risk; a quantitative statistical approach and a qualitative categorical ranking approach. A quantitative model linking rates of loss to risk factors was constructed based on generalized least squares regression and using mangrove loss data from 1992 to 2000. Population density, soil type and proximity to roads were the most important predictors. In order to validate this model it was used to generate a map of losses of Kenyan mangroves predicted to have occurred between 2000 and 2010. The qualitative categorical model was constructed using data from the same selection of variables, with the coincidence of different risk factors in particular mangrove areas used in an additive manner to create a relative risk index which was then mapped. Quantitative predictions of loss were significantly correlated with the actual loss of mangroves between 2000 and 2010 and the categorical risk index values were also highly correlated with the quantitative predictions. Hence, in this case the relatively simple categorical modelling approach was of similar predictive value to the more complex quantitative model of mangrove deforestation. The advantages and disadvantages of each approach are discussed, and the implications for mangroves are outlined. © 2013 Blackwell Publishing Ltd.

Analyzing polysemous concepts from a clinical perspective: Application to auditing concept categorization in the UMLS

PubMed Central

Mougin, Fleur; Bodenreider, Olivier; Burgun, Anita

2015-01-01

Objectives Polysemy is a frequent issue in biomedical terminologies. In the Unified Medical Language System (UMLS), polysemous terms are either represented as several independent concepts, or clustered into a single, multiply-categorized concept. The objective of this study is to analyze polysemous concepts in the UMLS through their categorization and hierarchical relations for auditing purposes. Methods We used the association of a concept with multiple Semantic Groups (SGs) as a surrogate for polysemy. We first extracted multi-SG (MSG) concepts from the UMLS Metathesaurus and characterized them in terms of the combinations of SGs with which they are associated. We then clustered MSG concepts in order to identify major types of polysemy. We also analyzed the inheritance of SGs in MSG concepts. Finally, we manually reviewed the categorization of the MSG concepts for auditing purposes. Results The 1208 MSG concepts in the Metathesaurus are associated with 30 distinct pairs of SGs. We created 75 semantically homogeneous clusters of MSG concepts, and 276 MSG concepts could not be clustered for lack of hierarchical relations. The clusters were characterized by the most frequent pairs of semantic types of their constituent MSG concepts. MSG concepts exhibit limited semantic compatibility with their parent and child concepts. A large majority of MSG concepts (92%) are adequately categorized. Examples of miscategorized concepts are presented. Conclusion This work is a systematic analysis and manual review of all concepts categorized by multiple SGs in the UMLS. The correctly-categorized MSG concepts do reflect polysemy in the UMLS Metathesaurus. The analysis of inheritance of SGs proved useful for auditing concept categorization in the UMLS. PMID:19303057

Physical 'disability' in Bantu languages: understanding the relativity of classification and meaning.

PubMed

Devlieger, P J

1998-03-01

The terminology related to 'physical disability' in proto-Bantu and in contemporary Bantu languages of Zone L are examined for a better understanding of African classification and meaning. The methods used in the examination include 'words and things' and ethnographic fieldwork. In proto-Bantu, nominal classes are used to categorize disability as both human and non-human. Based on the distribution of terminology, a support for differing regional and historical meaning is developed. The most ancient meaning links physical disability to 'becoming heavy' out of which variants developed. In contemporary Bantu languages in Zone L, the widespread use of the term -lema reemphasizes categorization in both human and non-human, and the use of meaning found in proto-Bantu is evident. However, ethnographic work in the same language area indicates that other terms are important to an understanding of classification and meaning related to physical disability in Zone L. These terms relate to sorcery or reincarnation as meanings attached to disability.

Heavy Drinking and Polydrug Use among College Students

PubMed Central

O’Grady, Kevin E.; Arria, Amelia M.; Fitzelle, Dawn M.B.; Wish, Eric D.

2008-01-01

Excessive alcohol consumption is a serious problem on college campuses but may not be adequately captured by traditional methods of defining binge drinking. This study examined a new approach to categorizing alcohol use and its relationship with illicit drug use. A survey was administered to 484 college students ages 18 to 25. Drinkers were divided into three groups based on the number of typical drinks consumed per day: “light”—1 to 4 (n=182); “moderate”—5 to 9 (n=173); and “heavy”—10+ (n=56). Heavy drinkers could be differentiated from moderate and light drinkers on age of onset of alcohol use, illicit drug use, and frequency of illicit drug use. A binary categorization of “binge” vs. “nonbinge” drinking may obscure important differences within binge drinkers. These findings have implications for prevention, as well as clinical risk assessment of college student drinkers for adverse consequences of concomitant alcohol and illicit drug consumption. PMID:19122887

Surface ozone at the Swiss Alpine site Arosa: the hemispheric background and the influence of large-scale anthropogenic emissions

NASA Astrophysics Data System (ADS)

Pochanart, Pakpong; Akimoto, Hajime; Maksyutov, Shamil; Staehelin, Johannes

An innovative and effective method using isentropic trajectory analysis based on the residence time of air masses over the polluted region of Europe was successfully applied to categorize surface ozone amounts at Arosa, Switzerland during 1996-1997. The "European representative" background ozone seasonal cycle at Arosa is associated with long-range transport of North Atlantic air masses, and displays the spring maximum-summer minimum with an annual average of 35 ppb. The photochemical ozone production due to the intense large-scale anthropogenic emission over Europe is estimated as high as 20 ppb in summer, whereas it is insignificant in winter. European sources contribute an annual net ozone production of 9-12 ppb at Arosa. Comparison with the selected regional representative site in Western Europe shows similar results indicating that the categorized ozone data at Arosa by this technique could be regarded as a representative for northern hemispheric mid-latitudes.

Increasing operating room productivity by duration categories and a newsvendor model.

PubMed

Lehtonen, Juha-Matti; Torkki, Paulus; Peltokorpi, Antti; Moilanen, Teemu

2013-01-01

Previous studies approach surgery scheduling mainly from the mathematical modeling perspective which is often hard to apply in a practical environment. The aim of this study is to develop a practical scheduling system that considers the advantages of both surgery categorization and newsvendor model to surgery scheduling. The research was carried out in a Finnish orthopaedic specialist centre that performs only joint replacement surgery. Four surgery categorization scenarios were defined and their productivity analyzed by simulation and newsvendor model. Detailed analyses of surgery durations and the use of more accurate case categories and their combinations in scheduling improved OR productivity 11.3 percent when compared to the base case. Planning to have one OR team to work longer led to remarkable decrease in scheduling inefficiency. In surgical services, productivity and cost-efficiency can be improved by utilizing historical data in case scheduling and by increasing flexibility in personnel management. The study increases the understanding of practical scheduling methods used to improve efficiency in surgical services.

Pearson's chi-square test and rank correlation inferences for clustered data.

PubMed

Shih, Joanna H; Fay, Michael P

2017-09-01

Pearson's chi-square test has been widely used in testing for association between two categorical responses. Spearman rank correlation and Kendall's tau are often used for measuring and testing association between two continuous or ordered categorical responses. However, the established statistical properties of these tests are only valid when each pair of responses are independent, where each sampling unit has only one pair of responses. When each sampling unit consists of a cluster of paired responses, the assumption of independent pairs is violated. In this article, we apply the within-cluster resampling technique to U-statistics to form new tests and rank-based correlation estimators for possibly tied clustered data. We develop large sample properties of the new proposed tests and estimators and evaluate their performance by simulations. The proposed methods are applied to a data set collected from a PET/CT imaging study for illustration. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

An Analysis of Effects of Variable Factors on Weapon Performance

DTIC Science & Technology

1993-03-01

ALTERNATIVE ANALYSIS A. CATEGORICAL DATA ANALYSIS Statistical methodology for categorical data analysis traces its roots to the work of Francis Galton in the...choice of statistical tests . This thesis examines an analysis performed by Surface Warfare Development Group (SWDG). The SWDG analysis is shown to be...incorrect due to the misapplication of testing methods. A corrected analysis is presented and recommendations suggested for changes to the testing

Newborn infants' sensitivity to perceptual cues to lexical and grammatical words.

PubMed

Shi, R; Werker, J F; Morgan, J L

1999-09-30

In our study newborn infants were presented with lists of lexical and grammatical words prepared from natural maternal speech. The results show that newborns are able to categorically discriminate these sets of words based on a constellation of perceptual cues that distinguish them. This general ability to detect and categorically discriminate sets of words on the basis of multiple acoustic and phonological cues may provide a perceptual base that can help older infants bootstrap into the acquisition of grammatical categories and syntactic structure.

Wavelet-based image analysis system for soil texture analysis

NASA Astrophysics Data System (ADS)

Sun, Yun; Long, Zhiling; Jang, Ping-Rey; Plodinec, M. John

2003-05-01

Soil texture is defined as the relative proportion of clay, silt and sand found in a given soil sample. It is an important physical property of soil that affects such phenomena as plant growth and agricultural fertility. Traditional methods used to determine soil texture are either time consuming (hydrometer), or subjective and experience-demanding (field tactile evaluation). Considering that textural patterns observed at soil surfaces are uniquely associated with soil textures, we propose an innovative approach to soil texture analysis, in which wavelet frames-based features representing texture contents of soil images are extracted and categorized by applying a maximum likelihood criterion. The soil texture analysis system has been tested successfully with an accuracy of 91% in classifying soil samples into one of three general categories of soil textures. In comparison with the common methods, this wavelet-based image analysis approach is convenient, efficient, fast, and objective.

Adolescent Asthma Self-Management: A Concept Analysis and Operational Definition.

PubMed

Mammen, Jennifer; Rhee, Hyekyun

2012-12-01

BACKGROUND: Adolescents with asthma have a higher risk of morbidity and mortality than other age groups. Asthma self-management has been shown to improve outcomes; however, the concept of asthma self-management is not explicitly defined. METHODS: We use the Norris method of concept clarification to delineate what constitutes the concept of asthma self-management in adolescents. Five databases were searched to identify components of the concept of adolescent asthma self-management, and lists of relevant subconcepts were compiled and categorized. RESULTS: Analysis revealed 4 specific domains of self-management behaviors: (1) symptom prevention; (2) symptom monitoring; (3) acute symptom management; and (4) communication with important others. These domains of self-management were mediated by intrapersonal/cognitive and interpersonal/contextual factors. CONCLUSIONS: Based on the analysis, we offer a research-based operational definition for adolescent asthma self-management and a preliminary model that can serve as a conceptual base for further research.

Enhanced HMAX model with feedforward feature learning for multiclass categorization.

PubMed

Li, Yinlin; Wu, Wei; Zhang, Bo; Li, Fengfu

2015-01-01

In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX) is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT) layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 ms of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: (1) To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; (2) To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; (3) Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.

Dual PECCS: a cognitive system for conceptual representation and categorization

NASA Astrophysics Data System (ADS)

Lieto, Antonio; Radicioni, Daniele P.; Rho, Valentina

2017-03-01

In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the hypothesis of conceptual structures represented as heterogeneous proxytypes. Dual-PECCS has been experimentally assessed in a task of conceptual categorization where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies, and its output has been compared to human responses. The obtained results suggest that our approach can be beneficial to improve the representational and reasoning conceptual capabilities of standard cognitive artificial systems, and - in addition - that it may be plausibly applied to different general computational models of cognition. The current version of the system, in fact, extends our previous work, in that Dual- PECCS is now integrated and tested into two cognitive architectures, ACT-R and CLARION, implementing different assumptions on the underlying invariant structures governing human cognition. Such integration allowed us to extend our previous evaluation.

Effects of classification context on categorization in natural categories.

PubMed

Hampton, James A; Dubois, Danièle; Yeh, Wenchi

2006-10-01

The patterns of classification of borderline instances of eight common taxonomic categories were examined under three different instructional conditions to test two predictions: first, that lack of a specified context contributes to vagueness in categorization, and second, that altering the purpose of classification can lead to greater or lesser dependence on similarity in classification. The instructional conditions contrasted purely pragmatic with more technical/quasi-legal contexts as purposes for classification, and these were compared with a no-context control. The measures of category vagueness were between-subjects disagreement and within-subjects consistency, and the measures of similarity-based categorization were category breadth and the correlation of instance categorization probability with mean rated typicality, independently measured in a neutral context. Contrary to predictions, none of the measures of vagueness, reliability, category breadth, or correlation with typicality were generally affected by the instructional setting as a function of pragmatic versus technical purposes. Only one subcondition, in which a situational context was implied in addition to a purposive context, produced a significant change in categorization. Further experiments demonstrated that the effect of context was not increased when participants talked their way through the task, and that a technical context did not elicit more all-or-none categorization than did a pragmatic context. These findings place an important boundary condition on the effects of instructional context on conceptual categorization.

K-Nearest Neighbor Algorithm Optimization in Text Categorization

NASA Astrophysics Data System (ADS)

Chen, Shufeng

2018-01-01

K-Nearest Neighbor (KNN) classification algorithm is one of the simplest methods of data mining. It has been widely used in classification, regression and pattern recognition. The traditional KNN method has some shortcomings such as large amount of sample computation and strong dependence on the sample library capacity. In this paper, a method of representative sample optimization based on CURE algorithm is proposed. On the basis of this, presenting a quick algorithm QKNN (Quick k-nearest neighbor) to find the nearest k neighbor samples, which greatly reduces the similarity calculation. The experimental results show that this algorithm can effectively reduce the number of samples and speed up the search for the k nearest neighbor samples to improve the performance of the algorithm.

Chemical fingerprinting and quantitative constituent analysis of Siwu decoction categorized formulae by UPLC-QTOF/MS/MS and HPLC-DAD

PubMed Central

2013-01-01

Background Siwu decoction categorized formulae (SWDCF) are widely used for treating gynecological diseases. This study aims to elucidate the differences of bioactive constituents in SWDCF by ultra-high performance liquid chromatography coupled with time-of-flight mass spectrometry (UPLC - QTOF - MS /MS) and HPLC-DAD. Methods An efficient method based on UPLC - QTOF - MS /MS was developed for identifying the chemical profiles of SWDCF. HPLC-DAD method was used for quantifying seven chemical markers in SWDCF. Results Eighty four components were identified or characterized, including ten organic acids, thirty glycosides (monoterpene or iridoid or phenylpropanoids glycosides), fourteen lactones, eighteen flavonoids, and eleven alkaloids in the complex system. The datasets of tR-m/z pairs, ion intensities and sample codes were processed with supervised orthogonal partial least squared discriminant analysis to compare these decoction samples. After a clear classification was established, OPLS-DA was performed and 16 common components with relative quantity in SWDCF samples were determined. Gallic acid, protocatechuic acid, vanillic acid, caffeic acid, paeoniflorin, ferulic acid, and senkyunolide I were selected as the chemical markers to identify SWDCF by HPLC-DAD. Conclusion The chemical profiles with 84 components in SWDCF, including monoterpene glycosides, acetophenones, galloyl glucoses, even some isomers in the complex system were characterized by UPLC–QTOF–MS/MS. PMID:23453004

Types of Lay Health Influencers in Tobacco Cessation: A Qualitative Study

PubMed Central

Yuan, Nicole P.; Wind, Steven; Nichter, Mimi; Nichter, Mark; Castañeda, Heide; Carruth, Lauren; Muramoto, Myra L.

2014-01-01

Objective To identify types of health influencers in tobacco cessation based on the frequency and characteristics of brief intervention activities. Methods Longitudinal qualitative interviews were completed with 28 individuals post-training. Results Four individuals were categorized as Rarely Active, 5 as Active with Family and Friends, 9 as Active in the Workplace, and 10 as Proactive in Multiple Settings. Unique motivators, intervention behaviors, and barriers were documented. Some individuals displayed high levels of self-efficacy necessary for expanding the reach of community-based interventions. Conclusion Training programs need to address the impact of contextual factors on initiating and sustaining intervention activities. PMID:20524890

Sticky Categorizations: Processes of Marginalization and (Im)possible Mo(ve)ments of Transcending Marginalization

ERIC Educational Resources Information Center

Lagermann, Laila Colding

2015-01-01

What are the possibilities and/or limitations for becoming subjects differenciated from previous categorizations, such as "troublemaker", to which certain students are subjected? This is the question analyzed in this paper, based on observations of, and narratives and perspectives of, two 15-year-old ethnic minority boys at a school in…

Introduction to the Special Section: Toward a Dimensionally Based Taxonomy of Psychopathology

PubMed Central

Krueger, Robert F.; Watson, David; Barlow, David H.

2008-01-01

Much current psychopathology research is framed by categorical constructs. Limitations of categorical constructs have been articulated, and dimensional constructs are often proposed as viable alternatives to categories of psychopathology. The purpose of this Special Section is to articulate and discuss diverse issues that arise in contemplating dimensional constructs as targets for psychopathology research. PMID:16351372

Sports participation and alcohol use among adolescents: the impact of measurement and other research design elements.

PubMed

Mays, Darren; Gatti, Margaret E; Thompson, Nancy J

2011-06-01

Sports participation, while offering numerous developmental benefits for adolescents, has been associated with alcohol use in prior research. However, the relationship between sports participation and alcohol use among adolescents remains unclear, particularly how research design elements impact evidence of this relationship. We reviewed the evidence regarding sports participation and alcohol use among adolescents, with a focus on examining the potential impact of research design elements on this evidence. Studies were assessed for eligibility and coded based on research design elements including: study design, sampling method, sample size, and measures of sports participation and alcohol use. Fifty-four studies were assessed for eligibility, 29 of which were included in the review. Nearly two-thirds used a cross-sectional design and a random sampling method, with sample sizes ranging from 178 to 50,168 adolescents (Median = 1,769). Sixteen studies used a categorical measure of sports participation, while 7 applied an index-type measure and 6 employed some other measure of sports participation. Most studies assessed alcohol-related behaviors (n = 18) through categorical measures, while only 6 applied frequency only measures of alcohol use, 1 study applied quantity only measures, and 3 studies used quantity and frequency measures. Sports participation has been defined and measured in various ways, most of which do not differentiate between interscholastic and community-based contexts, confounding this relationship. Stronger measures of both sports participation and alcohol use need to be applied in future studies to advance our understanding of this relationship among youths.

Meniscus repair using mesenchymal stem cells - a comprehensive review.

PubMed

Yu, Hana; Adesida, Adetola B; Jomha, Nadr M

2015-04-30

The menisci are a pair of semilunar fibrocartilage structures that play an essential role in maintaining normal knee function. Injury to the menisci can disrupt joint stability and lead to debilitating results. Because natural meniscal healing is limited, an efficient method of repair is necessary. Tissue engineering (TE) combines the principles of life sciences and engineering to restore the unique architecture of the native meniscus. Mesenchymal stem cells (MSCs) have been investigated for their therapeutic potential both in vitro and in vivo. This comprehensive review examines the English literature identified through a database search using Medline, Embase, Engineering Village, and SPORTDiscus. The search results were classified based on MSC type, animal model, and method of MSC delivery/culture. A variety of MSC types, including bone marrow-derived, synovium-derived, adipose-derived, and meniscus-derived MSCs, has been examined. Research results were categorized into and discussed by the different animal models used; namely murine, leporine, porcine, caprine, bovine, ovine, canine, equine, and human models of meniscus defect/repair. Within each animal model, studies were categorized further according to MSC delivery/culture techniques. These techniques included direct application, fibrin glue/gel/clot, intra-articular injection, scaffold, tissue-engineered construct, meniscus tissue, pellets/aggregates, and hydrogel. The purpose of this review is to inform the reader about the current state and advances in meniscus TE using MSCs. Future directions of MSC-based meniscus TE are also suggested to help guide prospective research.

The Importance of Measuring Strength-of-Preference Scores for Health Care Options in Preference-Sensitive Care

PubMed Central

Crump, R. Trafford; Llewellyn-Thomas, Hilary A.

2012-01-01

Objective The objective was to determine whether a paired-comparison/leaning scale method: a) could feasibly be used to elicit strength-of-preference scores for elective health care options in large community-based survey settings; and b) could reveal preferential sub-groups that would have been overlooked if only a categorical-response format had been used. Study Design Medicare beneficiaries in four different regions of the United States were interviewed in person. Participants considered 8 clinical scenarios, each with 2 to 3 different health care options. For each scenario, participants categorically selected their favored option, then indicated how strongly they favored that option relative to the alternative on a paired-comparison bi-directional Leaning Scale. Results Two hundred and two participants were interviewed. For 7 of the 8 scenarios, a clear majority (> 50%) indicated that, overall, they categorically favored one option over the alternative(s). However, the bi-directional strength-of-preference Leaning Scale scores revealed that, in 4 scenarios, for half of those participants, their preference for the favored option was actually “weak” or “neutral”. Conclusion Investigators aiming to assess population-wide preferential attitudes towards different elective health care scenarios should consider gathering ordinal-level strength-of-preference scores and could feasibly use the paired-comparison/bi-directional Leaning Scale to do so. PMID:22494579

Swimming with multiple propulsors: measurement and comparison of swimming gaits in three species of neotropical cichlids.

PubMed

Feilich, Kara L

2017-11-15

Comparative studies of fish swimming have been limited by the lack of quantitative definitions of fish gaits. Traditionally, steady swimming gaits have been defined categorically by the fin or region of the body that is used as the main propulsor and named after major fish clades (e.g. carangiform, anguilliform, balistiform, labriform). This method of categorization is limited by the lack of explicit measurements, the inability to incorporate contributions of multiple propulsors and the inability to compare gaits across different categories. I propose an alternative framework for the definition and comparison of fish gaits based on the propulsive contribution of each structure (body and/or fin) being used as a propulsor relative to locomotor output, and demonstrate the effectiveness of this framework by comparing three species of neotropical cichlids with different body shapes. This approach is modular with respect to the number of propulsors considered, flexible with respect to the definition of the propulsive inputs and the locomotor output of interest, and designed explicitly to handle combinations of propulsors. Using this approach, gait can be defined as a trajectory through propulsive space, and gait transitions can be defined as discontinuities in the gait trajectory. By measuring and defining gait in this way, patterns of clustering corresponding to existing categorical definitions of gait may emerge, and gaits can be rigorously compared across categories. © 2017. Published by The Company of Biologists Ltd.

Uncertainty of fast biological radiation dose assessment for emergency response scenarios.

PubMed

Ainsbury, Elizabeth A; Higueras, Manuel; Puig, Pedro; Einbeck, Jochen; Samaga, Daniel; Barquinero, Joan Francesc; Barrios, Lleonard; Brzozowska, Beata; Fattibene, Paola; Gregoire, Eric; Jaworska, Alicja; Lloyd, David; Oestreicher, Ursula; Romm, Horst; Rothkamm, Kai; Roy, Laurence; Sommer, Sylwester; Terzoudi, Georgia; Thierens, Hubert; Trompier, Francois; Vral, Anne; Woda, Clemens

2017-01-01

Reliable dose estimation is an important factor in appropriate dosimetric triage categorization of exposed individuals to support radiation emergency response. Following work done under the EU FP7 MULTIBIODOSE and RENEB projects, formal methods for defining uncertainties on biological dose estimates are compared using simulated and real data from recent exercises. The results demonstrate that a Bayesian method of uncertainty assessment is the most appropriate, even in the absence of detailed prior information. The relative accuracy and relevance of techniques for calculating uncertainty and combining assay results to produce single dose and uncertainty estimates is further discussed. Finally, it is demonstrated that whatever uncertainty estimation method is employed, ignoring the uncertainty on fast dose assessments can have an important impact on rapid biodosimetric categorization.

Vocal Identity Recognition in Autism Spectrum Disorder

PubMed Central

Lin, I-Fan; Yamada, Takashi; Komine, Yoko; Kato, Nobumasa; Kato, Masaharu; Kashino, Makio

2015-01-01

Voices can convey information about a speaker. When forming an abstract representation of a speaker, it is important to extract relevant features from acoustic signals that are invariant to the modulation of these signals. This study investigated the way in which individuals with autism spectrum disorder (ASD) recognize and memorize vocal identity. The ASD group and control group performed similarly in a task when asked to choose the name of the newly-learned speaker based on his or her voice, and the ASD group outperformed the control group in a subsequent familiarity test when asked to discriminate the previously trained voices and untrained voices. These findings suggest that individuals with ASD recognized and memorized voices as well as the neurotypical individuals did, but they categorized voices in a different way: individuals with ASD categorized voices quantitatively based on the exact acoustic features, while neurotypical individuals categorized voices qualitatively based on the acoustic patterns correlated to the speakers' physical and mental properties. PMID:26070199

Vocal Identity Recognition in Autism Spectrum Disorder.

PubMed

Lin, I-Fan; Yamada, Takashi; Komine, Yoko; Kato, Nobumasa; Kato, Masaharu; Kashino, Makio

2015-01-01

Voices can convey information about a speaker. When forming an abstract representation of a speaker, it is important to extract relevant features from acoustic signals that are invariant to the modulation of these signals. This study investigated the way in which individuals with autism spectrum disorder (ASD) recognize and memorize vocal identity. The ASD group and control group performed similarly in a task when asked to choose the name of the newly-learned speaker based on his or her voice, and the ASD group outperformed the control group in a subsequent familiarity test when asked to discriminate the previously trained voices and untrained voices. These findings suggest that individuals with ASD recognized and memorized voices as well as the neurotypical individuals did, but they categorized voices in a different way: individuals with ASD categorized voices quantitatively based on the exact acoustic features, while neurotypical individuals categorized voices qualitatively based on the acoustic patterns correlated to the speakers' physical and mental properties.

One Giant Leap for Categorizers: One Small Step for Categorization Theory

PubMed Central

Smith, J. David; Ell, Shawn W.

2015-01-01

We explore humans’ rule-based category learning using analytic approaches that highlight their psychological transitions during learning. These approaches confirm that humans show qualitatively sudden psychological transitions during rule learning. These transitions contribute to the theoretical literature contrasting single vs. multiple category-learning systems, because they seem to reveal a distinctive learning process of explicit rule discovery. A complete psychology of categorization must describe this learning process, too. Yet extensive formal-modeling analyses confirm that a wide range of current (gradient-descent) models cannot reproduce these transitions, including influential rule-based models (e.g., COVIS) and exemplar models (e.g., ALCOVE). It is an important theoretical conclusion that existing models cannot explain humans’ rule-based category learning. The problem these models have is the incremental algorithm by which learning is simulated. Humans descend no gradient in rule-based tasks. Very different formal-modeling systems will be required to explain humans’ psychology in these tasks. An important next step will be to build a new generation of models that can do so. PMID:26332587

Development of a Comprehensive Hospital-Based Elder Abuse Intervention: An Initial Systematic Scoping Review

PubMed Central

Du Mont, Janice; Macdonald, Sheila; Kosa, Daisy; Elliot, Shannon; Spencer, Charmaine; Yaffe, Mark

2015-01-01

Introduction Elder abuse, a universal human rights problem, is associated with many negative consequences. In most jurisdictions, however, there are no comprehensive hospital-based interventions for elder abuse that address the totality of needs of abused older adults: psychological, physical, legal, and social. As the first step towards the development of such an intervention, we undertook a systematic scoping review. Objectives Our primary objective was to systematically extract and synthesize actionable and applicable recommendations for components of a multidisciplinary intersectoral hospital-based elder abuse intervention. A secondary objective was to summarize the characteristics of the responses reviewed, including methods of development and validation. Methods The grey and scholarly literatures were systematically searched, with two independent reviewers conducting the title, abstract and full text screening. Documents were considered eligible for inclusion if they: 1) addressed a response (e.g., an intervention) to elder abuse, 2) contained recommendations for responding to abused older adults with potential relevance to a multidisciplinary and intersectoral hospital-based elder abuse intervention; and 3) were available in English. Analysis The extracted recommendations for care were collated, coded, categorized into themes, and further reviewed for relevancy to a comprehensive hospital-based response. Characteristics of the responses were summarized using descriptive statistics. Results 649 recommendations were extracted from 68 distinct elder abuse responses, 149 of which were deemed relevant and were categorized into 5 themes: Initial contact; Capacity and consent; Interview with older adult, caregiver, collateral contacts, and/or suspected abuser; Assessment: physical/forensic, mental, psychosocial, and environmental/functional; and care plan. Only 6 responses had been evaluated, suggesting a significant gap between development and implementation of recommendations. Discussion To address the lack of evidence to support the recommendations extracted in this review, in a future study, a group of experts will formally evaluate each recommendation for its inclusion in a comprehensive hospital-based response. PMID:25938414

A New Distance Metric for Unsupervised Learning of Categorical Data.

PubMed

Jia, Hong; Cheung, Yiu-Ming; Liu, Jiming

2016-05-01

Distance metric is the basis of many learning algorithms, and its effectiveness usually has a significant influence on the learning results. In general, measuring distance for numerical data is a tractable task, but it could be a nontrivial problem for categorical data sets. This paper, therefore, presents a new distance metric for categorical data based on the characteristics of categorical values. In particular, the distance between two values from one attribute measured by this metric is determined by both the frequency probabilities of these two values and the values of other attributes that have high interdependence with the calculated one. Dynamic attribute weight is further designed to adjust the contribution of each attribute-distance to the distance between the whole data objects. Promising experimental results on different real data sets have shown the effectiveness of the proposed distance metric.

Frequent frames as a cue for grammatical categories in child directed speech.

PubMed

Mintz, Toben H

2003-11-01

This paper introduces the notion of frequent frames, distributional patterns based on co-occurrence patterns of words in sentences, then investigates the usefulness of this information in grammatical categorization. A frame is defined as two jointly occurring words with one word intervening. Qualitative and quantitative results from distributional analyses of six different corpora of child directed speech are presented in two experiments. In the analyses, words that were surrounded by the same frequent frame were categorized together. The results show that frequent frames yield very accurate categories. Furthermore, evidence from behavioral studies suggests that infants and adults are sensitive to frame-like units, and that adults use them to categorize words. This evidence, along with the success of frames in categorizing words, provides support for frames as a basis for the acquisition of grammatical categories.

Fabricating biomedical origami: a state-of-the-art review

PubMed Central

Johnson, Meredith; Chen, Yue; Hovet, Sierra; Xu, Sheng; Wood, Bradford; Ren, Hongliang; Tokuda, Junichi; Tse, Zion Tsz Ho

2018-01-01

Purpose Origami-based biomedical device design is an emerging technology due to its ability to be deployed from a minimal foldable pattern to a larger volume. This paper aims to review state-of-the-art origami structures applied in the medical device field. Methods Publications and reports of origami structure related to medical device design from the past 10 years are reviewed and categorized according to engineering specifications, including the application field, fabrication material, size/volume, deployment method, manufacturability, and advantages. Results This paper presents an overview of the biomedical applications of devices based on origami structures, including disposable sterilization covers, cardiac catheterization, stent grafts, encapsulation and microsurgery, gastrointestinal microsurgery, laparoscopic surgical grippers, microgrippers, microfluidic devices, and drug delivery. Challenges in terms of materials and fabrication, assembly, modeling and computation design, and clinical adoptability are discussed at the end of this paper to provide guidance for future origami-based design in the medical device field. Conclusion Concepts from origami can be used to design and develop novel medical devices. Origami-based medical device design is currently progressing, with researchers improving design methods, materials, fabrication techniques, and folding efficiency. PMID:28260164

Foraging in Semantic Fields: How We Search Through Memory.

PubMed

Hills, Thomas T; Todd, Peter M; Jones, Michael N

2015-07-01

When searching for concepts in memory--as in the verbal fluency task of naming all the animals one can think of--people appear to explore internal mental representations in much the same way that animals forage in physical space: searching locally within patches of information before transitioning globally between patches. However, the definition of the patches being searched in mental space is not well specified. Do we search by activating explicit predefined categories (e.g., pets) and recall items from within that category (categorical search), or do we activate and recall a connected sequence of individual items without using categorical information, with each item recalled leading to the retrieval of an associated item in a stream (associative search), or both? Using semantic representations in a search of associative memory framework and data from the animal fluency task, we tested competing hypotheses based on associative and categorical search models. Associative, but not categorical, patch transitions took longer to make than position-matched productions, suggesting that categorical transitions were not true transitions. There was also clear evidence of associative search even within categorical patch boundaries. Furthermore, most individuals' behavior was best explained by an associative search model without the addition of categorical information. Thus, our results support a search process that does not use categorical information, but for which patch boundaries shift with each recall and local search is well described by a random walk in semantic space, with switches to new regions of the semantic space when the current region is depleted. Copyright © 2015 Cognitive Science Society, Inc.

Diagnostic Accuracy Assessment of Sensititre and Agar Disk Diffusion for Determining Antimicrobial Resistance Profiles of Bovine Clinical Mastitis Pathogens▿

PubMed Central

Saini, V.; Riekerink, R. G. M. Olde; McClure, J. T.; Barkema, H. W.

2011-01-01

Determining the accuracy and precision of a measuring instrument is pertinent in antimicrobial susceptibility testing. This study was conducted to predict the diagnostic accuracy of the Sensititre MIC mastitis panel (Sensititre) and agar disk diffusion (ADD) method with reference to the manual broth microdilution test method for antimicrobial resistance profiling of Escherichia coli (n = 156), Staphylococcus aureus (n = 154), streptococcal (n = 116), and enterococcal (n = 31) bovine clinical mastitis isolates. The activities of ampicillin, ceftiofur, cephalothin, erythromycin, oxacillin, penicillin, the penicillin-novobiocin combination, pirlimycin, and tetracycline were tested against the isolates. Diagnostic accuracy was determined by estimating the area under the receiver operating characteristic curve; intertest essential and categorical agreements were determined as well. Sensititre and the ADD method demonstrated moderate to highly accurate (71 to 99%) and moderate to perfect (71 to 100%) predictive accuracies for 74 and 76% of the isolate-antimicrobial MIC combinations, respectively. However, the diagnostic accuracy was low for S. aureus-ceftiofur/oxacillin combinations and other streptococcus-ampicillin combinations by either testing method. Essential agreement between Sensititre automatic MIC readings and MIC readings obtained by the broth microdilution test method was 87%. Essential agreement between Sensititre automatic and manual MIC reading methods was 97%. Furthermore, the ADD test method and Sensititre MIC method exhibited 92 and 91% categorical agreement (sensitive, intermediate, resistant) of results, respectively, compared with the reference method. However, both methods demonstrated lower agreement for E. coli-ampicillin/cephalothin combinations than for Gram-positive isolates. In conclusion, the Sensititre and ADD methods had moderate to high diagnostic accuracy and very good essential and categorical agreement for most udder pathogen-antimicrobial combinations and can be readily employed in veterinary diagnostic laboratories. PMID:21270215

Effects of age on cognitive control during semantic categorization.

PubMed

Mudar, Raksha A; Chiang, Hsueh-Sheng; Maguire, Mandy J; Spence, Jeffrey S; Eroh, Justin; Kraut, Michael A; Hart, John

2015-01-01

We used event-related potentials (ERPs) to study age effects of perceptual (basic-level) vs. perceptual-semantic (superordinate-level) categorization on cognitive control using the go/nogo paradigm. Twenty-two younger (11 M; 21 ± 2.2 years) and 22 older adults (9 M; 63 ± 5.8 years) completed two visual go/nogo tasks. In the single-car task (SiC) (basic), go/nogo responses were made based on single exemplars of a car (go) and a dog (nogo). In the object animal task (ObA) (superordinate), responses were based on multiple exemplars of objects (go) and animals (nogo). Each task consisted of 200 trials: 160 (80%) 'go' trials that required a response through button pressing and 40 (20%) 'nogo' trials that required inhibition/withholding of a response. ERP data revealed significantly reduced nogo-N2 and nogo-P3 amplitudes in older compared to younger adults, whereas go-N2 and go-P3 amplitudes were comparable in both groups during both categorization tasks. Although the effects of categorization levels on behavioral data and P3 measures were similar in both groups with longer response times, lower accuracy scores, longer P3 latencies, and lower P3 amplitudes in ObA compared to SiC, N2 latency revealed age group differences moderated by the task. Older adults had longer N2 latency for ObA compared to SiC, in contrast, younger adults showed no N2 latency difference between SiC and ObA. Overall, these findings suggest that age differentially affects neural processing related to cognitive control during semantic categorization. Furthermore, in older adults, unlike in younger adults, levels of categorization modulate neural processing related to cognitive control even at the early stages (N2). Published by Elsevier B.V.

Overdrive and Edge as Refiners of "Belting"?: An Empirical Study Qualifying and Categorizing "Belting" Based on Audio Perception, Laryngostroboscopic Imaging, Acoustics, LTAS, and EGG.

PubMed

McGlashan, Julian; Thuesen, Mathias Aaen; Sadolin, Cathrine

2017-05-01

We aimed to study the categorizations "Overdrive" and "Edge" from the pedagogical method Complete Vocal Technique as refiners of the often ill-defined concept of "belting" by means of audio perception, laryngostroboscopic imaging, acoustics, long-term average spectrum (LTAS), and electroglottography (EGG). This is a case-control study. Twenty singers were recorded singing sustained vowels in a "belting" quality refined by audio perception as "Overdrive" and "Edge." Two studies were performed: (1) a laryngostroboscopic examination using a videonasoendoscopic camera system (Olympus) and the Laryngostrobe program (Laryngograph); (2) a simultaneous recording of the EGG and acoustic signals using Speech Studio (Laryngograph). The images were analyzed based on consensus agreement. Statistical analysis of the acoustic, LTAS, and EGG parameters was undertaken using the Student paired t test. The two modes of singing determined by audio perception have visibly different laryngeal gestures: Edge has a more constricted setting than that of Overdrive, where the ventricular folds seem to cover more of the vocal folds, the aryepiglottic folds show a sharper edge in Edge, and the cuneiform cartilages are rolled in anteromedially. LTAS analysis shows a statistical difference, particularly after the ninth harmonic, with a coinciding first formant. The combined group showed statistical differences in shimmer, harmonics-to-noise ratio, normalized noise energy, and mean sound pressure level (P ≤ 0.05). "Belting" sounds can be categorized using audio perception into two modes of singing: "Overdrive" and "Edge." This study demonstrates consistent visibly different laryngeal gestures between these modes and with some correspondingly significant differences in LTAS, EGG, and acoustic measures. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Automatic categorization of diverse experimental information in the bioscience literature

PubMed Central

2012-01-01

Background Curation of information from bioscience literature into biological knowledge databases is a crucial way of capturing experimental information in a computable form. During the biocuration process, a critical first step is to identify from all published literature the papers that contain results for a specific data type the curator is interested in annotating. This step normally requires curators to manually examine many papers to ascertain which few contain information of interest and thus, is usually time consuming. We developed an automatic method for identifying papers containing these curation data types among a large pool of published scientific papers based on the machine learning method Support Vector Machine (SVM). This classification system is completely automatic and can be readily applied to diverse experimental data types. It has been in use in production for automatic categorization of 10 different experimental datatypes in the biocuration process at WormBase for the past two years and it is in the process of being adopted in the biocuration process at FlyBase and the Saccharomyces Genome Database (SGD). We anticipate that this method can be readily adopted by various databases in the biocuration community and thereby greatly reducing time spent on an otherwise laborious and demanding task. We also developed a simple, readily automated procedure to utilize training papers of similar data types from different bodies of literature such as C. elegans and D. melanogaster to identify papers with any of these data types for a single database. This approach has great significance because for some data types, especially those of low occurrence, a single corpus often does not have enough training papers to achieve satisfactory performance. Results We successfully tested the method on ten data types from WormBase, fifteen data types from FlyBase and three data types from Mouse Genomics Informatics (MGI). It is being used in the curation work flow at WormBase for automatic association of newly published papers with ten data types including RNAi, antibody, phenotype, gene regulation, mutant allele sequence, gene expression, gene product interaction, overexpression phenotype, gene interaction, and gene structure correction. Conclusions Our methods are applicable to a variety of data types with training set containing several hundreds to a few thousand documents. It is completely automatic and, thus can be readily incorporated to different workflow at different literature-based databases. We believe that the work presented here can contribute greatly to the tremendous task of automating the important yet labor-intensive biocuration effort. PMID:22280404

Automatic categorization of diverse experimental information in the bioscience literature.

PubMed

Fang, Ruihua; Schindelman, Gary; Van Auken, Kimberly; Fernandes, Jolene; Chen, Wen; Wang, Xiaodong; Davis, Paul; Tuli, Mary Ann; Marygold, Steven J; Millburn, Gillian; Matthews, Beverley; Zhang, Haiyan; Brown, Nick; Gelbart, William M; Sternberg, Paul W

2012-01-26

Curation of information from bioscience literature into biological knowledge databases is a crucial way of capturing experimental information in a computable form. During the biocuration process, a critical first step is to identify from all published literature the papers that contain results for a specific data type the curator is interested in annotating. This step normally requires curators to manually examine many papers to ascertain which few contain information of interest and thus, is usually time consuming. We developed an automatic method for identifying papers containing these curation data types among a large pool of published scientific papers based on the machine learning method Support Vector Machine (SVM). This classification system is completely automatic and can be readily applied to diverse experimental data types. It has been in use in production for automatic categorization of 10 different experimental datatypes in the biocuration process at WormBase for the past two years and it is in the process of being adopted in the biocuration process at FlyBase and the Saccharomyces Genome Database (SGD). We anticipate that this method can be readily adopted by various databases in the biocuration community and thereby greatly reducing time spent on an otherwise laborious and demanding task. We also developed a simple, readily automated procedure to utilize training papers of similar data types from different bodies of literature such as C. elegans and D. melanogaster to identify papers with any of these data types for a single database. This approach has great significance because for some data types, especially those of low occurrence, a single corpus often does not have enough training papers to achieve satisfactory performance. We successfully tested the method on ten data types from WormBase, fifteen data types from FlyBase and three data types from Mouse Genomics Informatics (MGI). It is being used in the curation work flow at WormBase for automatic association of newly published papers with ten data types including RNAi, antibody, phenotype, gene regulation, mutant allele sequence, gene expression, gene product interaction, overexpression phenotype, gene interaction, and gene structure correction. Our methods are applicable to a variety of data types with training set containing several hundreds to a few thousand documents. It is completely automatic and, thus can be readily incorporated to different workflow at different literature-based databases. We believe that the work presented here can contribute greatly to the tremendous task of automating the important yet labor-intensive biocuration effort.

Experiments on vibration-driven stick-slip locomotion: A sliding bifurcation perspective

NASA Astrophysics Data System (ADS)

Du, Zhouwei; Fang, Hongbin; Zhan, Xiong; Xu, Jian

2018-05-01

Dry friction appears at the contact interface between two surfaces and is the source of stick-slip vibrations. Instead of being a negative factor, dry friction is essential for vibration-driven locomotion system to take effect. However, the dry-friction-induced stick-slip locomotion has not been fully understood in previous research, especially in terms of experiments. In this paper, we experimentally study the stick-slip dynamics of a vibration-driven locomotion system from a sliding bifurcation perspective. To this end, we first design and build a vibration-driven locomotion prototype based on an internal piezoelectric cantilever. By utilizing the mechanical resonance, the small piezoelectric deformation is significantly amplified to drive the prototype to achieve effective locomotion. Through identifying the stick-slip characteristics in velocity histories, we could categorize the system's locomotion into four types and obtain a stick-slip categorization diagram. In each zone of the diagram the locomotion exhibits qualitatively different stick-slip dynamics. Such categorization diagram is actually a sliding bifurcation diagram; crossing from one stick-slip zone to another corresponds to the triggering of a sliding bifurcation. In addition, a simplified single degree-of-freedom model is established, with the rationality of simplification been explained theoretically and numerically. Based on the equivalent model, a numerical stick-slip categorization is also obtained, which shows good agreement with the experiments both qualitatively and quantitatively. To the best of our knowledge, this is the first work that experimentally generates a sliding bifurcation diagram. The obtained stick-slip categorizations deepen our understanding of stick-slip dynamics in vibration-driven systems and could serve as a base for system design and optimization.

Clustering Heart Rate Dynamics Is Associated with β-Adrenergic Receptor Polymorphisms: Analysis by Information-Based Similarity Index

PubMed Central

Yang, Albert C.; Tsai, Shih-Jen; Hong, Chen-Jee; Wang, Cynthia; Chen, Tai-Jui; Liou, Ying-Jay; Peng, Chung-Kang

2011-01-01

Background Genetic polymorphisms in the gene encoding the β-adrenergic receptors (β-AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype–phenotype analysis to investigate the association between β-AR gene polymorphisms and heart rate dynamics. Methods A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6±10.8 years, range 19 to 63 years) were recruited and genotyped for three common β-AR polymorphisms: β1-AR Ser49Gly, β2-AR Arg16Gly and β2-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects. Results With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β2-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity. Conclusions We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms. Our results provide evidence that β2-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control. PMID:21573230

Comparative evaluation of topographical data of dental implant surfaces applying optical interferometry and scanning electron microscopy.

PubMed

Kournetas, N; Spintzyk, S; Schweizer, E; Sawada, T; Said, F; Schmid, P; Geis-Gerstorfer, J; Eliades, G; Rupp, F

2017-08-01

Comparability of topographical data of implant surfaces in literature is low and their clinical relevance often equivocal. The aim of this study was to investigate the ability of scanning electron microscopy and optical interferometry to assess statistically similar 3-dimensional roughness parameter results and to evaluate these data based on predefined criteria regarded relevant for a favorable biological response. Four different commercial dental screw-type implants (NanoTite Certain Prevail, TiUnite Brånemark Mk III, XiVE S Plus and SLA Standard Plus) were analyzed by stereo scanning electron microscopy and white light interferometry. Surface height, spatial and hybrid roughness parameters (Sa, Sz, Ssk, Sku, Sal, Str, Sdr) were assessed from raw and filtered data (Gaussian 50μm and 5μm cut-off-filters), respectively. Data were statistically compared by one-way ANOVA and Tukey-Kramer post-hoc test. For a clinically relevant interpretation, a categorizing evaluation approach was used based on predefined threshold criteria for each roughness parameter. The two methods exhibited predominantly statistical differences. Dependent on roughness parameters and filter settings, both methods showed variations in rankings of the implant surfaces and differed in their ability to discriminate the different topographies. Overall, the analyses revealed scale-dependent roughness data. Compared to the pure statistical approach, the categorizing evaluation resulted in much more similarities between the two methods. This study suggests to reconsider current approaches for the topographical evaluation of implant surfaces and to further seek after proper experimental settings. Furthermore, the specific role of different roughness parameters for the bioresponse has to be studied in detail in order to better define clinically relevant, scale-dependent and parameter-specific thresholds and ranges. Copyright © 2017 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

White matter hyperintensities and headache: A population-based imaging study (HUNT MRI).

PubMed

Honningsvåg, Lasse-Marius; Håberg, Asta Kristine; Hagen, Knut; Kvistad, Kjell Arne; Stovner, Lars Jacob; Linde, Mattias

2018-01-01

Objective To examine the relationship between white matter hyperintensities and headache. Methods White matter hyperintensities burden was assessed semi-quantitatively using Fazekas and Scheltens scales, and by manual and automated volumetry of MRI in a sub-study of the general population-based Nord-Trøndelag Health Study (HUNT MRI). Using validated questionnaires, participants were categorized into four cross-sectional headache groups: Headache-free (n = 551), tension-type headache (n = 94), migraine (n = 91), and unclassified headache (n = 126). Prospective questionnaire data was used to further categorize participants into groups according to the evolution of headache during the last 12 years: Stable headache-free, past headache, new onset headache, and persistent headache. White matter hyperintensities burden was compared across headache groups using adjusted multivariate regression models. Results Individuals with tension-type headache were more likely to have extensive white matter hyperintensities than headache-free subjects, with this being the case across all methods of white matter hyperintensities assessment (Scheltens scale: Odds ratio, 2.46; 95% CI, 1.44-4.20). Migraine or unclassified headache did not influence the odds of having extensive white matter hyperintensities. Those with new onset headache were more likely to have extensive white matter hyperintensities than those who were stable headache-free (Scheltens scale: Odds ratio, 2.24; 95% CI, 1.13-4.44). Conclusions Having tension-type headache or developing headache in middle age was linked to extensive white matter hyperintensities. These results were similar across all methods of assessing white matter hyperintensities. If white matter hyperintensities treatment strategies emerge in the future, this association should be taken into consideration.

Diagnosing and ranking retinopathy disease level using diabetic fundus image recuperation approach.

PubMed

Somasundaram, K; Rajendran, P Alli

2015-01-01

Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.

Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach

PubMed Central

Somasundaram, K.; Alli Rajendran, P.

2015-01-01

Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time. PMID:25945362

Examining Solutions to Missing Data in Longitudinal Nursing Research

PubMed Central

Roberts, Mary B.; Sullivan, Mary C.; Winchester, Suzy B.

2017-01-01

Purpose Longitudinal studies are highly valuable in pediatrics because they provide useful data about developmental patterns of child health and behavior over time. When data are missing, the value of the research is impacted. The study’s purpose was to: (1) introduce a 3-step approach to assess and address missing data; (2) illustrate this approach using categorical and continuous level variables from a longitudinal study of premature infants. Methods A three-step approach with simulations was followed to assess the amount and pattern of missing data and to determine the most appropriate imputation method for the missing data. Patterns of missingness were Missing Completely at Random, Missing at Random, and Not Missing at Random. Missing continuous-level data were imputed using mean replacement, stochastic regression, multiple imputation, and fully conditional specification. Missing categorical-level data were imputed using last value carried forward, hot-decking, stochastic regression, and fully conditional specification. Simulations were used to evaluate these imputation methods under different patterns of missingness at different levels of missing data. Results The rate of missingness was 16–23% for continuous variables and 1–28% for categorical variables. Fully conditional specification imputation provided the least difference in mean and standard deviation estimates for continuous measures. Fully conditional specification imputation was acceptable for categorical measures. Results obtained through simulation reinforced and confirmed these findings. Practice Implications Significant investments are made in the collection of longitudinal data. The prudent handling of missing data can protect these investments and potentially improve the scientific information contained in pediatric longitudinal studies. PMID:28425202

Computational Methods for Analyzing Health News Coverage

ERIC Educational Resources Information Center

McFarlane, Delano J.

2011-01-01

Researchers that investigate the media's coverage of health have historically relied on keyword searches to retrieve relevant health news coverage, and manual content analysis methods to categorize and score health news text. These methods are problematic. Manual content analysis methods are labor intensive, time consuming, and inherently…

Similarity, Induction, Naming, and Categorization (SINC): Generalization or Inductive Reasoning? Reply to Heit and Hayes (2005)

ERIC Educational Resources Information Center

Sloutsky, Vladimir M.; Fisher, Anna V.

2006-01-01

This article is a response to E. Heit and B. K. Hayes's comment on the target article "Induction and Categorization in Young Children: A Similarity-Based Model" (V. M. Sloutsky & A. V. Fisher, 2004a). The response discusses points of agreement and disagreement with Heit and Hayes; phenomena predicted by similarity, induction, naming, and…

Investigating Preschoolers' Categorical Thinking about Gender through Imitation, Attention, and the Use of Self-Categories

ERIC Educational Resources Information Center

Grace, Diana M.; David, Barbara J.; Ryan, Michelle K.

2008-01-01

Whereas traditional theories of gender development have focused on individualistic paths, recent analyses have argued for a more social categorical approach to children's understanding of gender. Using a modeling paradigm based on K. Bussey and A. Bandura (1984), 3 experiments (N = 62, N = 32, and N = 64) examined preschoolers' (M age = 52.9…

An Investigation into the Community of Inquiry Model in the Malaysian ESL Learners' Context

ERIC Educational Resources Information Center

Annamalai, Nagaletchimee

2017-01-01

Purpose: This study aims to explore how the Community of Inquiry (CoI) model (2000) is used to categorize students' and teachers' interactions in an asynchronous discussion and how these interactions are able to help students add quality to their narrative writing. Design/methodology/approach: The interactions were categorized based on teaching,…

Examining Potential Predictors for Completion of the Gardasil Vaccine Sequence Based on Data Gathered at Clinics of Johns Hopkins Medical Institutions

ERIC Educational Resources Information Center

Barat, Christopher E.; Wright, Courtney; Chou, Betty

2011-01-01

This paper presents categorical data that were gathered at two urban clinics and two suburban clinics of Johns Hopkins in an effort to identify characteristics of young female patients who successfully complete the three-injection sequence of the Gardasil quadrivalent human papillomavirus vaccine (HPV4). Available categorical correlates included…

Utility-based designs for randomized comparative trials with categorical outcomes

PubMed Central

Murray, Thomas A.; Thall, Peter F.; Yuan, Ying

2016-01-01

A general utility-based testing methodology for design and conduct of randomized comparative clinical trials with categorical outcomes is presented. Numerical utilities of all elementary events are elicited to quantify their desirabilities. These numerical values are used to map the categorical outcome probability vector of each treatment to a mean utility, which is used as a one-dimensional criterion for constructing comparative tests. Bayesian tests are presented, including fixed sample and group sequential procedures, assuming Dirichlet-multinomial models for the priors and likelihoods. Guidelines are provided for establishing priors, eliciting utilities, and specifying hypotheses. Efficient posterior computation is discussed, and algorithms are provided for jointly calibrating test cutoffs and sample size to control overall type I error and achieve specified power. Asymptotic approximations for the power curve are used to initialize the algorithms. The methodology is applied to re-design a completed trial that compared two chemotherapy regimens for chronic lymphocytic leukemia, in which an ordinal efficacy outcome was dichotomized and toxicity was ignored to construct the trial’s design. The Bayesian tests also are illustrated by several types of categorical outcomes arising in common clinical settings. Freely available computer software for implementation is provided. PMID:27189672

Contour matching for a fish recognition and migration-monitoring system

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Schoenberger, Robert B.; Shiozawa, Dennis; Xu, Xiaoqian; Zhan, Pengcheng

2004-12-01

Fish migration is being monitored year round to provide valuable information for the study of behavioral responses of fish to environmental variations. However, currently all monitoring is done by human observers. An automatic fish recognition and migration monitoring system is more efficient and can provide more accurate data. Such a system includes automatic fish image acquisition, contour extraction, fish categorization, and data storage. Shape is a very important characteristic and shape analysis and shape matching are studied for fish recognition. Previous work focused on finding critical landmark points on fish shape using curvature function analysis. Fish recognition based on landmark points has shown satisfying results. However, the main difficulty of this approach is that landmark points sometimes cannot be located very accurately. Whole shape matching is used for fish recognition in this paper. Several shape descriptors, such as Fourier descriptors, polygon approximation and line segments, are tested. A power cepstrum technique has been developed in order to improve the categorization speed using contours represented in tangent space with normalized length. Design and integration including image acquisition, contour extraction and fish categorization are discussed in this paper. Fish categorization results based on shape analysis and shape matching are also included.

Pragmatic precision oncology: the secondary uses of clinical tumor molecular profiling

PubMed Central

Thota, Ramya; Staggs, David B; Johnson, Douglas B; Warner, Jeremy L

2016-01-01

Background Precision oncology increasingly utilizes molecular profiling of tumors to determine treatment decisions with targeted therapeutics. The molecular profiling data is valuable in the treatment of individual patients as well as for multiple secondary uses. Objective To automatically parse, categorize, and aggregate clinical molecular profile data generated during cancer care as well as use this data to address multiple secondary use cases. Methods A system to parse, categorize and aggregate molecular profile data was created. A naÿve Bayesian classifier categorized results according to clinical groups. The accuracy of these systems were validated against a published expertly-curated subset of molecular profiling data. Results Following one year of operation, 819 samples have been accurately parsed and categorized to generate a data repository of 10,620 genetic variants. The database has been used for operational, clinical trial, and discovery science research. Conclusions A real-time database of molecular profiling data is a pragmatic solution to several knowledge management problems in the practice and science of precision oncology. PMID:27026612

Emotions in ‘black or white’ or shades of gray? How we think about emotion shapes our perception and neural representation of emotion

PubMed Central

Satpute, Ajay B.; Nook, Erik C.; Narayanan, Sandhya; Shu, Jocelyn; Weber, Jochen; Ochsner, Kevin N.

2016-01-01

The demands of social life often require categorically judging whether someone's continuously varying facial movements express “calm” or “fear”, or whether our fluctuating internal states mean we feel “good” or “bad”. In two neuroimaging studies, we ask whether this kind of categorical, ‘black and white’, thinking can shape the perception and neural representation of emotion. Using psychometric and neuroimaging methods, we found that (1) across participants, judging emotions using a ‘black and white’ scale vs. a ‘shades of gray’ scale shifted subjective emotion perception thresholds, (2) these shifts corresponded with activity in regions associated with affective responding including the amygdala and ventral anterior insula, and (3) connectivity of these regions with the medial prefrontal cortex correlated with the magnitude of categorization-related shifts. These findings suggest that categorical thinking about emotion may actively shape the perception and neural representation of the emotions in question. PMID:27670663

Nanomaterial categorization for assessing risk potential to facilitate regulatory decision-making.

PubMed

Godwin, Hilary; Nameth, Catherine; Avery, David; Bergeson, Lynn L; Bernard, Daniel; Beryt, Elizabeth; Boyes, William; Brown, Scott; Clippinger, Amy J; Cohen, Yoram; Doa, Maria; Hendren, Christine Ogilvie; Holden, Patricia; Houck, Keith; Kane, Agnes B; Klaessig, Frederick; Kodas, Toivo; Landsiedel, Robert; Lynch, Iseult; Malloy, Timothy; Miller, Mary Beth; Muller, Julie; Oberdorster, Gunter; Petersen, Elijah J; Pleus, Richard C; Sayre, Philip; Stone, Vicki; Sullivan, Kristie M; Tentschert, Jutta; Wallis, Philip; Nel, Andre E

2015-01-01

For nanotechnology to meet its potential as a game-changing and sustainable technology, it is important to ensure that the engineered nanomaterials and nanoenabled products that gain entry to the marketplace are safe and effective. Tools and methods are needed for regulatory purposes to allow rapid material categorization according to human health and environmental risk potential, so that materials of high concern can be targeted for additional scrutiny, while material categories that pose the least risk can receive expedited review. Using carbon nanotubes as an example, we discuss how data from alternative testing strategies can be used to facilitate engineered nanomaterial categorization according to risk potential and how such an approach could facilitate regulatory decision-making in the future.

DISSECT: a new mnemonic-based approach to the categorization of aortic dissection.

PubMed

Dake, M D; Thompson, M; van Sambeek, M; Vermassen, F; Morales, J P

2013-08-01

Classification systems for aortic dissection provide important guides to clinical decision-making, but the relevance of traditional categorization schemes is being questioned in an era when endovascular techniques are assuming a growing role in the management of this frequently complex and catastrophic entity. In recognition of the expanding range of interventional therapies now used as alternatives to conventional treatment approaches, the Working Group on Aortic Diseases of the DEFINE Project developed a categorization system that features the specific anatomic and clinical manifestations of the disease process that are most relevant to contemporary decision-making. The DISSECT classification system is a mnemonic-based approach to the evaluation of aortic dissection. It guides clinicians through an assessment of six critical characteristics that facilitate optimal communication of the most salient details that currently influence the selection of a therapeutic option, including those findings that are key when considering an endovascular procedure, but are not taken into account by the DeBakey or Stanford categorization schemes. The six features of aortic dissection include: duration of disease; intimal tear location; size of the dissected aorta; segmental extent of aortic involvement; clinical complications of the dissection, and thrombus within the aortic false lumen. In current clinical practice, endovascular therapy is increasingly considered as an alternative to medical management or open surgical repair in select cases of type B aortic dissection. Currently, endovascular aortic repair is not used for patients with type A aortic dissection, but catheter-based techniques directed at peripheral branch vessel ischemia that may complicate type A dissection are considered valuable adjunctive interventions, when indicated. The use of a new system for categorization of aortic dissection, DISSECT, addresses the shortcomings of well-known established schemes devised more than 40 years ago, before the introduction of endovascular techniques. It will serve as a guide to support a critical analysis of contemporary therapeutic options and inform management decisions based on specific features of the disease process. Copyright © 2013 European Society for Vascular Surgery. All rights reserved.

Categorical speech processing in Broca's area: an fMRI study using multivariate pattern-based analysis.

PubMed

Lee, Yune-Sang; Turkeltaub, Peter; Granger, Richard; Raizada, Rajeev D S

2012-03-14

Although much effort has been directed toward understanding the neural basis of speech processing, the neural processes involved in the categorical perception of speech have been relatively less studied, and many questions remain open. In this functional magnetic resonance imaging (fMRI) study, we probed the cortical regions mediating categorical speech perception using an advanced brain-mapping technique, whole-brain multivariate pattern-based analysis (MVPA). Normal healthy human subjects (native English speakers) were scanned while they listened to 10 consonant-vowel syllables along the /ba/-/da/ continuum. Outside of the scanner, individuals' own category boundaries were measured to divide the fMRI data into /ba/ and /da/ conditions per subject. The whole-brain MVPA revealed that Broca's area and the left pre-supplementary motor area evoked distinct neural activity patterns between the two perceptual categories (/ba/ vs /da/). Broca's area was also found when the same analysis was applied to another dataset (Raizada and Poldrack, 2007), which previously yielded the supramarginal gyrus using a univariate adaptation-fMRI paradigm. The consistent MVPA findings from two independent datasets strongly indicate that Broca's area participates in categorical speech perception, with a possible role of translating speech signals into articulatory codes. The difference in results between univariate and multivariate pattern-based analyses of the same data suggest that processes in different cortical areas along the dorsal speech perception stream are distributed on different spatial scales.

Interpretable Categorization of Heterogeneous Time Series Data

NASA Technical Reports Server (NTRS)

Lee, Ritchie; Kochenderfer, Mykel J.; Mengshoel, Ole J.; Silbermann, Joshua

2017-01-01

We analyze data from simulated aircraft encounters to validate and inform the development of a prototype aircraft collision avoidance system. The high-dimensional and heterogeneous time series dataset is analyzed to discover properties of near mid-air collisions (NMACs) and categorize the NMAC encounters. Domain experts use these properties to better organize and understand NMAC occurrences. Existing solutions either are not capable of handling high-dimensional and heterogeneous time series datasets or do not provide explanations that are interpretable by a domain expert. The latter is critical to the acceptance and deployment of safety-critical systems. To address this gap, we propose grammar-based decision trees along with a learning algorithm. Our approach extends decision trees with a grammar framework for classifying heterogeneous time series data. A context-free grammar is used to derive decision expressions that are interpretable, application-specific, and support heterogeneous data types. In addition to classification, we show how grammar-based decision trees can also be used for categorization, which is a combination of clustering and generating interpretable explanations for each cluster. We apply grammar-based decision trees to a simulated aircraft encounter dataset and evaluate the performance of four variants of our learning algorithm. The best algorithm is used to analyze and categorize near mid-air collisions in the aircraft encounter dataset. We describe each discovered category in detail and discuss its relevance to aircraft collision avoidance.

Quantifying the impact of using Coronary Artery Calcium Score for risk categorization instead of Framingham Score or European Heart SCORE in lipid lowering algorithms in a Middle Eastern population

PubMed Central

Isma’eel, Hussain A.; Almedawar, Mohamad M.; Harbieh, Bernard; Alajaji, Wissam; Al-Shaar, Laila; Hourani, Mukbil; El-Merhi, Fadi; Alam, Samir; Abchee, Antoine

2015-01-01

Background The use of the Coronary Artery Calcium Score (CACS) for risk categorization instead of the Framingham Risk Score (FRS) or European Heart SCORE (EHS) to improve classification of individuals is well documented. However, the impact of reclassifying individuals using CACS on initiating lipid lowering therapy is not well understood. We aimed to determine the percentage of individuals not requiring lipid lowering therapy as per the FRS and EHS models but are found to require it using CACS and vice versa; and to determine the level of agreement between CACS, FRS and EHS based models. Methods Data was collected for 500 consecutive patients who had already undergone CACS. However, only 242 patients met the inclusion criteria and were included in the analysis. Risk stratification comparisons were conducted according to CACS, FRS, and EHS, and the agreement (Kappa) between them was calculated. Results In accordance with the models, 79.7% to 81.5% of high-risk individuals were down-classified by CACS, while 6.8% to 7.6% of individuals at intermediate risk were up-classified to high risk by CACS, with slight to moderate agreement. Moreover, CACS recommended treatment to 5.7% and 5.8% of subjects untreated according to European and Canadian guidelines, respectively; whereas 75.2% to 81.2% of those treated in line with the guidelines would not be treated based on CACS. Conclusion In this simulation, using CACS for risk categorization warrants lipid lowering treatment for 5–6% and spares 70–80% from treatment in accordance with the guidelines. Current strong evidence from double randomized clinical trials is in support of guideline recommendations. Our results call for a prospective trial to explore the benefits/risks of a CACS-based approach before any recommendations can be made. PMID:26557741

Direct versus indirect processing changes the influence of color in natural scene categorization.

PubMed

Otsuka, Sachio; Kawaguchi, Jun

2009-10-01

We examined whether participants would use a negative priming (NP) paradigm to categorize color and grayscale images of natural scenes that were presented peripherally and were ignored. We focused on (1) attentional resources allocated to natural scenes and (2) direct versus indirect processing of them. We set up low and high attention-load conditions, based on the set size of the searched stimuli in the prime display (one and five). Participants were required to detect and categorize the target objects in natural scenes in a central visual search task, ignoring peripheral natural images in both the prime and probe displays. The results showed that, irrespective of attention load, NP was observed for color scenes but not for grayscale scenes. We did not observe any effect of color information in central visual search, where participants responded directly to natural scenes. These results indicate that, in a situation in which participants indirectly process natural scenes, color information is critical to object categorization, but when the scenes are processed directly, color information does not contribute to categorization.

Robust categorization of microfacet BRDF models to enable flexible application-specific BRDF adaptation

NASA Astrophysics Data System (ADS)

Butler, Samuel D.; Marciniak, Michael A.

2014-09-01

Since the development of the Torrance-Sparrow bidirectional re ectance distribution function (BRDF) model in 1967, several BRDF models have been created. Previous attempts to categorize BRDF models have relied upon somewhat vague descriptors, such as empirical, semi-empirical, and experimental. Our approach is to instead categorize BRDF models based on functional form: microfacet normal distribution, geometric attenua- tion, directional-volumetric and Fresnel terms, and cross section conversion factor. Several popular microfacet models are compared to a standardized notation for a microfacet BRDF model. A library of microfacet model components is developed, allowing for creation of unique microfacet models driven by experimentally measured BRDFs.

Variability of wetland reflectance and its effect on automatic categorization of satellite imagery

NASA Technical Reports Server (NTRS)

Klemas, V. (Principal Investigator); Bartlett, D.

1977-01-01

The author has identified the following significant results. Land cover categorization of data from the same overpass in four test wetland areas was carried out using a four category classification system. The tests indicate that training data based on in situ reflectance measurements and atmospheric correction of LANDSAT data can produce comparable accuracy of categorization to that achieved using more than four wetlands cover categories (salt marsh cordgrass, salt hay, unvegetated, and water tidal flat) produced overall classification accuracies of 85% by conventional and relative radiance training and 81% by use of in situ measurements. Overall mapping accuracies were 76% and 72% respectively.

Basic-level categorization of intermediate complexity fragments reveals top-down effects of expertise in visual perception.

PubMed

Harel, Assaf; Ullman, Shimon; Harari, Danny; Bentin, Shlomo

2011-07-28

Visual expertise is usually defined as the superior ability to distinguish between exemplars of a homogeneous category. Here, we ask how real-world expertise manifests at basic-level categorization and assess the contribution of stimulus-driven and top-down knowledge-based factors to this manifestation. Car experts and novices categorized computer-selected image fragments of cars, airplanes, and faces. Within each category, the fragments varied in their mutual information (MI), an objective quantifiable measure of feature diagnosticity. Categorization of face and airplane fragments was similar within and between groups, showing better performance with increasing MI levels. Novices categorized car fragments more slowly than face and airplane fragments, while experts categorized car fragments as fast as face and airplane fragments. The experts' advantage with car fragments was similar across MI levels, with similar functions relating RT with MI level for both groups. Accuracy was equal between groups for cars as well as faces and airplanes, but experts' response criteria were biased toward cars. These findings suggest that expertise does not entail only specific perceptual strategies. Rather, at the basic level, expertise manifests as a general processing advantage arguably involving application of top-down mechanisms, such as knowledge and attention, which helps experts to distinguish between object categories. © ARVO

Comparison of alphabetical versus categorical display format for medication order entry in a simulated touch screen anesthesia information management system: an experiment in clinician-computer interaction in anesthesia

PubMed Central

2012-01-01

Background Anesthesia information management system (AIMS) records should be designed and configured to facilitate the accurate and prompt recording of multiple drugs administered coincidentally or in rapid succession. Methods We proposed two touch-screen display formats for use with our department’s new EPIC touch-screen AIMS. In one format, medication “buttons” were arranged in alphabetical order (i.e. A-C, D-H etc.). In the other, buttons were arranged in categories (Common, Fluids, Cardiovascular, Coagulation etc.). Both formats were modeled on an iPad screen to resemble the AIMS interface. Anesthesia residents, anesthesiologists, and Certified Registered Nurse Anesthetists (n = 60) were then asked to find and touch the correct buttons for a series of medications whose names were displayed to the side of the entry screen. The number of entries made within 2 minutes was recorded. This was done 3 times for each format, with the 1st format chosen randomly. Data were analyzed from the third trials with each format to minimize differences in learning. Results The categorical format had a mean of 5.6 more drugs entered using the categorical method in two minutes than the alphabetical format (95% confidence interval [CI] 4.5 to 6.8, P < 0.0001). The findings were the same regardless of the order of testing (i.e. alphabetical-categorical vs. categorical - alphabetical) and participants’ years of clinical experience. Most anesthesia providers made no (0) errors for most trials (N = 96/120 trials, lower 95% limit 73%, P < 0.0001). There was no difference in error rates between the two formats (P = 0.53). Conclusions The use of touch-screen user interfaces in healthcare is increasingly common. Arrangement of drugs names in a categorical display format in the medication order-entry touch screen of an AIMS can result in faster data entry compared to an alphabetical arrangement of drugs. Results of this quality improvement project were used in our department’s design of our final intraoperative electronic anesthesia record. This testing approach using cognitive and usability engineering methods can be used to objectively design and evaluate many aspects of the clinician-computer interaction in electronic health records. PMID:22643058

Angry facial expressions bias gender categorization in children and adults: behavioral and computational evidence

PubMed Central

Bayet, Laurie; Pascalis, Olivier; Quinn, Paul C.; Lee, Kang; Gentaz, Édouard; Tanaka, James W.

2015-01-01

Angry faces are perceived as more masculine by adults. However, the developmental course and underlying mechanism (bottom-up stimulus driven or top-down belief driven) associated with the angry-male bias remain unclear. Here we report that anger biases face gender categorization toward “male” responding in children as young as 5–6 years. The bias is observed for both own- and other-race faces, and is remarkably unchanged across development (into adulthood) as revealed by signal detection analyses (Experiments 1–2). The developmental course of the angry-male bias, along with its extension to other-race faces, combine to suggest that it is not rooted in extensive experience, e.g., observing males engaging in aggressive acts during the school years. Based on several computational simulations of gender categorization (Experiment 3), we further conclude that (1) the angry-male bias results, at least partially, from a strategy of attending to facial features or their second-order relations when categorizing face gender, and (2) any single choice of computational representation (e.g., Principal Component Analysis) is insufficient to assess resemblances between face categories, as different representations of the very same faces suggest different bases for the angry-male bias. Our findings are thus consistent with stimulus-and stereotyped-belief driven accounts of the angry-male bias. Taken together, the evidence suggests considerable stability in the interaction between some facial dimensions in social categorization that is present prior to the onset of formal schooling. PMID:25859238

The degree of social difficulties experienced by cancer patients and their spouses.

PubMed

Takeuchi, Takashi; Ichikura, Kanako; Amano, Kanako; Takeshita, Wakana; Hisamura, Kazuho

2018-06-08

Although recent studies have increasingly reported physical and psychological problems associated with cancer and its treatment, social problems of cancer patients and their families have not been sufficiently elucidated. The present study aimed to identify cancer-associated social problems from the perspectives of both patients and their spouses and to compare and analyze differences in their problems. This was a cross-sectional internet-based study. Subjects were 259 patients who developed cancer within the previous five years and 259 patients' spouses; the data were derived from two surveys in 2010 (patients) and 2016 (spouses) whose participants were not part of the same dyad but matched by propensity scores, estimated for age, sex, and the presence or absence of recurrence. We investigated the social difficulties of cancer patients and patients' spouses. Regarding social difficulties experienced by cancer patients and spouses, the 60 patient survey items were categorized into 14 labels by the Jiro Kawakita (KJ) method, which is a qualitative synthesis method developed by Kawakita to classify categorical data. Although patients had higher scores on most subcategories, young spouses aged 39 or younger and female spouses had difficulty scores as high as the corresponding patients on many subcategories. Health care providers should show sufficient concern for both patients and their spouses, particularly young and female spouses.

Categorization of common sounds by cochlear implanted and normal hearing adults.

PubMed

Collett, E; Marx, M; Gaillard, P; Roby, B; Fraysse, B; Deguine, O; Barone, P

2016-05-01

Auditory categorization involves grouping of acoustic events along one or more shared perceptual dimensions which can relate to both semantic and physical attributes. This process involves both high level cognitive processes (categorization) and low-level perceptual encoding of the acoustic signal, both of which are affected by the use of a cochlear implant (CI) device. The goal of this study was twofold: I) compare the categorization strategies of CI users and normal hearing listeners (NHL) II) investigate if any characteristics of the raw acoustic signal could explain the results. 16 experienced CI users and 20 NHL were tested using a Free-Sorting Task of 16 common sounds divided into 3 predefined categories of environmental, musical and vocal sounds. Multiple Correspondence Analysis (MCA) and Hierarchical Clustering based on Principal Components (HCPC) show that CI users followed a similar categorization strategy to that of NHL and were able to discriminate between the three different types of sounds. However results for CI users were more varied and showed less inter-participant agreement. Acoustic analysis also highlighted the average pitch salience and average autocorrelation peak as being important for the perception and categorization of the sounds. The results therefore show that on a broad level of categorization CI users may not have as many difficulties as previously thought in discriminating certain kinds of sound; however the perception of individual sounds remains challenging. Copyright © 2016 Elsevier B.V. All rights reserved.

Nanomaterials for Defense Applications

NASA Astrophysics Data System (ADS)

Turaga, Uday; Singh, Vinitkumar; Lalagiri, Muralidhar; Kiekens, Paul; Ramkumar, Seshadri S.

Nanotechnology has found a number of applications in electronics and healthcare. Within the textile field, applications of nanotechnology have been limited to filters, protective liners for chemical and biological clothing and nanocoatings. This chapter presents an overview of the applications of nanomaterials such as nanofibers and nanoparticles that are of use to military and industrial sectors. An effort has been made to categorize nanofibers based on the method of production. This chapter particularly focuses on a few latest developments that have taken place with regard to the application of nanomaterials such as metal oxides in the defense arena.

Machine learning and computer vision approaches for phenotypic profiling.

PubMed

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

Machine learning and computer vision approaches for phenotypic profiling

PubMed Central

Morris, Quaid

2017-01-01

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. PMID:27940887

Satellite recovery - Attitude dynamics of the targets

NASA Technical Reports Server (NTRS)

Cochran, J. E., Jr.; Lahr, B. S.

1986-01-01

The problems of categorizing and modeling the attitude dynamics of uncontrolled artificial earth satellites which may be targets in recovery attempts are addressed. Methods of classification presented are based on satellite rotational kinetic energy, rotational angular momentum and orbit and on the type of control present prior to the benign failure of the control system. The use of approximate analytical solutions and 'exact' numerical solutions to the equations governing satellite attitude motions to predict uncontrolled attitude motion is considered. Analytical and numerical results are presented for the evolution of satellite attitude motions after active control termination.

Perception of the pitch of unresolved harmonics by 3- and 7-month-old human infants.

PubMed

Lau, Bonnie K; Werner, Lynne A

2014-08-01

Three-month-olds discriminate resolved harmonic complexes on the basis of missing fundamental (MF) pitch. In view of reported difficulty in discriminating unresolved complexes at 7 months and striking changes in the organization of the auditory system during early infancy, infants' ability to discriminate unresolved complexes is of some interest. This study investigated the ability of 3-month-olds, 7-month-olds, and adults to discriminate the pitch of unresolved harmonic complexes using an observer-based method. Stimuli were MF complexes bandpass filtered with a -12 dB/octave slope, combined in random phase, presented at 70 dB sound pressure level (SPL) for 650 ms with a 50 ms rise/fall with a pink noise at 65 dB SPL. The conditions were (1) "LOW" unresolved harmonics (2500-4500 Hz) based on MFs of 160 and 200 Hz and (2) "HIGH" unresolved harmonics (4000-6000 Hz) based on MFs of 190 and 200 Hz. To demonstrate MF discrimination, participants had to ignore spectral changes in complexes with the same fundamental and respond only when the fundamental changed. Nearly all infants tested categorized complexes by MF pitch suggesting discrimination of pitch extracted from unresolved harmonics by 3 months. Adults also categorized the complexes by MF pitch, although musically trained adults were more successful than musically untrained adults.

Quality assurance using outlier detection on an automatic segmentation method for the cerebellar peduncles

NASA Astrophysics Data System (ADS)

Li, Ke; Ye, Chuyang; Yang, Zhen; Carass, Aaron; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis. In this work, two outlier detection methods aimed to assess the performance of an automatic CP segmentation algorithm are presented. The first one is a univariate non-parametric method using a box-whisker plot. We first categorize automatic segmentation results of a dataset of diffusion tensor imaging (DTI) scans from 48 subjects as either a success or a failure. We then design three groups of features from the image data of nine categorized failures for failure detection. Results show that most of these features can efficiently detect the true failures. The second method—supervised classification—was employed on a larger DTI dataset of 249 manually categorized subjects. Four classifiers—linear discriminant analysis (LDA), logistic regression (LR), support vector machine (SVM), and random forest classification (RFC)—were trained using the designed features and evaluated using a leave-one-out cross validation. Results show that the LR performs worst among the four classifiers and the other three perform comparably, which demonstrates the feasibility of automatically detecting segmentation failures using classification methods.

Electrophysiological evidence for early perceptual facilitation and efficient categorization of self-related stimuli during an Implicit Association Test measuring neuroticism.

PubMed

Fleischhauer, Monika; Strobel, Alexander; Diers, Kersten; Enge, Sören

2014-02-01

The Implicit Association Test (IAT) is a widely used latency-based categorization task that indirectly measures the strength of automatic associations between target and attribute concepts. So far, little is known about the perceptual and cognitive processes underlying personality IATs. Thus, the present study examined event-related potential indices during the execution of an IAT measuring neuroticism (N  =  70). The IAT effect was strongly modulated by the P1 component indicating early facilitation of relevant visual input and by a P3b-like late positive component reflecting the efficacy of stimulus categorization. Both components covaried, and larger amplitudes led to faster responses. The results suggest a relationship between early perceptual and semantic processes operating at a more automatic, implicit level and later decision-related categorization of self-relevant stimuli contributing to the IAT effect. Copyright © 2013 Society for Psychophysiological Research.

Overcoming default categorical bias in spatial memory.

PubMed

Sampaio, Cristina; Wang, Ranxiao Frances

2010-12-01

In the present study, we investigated whether a strong default categorical bias can be overcome in spatial memory by using alternative membership information. In three experiments, we tested location memory in a circular space while providing participants with an alternative categorization. We found that visual presentation of the boundaries of the alternative categories (Experiment 1) did not induce the use of the alternative categories in estimation. In contrast, visual cuing of the alternative category membership of a target (Experiment 2) and unique target feature information associated with each alternative category (Experiment 3) successfully led to the use of the alternative categories in estimation. Taken together, the results indicate that default categorical bias in spatial memory can be overcome when appropriate cues are provided. We discuss how these findings expand the category adjustment model (Huttenlocher, Hedges, & Duncan, 1991) in spatial memory by proposing a retrieval-based category adjustment (RCA) model.

The Characteristics and Limits of Rapid Visual Categorization

PubMed Central

Fabre-Thorpe, Michèle

2011-01-01

Visual categorization appears both effortless and virtually instantaneous. The study by Thorpe et al. (1996) was the first to estimate the processing time necessary to perform fast visual categorization of animals in briefly flashed (20 ms) natural photographs. They observed a large differential EEG activity between target and distracter correct trials that developed from 150 ms after stimulus onset, a value that was later shown to be even shorter in monkeys! With such strong processing time constraints, it was difficult to escape the conclusion that rapid visual categorization was relying on massively parallel, essentially feed-forward processing of visual information. Since 1996, we have conducted a large number of studies to determine the characteristics and limits of fast visual categorization. The present chapter will review some of the main results obtained. I will argue that rapid object categorizations in natural scenes can be done without focused attention and are most likely based on coarse and unconscious visual representations activated with the first available (magnocellular) visual information. Fast visual processing proved efficient for the categorization of large superordinate object or scene categories, but shows its limits when more detailed basic representations are required. The representations for basic objects (dogs, cars) or scenes (mountain or sea landscapes) need additional processing time to be activated. This finding is at odds with the widely accepted idea that such basic representations are at the entry level of the system. Interestingly, focused attention is still not required to perform these time consuming basic categorizations. Finally we will show that object and context processing can interact very early in an ascending wave of visual information processing. We will discuss how such data could result from our experience with a highly structured and predictable surrounding world that shaped neuronal visual selectivity. PMID:22007180

A framework for medical image retrieval using machine learning and statistical similarity matching techniques with relevance feedback.

PubMed

Rahman, Md Mahmudur; Bhattacharya, Prabir; Desai, Bipin C

2007-01-01

A content-based image retrieval (CBIR) framework for diverse collection of medical images of different imaging modalities, anatomic regions with different orientations and biological systems is proposed. Organization of images in such a database (DB) is well defined with predefined semantic categories; hence, it can be useful for category-specific searching. The proposed framework consists of machine learning methods for image prefiltering, similarity matching using statistical distance measures, and a relevance feedback (RF) scheme. To narrow down the semantic gap and increase the retrieval efficiency, we investigate both supervised and unsupervised learning techniques to associate low-level global image features (e.g., color, texture, and edge) in the projected PCA-based eigenspace with their high-level semantic and visual categories. Specially, we explore the use of a probabilistic multiclass support vector machine (SVM) and fuzzy c-mean (FCM) clustering for categorization and prefiltering of images to reduce the search space. A category-specific statistical similarity matching is proposed in a finer level on the prefiltered images. To incorporate a better perception subjectivity, an RF mechanism is also added to update the query parameters dynamically and adjust the proposed matching functions. Experiments are based on a ground-truth DB consisting of 5000 diverse medical images of 20 predefined categories. Analysis of results based on cross-validation (CV) accuracy and precision-recall for image categorization and retrieval is reported. It demonstrates the improvement, effectiveness, and efficiency achieved by the proposed framework.

New support vector machine-based method for microRNA target prediction.

PubMed

Li, L; Gao, Q; Mao, X; Cao, Y

2014-06-09

MicroRNA (miRNA) plays important roles in cell differentiation, proliferation, growth, mobility, and apoptosis. An accurate list of precise target genes is necessary in order to fully understand the importance of miRNAs in animal development and disease. Several computational methods have been proposed for miRNA target-gene identification. However, these methods still have limitations with respect to their sensitivity and accuracy. Thus, we developed a new miRNA target-prediction method based on the support vector machine (SVM) model. The model supplies information of two binding sites (primary and secondary) for a radial basis function kernel as a similarity measure for SVM features. The information is categorized based on structural, thermodynamic, and sequence conservation. Using high-confidence datasets selected from public miRNA target databases, we obtained a human miRNA target SVM classifier model with high performance and provided an efficient tool for human miRNA target gene identification. Experiments have shown that our method is a reliable tool for miRNA target-gene prediction, and a successful application of an SVM classifier. Compared with other methods, the method proposed here improves the sensitivity and accuracy of miRNA prediction. Its performance can be further improved by providing more training examples.

Recognition and Sex Categorization of Adults' and Children's Faces: Examining Performance in the Absence of Sex-Stereotyped Cues.

ERIC Educational Resources Information Center

Wild, Heather A.; Barett, Susan E.; Spence, Melanie J.; O'Toole, Alice J.; Cheng, Yi D.; Brooke, Jessica

2000-01-01

Investigated 7-year-olds', 9-year-olds', and adults' ability to classify children's and adults' faces by sex using only biological based internal facial structure. Found that participants categorized adult faces by sex at accuracy levels varying from just above chance (7-year-olds) to nearly perfect (adults). All groups were less accurate for…

Categorization of videogames: some comments on 'Children and electronic games' by Funk, et al.

PubMed

Griffiths, M

2000-06-01

Comments are made on an article by Funk, et al. about children and electronic games. This author argues the cross-cultural differences and developmental effects must be taken into account and that the categorization system of videogames based on content is incomplete or too general to cover the complex actions of contemporary videogames. These factors alone may have implications for research.

Clustering of Variables for Mixed Data

NASA Astrophysics Data System (ADS)

Saracco, J.; Chavent, M.

2016-05-01

This chapter presents clustering of variables which aim is to lump together strongly related variables. The proposed approach works on a mixed data set, i.e. on a data set which contains numerical variables and categorical variables. Two algorithms of clustering of variables are described: a hierarchical clustering and a k-means type clustering. A brief description of PCAmix method (that is a principal component analysis for mixed data) is provided, since the calculus of the synthetic variables summarizing the obtained clusters of variables is based on this multivariate method. Finally, the R packages ClustOfVar and PCAmixdata are illustrated on real mixed data. The PCAmix and ClustOfVar approaches are first used for dimension reduction (step 1) before applying in step 2 a standard clustering method to obtain groups of individuals.

Video copy protection and detection framework (VPD) for e-learning systems

NASA Astrophysics Data System (ADS)

ZandI, Babak; Doustarmoghaddam, Danial; Pour, Mahsa R.

2013-03-01

This Article reviews and compares the copyright issues related to the digital video files, which can be categorized as contended based and Digital watermarking copy Detection. Then we describe how to protect a digital video by using a special Video data hiding method and algorithm. We also discuss how to detect the copy right of the file, Based on expounding Direction of the technology of the video copy detection, and Combining with the own research results, brings forward a new video protection and copy detection approach in terms of plagiarism and e-learning systems using the video data hiding technology. Finally we introduce a framework for Video protection and detection in e-learning systems (VPD Framework).

Measures of Agreement Between Many Raters for Ordinal Classifications

PubMed Central

Nelson, Kerrie P.; Edwards, Don

2015-01-01

Screening and diagnostic procedures often require a physician's subjective interpretation of a patient's test result using an ordered categorical scale to define the patient's disease severity. Due to wide variability observed between physicians’ ratings, many large-scale studies have been conducted to quantify agreement between multiple experts’ ordinal classifications in common diagnostic procedures such as mammography. However, very few statistical approaches are available to assess agreement in these large-scale settings. Existing summary measures of agreement rely on extensions of Cohen's kappa [1 - 5]. These are prone to prevalence and marginal distribution issues, become increasingly complex for more than three experts or are not easily implemented. Here we propose a model-based approach to assess agreement in large-scale studies based upon a framework of ordinal generalized linear mixed models. A summary measure of agreement is proposed for multiple experts assessing the same sample of patients’ test results according to an ordered categorical scale. This measure avoids some of the key flaws associated with Cohen's kappa and its extensions. Simulation studies are conducted to demonstrate the validity of the approach with comparison to commonly used agreement measures. The proposed methods are easily implemented using the software package R and are applied to two large-scale cancer agreement studies. PMID:26095449

Circumventing Imprecise Geometric Information and Development of a Unified Modeling Technique for Various Flow Regimes in Capillary Tubes

NASA Astrophysics Data System (ADS)

Abbasi, Bahman

2012-11-01

Owing to their manufacturability and reliability, capillary tubes are the most common expansion devices in household refrigerators. Therefore, investigating flow properties in the capillary tubes is of immense appeal in the said business. The models to predict pressure drop in two-phase internal flows invariably rely upon highly precise geometric information. The manner in which capillary tubes are manufactured makes them highly susceptible to geometric imprecisions, which renders geometry-based models unreliable to the point of obsoleteness. Aware of the issue, manufacturers categorize capillary tubes based on Nitrogen flow rate through them. This categorization method presents an opportunity to substitute geometric details with Nitrogen flow data as the basis for customized models. The simulation tools developed by implementation of this technique have the singular advantage of being applicable across flow regimes. Thus the error-prone process of identifying compatible correlations is eliminated. Equally importantly, compressibility and chocking effects can be incorporated in the same model. The outcome is a standalone correlation that provides accurate predictions, regardless of any particular fluid or flow regime. Thereby, exploratory investigations for capillary tube design and optimization are greatly simplified. Bahman Abbasi, Ph.D., is Lead Advanced Systems Engineer at General Electric Appliances in Louisville, KY. He conducts research projects across disciplines in the household refrigeration industry.

AdaBoost-based algorithm for network intrusion detection.

PubMed

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

Extending the Reach of Evidence-Based Medicine: A Proposed Categorization of Lower-Level Evidence.

PubMed

Detterbeck, Frank C; Gould, Michael K; Lewis, Sandra Zelman; Patel, Sheena

2018-02-01

Clinical practice involves making many treatment decisions for which only limited formal evidence exists. While the methodology of evidence-based medicine (EBM) has evolved tremendously, there is a need to better characterize lower-level evidence. This should enhance the ability to appropriately weigh the evidence against other considerations, and counter the temptation to think it is more robust than it actually is. A framework to categorize lower-level evidence is proposed, consisting of nonrandomized comparisons, extrapolation using indirect evidence, rationale, and clinical experience (ie, an accumulated general impression). Subtypes are recognized within these categories, based on the degree of confounding in nonrandomized comparisons, the uncertainty involved in extrapolation from indirect evidence, and the plausibility of a rationale. Categorizing the available evidence in this way can promote a better understanding of the strengths and limitations of using such evidence as the basis for treatment decisions in clinically relevant areas that are devoid of higher-level evidence. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

From Concrete Examples to Abstract Relations: The Rostrolateral Prefrontal Cortex Integrates Novel Examples into Relational Categories.

PubMed

Davis, Tyler; Goldwater, Micah; Giron, Josue

2017-04-01

The ability to form relational categories for objects that share few features in common is a hallmark of human cognition. For example, anything that can play a preventative role, from a boulder to poverty, can be a "barrier." However, neurobiological research has focused solely on how people acquire categories defined by features. The present functional magnetic resonance imaging study examines how relational and feature-based category learning compare in well-matched learning tasks. Using a computational model-based approach, we observed a cluster in left rostrolateral prefrontal cortex (rlPFC) that tracked quantitative predictions for the representational distance between test and training examples during relational categorization. Contrastingly, medial and dorsal PFC exhibited graded activation that tracked decision evidence during both feature-based and relational categorization. The results suggest that rlPFC computes an alignment signal that is critical for integrating novel examples during relational categorization whereas other PFC regions support more general decision functions. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Bivariate categorical data analysis using normal linear conditional multinomial probability model.

PubMed

Sun, Bingrui; Sutradhar, Brajendra

2015-02-10

Bivariate multinomial data such as the left and right eyes retinopathy status data are analyzed either by using a joint bivariate probability model or by exploiting certain odds ratio-based association models. However, the joint bivariate probability model yields marginal probabilities, which are complicated functions of marginal and association parameters for both variables, and the odds ratio-based association model treats the odds ratios involved in the joint probabilities as 'working' parameters, which are consequently estimated through certain arbitrary 'working' regression models. Also, this later odds ratio-based model does not provide any easy interpretations of the correlations between two categorical variables. On the basis of pre-specified marginal probabilities, in this paper, we develop a bivariate normal type linear conditional multinomial probability model to understand the correlations between two categorical variables. The parameters involved in the model are consistently estimated using the optimal likelihood and generalized quasi-likelihood approaches. The proposed model and the inferences are illustrated through an intensive simulation study as well as an analysis of the well-known Wisconsin Diabetic Retinopathy status data. Copyright © 2014 John Wiley & Sons, Ltd.

Bifactor Structure for the Categorical Chinese Rosenberg Self-Esteem Scale.

PubMed

Xu, Menglin; Leung, Shing-On

2016-10-11

Recently, the bifactor model was suggested for the latent structure of the Rosenberg Self-Esteem Scale (RSES). The present paper investigates (i) the differences among bifactor, bifactor negative and other models; (ii) the effects of treating data as both categorical vs continuous; (iii) whether a problematic item in the Chinese RSES should be removed; and (iv) whether the final scoring would be affected. With a sample of 1.734 grade 4-6 school pupils in Hong Kong, we used BIC differences in addition to the usual model fit indices, and found that there was strong evidence for using the bifactor model (RMSEA = .052, 90% CI [.043, .062], CFI = .992, TLI = .984 for 9-item RSES categorical). Little difference is found between treating data as categorical or continuous for fit indices, but the factor loading patterns are better in categorical case. Keeping a problematic item has little effect on fit indices, but would lead to unexpected negative loading. The ranking of loadings within positive and negative items across different conditions are the same, which has important effects on scoring. Loadings in the method effects in the bifactor models are all positive (p < .001), which is different from previous research. All models show similar results on scoring, and support the usual simple sum score in most practice.

Do infant Japanese macaques ( Macaca fuscata) categorize objects without specific training?

PubMed

Murai, Chizuko; Tomonaga, Masaki; Kamegai, Kimi; Terazawa, Naoko; Yamaguchi, Masami K

2004-01-01

In the present study, we examined whether infant Japanese macaques categorize objects without any training, using a similar technique also used with human infants (the paired-preference method). During the familiarization phase, subjects were presented twice with two pairs of different objects from one global-level category. During the test phase, they were presented twice with a pair consisting of a novel familiar-category object and a novel global-level category object. The subjects were tested with three global-level categories (animal, furniture, and vehicle). It was found that they showed significant novelty preferences as a whole, indicating that they processed similarities between familiarization objects and novel familiar-category objects. These results suggest that subjects responded distinctively to objects without training, indicating the possibility that infant macaques possess the capacity for categorization.

Quantifying growing versus non-growing ovarian follicles in the mouse.

PubMed

Uslu, Bahar; Dioguardi, Carola Conca; Haynes, Monique; Miao, De-Qiang; Kurus, Meltem; Hoffman, Gloria; Johnson, Joshua

2017-01-13

A standard histomorphometric approach has been used for nearly 40 years that identifies atretic (e.g., dying) follicles by counting the number of pyknotic granulosa cells (GC) in the largest follicle cross-section. This method holds that if one pyknotic granulosa nucleus is seen in the largest cross section of a primary follicle, or three pyknotic cells are found in a larger follicle, it should be categorized as atretic. Many studies have used these criteria to estimate the fraction of atretic follicles that result from genetic manipulation or environmental insult. During an analysis of follicle development in a mouse model of Fragile X premutation, we asked whether these 'historical' criteria could correctly identify follicles that were not growing (and could thus confirmed to be dying). Reasoning that the fraction of mitotic GC reveals whether the GC population was increasing at the time of sample fixation, we compared the number of pyknotic nuclei to the number of mitotic figures in follicles within a set of age-matched ovaries. We found that, by itself, pyknotic nuclei quantification resulted in high numbers of false positives (improperly categorized as atretic) and false negatives (improperly categorized intact). For preantral follicles, scoring mitotic and pyknotic GC nuclei allowed rapid, accurate identification of non-growing follicles with 98% accuracy. This method most often required the evaluation of one follicle section, and at most two serial follicle sections to correctly categorize follicle status. For antral follicles, we show that a rapid evaluation of follicle shape reveals which are intact and likely to survive to ovulation. Combined, these improved, non-arbitrary methods will greatly improve our ability to estimate the fractions of growing/intact and non-growing/atretic follicles in mouse ovaries.

Detection and avoidance of errors in computer software

NASA Technical Reports Server (NTRS)

Kinsler, Les

1989-01-01

The acceptance test errors of a computer software project to determine if the errors could be detected or avoided in earlier phases of development. GROAGSS (Gamma Ray Observatory Attitude Ground Support System) was selected as the software project to be examined. The development of the software followed the standard Flight Dynamics Software Development methods. GROAGSS was developed between August 1985 and April 1989. The project is approximately 250,000 lines of code of which approximately 43,000 lines are reused from previous projects. GROAGSS had a total of 1715 Change Report Forms (CRFs) submitted during the entire development and testing. These changes contained 936 errors. Of these 936 errors, 374 were found during the acceptance testing. These acceptance test errors were first categorized into methods of avoidance including: more clearly written requirements; detail review; code reading; structural unit testing; and functional system integration testing. The errors were later broken down in terms of effort to detect and correct, class of error, and probability that the prescribed detection method would be successful. These determinations were based on Software Engineering Laboratory (SEL) documents and interviews with the project programmers. A summary of the results of the categorizations is presented. The number of programming errors at the beginning of acceptance testing can be significantly reduced. The results of the existing development methodology are examined for ways of improvements. A basis is provided for the definition is a new development/testing paradigm. Monitoring of the new scheme will objectively determine its effectiveness on avoiding and detecting errors.

Self-supervised online metric learning with low rank constraint for scene categorization.

PubMed

Cong, Yang; Liu, Ji; Yuan, Junsong; Luo, Jiebo

2013-08-01

Conventional visual recognition systems usually train an image classifier in a bath mode with all training data provided in advance. However, in many practical applications, only a small amount of training samples are available in the beginning and many more would come sequentially during online recognition. Because the image data characteristics could change over time, it is important for the classifier to adapt to the new data incrementally. In this paper, we present an online metric learning method to address the online scene recognition problem via adaptive similarity measurement. Given a number of labeled data followed by a sequential input of unseen testing samples, the similarity metric is learned to maximize the margin of the distance among different classes of samples. By considering the low rank constraint, our online metric learning model not only can provide competitive performance compared with the state-of-the-art methods, but also guarantees convergence. A bi-linear graph is also defined to model the pair-wise similarity, and an unseen sample is labeled depending on the graph-based label propagation, while the model can also self-update using the more confident new samples. With the ability of online learning, our methodology can well handle the large-scale streaming video data with the ability of incremental self-updating. We evaluate our model to online scene categorization and experiments on various benchmark datasets and comparisons with state-of-the-art methods demonstrate the effectiveness and efficiency of our algorithm.

Financial performance monitoring of the technical efficiency of critical access hospitals: a data envelopment analysis and logistic regression modeling approach.

PubMed

Wilson, Asa B; Kerr, Bernard J; Bastian, Nathaniel D; Fulton, Lawrence V

2012-01-01

From 1980 to 1999, rural designated hospitals closed at a disproportionally high rate. In response to this emergent threat to healthcare access in rural settings, the Balanced Budget Act of 1997 made provisions for the creation of a new rural hospital--the critical access hospital (CAH). The conversion to CAH and the associated cost-based reimbursement scheme significantly slowed the closure rate of rural hospitals. This work investigates which methods can ensure the long-term viability of small hospitals. This article uses a two-step design to focus on a hypothesized relationship between technical efficiency of CAHs and a recently developed set of financial monitors for these entities. The goal is to identify the financial performance measures associated with efficiency. The first step uses data envelopment analysis (DEA) to differentiate efficient from inefficient facilities within a data set of 183 CAHs. Determining DEA efficiency is an a priori categorization of hospitals in the data set as efficient or inefficient. In the second step, DEA efficiency is the categorical dependent variable (efficient = 0, inefficient = 1) in the subsequent binary logistic regression (LR) model. A set of six financial monitors selected from the array of 20 measures were the LR independent variables. We use a binary LR to test the null hypothesis that recently developed CAH financial indicators had no predictive value for categorizing a CAH as efficient or inefficient, (i.e., there is no relationship between DEA efficiency and fiscal performance).

Percentage of free prostate-specific antigen (PSA) is a useful method in deciding to perform prostate biopsy with higher core numbers in patients with low PSA cut-off values.

PubMed

Yilmaz, Hasan; Ciftci, Seyfettin; Yavuz, Ufuk; Ustuner, Murat; Saribacak, Ali; Dillioglugil, Ozdal

2015-06-01

The aim of this study was to evaluate the predictive role of percentage of free prostate-specific antigen (%fPSA) cut-points in prostate cancer (PCa) detection in patients with total PSA (tPSA) levels between 2.5 ng/mL and 10.0 ng/mL. In total, 1321 consecutive initial transrectal ultrasound (TRUS)-guided 12-core biopsies performed between 2005 and 2011 were evaluated retrospectively. Benign pathologies, high-grade prostatic intraepithelial neoplasia, and atypical small acinary proliferations were categorized as noncancerous (benign), and prostate adenocarcinomas were categorized as cancerous (malignant). The patients were categorized according to: Catalona's published %fPSA categories (<10%, 10-15%, 15-20%, 20-25%, or > 25%); digital rectal examination (DRE) results [benign (negative) or suspicious of malignancy (positive)]. There was a significant relationship between the %fPSA cut-points and detection of PCa in DRE-negative patients. The presence of a 10% cut-point increased the probability of PCa threefold. The %fPSA was significantly more related to PCa than the tPSA value in receiver operating characteristic (ROC) curve analyses (p = 0.001). Based on our findings, a lower %fPSA, especially <10%, is an important parameter when deciding whether to perform a biopsy on patients with a tPSA between 2.5 ng/mL and 10 ng/mL. Copyright © 2015. Published by Elsevier Taiwan.

Rank-based permutation approaches for non-parametric factorial designs.

PubMed

Umlauft, Maria; Konietschke, Frank; Pauly, Markus

2017-11-01

Inference methods for null hypotheses formulated in terms of distribution functions in general non-parametric factorial designs are studied. The methods can be applied to continuous, ordinal or even ordered categorical data in a unified way, and are based only on ranks. In this set-up Wald-type statistics and ANOVA-type statistics are the current state of the art. The first method is asymptotically exact but a rather liberal statistical testing procedure for small to moderate sample size, while the latter is only an approximation which does not possess the correct asymptotic α level under the null. To bridge these gaps, a novel permutation approach is proposed which can be seen as a flexible generalization of the Kruskal-Wallis test to all kinds of factorial designs with independent observations. It is proven that the permutation principle is asymptotically correct while keeping its finite exactness property when data are exchangeable. The results of extensive simulation studies foster these theoretical findings. A real data set exemplifies its applicability. © 2017 The British Psychological Society.

Generalizing a categorization of students' interpretations of linear kinematics graphs

NASA Astrophysics Data System (ADS)

Bollen, Laurens; De Cock, Mieke; Zuza, Kristina; Guisasola, Jenaro; van Kampen, Paul

2016-06-01

We have investigated whether and how a categorization of responses to questions on linear distance-time graphs, based on a study of Irish students enrolled in an algebra-based course, could be adopted and adapted to responses from students enrolled in calculus-based physics courses at universities in Flanders, Belgium (KU Leuven) and the Basque Country, Spain (University of the Basque Country). We discuss how we adapted the categorization to accommodate a much more diverse student cohort and explain how the prior knowledge of students may account for many differences in the prevalence of approaches and success rates. Although calculus-based physics students make fewer mistakes than algebra-based physics students, they encounter similar difficulties that are often related to incorrectly dividing two coordinates. We verified that a qualitative understanding of kinematics is an important but not sufficient condition for students to determine a correct value for the speed. When comparing responses to questions on linear distance-time graphs with responses to isomorphic questions on linear water level versus time graphs, we observed that the context of a question influences the approach students use. Neither qualitative understanding nor an ability to find the slope of a context-free graph proved to be a reliable predictor for the approach students use when they determine the instantaneous speed.

Valley and channel networks extraction based on local topographic curvature and k-means clustering of contours

NASA Astrophysics Data System (ADS)

Hooshyar, Milad; Wang, Dingbao; Kim, Seoyoung; Medeiros, Stephen C.; Hagen, Scott C.

2016-10-01

A method for automatic extraction of valley and channel networks from high-resolution digital elevation models (DEMs) is presented. This method utilizes both positive (i.e., convergent topography) and negative (i.e., divergent topography) curvature to delineate the valley network. The valley and ridge skeletons are extracted using the pixels' curvature and the local terrain conditions. The valley network is generated by checking the terrain for the existence of at least one ridge between two intersecting valleys. The transition from unchannelized to channelized sections (i.e., channel head) in each first-order valley tributary is identified independently by categorizing the corresponding contours using an unsupervised approach based on k-means clustering. The method does not require a spatially constant channel initiation threshold (e.g., curvature or contributing area). Moreover, instead of a point attribute (e.g., curvature), the proposed clustering method utilizes the shape of contours, which reflects the entire cross-sectional profile including possible banks. The method was applied to three catchments: Indian Creek and Mid Bailey Run in Ohio and Feather River in California. The accuracy of channel head extraction from the proposed method is comparable to state-of-the-art channel extraction methods.

A Mixed-Methods Investigation of Clicker Implementation Styles in STEM.

PubMed

Solomon, Erin D; Repice, Michelle D; Mutambuki, Jacinta M; Leonard, Denise A; Cohen, Cheryl A; Luo, Jia; Frey, Regina F

2018-06-01

Active learning with clickers is a common approach in high-enrollment, lecture-based courses in science, technology, engineering, and mathematics. In this study, we describe the procedures that faculty at one institution used when implementing clicker-based active learning, and how they situated these activities in their class sessions. Using a mixed-methods approach, we categorized faculty into four implementation styles based on quantitative observation data and conducted qualitative interviews to further understand why faculty used these styles. We found that faculty tended to use similar procedures when implementing a clicker activity, but differed on how they situated the clicker-based active learning into their courses. These variations were attributed to different faculty goals for using clicker-based active learning, with some using it to engage students at specific time points throughout their class sessions and others who selected it as the best way to teach a concept from several possible teaching techniques. Future research should continue to investigate and describe how active-learning strategies from literature may differ from what is being implemented.

Effects of Group Membership, Intergroup Competition and Out-Group Ethnicity on Children's Ratings of In-Group and Out-Group Similarity and Positivity

ERIC Educational Resources Information Center

Nesdale, Drew; Griffiths, Judith A.; Durkin, Kevin; Maass, Anne

2007-01-01

Based on self-categorization theory (SCT; Turner, Hogg, Oakes, Reicher, & Wetherell, 1987), this study examined the extent to which 7- and 10-year-old children's perceptions of similarity to, and positivity towards, their in-group would be increased by factors predicted to enhance the salience of in-group-out-group categorizations. In a minimal…

Soft Biometrics; Human Identification Using Comparative Descriptions.

PubMed

Reid, Daniel A; Nixon, Mark S; Stevenage, Sarah V

2014-06-01

Soft biometrics are a new form of biometric identification which use physical or behavioral traits that can be naturally described by humans. Unlike other biometric approaches, this allows identification based solely on verbal descriptions, bridging the semantic gap between biometrics and human description. To permit soft biometric identification the description must be accurate, yet conventional human descriptions comprising of absolute labels and estimations are often unreliable. A novel method of obtaining human descriptions will be introduced which utilizes comparative categorical labels to describe differences between subjects. This innovative approach has been shown to address many problems associated with absolute categorical labels-most critically, the descriptions contain more objective information and have increased discriminatory capabilities. Relative measurements of the subjects' traits can be inferred from comparative human descriptions using the Elo rating system. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate recognition of subjects. Relative measurements can also be obtained from other forms of human representation. This is demonstrated using a support vector machine to determine relative measurements from gait biometric signatures-allowing retrieval of subjects from video footage by using human comparisons, bridging the semantic gap.

Electron microscopic examination of uncultured soil-dwelling bacteria.

PubMed

Amako, Kazunobu; Takade, Akemi; Taniai, Hiroaki; Yoshida, Shin-ichi

2008-05-01

Bacteria living in soil collected from a rice paddy in Fukuoka, Japan, were examined by electron microscopy using a freeze-substitution fixation method. Most of the observed bacteria could be categorized, based on the structure of the cell envelope and overall morphology, into one of five groups: (i) bacterial spore; (ii) Gram-positive type; (iii) Gram-negative type; (iv) Mycobacterium like; and (v) Archaea like. However, a few of the bacteria could not be readily categorized into one of these groups because they had unique cell wall structures, basically resembling those of Gram-negative bacteria, but with the layer corresponding to the peptidoglycan layer in Gram-negative bacteria being extremely thick, like that of the cortex of a bacterial spore. The characteristic morphological features found in many of these uncultured, soil-dwelling cells were the nucleoid being in a condensed state and the cytoplasm being shrunken. We were able to produce similar morphologies in vitro using a Salmonella sp. by culturing under low-temperature, low-nutrient conditions, similar to those found in some natural environments. These unusual morphologies are therefore hypothesized to be characteristic of bacteria in resting or dormant stages.

Implementation of several mathematical algorithms to breast tissue density classification

NASA Astrophysics Data System (ADS)

Quintana, C.; Redondo, M.; Tirao, G.

2014-02-01

The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories.

Recommendations for the treatment of knee osteoarthritis, using various therapy techniques, based on categorizations of a literature review.

PubMed

Thomas, Anthony; Eichenberger, Gary; Kempton, Curtis; Pape, Darin; York, Sarah; Decker, Ann Marie; Kohia, Mohamed

2009-01-01

This literature review is to evaluate current research articles pertinent to physical therapy treatment of osteoarthritis (OA) of the knee. Osteoarthritis of the knee is an increasingly common diagnosis, with a prognosis that can lead to loss in an individual's functional abilities. Literature on the subject of OA and its physical therapy treatment is vast and current, however, obtaining and analyzing it can be time consuming and costly to a Physical Therapist. The primary aim of this paper is to review current trends for treatment of OA of the knee, and to compare each intervention for effectiveness. This article provides a systematic categorization as well as recommendations for physical therapists based on current (1996 or sooner) literature. Twenty-two articles were located using various online databases, critically analyzed, and categorized using Sackett's levels of evidence. Recommendations for the treatment of OA of the knee by a physical therapist were then made. Two grade A recommendations, 5 grade B recommendation, and 2 grade C recommendations were made from the categorization of the articles. This article also contains recommendations outside the scope of a therapist's practice, which a physical therapist could consider when treating a patient with knee osteoarthritis. Further research recommendations are also provided.

Bryological exploration: field-trip based learning to develop competencies of science teacher candidate

NASA Astrophysics Data System (ADS)

Wisanti; Astriani, D.

2018-04-01

The purpose of this study was analyze the competencies of science teacher candidate after the bryological exploration. The intended competence of science teacher candidate was the ability to apply the concept and science ability to explore plant diversity that could be found around the environment.This field trip was conducted by exploring liverworts, hornworts, and mosses as well. This descriptive research was conducted during March until April 2017 at Universitas Negeri Surabaya (UNESA) and Sumber Brantas Arboretum in Malang, as the location of exploration. The subjects of this study were 76 candidate of teachers from science educations department, which is divided into three classes. The competences observed on this study were describing, identifying, collecting specimens, furthermore. The research instruments were observation sheets, product assessment sheets, and response questionnaire. The data were analyzed descriptive-quantitatively, in percentage and then categorized. The results of this study indicated that: the describing skill was categorized as ‘good’ identifying skill and collecting bryophytes was categorized as ‘very good’ and communicating skills was categorized ‘good’. In addition, the teacher candidates gave a very good response to field-trip-based learning. It can be concluded that the bryological exploration can develop the competences of science teacher candidates of Science Education Department of UNESA.

Criterion learning in rule-based categorization: Simulation of neural mechanism and new data

PubMed Central

Helie, Sebastien; Ell, Shawn W.; Filoteo, J. Vincent; Maddox, W. Todd

2015-01-01

In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g, categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define ‘long’ and ‘short’). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL’s implications for future research on rule learning. PMID:25682349

Criterion learning in rule-based categorization: simulation of neural mechanism and new data.

PubMed

Helie, Sebastien; Ell, Shawn W; Filoteo, J Vincent; Maddox, W Todd

2015-04-01

In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g., categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define 'long' and 'short'). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL's implications for future research on rule learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Measurement invariance study of the training satisfaction questionnaire (TSQ).

PubMed

Sanduvete-Chaves, Susana; Holgado-Tello, F Pablo; Chacón-Moscoso, Salvador; Barbero-García, M Isabel

2013-01-01

This article presents an empirical measurement invariance study in the substantive area of satisfaction evaluation in training programs. Specifically, it (I) provides an empirical solution to the lack of explicit measurement models of satisfaction scales, offering a way of analyzing and operationalizing the substantive theoretical dimensions; (II) outlines and discusses the analytical consequences of considering the effects of categorizing supposedly continuous variables, which are not usually taken into account; (III) presents empirical results from a measurement invariance study based on 5,272 participants' responses to a training satisfaction questionnaire in three different organizations and in two different training methods, taking into account the factor structure of the measured construct and the ordinal nature of the recorded data; and (IV) describes the substantive implications in the area of training satisfaction evaluation, such as the usefulness of the training satisfaction questionnaire to measure satisfaction in different organizations and different training methods. It also discusses further research based on these findings.

Tuberculosis disease diagnosis using artificial immune recognition system.

PubMed

Shamshirband, Shahaboddin; Hessam, Somayeh; Javidnia, Hossein; Amiribesheli, Mohsen; Vahdat, Shaghayegh; Petković, Dalibor; Gani, Abdullah; Kiah, Miss Laiha Mat

2014-01-01

There is a high risk of tuberculosis (TB) disease diagnosis among conventional methods. This study is aimed at diagnosing TB using hybrid machine learning approaches. Patient epicrisis reports obtained from the Pasteur Laboratory in the north of Iran were used. All 175 samples have twenty features. The features are classified based on incorporating a fuzzy logic controller and artificial immune recognition system. The features are normalized through a fuzzy rule based on a labeling system. The labeled features are categorized into normal and tuberculosis classes using the Artificial Immune Recognition Algorithm. Overall, the highest classification accuracy reached was for the 0.8 learning rate (α) values. The artificial immune recognition system (AIRS) classification approaches using fuzzy logic also yielded better diagnosis results in terms of detection accuracy compared to other empirical methods. Classification accuracy was 99.14%, sensitivity 87.00%, and specificity 86.12%.

Antioxidative Categorization of Twenty Amino Acids Based on Experimental Evaluation.

PubMed

Xu, Naijin; Chen, Guanqun; Liu, Hui

2017-11-27

In view of the great importance bestowed on amino acids as antioxidants in oxidation resistance, we attempted two common redox titration methods in this report, including micro-potassium permanganate titration and iodometric titration, to measure the antioxidative capacity of 20 amino acids, which are the construction units of proteins in living organisms. Based on the relative intensities of the antioxidative capacity, we further conducted a quantitative comparison and found out that the product of experimental values obtained from the two methods was proven to be a better indicator for evaluating the relative antioxidative capacity of amino acids. The experimental results were largely in accordance with structural analysis made on amino acids. On the whole, the 20 amino acids concerned could be divided into two categories according to their antioxidative capacity. Seven amino acids, including tryptophan, methionine, histidine, lysine, cysteine, arginine and tyrosine, were greater in total antioxidative capacity compared with the other 13 amino acids.

Perceptions of Others' Political Affiliation Are Moderated by Individual Perceivers' Own Political Attitudes

PubMed Central

Wilson, John Paul; Rule, Nicholas O.

2014-01-01

Previous research has shown that perceivers can accurately extract information about perceptually ambiguous group memberships from facial information alone. For example, people demonstrate above-chance accuracy in categorizing political ideology from faces. Further, they ascribe particular personality traits to faces according to political party (e.g., Republicans are dominant and mature, Democrats are likeable and trustworthy). Here, we report three studies that replicated and extended these effects. In Study 1a, we provide evidence that, in addition to showing accuracy in categorization, politically-conservative participants expressed a bias toward categorizing targets as outgroup members. In Study 1b, we replicate this relationship with a larger sample and a stimulus set consisting of faces of professional politicians. In Study 2, we find that trait ascriptions based on target political affiliation are moderated by perceiver political ideology. Specifically, although Democrats are stereotyped as more likeable and trustworthy, conservative participants rated faces that were categorized as Republicans in Study 1a as more likeable and trustworthy than faces categorized as Democrats. Thus, this paper joins a growing literature showing that it is critical to consider perceiver identity in examining perceptions of identities and traits from faces. PMID:24781819

Perceptions of others' political affiliation are moderated by individual perceivers' own political attitudes.

PubMed

Wilson, John Paul; Rule, Nicholas O

2014-01-01

Previous research has shown that perceivers can accurately extract information about perceptually ambiguous group memberships from facial information alone. For example, people demonstrate above-chance accuracy in categorizing political ideology from faces. Further, they ascribe particular personality traits to faces according to political party (e.g., Republicans are dominant and mature, Democrats are likeable and trustworthy). Here, we report three studies that replicated and extended these effects. In Study 1a, we provide evidence that, in addition to showing accuracy in categorization, politically-conservative participants expressed a bias toward categorizing targets as outgroup members. In Study 1b, we replicate this relationship with a larger sample and a stimulus set consisting of faces of professional politicians. In Study 2, we find that trait ascriptions based on target political affiliation are moderated by perceiver political ideology. Specifically, although Democrats are stereotyped as more likeable and trustworthy, conservative participants rated faces that were categorized as Republicans in Study 1a as more likeable and trustworthy than faces categorized as Democrats. Thus, this paper joins a growing literature showing that it is critical to consider perceiver identity in examining perceptions of identities and traits from faces.

An efficient auto TPT stitch guidance generation for optimized standard cell design

NASA Astrophysics Data System (ADS)

Samboju, Nagaraj C.; Choi, Soo-Han; Arikati, Srini; Cilingir, Erdem

2015-03-01

As the technology continues to shrink below 14nm, triple patterning lithography (TPT) is a worthwhile lithography methodology for printing dense layers such as Metal1. However, this increases the complexity of standard cell design, as it is very difficult to develop a TPT compliant layout without compromising on the area. Hence, this emphasizes the importance to have an accurate stitch generation methodology to meet the standard cell area requirement as defined by the technology shrink factor. In this paper, we present an efficient auto TPT stitch guidance generation technique for optimized standard cell design. The basic idea here is to first identify the conflicting polygons based on the Fix Guidance [1] solution developed by Synopsys. Fix Guidance is a reduced sub-graph containing minimum set of edges along with the connecting polygons; by eliminating these edges in a design 3-color conflicts can be resolved. Once the conflicting polygons are identified using this method, they are categorized into four types [2] - (Type 1 to 4). The categorization is based on number of interactions a polygon has with the coloring links and the triangle loops of fix guidance. For each type a certain criteria for keep-out region is defined, based on which the final stitch guidance locations are generated. This technique provides various possible stitch locations to the user and helps the user to select the best stitch location considering both design flexibility (max. pin access/small area) and process-preferences. Based on this technique, a standard cell library for place and route (P and R) can be developed with colorless data and a stitch marker defined by designer using our proposed method. After P and R, the full chip (block) would contain the colorless data and standard cell stitch markers only. These stitch markers are considered as "must be stitch" candidates. Hence during full chip decomposition it is not required to generate and select the stitch markers again for the complete data; therefore, the proposed method reduces the decomposition time significantly.

The solitary wave solution of coupled Klein-Gordon-Zakharov equations via two different numerical methods

NASA Astrophysics Data System (ADS)

Dehghan, Mehdi; Nikpour, Ahmad

2013-09-01

In this research, we propose two different methods to solve the coupled Klein-Gordon-Zakharov (KGZ) equations: the Differential Quadrature (DQ) and Globally Radial Basis Functions (GRBFs) methods. In the DQ method, the derivative value of a function with respect to a point is directly approximated by a linear combination of all functional values in the global domain. The principal work in this method is the determination of weight coefficients. We use two ways for obtaining these coefficients: cosine expansion (CDQ) and radial basis functions (RBFs-DQ), the former is a mesh-based method and the latter categorizes in the set of meshless methods. Unlike the DQ method, the GRBF method directly substitutes the expression of the function approximation by RBFs into the partial differential equation. The main problem in the GRBFs method is ill-conditioning of the interpolation matrix. Avoiding this problem, we study the bases introduced in Pazouki and Schaback (2011) [44]. Some examples are presented to compare the accuracy and easy implementation of the proposed methods. In numerical examples, we concentrate on Inverse Multiquadric (IMQ) and second-order Thin Plate Spline (TPS) radial basis functions. The variable shape parameter (exponentially and random) strategies are applied in the IMQ function and the results are compared with the constant shape parameter.

Argument Based Science Inquiry (ABSI) Learning Model in Voltaic Cell Concept

NASA Astrophysics Data System (ADS)

Subarkah, C. Z.; Fadilah, A.; Aisyah, R.

2017-09-01

Voltaic Cell is a sub-concept of electrochemistry that is considered difficult to be comprehended by learners Voltaic Cell is a sub concept of electrochemistry that is considered difficult to be understood by learners so that impacts on student activity in learning process. Therefore the learning model Argument Based Science Inquiry (ABSI) will be applied to the concept of Voltaic cell. This research aims to describe students’ activities during learning process using ABSI model and to analyze students’ competency to solve ABSI-based worksheets (LK) of Voltaic Cell concept. The method used in this research was the “mix-method-quantitative-embedded” method with subjects of the study: 39 second-semester students of Chemistry Education study program. The student activity is quite good during ABSI learning. The students’ ability to complete worksheet (LK) for every average phase is good. In the phase of exploration of post instruction understanding, it is categorized very good, and in the phase of negotiation shape III: comparing science ideas to textbooks or other printed resources merely reach enough category. Thus, the ABSI learning has improved the student levels of activity and students’ competency to solve the ABSI-based worksheet (LK).

Data base for the prediction of inlet external drag

NASA Technical Reports Server (NTRS)

Mcmillan, O. J.; Perkins, E. W.; Perkins, S. C., Jr.

1980-01-01

Results are presented from a study to define and evaluate the data base for predicting an airframe/propulsion system interference effect shown to be of considerable importance, inlet external drag. The study is focused on supersonic tactical aircraft with highly integrated jet propulsion systems, although some information is included for supersonic strategic aircraft and for transport aircraft designed for high subsonic or low supersonic cruise. The data base for inlet external drag is considered to consist of the theoretical and empirical prediction methods as well as the experimental data identified in an extensive literature search. The state of the art in the subsonic and transonic speed regimes is evaluated. The experimental data base is organized and presented in a series of tables in which the test article, the quantities measured and the ranges of test conditions covered are described for each set of data; in this way, the breadth of coverage and gaps in the existing experimental data are evident. Prediction methods are categorized by method of solution, type of inlet and speed range to which they apply, major features are given, and their accuracy is assessed by means of comparison to experimental data.

Susceptibility of 100 filamentous fungi: comparison of two diffusion methods, Neo-Sensitabs and E-test, for amphotericin B, caspofungin, itraconazole, voriconazole and posaconazole.

PubMed

Colosi, Ioana A; Faure, Odile; Dessaigne, Bérangére; Bourdon, Cécile; Lebeau, Bernadette; Colosi, Horaţiu A; Pelloux, Hervé

2012-05-01

We compared the E-test method to that of the Neo-Sensitabs tablet diffusion assay for evaluating the in vitro susceptibility of 100 clinical isolates of filamentous fungi (Aspergillus spp., Fusarium spp., Scedosporium spp., zygomycetes and other molds) to amphotericin B, itraconazole, voriconazole, caspofungin, and posaconazole. We determined the categorical agreement level between E-test minimum inhibitory concentrations (MIC) and tablet end-points, as opposed to the following disagreement parameters: very major error - resistant parameter (R) in E-test and susceptible (S) in tablet; major error - S by E-test and R by tablet; minor error - shifts between S and susceptible dose-dependent (S-DD) or S-DD and R. We also performed linear regression analyses and computed Pearson's correlation coefficients (R values) between the log transforms of MICs and the inhibition zone diameters of the five studied antifungal agents. For itraconazole we obtained 97% categorical agreement and R = -0.727. Categorical agreement for caspofungin and voriconazole was 96% and R =-0.821 and R = -0.789, respectively. For posaconazole the categorical agreement was 94% and R =-0.743. Amphotericin B exhibited a lower degree of agreement (76%, R = -0.672), especially in studies of Aspergillus spp. Our results suggest a potential value of the Neo-Sensitabs assay for in vitro susceptibility testing of molds to itraconazole, voriconazole, caspofungin and posaconazole, while amphotericin B exhibited an overall lower degree of agreement.

Examining solutions to missing data in longitudinal nursing research.

PubMed

Roberts, Mary B; Sullivan, Mary C; Winchester, Suzy B

2017-04-01

Longitudinal studies are highly valuable in pediatrics because they provide useful data about developmental patterns of child health and behavior over time. When data are missing, the value of the research is impacted. The study's purpose was to (1) introduce a three-step approach to assess and address missing data and (2) illustrate this approach using categorical and continuous-level variables from a longitudinal study of premature infants. A three-step approach with simulations was followed to assess the amount and pattern of missing data and to determine the most appropriate imputation method for the missing data. Patterns of missingness were Missing Completely at Random, Missing at Random, and Not Missing at Random. Missing continuous-level data were imputed using mean replacement, stochastic regression, multiple imputation, and fully conditional specification (FCS). Missing categorical-level data were imputed using last value carried forward, hot-decking, stochastic regression, and FCS. Simulations were used to evaluate these imputation methods under different patterns of missingness at different levels of missing data. The rate of missingness was 16-23% for continuous variables and 1-28% for categorical variables. FCS imputation provided the least difference in mean and standard deviation estimates for continuous measures. FCS imputation was acceptable for categorical measures. Results obtained through simulation reinforced and confirmed these findings. Significant investments are made in the collection of longitudinal data. The prudent handling of missing data can protect these investments and potentially improve the scientific information contained in pediatric longitudinal studies. © 2017 Wiley Periodicals, Inc.

Design of a general methodology for the evaluation and categorization of an environmental program with special reference to Costa Rica

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

Castillo, H.

1982-01-01

The Government of Costa Rica has stated the need for a formal procedure for the evaluation and categorization of an environmental program. Methodological studies were prepared as the basis for the development of the general methodology by which each government or institution can adapt and implement the procedure. The methodology was established by using different techniques according to their contribution to the evaluation process, such as: Systemic Approach, Delphi, and Saaty Methods. The methodology consists of two main parts: 1) evaluation of the environmental aspects by using different techniques; 2) categorization of the environmental aspects by applying the methodology tomore » the Costa Rican Environmental affairs using questionnaire answers supplied by experts both inside and outside of the country. The second part of the research includes Appendixes in which is presented general information concerning institutions related to environmental affairs; description of the methods used; results of the current status evaluation and its scale; the final scale of categorization; and the questionnaires and a list of experts. The methodology developed in this research will have a beneficial impact on environmental concerns in Costa Rica. As a result of this research, a Commission Office of Environmental Affairs, providing links between consumers, engineers, scientists, and the Government, is recommended. Also there is significant potential use of this methodology in developed countries for a better balancing of the budgets of major research programs such as cancer, heart, and other research areas.« less

Exploring the Position of Community-Based Nursing in Iran: A Qualitative Study

PubMed Central

Heydari, Heshmatolah; Rahnavard, Zahra; Ghaffari, Fatemeh

2017-01-01

ABSTRACT Background: Community-based nursing focuses on providing health services to families and communities in the second and third levels of prevention and this can improve the individuals, families and communities’ quality of life, and reduce the healthcare costs. The aim of this study was to explore the status of community-based nursing in Iran. Methods: This qualitative study was conducted from March to November 2015, in Tehran, Iran, using the content analysis approach. The study setting consisted of Iran and Tehran Faculties of Nursing and Midwifery, Tehran, Iran. The purposive sampling method was used. Twenty faculty members and Master’s and PhD students were interviewed by using the face-to-face semi-structured interview method. Moreover, two focus groups were conducted for complementing and enriching the study data. The data were analyzed using the Graneheim and Lundman’s approach to content analysis. The trustworthiness of the study findings was maintained by employing the Lincoln and Guba’s criteria of credibility, dependability, and confirmability. Results: In total, 580 codes were generated and categorized into three main categories of conventional services, the necessity for creating infrastructures, and multidimensional outcomes of community-based nursing. Conclusion: Introducing community-based nursing into nursing education curricula and creating ample job opportunities for community-based nurses seem clearly essential. PMID:29043284

Combined qualitative and quantitative research designs.

PubMed

Seymour, Jane

2012-12-01

Mixed methods research designs have been recognized as important in addressing complexity and are recommended particularly in the development and evaluation of complex interventions. This article reports a review of studies in palliative care published between 2010 and March 2012 that combine qualitative and quantitative approaches. A synthesis of approaches to mixed methods research taken in 28 examples of published research studies of relevance to palliative and supportive care is provided, using a typology based on a classic categorization put forward in 1992. Mixed-method studies are becoming more frequently employed in palliative care research and resonate with the complexity of the palliative care endeavour. Undertaking mixed methods research requires a sophisticated understanding of the research process and recognition of some of the underlying complexities encountered when working with different traditions and perspectives on issues of: sampling, validity, reliability and rigour, different sources of data and different data collection and analysis techniques.

Bone healing in 2016

PubMed Central

Buza, John A.; Einhorn, Thomas

2016-01-01

Summary Delayed fracture healing and nonunion occurs in up to 5–10% of all fractures, and can present a challenging clinical scenario for the treating physician. Methods for the enhancement of skeletal repair may benefit patients that are at risk of, or have experienced, delayed healing or nonunion. These methods can be categorized into either physical stimulation therapies or biological therapies. Physical stimulation therapies include electrical stimulation, low-intensity pulsed ultrasonography, or extracorporeal shock wave therapy. Biological therapies can be further classified into local or systemic therapy based on the method of delivery. Local methods include autologous bone marrow, autologous bone graft, fibroblast growth factor-2, platelet-rich plasma, platelet-derived growth factor, and bone morphogenetic proteins. Systemic therapies include parathyroid hormone and bisphosphonates. This article reviews the current applications and supporting evidence for the use of these therapies in the enhancement of fracture healing. PMID:27920804

Application of Enrofloxacin and Orbifloxacin Disks Approved in Japan for Susceptibility Testing of Representative Veterinary Respiratory Pathogens

PubMed Central

HARADA, Kazuki; USUI, Masaru; ASAI, Tetsuo

2014-01-01

ABSTRACT In this study, susceptibilities of Pasteurella multocida, Mannheimia haemolytica and Actinobacillus pleuropneumoniae to enrofloxacin and orbifloxacin were tested using an agar diffusion method with the commercial disks and a broth microdilution method. Good correlation between the 2 methods for enrofloxacin and orbifloxacin was observed for P. multocida (r = −0.743 and −0.818, respectively), M. haemolytica (r = −0.739 and −0.800, respectively) and A. pleuropneumoniae (r = −0.785 and −0.809, respectively). Based on the Clinical and Laboratory Standards Institute interpretive criteria for enrofloxacin, high-level categorical agreement between the 2 methods was found for P. multocida (97.9%), M. haemolytica (93.8%) and A. pleuropneumoniae (92.0%). Our findings indicate that the tested commercial disks can be applied for susceptibility testing of veterinary respiratory pathogens. PMID:25008965

Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering.

PubMed

He, Zhaoshui; Xie, Shengli; Zdunek, Rafal; Zhou, Guoxu; Cichocki, Andrzej

2011-12-01

Nonnegative matrix factorization (NMF) is an unsupervised learning method useful in various applications including image processing and semantic analysis of documents. This paper focuses on symmetric NMF (SNMF), which is a special case of NMF decomposition. Three parallel multiplicative update algorithms using level 3 basic linear algebra subprograms directly are developed for this problem. First, by minimizing the Euclidean distance, a multiplicative update algorithm is proposed, and its convergence under mild conditions is proved. Based on it, we further propose another two fast parallel methods: α-SNMF and β -SNMF algorithms. All of them are easy to implement. These algorithms are applied to probabilistic clustering. We demonstrate their effectiveness for facial image clustering, document categorization, and pattern clustering in gene expression.

A Review of Astronomy Education Research

NASA Astrophysics Data System (ADS)

Bailey, Janelle M.; Slater, Timothy F.

The field of astronomy education is rapidly growing beyond merely sharing effective activities or curriculum ideas. This paper categorizes and summarizes the literature in astronomy education research and contains more than 100 references to articles, books, and Web-based materials. Research into student understanding on a variety of topics now occupies a large part of the literature. Topics include the shape of Earth and gravity, lunar phases, seasons, astrobiology, and cosmology. The effectiveness of instructional methods is now being tested systematically, taking data beyond the anecdotal with powerful research designs and statistical analyses. Quantitative, qualitative, and mixed-methods approaches have found their places in the researcher's toolbox. In all cases, the connection between the research performed and its effect on classroom instruction is largely lacking.

Verification of an Automated, Digital Dispensing Platform for At-Will Broth Microdilution-Based Antimicrobial Susceptibility Testing.

PubMed

Smith, Kenneth P; Kirby, James E

2016-09-01

With rapid emergence of multidrug-resistant bacteria, there is often a need to perform susceptibility testing for less commonly used or newer antimicrobial agents. Such testing can often be performed only by using labor-intensive, manual dilution methods and lies outside the capacity of most clinical labs, necessitating reference laboratory testing and thereby delaying the availability of susceptibility data. To address the compelling clinical need for microbiology laboratories to perform such testing in-house, we explored a novel, automated, at-will broth microdilution-based susceptibility testing platform. Specifically, we used the modified inkjet printer technology in the HP D300 digital dispensing system to dispense, directly from stock solutions into a 384-well plate, the 2-fold serial dilution series required for broth microdilution testing. This technology was combined with automated absorbance readings and data analysis to determine MICs. Performance was verified by testing members of the Enterobacteriaceae for susceptibility to ampicillin, cefazolin, ciprofloxacin, colistin, gentamicin, meropenem, and tetracycline in comparison to the results obtained with a broth microdilution reference standard. In precision studies, essential and categorical agreement levels were 96.8% and 98.3%, respectively. Furthermore, significantly fewer D300-based measurements were outside ±1 dilution from the modal MIC, suggesting enhanced reproducibility. In accuracy studies performed using a panel of 80 curated clinical isolates, rates of essential and categorical agreement and very major, major, and minor errors were 94%, 96.6%, 0%, 0%, and 3.4%, respectively. Based on these promising initial results, it is anticipated that the D300-based methodology will enable hospital-based clinical microbiology laboratories to perform at-will broth microdilution testing of antimicrobials and to address a critical testing gap. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Assessing the influence of component processing and donor characteristics on quality of red cell concentrates using quality control data.

PubMed

Jordan, A; Chen, D; Yi, Q-L; Kanias, T; Gladwin, M T; Acker, J P

2016-07-01

Quality control (QC) data collected by blood services are used to monitor production and to ensure compliance with regulatory standards. We demonstrate how analysis of quality control data can be used to highlight the sources of variability within red cell concentrates (RCCs). We merged Canadian Blood Services QC data with manufacturing and donor records for 28 227 RCC between June 2011 and October 2014. Units were categorized based on processing method, bag manufacturer, donor age and donor sex, then assessed based on product characteristics: haemolysis and haemoglobin levels, unit volume, leucocyte count and haematocrit. Buffy-coat method (top/bottom)-processed units exhibited lower haemolysis than units processed using the whole-blood filtration method (top/top). Units from female donors exhibited lower haemolysis than male donations. Processing method influenced unit volume and the ratio of additive solution to residual plasma. Stored red blood cell characteristics are influenced by prestorage processing and donor factors. Understanding the relationship between processing, donors and RCC quality will help blood services to ensure the safety of transfused products. © 2016 International Society of Blood Transfusion.

Recent Advances in Biomaterials for 3D Printing and Tissue Engineering

PubMed Central

Jammalamadaka, Udayabhanu

2018-01-01

Three-dimensional printing has significant potential as a fabrication method in creating scaffolds for tissue engineering. The applications of 3D printing in the field of regenerative medicine and tissue engineering are limited by the variety of biomaterials that can be used in this technology. Many researchers have developed novel biomaterials and compositions to enable their use in 3D printing methods. The advantages of fabricating scaffolds using 3D printing are numerous, including the ability to create complex geometries, porosities, co-culture of multiple cells, and incorporate growth factors. In this review, recently-developed biomaterials for different tissues are discussed. Biomaterials used in 3D printing are categorized into ceramics, polymers, and composites. Due to the nature of 3D printing methods, most of the ceramics are combined with polymers to enhance their printability. Polymer-based biomaterials are 3D printed mostly using extrusion-based printing and have a broader range of applications in regenerative medicine. The goal of tissue engineering is to fabricate functional and viable organs and, to achieve this, multiple biomaterials and fabrication methods need to be researched. PMID:29494503

Recent Advances in Biomaterials for 3D Printing and Tissue Engineering.

PubMed

Jammalamadaka, Udayabhanu; Tappa, Karthik

2018-03-01

Three-dimensional printing has significant potential as a fabrication method in creating scaffolds for tissue engineering. The applications of 3D printing in the field of regenerative medicine and tissue engineering are limited by the variety of biomaterials that can be used in this technology. Many researchers have developed novel biomaterials and compositions to enable their use in 3D printing methods. The advantages of fabricating scaffolds using 3D printing are numerous, including the ability to create complex geometries, porosities, co-culture of multiple cells, and incorporate growth factors. In this review, recently-developed biomaterials for different tissues are discussed. Biomaterials used in 3D printing are categorized into ceramics, polymers, and composites. Due to the nature of 3D printing methods, most of the ceramics are combined with polymers to enhance their printability. Polymer-based biomaterials are 3D printed mostly using extrusion-based printing and have a broader range of applications in regenerative medicine. The goal of tissue engineering is to fabricate functional and viable organs and, to achieve this, multiple biomaterials and fabrication methods need to be researched.

A new adaptive algorithm for automated feature extraction in exponentially damped signals for health monitoring of smart structures

NASA Astrophysics Data System (ADS)

Qarib, Hossein; Adeli, Hojjat

2015-12-01

In this paper authors introduce a new adaptive signal processing technique for feature extraction and parameter estimation in noisy exponentially damped signals. The iterative 3-stage method is based on the adroit integration of the strengths of parametric and nonparametric methods such as multiple signal categorization, matrix pencil, and empirical mode decomposition algorithms. The first stage is a new adaptive filtration or noise removal scheme. The second stage is a hybrid parametric-nonparametric signal parameter estimation technique based on an output-only system identification technique. The third stage is optimization of estimated parameters using a combination of the primal-dual path-following interior point algorithm and genetic algorithm. The methodology is evaluated using a synthetic signal and a signal obtained experimentally from transverse vibrations of a steel cantilever beam. The method is successful in estimating the frequencies accurately. Further, it estimates the damping exponents. The proposed adaptive filtration method does not include any frequency domain manipulation. Consequently, the time domain signal is not affected as a result of frequency domain and inverse transformations.

Automatic Calibration Method for Driver’s Head Orientation in Natural Driving Environment

PubMed Central

Fu, Xianping; Guan, Xiao; Peli, Eli; Liu, Hongbo; Luo, Gang

2013-01-01

Gaze tracking is crucial for studying driver’s attention, detecting fatigue, and improving driver assistance systems, but it is difficult in natural driving environments due to nonuniform and highly variable illumination and large head movements. Traditional calibrations that require subjects to follow calibrators are very cumbersome to be implemented in daily driving situations. A new automatic calibration method, based on a single camera for determining the head orientation and which utilizes the side mirrors, the rear-view mirror, the instrument board, and different zones in the windshield as calibration points, is presented in this paper. Supported by a self-learning algorithm, the system tracks the head and categorizes the head pose in 12 gaze zones based on facial features. The particle filter is used to estimate the head pose to obtain an accurate gaze zone by updating the calibration parameters. Experimental results show that, after several hours of driving, the automatic calibration method without driver’s corporation can achieve the same accuracy as a manual calibration method. The mean error of estimated eye gazes was less than 5°in day and night driving. PMID:24639620

Accelerating atomic structure search with cluster regularization

NASA Astrophysics Data System (ADS)

Sørensen, K. H.; Jørgensen, M. S.; Bruix, A.; Hammer, B.

2018-06-01

We present a method for accelerating the global structure optimization of atomic compounds. The method is demonstrated to speed up the finding of the anatase TiO2(001)-(1 × 4) surface reconstruction within a density functional tight-binding theory framework using an evolutionary algorithm. As a key element of the method, we use unsupervised machine learning techniques to categorize atoms present in a diverse set of partially disordered surface structures into clusters of atoms having similar local atomic environments. Analysis of more than 1000 different structures shows that the total energy of the structures correlates with the summed distances of the atomic environments to their respective cluster centers in feature space, where the sum runs over all atoms in each structure. Our method is formulated as a gradient based minimization of this summed cluster distance for a given structure and alternates with a standard gradient based energy minimization. While the latter minimization ensures local relaxation within a given energy basin, the former enables escapes from meta-stable basins and hence increases the overall performance of the global optimization.

Critical thinking analysis based on Facione (2015) – Angelo (1995) logical mathematics material of vocational high school (VHS)

NASA Astrophysics Data System (ADS)

Seventika, S. Y.; Sukestiyarno, Y. L.; Mariani, Scolastika

2018-03-01

The research has purpose to analyze and categorize the critical thinking ability of VHS students based on modified critical thinking indicator according to Facione-Angelo covering: interpreting the problem, analyzing alternative solution, applying the problem, evaluating the solution and concluding the results gained – attached by supportive evidence. The subject of the research is 30 eleventh graders of TKJ in Yabujah VHS, Indramayu in the odd semester 2016/2017. The collected data are critical thinking test and interviews. The result shows 15% is in good category, 30% in fair category, and 55% in low category. The students in “Good” category has accomplished critical thinking steps although imperfect, especially the indicators of evaluating and concluding attached by supportive evidence. The “Fair” categorized students only show partial steps of the indicators. The analyzing, evaluating, and concluding indicators are the most seldom to do, meanwhile the “low” categorized students show all indicators in low quality even to identify has problem to do.

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database

PubMed Central

Seo, Jeong Gi; Kwak, Jiyong; Um, Terry Taewoong; Rim, Tyler Hyungtaek

2017-01-01

Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNet for an automated detection of multiple retinal diseases with fundus photographs involved in STructured Analysis of the REtina (STARE) database. Dataset was built by expanding data on 10 categories, including normal retina and nine retinal diseases. The optimal outcomes were acquired by using a random forest transfer learning based on VGG-19 architecture. The classification results depended greatly on the number of categories. As the number of categories increased, the performance of deep learning models was diminished. When all 10 categories were included, we obtained results with an accuracy of 30.5%, relative classifier information (RCI) of 0.052, and Cohen’s kappa of 0.224. Considering three integrated normal, background diabetic retinopathy, and dry age-related macular degeneration, the multi-categorical classifier showed accuracy of 72.8%, 0.283 RCI, and 0.577 kappa. In addition, several ensemble classifiers enhanced the multi-categorical classification performance. The transfer learning incorporated with ensemble classifier of clustering and voting approach presented the best performance with accuracy of 36.7%, 0.053 RCI, and 0.225 kappa in the 10 retinal diseases classification problem. First, due to the small size of datasets, the deep learning techniques in this study were ineffective to be applied in clinics where numerous patients suffering from various types of retinal disorders visit for diagnosis and treatment. Second, we found that the transfer learning incorporated with ensemble classifiers can improve the classification performance in order to detect multi-categorical retinal diseases. Further studies should confirm the effectiveness of algorithms with large datasets obtained from hospitals. PMID:29095872

Evidence-based risk assessment and communication: a new global dengue-risk map for travellers and clinicians#

PubMed Central

Lash, R. Ryan; Johansson, Michael A.; Sharp, Tyler M.; Henry, Ronnie; Brady, Oliver J.; Sotir, Mark J.; Hay, Simon I.; Margolis, Harold S.; Brunette, Gary W.

2016-01-01

Abstract Background: International travel can expose travellers to pathogens not commonly found in their countries of residence, like dengue virus. Travellers and the clinicians who advise and treat them have unique needs for understanding the geographic extent of risk for dengue. Specifically, they should assess the need for prevention measures before travel and ensure appropriate treatment of illness post-travel. Previous dengue-risk maps published in the Centers for Disease Control and Prevention’s Yellow Book lacked specificity, as there was a binary (risk, no risk) classification. We developed a process to compile evidence, evaluate it and apply more informative risk classifications. Methods: We collected more than 839 observations from official reports, ProMED reports and published scientific research for the period 2005–2014. We classified each location as frequent/continuous risk if there was evidence of more than 10 dengue cases in at least three of the previous 10 years. For locations that did not fit this criterion, we classified locations as sporadic/uncertain risk if the location had evidence of at least one locally acquired dengue case during the last 10 years. We used expert opinion in limited instances to augment available data in areas where data were sparse. Results: Initial categorizations classified 134 areas as frequent/continuous and 140 areas as sporadic/uncertain. CDC subject matter experts reviewed all initial frequent/continuous and sporadic/uncertain categorizations and the previously uncategorized areas. From this review, most categorizations stayed the same; however, 11 categorizations changed from the initial determinations. Conclusions: These new risk classifications enable detailed consideration of dengue risk, with clearer meaning and a direct link to the evidence that supports the specific classification. Since many infectious diseases have dynamic risk, strong geographical heterogeneities and varying data quality and availability, using this approach for other diseases can improve the accuracy, clarity and transparency of risk communication. PMID:27625400

A Risk-Continuum Categorization of Product Use Among US Youth Tobacco Users

PubMed Central

El-Toukhy, Sherine

2016-01-01

Introduction: To examine prevalence and correlates of five mutually exclusive tobacco-use patterns among US youth tobacco users. Methods: A nationally representative sample of tobacco users (N = 3202, 9–17 years) was classified into five product-use patterns. Weighted multinominal and multivariate logistic regression models were used to examine prevalence of product-use patterns by gender, race and ethnicity, and grade level; and associations between product-use patterns and perceived accessibility of tobacco products, exposure and receptivity to pro-tobacco marketing, social benefits of smoking, and tobacco-associated risks. Results: Dual use (ie, use of two product categories) was the most prevalent pattern (30.5%), followed by non-cigarette combustible only (26.7%), polytobacco (ie, use of three product categories; 17.5%), cigarette only (14.9%), and noncombustible only (10.4%) use. Product-use patterns differed by gender, race, and ethnicity. Compared to cigarette only users, dual and polytobacco users were more likely to be exposed to and be receptive to pro-tobacco marketing, and were less likely to acknowledge tobacco-use related risks (Ps < .05). Conclusions: Curbing tobacco use warrants research on users of more than one tobacco-product categories according to the risk-continuum categorization. Implications: We present a risk-continuum categorization of product-use patterns among tobacco users not older than 17 years. We classify tobacco users into five mutually exclusive product-use patterns: cigarette only users, non-cigarette combustible only users, noncombustible only users, dual use, and polytobacco use. This categorization overcomes limitations in current literature on tobacco-use patterns, which include exclusion of certain products (eg, e-cigarettes) and product-use patterns (eg, exclusive users of non-cigarette products), and inconsistent classification of tobacco users. It is parsimonious yet complex enough to retain differential characteristics of sub-tobacco users based on number (single, dual, polytobacco) and categories (cigarettes, non-cigarette combustibles, noncombustibles) of tobacco products consumed. PMID:26764258

Categorization of In-use Radioactive Sealed Sources in Egypt

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

Hasan, M.A.; Mohamed, Y.T.; El Haleim, K.A.

2006-07-01

Radioactive sealed sources have widespread applications in industry, medicine, research and education. While most sources are of relatively low activity, there are many of medium or very high activity. The mismanagement of high activity sources is responsible for most of the radiological accidents that result in loss of life or disabling injuries. Because of the variety of applications and activities of radioactive sources, a categorization system is necessary so that the controls that are applied to the sources are adequate with its radiological risk. The aim of this work is to use the international Atomic Energy Agency (IAEA) categorization systemmore » to provide a simple, logical system for grading radioactive sealed sources in Egypt. The categorizations of radioactive sealed sources are based on their potential to cause harm to human health. This study revealed that total of 1916 sources have been used in Egypt in the different applications with a total activity of 89400 Ci according to available data in October 2005. (authors)« less

Evaluating Structural Equation Models for Categorical Outcomes: A New Test Statistic and a Practical Challenge of Interpretation.

PubMed

Monroe, Scott; Cai, Li

2015-01-01

This research is concerned with two topics in assessing model fit for categorical data analysis. The first topic involves the application of a limited-information overall test, introduced in the item response theory literature, to structural equation modeling (SEM) of categorical outcome variables. Most popular SEM test statistics assess how well the model reproduces estimated polychoric correlations. In contrast, limited-information test statistics assess how well the underlying categorical data are reproduced. Here, the recently introduced C2 statistic of Cai and Monroe (2014) is applied. The second topic concerns how the root mean square error of approximation (RMSEA) fit index can be affected by the number of categories in the outcome variable. This relationship creates challenges for interpreting RMSEA. While the two topics initially appear unrelated, they may conveniently be studied in tandem since RMSEA is based on an overall test statistic, such as C2. The results are illustrated with an empirical application to data from a large-scale educational survey.

Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization.

PubMed

Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

2018-02-28

The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to predict cortical responses to natural movies. Using this predictive model, we mapped human cortical representations to 64,000 visual objects from 80 categories with high throughput and accuracy. Such representations covered both the ventral and dorsal pathways, reflected multiple levels of object features, and preserved semantic relationships between categories. In the entire visual cortex, object representations were organized into three clusters of categories: biological objects, non-biological objects, and background scenes. In a finer scale specific to each cluster, object representations revealed sub-clusters for further categorization. Such hierarchical clustering of category representations was mostly contributed by cortical representations of object features from middle to high levels. In summary, this study demonstrates a useful computational strategy to characterize the cortical organization and representations of visual features for rapid categorization.