factorial discriminant analysis: Topics by Science.gov

Sample records for factorial discriminant analysis

Assessment of sampling stability in ecological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.

1988-01-01

A simulation study was undertaken to assess the sampling stability of the variable loadings in linear discriminant function analysis. A factorial design was used for the factors of multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. A review of 60 published studies and 142 individual analyses indicated that sample sizes in ecological studies often have met that requirement. However, individual group sample sizes frequently were very unequal, and checks of assumptions usually were not reported. The authors recommend that ecologists obtain group sample sizes that are at least three times as large as the number of variables measured.
Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine.

PubMed

Monakhova, Yulia B; Godelmann, Rolf; Kuballa, Thomas; Mushtakova, Svetlana P; Rutledge, Douglas N

2015-08-15

Discriminant analysis (DA) methods, such as linear discriminant analysis (LDA) or factorial discriminant analysis (FDA), are well-known chemometric approaches for solving classification problems in chemistry. In most applications, principle components analysis (PCA) is used as the first step to generate orthogonal eigenvectors and the corresponding sample scores are utilized to generate discriminant features for the discrimination. Independent components analysis (ICA) based on the minimization of mutual information can be used as an alternative to PCA as a preprocessing tool for LDA and FDA classification. To illustrate the performance of this ICA/DA methodology, four representative nuclear magnetic resonance (NMR) data sets of wine samples were used. The classification was performed regarding grape variety, year of vintage and geographical origin. The average increase for ICA/DA in comparison with PCA/DA in the percentage of correct classification varied between 6±1% and 8±2%. The maximum increase in classification efficiency of 11±2% was observed for discrimination of the year of vintage (ICA/FDA) and geographical origin (ICA/LDA). The procedure to determine the number of extracted features (PCs, ICs) for the optimum DA models was discussed. The use of independent components (ICs) instead of principle components (PCs) resulted in improved classification performance of DA methods. The ICA/LDA method is preferable to ICA/FDA for recognition tasks based on NMR spectroscopic measurements. Copyright © 2015 Elsevier B.V. All rights reserved.
The Role of Spatial Analysis in Detecting the Consequence of the Factory Sites : Case Study of Assalaya Factory-Sudan

NASA Astrophysics Data System (ADS)

Khair, Amar Sharaf Eldin; Purwanto; RyaSunoko, Henna; Abdullah, Omer Adam

2018-02-01

Spatial analysis is considered as one of the most important science for identifying the most appropriate site for industrialization and also to alleviate the environmental ramifications caused by factories. This study aims at analyzing the Assalaya sugarcane factory site by the use of spatial analysis to determine whether it has ramification on the White Nile River. The methodology employed for this study is Global Position System (GPS) to identify the coordinate system of the study phenomena and other relative factors. The study will also make use Geographical Information System (GIS) to implement the spatial analysis. Satellite data (LandsatDem-Digital Elevation Model) will be considered for the study area and factory in identifying the consequences by analyzing the location of the factory through several features such as hydrological, contour line and geological analysis. Data analysis reveals that the factory site is inappropriate and according to observation on the ground it has consequences on the White Nile River. Based on the finding, the study recommended some suggestions to avoid the aftermath of any factory in general. We have to take advantage of this new technological method to aid in selecting most apt locations for industries that will create an ambient environment.
The factorial and discriminant validity of the German version of the Post-traumatic Growth Inventory in stroke patients.

PubMed

Mack, Julian; Herrberg, Marlene; Hetzel, Andreas; Wallesch, Claus Werner; Bengel, Jürgen; Schulz, Moritz; Rohde, Nathalie; Schönberger, Michael

2015-01-01

Post-traumatic growth (PTG) is the experience of positive changes that can follow a traumatic event. The current study examined the factorial as well as the discriminant validity of the German version of the Post-traumatic Growth Inventory (PTGI-G) in stroke patients. A total of 188 adult stroke patients (63.3% male; median age 69 years) completed the PTGI-G and the German version of the Hospital Anxiety and Depression Scale (HADS-D) at the end of their inpatient rehabilitation. Confirmatory factor analyses indicate an acceptable model fit of both the original five-factor solution as well as a second-order factor model of the PTGI-G (CFI > .95; RMSEA < .01). Small and non-significant correlations between the PTGI-G subscales and the depression scale of the HADS-D support the discriminant validity of the PTGI-G. The PTGI-G appears to be a valid tool in the context of stroke research.
European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30: factorial models to Brazilian cancer patients

PubMed Central

Campos, Juliana Alvares Duarte Bonini; Spexoto, Maria Cláudia Bernardes; da Silva, Wanderson Roberto; Serrano, Sergio Vicente; Marôco, João

2018-01-01

ABSTRACT Objective To evaluate the psychometric properties of the seven theoretical models proposed in the literature for European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30), when applied to a sample of Brazilian cancer patients. Methods Content and construct validity (factorial, convergent, discriminant) were estimated. Confirmatory factor analysis was performed. Convergent validity was analyzed using the average variance extracted. Discriminant validity was analyzed using correlational analysis. Internal consistency and composite reliability were used to assess the reliability of instrument. Results A total of 1,020 cancer patients participated. The mean age was 53.3±13.0 years, and 62% were female. All models showed adequate factorial validity for the study sample. Convergent and discriminant validities and the reliability were compromised in all of the models for all of the single items referring to symptoms, as well as for the “physical function” and “cognitive function” factors. Conclusion All theoretical models assessed in this study presented adequate factorial validity when applied to Brazilian cancer patients. The choice of the best model for use in research and/or clinical protocols should be centered on the purpose and underlying theory of each model. PMID:29694609
Design, analysis and presentation of factorial randomised controlled trials

PubMed Central

Montgomery, Alan A; Peters, Tim J; Little, Paul

2003-01-01

Background The evaluation of more than one intervention in the same randomised controlled trial can be achieved using a parallel group design. However this requires increased sample size and can be inefficient, especially if there is also interest in considering combinations of the interventions. An alternative may be a factorial trial, where for two interventions participants are allocated to receive neither intervention, one or the other, or both. Factorial trials require special considerations, however, particularly at the design and analysis stages. Discussion Using a 2 × 2 factorial trial as an example, we present a number of issues that should be considered when planning a factorial trial. The main design issue is that of sample size. Factorial trials are most often powered to detect the main effects of interventions, since adequate power to detect plausible interactions requires greatly increased sample sizes. The main analytical issues relate to the investigation of main effects and the interaction between the interventions in appropriate regression models. Presentation of results should reflect the analytical strategy with an emphasis on the principal research questions. We also give an example of how baseline and follow-up data should be presented. Lastly, we discuss the implications of the design, analytical and presentational issues covered. Summary Difficulties in interpreting the results of factorial trials if an influential interaction is observed is the cost of the potential for efficient, simultaneous consideration of two or more interventions. Factorial trials can in principle be designed to have adequate power to detect realistic interactions, and in any case they are the only design that allows such effects to be investigated. PMID:14633287
Stability and bias of classification rates in biological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.; Hines, J.E.

1990-01-01

We assessed the sampling stability of classification rates in discriminant analysis by using a factorial design with factors for multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. Simulation results indicated strong bias in correct classification rates when group sample sizes were small and when overlap among groups was high. We also found that stability of the correct classification rates was influenced by these factors, indicating that the number of samples required for a given level of precision increases with the amount of overlap among groups. In a review of 60 published studies, we found that 57% of the articles presented results on classification rates, though few of them mentioned potential biases in their results. Wildlife researchers should choose the total number of samples per group to be at least 2 times the number of variables to be measured when overlap among groups is low. Substantially more samples are required as the overlap among groups increases
Heuristics to Facilitate Understanding of Discriminant Analysis.

ERIC Educational Resources Information Center

Van Epps, Pamela D.

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…
Factorial correspondence analysis of fear-related behaviour traits in Japanese quail.

PubMed

Mignon-Grasteau, S; Roussot, O; Delaby, C; Faure, J M.; Mills, A; Leterrier, C; Guéméné, D; Constantin, P; Mills, M; Lepape, G; Beaumont, C

2003-02-28

Factorial correspondence analysis was performed on 341 quails from a F2 cross between two lines divergently selected on the duration of tonic immobility over 29 generations. Several fear- or stress-related traits were recorded, i.e. tonic immobility duration, number of inductions needed to induce tonic immobility, open-field behaviour (time spent walking, latency before first movement and number of defecations), asymmetry of tibia lengths and corticosterone concentration after restraint stress. Variables were categorised in classes and analysed by factorial correspondence analysis. The first axis was mostly described by open-field behaviour, and the second by tonic immobility traits (duration of tonic immobility and number of inductions), which showed that these behaviours were almost independent. No relationship was found between axes of the factorial correspondence analysis and corticosterone concentration or asymmetry of tibia lengths, showing that these variables reflected other characteristics of stress susceptibility than those described by tonic immobility and open-field behaviour. These results show that reaction to stress of quails is a multidimensional trait and cannot be summarised by one trait.
Orthogonal sparse linear discriminant analysis

NASA Astrophysics Data System (ADS)

Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun

2018-03-01

Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.
Legitimating Racial Discrimination: Emotions, Not Beliefs, Best Predict Discrimination in a Meta-Analysis

PubMed Central

Talaska, Cara A.; Chaiken, Shelly

2013-01-01

Investigations of racial bias have emphasized stereotypes and other beliefs as central explanatory mechanisms and as legitimating discrimination. In recent theory and research, emotional prejudices have emerged as another, more direct predictor of discrimination. A new comprehensive meta-analysis of 57 racial attitude-discrimination studies finds a moderate relationship between overall attitudes and discrimination. Emotional prejudices are twices as closely related to racial discrimination as stereotypes and beliefs are. Moreover, emotional prejudices are closely related to both observed and self-reported discrimination, whereas stereotypes and beliefs are related only to self-reported discrimination. Implications for justifying discrimination are discussed. PMID:24052687
Ergonomic analysis jobs in recovered factories.

PubMed

Cuenca, Gabriela; Zotta, Gastón

2012-01-01

With the advent of the deep economic crisis in Argentina on 2001, the recovery of companies through to the creation of the Cooperatives Working Self-Management or Factories Recovered by its workers was constituted as one of the ways in which the salaried disobeyed the increasing unemployment. When the companies turn into recovered factories they tend to leave of side practices that have been seen like imposed by the previous organization and not understanding them as a primary condition for the execution of his tasks. Safety and ergonomics are two disciplines that are no longer considered relevant to the daily work. Therefore this investigation aims to revalue, undergo semantic to give back to a place in every organization analyzed. This research developed a self-diagnostic tool for working conditions, and the environment, present in the recovered factories.
Factorial validity of the Movement Assessment Battery for Children-2 (age band 2).

PubMed

Wagner, Matthias Oliver; Kastner, Julia; Petermann, Franz; Bös, Klaus

2011-01-01

The Movement Assessment Battery for Children-2 (M-ABC-2) is one of the most commonly used tests for the diagnosis of specific developmental disorders of motor function (F82). The M-ABC-2 comprises eight subtests per age band (AB) that are assigned to three dimensions: manual dexterity, aiming and catching, and balance. However, while previous exploratory findings suggested the correctness of the assumption of factorial validity, there is no empirical evidence that the M-ABC-2 subtests allow for a valid reproduction of the postulated factorial structure. The purpose of this study was to empirically confirm the factorial validity of the M-ABC-2. The German normative sample of AB2 (7-10 years; N=323) was used as the study sample for the empirical analyses. Confirmatory factor analysis was used to verify the factorial validity of the M-ABC-2 (AB2). The incremental fit indices (χ2=28.675; df=17; Bollen-Stine p value=0.318; RMSEA=0.046 [0.011-0.075]; SRMR=0.038; CFI=0.960) provided evidence for the factorial validity of the M-ABC-2 (AB2). However, because of a lack of empirical verification for convergent and discriminant validity, there is still no evidence that F82 can be diagnosed using M-ABC-2 (AB2). Copyright © 2010 Elsevier Ltd. All rights reserved.
Analysis of replication factories in human cells by super-resolution light microscopy

PubMed Central

2009-01-01

Background DNA replication in human cells is performed in discrete sub-nuclear locations known as replication foci or factories. These factories form in the nucleus during S phase and are sites of DNA synthesis and high local concentrations of enzymes required for chromatin replication. Why these structures are required, and how they are organised internally has yet to be identified. It has been difficult to analyse the structure of these factories as they are small in size and thus below the resolution limit of the standard confocal microscope. We have used stimulated emission depletion (STED) microscopy, which improves on the resolving power of the confocal microscope, to probe the structure of these factories at sub-diffraction limit resolution. Results Using immunofluorescent imaging of PCNA (proliferating cell nuclear antigen) and RPA (replication protein A) we show that factories are smaller in size (approximately 150 nm diameter), and greater in number (up to 1400 in an early S- phase nucleus), than is determined by confocal imaging. The replication inhibitor hydroxyurea caused an approximately 40% reduction in number and a 30% increase in diameter of replication factories, changes that were not clearly identified by standard confocal imaging. Conclusions These measurements for replication factory size now approach the dimensions suggested by electron microscopy. This agreement between these two methods, that use very different sample preparation and imaging conditions, suggests that we have arrived at a true measurement for the size of these structures. The number of individual factories present in a single nucleus that we measure using this system is greater than has been previously reported. This analysis therefore suggests that each replication factory contains fewer active replication forks than previously envisaged. PMID:20015367
Study on bayes discriminant analysis of EEG data.

PubMed

Shi, Yuan; He, DanDan; Qin, Fang

2014-01-01

In this paper, we have done Bayes Discriminant analysis to EEG data of experiment objects which are recorded impersonally come up with a relatively accurate method used in feature extraction and classification decisions. In accordance with the strength of α wave, the head electrodes are divided into four species. In use of part of 21 electrodes EEG data of 63 people, we have done Bayes Discriminant analysis to EEG data of six objects. Results In use of part of EEG data of 63 people, we have done Bayes Discriminant analysis, the electrode classification accuracy rates is 64.4%. Bayes Discriminant has higher prediction accuracy, EEG features (mainly αwave) extract more accurate. Bayes Discriminant would be better applied to the feature extraction and classification decisions of EEG data.
Credit scoring analysis using kernel discriminant

NASA Astrophysics Data System (ADS)

Widiharih, T.; Mukid, M. A.; Mustafid

2018-05-01

Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.
EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES.

PubMed

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D

2008-05-12

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component's discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies.
Score-moment combined linear discrimination analysis (SMC-LDA) as an improved discrimination method.

PubMed

Han, Jintae; Chung, Hoeil; Han, Sung-Hwan; Yoon, Moon-Young

2007-01-01

A new discrimination method called the score-moment combined linear discrimination analysis (SMC-LDA) has been developed and its performance has been evaluated using three practical spectroscopic datasets. The key concept of SMC-LDA was to use not only the score from principal component analysis (PCA), but also the moment of the spectrum, as inputs for LDA to improve discrimination. Along with conventional score, moment is used in spectroscopic fields as an effective alternative for spectral feature representation. Three different approaches were considered. Initially, the score generated from PCA was projected onto a two-dimensional feature space by maximizing Fisher's criterion function (conventional PCA-LDA). Next, the same procedure was performed using only moment. Finally, both score and moment were utilized simultaneously for LDA. To evaluate discrimination performances, three different spectroscopic datasets were employed: (1) infrared (IR) spectra of normal and malignant stomach tissue, (2) near-infrared (NIR) spectra of diesel and light gas oil (LGO) and (3) Raman spectra of Chinese and Korean ginseng. For each case, the best discrimination results were achieved when both score and moment were used for LDA (SMC-LDA). Since the spectral representation character of moment was different from that of score, inclusion of both score and moment for LDA provided more diversified and descriptive information.
Gender bias in nineteenth-century England: Evidence from factory children.

PubMed

Horrell, Sara; Oxley, Deborah

2016-09-01

Gender bias against girls in nineteenth-century England has received much interest but establishing its existence has proved difficult. We utilise data on heights of 16,402 children working in northern textile factories in 1837 to examine whether gender bias was evident. Current interpretations argue against any difference. Here our comparisons with modern height standards reveal greater deprivation for girls than for boys. Discrimination is measured in girls' height-for-age score (HAZ) falling eight standard errors below boys' at ages 11, 11.5 and 12 years of age, capturing the very poor performance of factory girls. But this result cannot be taken at face value. We query whether modern standards require adjustment to account for the later timing of puberty in historical populations and develop an alternative. We also test the validity of the age data, considering whether parents were more prone to lie about the ages of their daughters, and question whether the supply of girls was fundamentally different from that of boys. We conclude that neither proposition is justified. Disadvantage to girls remains, although its absence amongst younger children precludes an indictment of culturally founded gender bias. The height data must remain mute on the source of this discrimination but we utilise additional information to examine some hypotheses: occupational sorting, differential susceptibility to disease, poorer nutrition for girls, disproportionate stunting from the effects of nutritional deprivation, and type and amount of work undertaken. Of these we suggest that girls had to do arduous physical labour in the home alongside their factory work. The only (unsubstantiated) alternative is that girls were more likely than boys to be put into factory work below the legal age limit. Both represent forms of gender bias. Copyright © 2016 Elsevier B.V. All rights reserved.
EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES

PubMed Central

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D.

2009-01-01

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component’s discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies. PMID:20582334

A Critical Analysis of Anti-Discrimination Law and Microaggressions in Academia

ERIC Educational Resources Information Center

Lukes, Robin; Bangs, Joann

2014-01-01

This article provides a critical analysis of microaggressions and anti-discrimination law in academia. There are many challenges for faculty claiming discrimination under current civil rights laws. Examples of microaggressions that fall outside of anti-discrimination law will be provided. Traditional legal analysis of discrimination will not end…
The share of southeastern black counties in the southern rural renaissance: were they bypassed by factory job gains, 1959-77?

PubMed

Till, T E

1986-04-01

Some authors have suggested that a leading problem associated with US factory employment for blacks may be that the nonfarm jobs--specifically manufacturing--have tended to go to heavily white counties rather than to the mainly black counties of the Deep South. This study is limited to the 1959-1977 period, the time of the most vigorous nonmetropolitan employment growth. To test the hypothesis that factory jobs have bypassed heavily black counties, a 100% sample of nonmetropolitan counties was used from 13 Southern states for the 2 time periods, 1959-1969 and 1969-1977. Results show that the minority counties were not bypassed by Southern rural factory job growth either in the 1960s or the 1970s, but their gains were not as sizeable as those of more heavily white counties. Both the neoclassical economics of discrimination--with its individualistic "taste for discrimination"--and the stinging critique by Marshall in 1974 that such analysis ignores the important role of institutionalized racism--can "explain the empirical conclusions of this article." Traditional "smokestack-chasing" methods are by no means hopeless. While co-ops and community development corporation strategies can be combined with traditional methods, it is important that foundations, government agencies, anti-poverty programs, and black leadership also focus on projects to competitively attract jobs in the traditional fashion.
Performing Contrast Analysis in Factorial Designs: From NHST to Confidence Intervals and Beyond

PubMed Central

Wiens, Stefan; Nilsson, Mats E.

2016-01-01

Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful because it can be used to test specific questions of central interest in studies with factorial designs. It weighs several means and combines them into one or two sets that can be tested with t tests. The effect size produced by a contrast analysis is simply the difference between means. The CI of the effect size informs directly about direction, hypothesis exclusion, and the relevance of the effects of interest. However, any interpretation in terms of precision or likelihood requires the use of likelihood intervals or credible intervals (Bayesian). These various intervals and even a Bayesian t test can be obtained easily with free software. This tutorial reviews these methods to guide researchers in answering the following questions: When I analyze mean differences in factorial designs, where can I find the effects of central interest, and what can I learn about their effect sizes? PMID:29805179
Graphical methods for the sensitivity analysis in discriminant analysis

DOE PAGES

Kim, Youngil; Anderson-Cook, Christine M.; Dae-Heung, Jang

2015-09-30

Similar to regression, many measures to detect influential data points in discriminant analysis have been developed. Many follow similar principles as the diagnostic measures used in linear regression in the context of discriminant analysis. Here we focus on the impact on the predicted classification posterior probability when a data point is omitted. The new method is intuitive and easily interpretative compared to existing methods. We also propose a graphical display to show the individual movement of the posterior probability of other data points when a specific data point is omitted. This enables the summaries to capture the overall pattern ofmore » the change.« less
Generalized Factorial Moments

NASA Astrophysics Data System (ADS)

Bialas, A.

2004-02-01

It is shown that the method of eliminating the statistical fluctuations from event-by-event analysis proposed recently by Fu and Liu can be rewritten in a compact form involving the generalized factorial moments.
On the use of metabolic control analysis in the optimization of cyanobacterial biosolar cell factories.

PubMed

Angermayr, S Andreas; Hellingwerf, Klaas J

2013-09-26

Oxygenic photosynthesis will have a key role in a sustainable future. It is therefore significant that this process can be engineered in organisms such as cyanobacteria to construct cell factories that catalyze the (sun)light-driven conversion of CO2 and water into products like ethanol, butanol, or other biofuels or lactic acid, a bioplastic precursor, and oxygen as a byproduct. It is of key importance to optimize such cell factories to maximal efficiency. This holds for their light-harvesting capabilities under, for example, circadian illumination in large-scale photobioreactors. However, this also holds for the "dark" reactions of photosynthesis, that is, the conversion of CO2, NADPH, and ATP into a product. Here, we present an analysis, based on metabolic control theory, to estimate the optimal capacity for product formation with which such cyanobacterial cell factories have to be equipped. Engineered l-lactic acid producing Synechocystis sp. PCC6803 strains are used to identify the relation between production rate and enzymatic capacity. The analysis shows that the engineered cell factories for l-lactic acid are fully limited by the metabolic capacity of the product-forming pathway. We attribute this to the fact that currently available promoter systems in cyanobacteria lack the genetic capacity to a provide sufficient expression in single-gene doses.
Discriminant Analysis of Student Loan Applications

ERIC Educational Resources Information Center

Dyl, Edward A.; McGann, Anthony F.

1977-01-01

The use of discriminant analysis in identifying potentially "good" versus potentially "bad" student loans is explained. The technique is applied to a sample of 200 student loan applications at the University of Wyoming. (LBH)
Discrimination between smiling faces: Human observers vs. automated face analysis.

PubMed

Del Líbano, Mario; Calvo, Manuel G; Fernández-Martín, Andrés; Recio, Guillermo

2018-05-11

This study investigated (a) how prototypical happy faces (with happy eyes and a smile) can be discriminated from blended expressions with a smile but non-happy eyes, depending on type and intensity of the eye expression; and (b) how smile discrimination differs for human perceivers versus automated face analysis, depending on affective valence and morphological facial features. Human observers categorized faces as happy or non-happy, or rated their valence. Automated analysis (FACET software) computed seven expressions (including joy/happiness) and 20 facial action units (AUs). Physical properties (low-level image statistics and visual saliency) of the face stimuli were controlled. Results revealed, first, that some blended expressions (especially, with angry eyes) had lower discrimination thresholds (i.e., they were identified as "non-happy" at lower non-happy eye intensities) than others (especially, with neutral eyes). Second, discrimination sensitivity was better for human perceivers than for automated FACET analysis. As an additional finding, affective valence predicted human discrimination performance, whereas morphological AUs predicted FACET discrimination. FACET can be a valid tool for categorizing prototypical expressions, but is currently more limited than human observers for discrimination of blended expressions. Configural processing facilitates detection of in/congruence(s) across regions, and thus detection of non-genuine smiling faces (due to non-happy eyes). Copyright © 2018 Elsevier B.V. All rights reserved.
Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

NASA Astrophysics Data System (ADS)

Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan

2010-12-01

This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB) with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO) algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.
Discrimination Enhancement with Transient Feature Analysis of a Graphene Chemical Sensor.

PubMed

Nallon, Eric C; Schnee, Vincent P; Bright, Collin J; Polcha, Michael P; Li, Qiliang

2016-01-19

A graphene chemical sensor is subjected to a set of structurally and chemically similar hydrocarbon compounds consisting of toluene, o-xylene, p-xylene, and mesitylene. The fractional change in resistance of the sensor upon exposure to these compounds exhibits a similar response magnitude among compounds, whereas large variation is observed within repetitions for each compound, causing a response overlap. Therefore, traditional features depending on maximum response change will cause confusion during further discrimination and classification analysis. More robust features that are less sensitive to concentration, sampling, and drift variability would provide higher quality information. In this work, we have explored the advantage of using transient-based exponential fitting coefficients to enhance the discrimination of similar compounds. The advantages of such feature analysis to discriminate each compound is evaluated using principle component analysis (PCA). In addition, machine learning-based classification algorithms were used to compare the prediction accuracies when using fitting coefficients as features. The additional features greatly enhanced the discrimination between compounds while performing PCA and also improved the prediction accuracy by 34% when using linear discrimination analysis.
The Analysis of Completely Randomized Factorial Experiments When Observations Are Lost at Random.

ERIC Educational Resources Information Center

Hummel, Thomas J.

An investigation was conducted of the characteristics of two estimation procedures and corresponding test statistics used in the analysis of completely randomized factorial experiments when observations are lost at random. For one estimator, contrast coefficients for cell means did not involve the cell frequencies. For the other, contrast…
Discrimination of Swiss cheese from 5 different factories by high impact volatile organic compound profiles determined by odor activity value using selected ion flow tube mass spectrometry and odor threshold.

PubMed

Taylor, Kaitlyn; Wick, Cheryl; Castada, Hardy; Kent, Kyle; Harper, W James

2013-10-01

Swiss cheese contains more than 200 volatile organic compounds (VOCs). Gas chromatography-mass spectrometry has been utilized for the analysis of volatile compounds in food products; however, it is not sensitive enough to measure VOCs directly in the headspace of a food at low concentrations. Selected ion flow tube mass spectrometry (SIFT-MS) provides a basis for determining the concentrations of VOCs in the head space of the sample in real time at low concentration levels of parts per billion/trillion by volume. Of the Swiss cheese VOCs, relatively few have a major impact on flavor quality. VOCs with odor activity values (OAVs) (concentration/odor threshold) greater than one are considered high-impact flavor compounds. The objective of this study was to utilize SIFT-MS concentrations in conjunction with odor threshold values to determine OAVs thereby identifying high-impact VOCs to use for differentiating Swiss cheese from five factories and identify the factory variability. Seventeen high-impact VOCs were identified for Swiss cheese based on an OAV greater than one in at least 1 of the 5 Swiss cheese factories. Of these, 2,3-butanedione was the only compound with significantly different OAVs in all factories; however, cheese from any pair of factories had multiple statistically different compounds based on OAV. Principal component analysis using soft independent modeling of class analogy statistical differentiation plots, with all of the OAVs, showed differentiation between the 5 factories. Overall, Swiss cheese from different factories was determined to have different OAV profiles utilizing SIFT-MS to determine OAVs of high impact compounds. © 2013 Institute of Food Technologists®
Performing Contrast Analysis in Factorial Designs: From NHST to Confidence Intervals and Beyond

ERIC Educational Resources Information Center

Wiens, Stefan; Nilsson, Mats E.

2017-01-01

Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful…
Ranking procedure for partial discriminant analysis

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

Beckman, R.J.; Johnson, M.E.

1981-09-01

A rank procedure developed by Broffitt, Randles, and Hogg (1976) is modified to control the conditional probability of misclassification given that classification has been attempted. This modification leads to a useful solution to the two-population partial discriminant analysis problem for even moderately sized training sets.
Discriminant analysis of functional optical topography for schizophrenia diagnosis

NASA Astrophysics Data System (ADS)

Chuang, Ching-Cheng; Nakagome, Kazuyuki; Pu, Shenghong; Lan, Tsuo-Hung; Lee, Chia-Yen; Sun, Chia-Wei

2014-01-01

Abnormal prefrontal function plays a central role in the cognition deficits of schizophrenic patients; however, the character of the relationship between discriminant analysis and prefrontal activation remains undetermined. Recently, evidence of low prefrontal cortex (PFC) activation in individuals with schizophrenia has also been found during verbal fluency tests (VFT) and other cognitive tests with several neuroimaging methods. The purpose of this study is to assess the hemodynamic changes of the PFC and discriminant analysis between schizophrenia patients and healthy controls during VFT task by utilizing functional optical topography. A total of 99 subjects including 53 schizophrenic patients and 46 age- and gender-matched healthy controls were studied. The results showed that the healthy group had larger activation in the right and left PFC than in the middle PFC. Besides, the schizophrenic group showed weaker task performance and lower activation in the whole PFC than the healthy group. The result of the discriminant analysis showed a significant difference with P value <0.001 in six channels (CH 23, 29, 31, 40, 42, 52) between the schizophrenic and healthy groups. Finally, 68.69% and 71.72% of subjects are correctly classified as being schizophrenic or healthy with all 52 channels and six significantly different channels, respectively. Our findings suggest that the left PFC can be a feature region for discriminant analysis of schizophrenic diagnosis.
Comparison of cranial sex determination by discriminant analysis and logistic regression.

PubMed

Amores-Ampuero, Anabel; Alemán, Inmaculada

2016-04-05

Various methods have been proposed for estimating dimorphism. The objective of this study was to compare sex determination results from cranial measurements using discriminant analysis or logistic regression. The study sample comprised 130 individuals (70 males) of known sex, age, and cause of death from San José cemetery in Granada (Spain). Measurements of 19 neurocranial dimensions and 11 splanchnocranial dimensions were subjected to discriminant analysis and logistic regression, and the percentages of correct classification were compared between the sex functions obtained with each method. The discriminant capacity of the selected variables was evaluated with a cross-validation procedure. The percentage accuracy with discriminant analysis was 78.2% for the neurocranium (82.4% in females and 74.6% in males) and 73.7% for the splanchnocranium (79.6% in females and 68.8% in males). These percentages were higher with logistic regression analysis: 85.7% for the neurocranium (in both sexes) and 94.1% for the splanchnocranium (100% in females and 91.7% in males).
MATRIX DISCRIMINANT ANALYSIS WITH APPLICATION TO COLORIMETRIC SENSOR ARRAY DATA

PubMed Central

Suslick, Kenneth S.

2014-01-01

With the rapid development of nano-technology, a “colorimetric sensor array” (CSA) which is referred to as an optical electronic nose has been developed for the identification of toxicants. Unlike traditional sensors which rely on a single chemical interaction, CSA can measure multiple chemical interactions by using chemo-responsive dyes. The color changes of the chemo-responsive dyes are recorded before and after exposure to toxicants and serve as a template for classification. The color changes are digitalized in the form of a matrix with rows representing dye effects and columns representing the spectrum of colors. Thus, matrix-classification methods are highly desirable. In this article, we develop a novel classification method, matrix discriminant analysis (MDA), which is a generalization of linear discriminant analysis (LDA) for the data in matrix form. By incorporating the intrinsic matrix-structure of the data in discriminant analysis, the proposed method can improve CSA’s sensitivity and more importantly, specificity. A penalized MDA method, PMDA, is also introduced to further incorporate sparsity structure in discriminant function. Numerical studies suggest that the proposed MDA and PMDA methods outperform LDA and other competing discriminant methods for matrix predictors. The asymptotic consistency of MDA is also established. R code and data are available online as supplementary material. PMID:26783371
The effect of perceived discrimination on the health of immigrant workers in Spain.

PubMed

Agudelo-Suárez, Andrés A; Ronda-Pérez, Elena; Gil-González, Diana; Vives-Cases, Carmen; García, Ana M; Ruiz-Frutos, Carlos; Felt, Emily; Benavides, Fernando G

2011-08-17

Discrimination is an important determinant of health inequalities, and immigrants may be more vulnerable to certain types of discrimination than the native-born. This study analyses the relationship between immigrants' perceived discrimination and various self-reported health indicators. A cross-sectional survey was conducted (2008) amongst a non-random sample of 2434 immigrants from Ecuador, Morocco, Romania and Colombia in four Spanish cities: Barcelona, Huelva, Madrid and Valencia. A factorial analysis of variables revealed three dimensions of perceived discrimination (due to immigrant status, due to physical appearance, and workplace-related). The association of these dimensions with self-rated health, mental health (GHQ-12), change in self-rated health between origin and host country, and other self-reported health outcomes was analysed. Logistic regression was used adjusting for potential confounders (aOR-95%CI). Subjects with worsening self-reported health status potentially attributable to perceived discrimination was estimated (population attributable proportion, PAP %). 73.3% of men and 69.3% of women immigrants reported discrimination due to immigrant status. Moroccans showed the highest prevalence of perceived discrimination. Immigrants reporting discrimination were at significantly higher risk of reporting health problems than those not reporting discrimination. Workplace-related discrimination was associated with poor mental health (aOR 2.97 95%CI 2.45-3.60), and the worsening of self-rated health (aOR 2.20 95%CI 1.73- 2.80). 40% (95% CI 24-53) PAP of those reporting worse self-rated health could be attributable to discrimination due to immigrant status. Discrimination may constitute a risk factor for health in immigrant workers in Spain and could explain some health inequalities among immigrant populations in Spanish society.
Racial discrimination and cortisol output: A meta-analysis.

PubMed

Korous, Kevin M; Causadias, José M; Casper, Deborah M

2017-11-01

Although the relation between stress and physiology is well documented, attempts at understanding the link between racial discrimination and cortisol output, specifically, have produced mixed results, likely due to study characteristics such as racial/ethnic composition of the samples (e.g., African American, Latino), measures of discrimination, and research design (e.g., cross-sectional, experimental). To estimate the overall association between racial discrimination and cortisol output among racial/ethnic minority individuals and to determine if the association between racial discrimination and cortisol output is moderated by age, race/ethnicity, type of discrimination measure, sex, and research design. Using a random effects model, the overall effect size based on k = 16 studies (19% unpublished) and N = 1506 participants was r¯ = 0.040, 95% CI = -0.038 to 0.117. Studies were conducted predominantly in the U.S. (81%). Notably, experimental studies (r¯ = 0.267) exhibited larger effect sizes compared to non-experimental studies (r¯ = -0.007). Age, race/ethnicity, type of discrimination measure, and sex did not moderate the effect sizes. This meta-analysis provides evidence that the measurement of the association between racial discrimination and cortisol is complex, and it offers valuable insight regarding methods and designs that can inform future research on this topic. Limitations and future directions are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Discrimination surfaces with application to region-specific brain asymmetry analysis.

PubMed

Martos, Gabriel; de Carvalho, Miguel

2018-05-20

Discrimination surfaces are here introduced as a diagnostic tool for localizing brain regions where discrimination between diseased and nondiseased participants is higher. To estimate discrimination surfaces, we introduce a Mann-Whitney type of statistic for random fields and present large-sample results characterizing its asymptotic behavior. Simulation results demonstrate that our estimator accurately recovers the true surface and corresponding interval of maximal discrimination. The empirical analysis suggests that in the anterior region of the brain, schizophrenic patients tend to present lower local asymmetry scores in comparison with participants in the control group. Copyright © 2018 John Wiley & Sons, Ltd.

Declining Bias and Gender Wage Discrimination? A Meta-Regression Analysis

ERIC Educational Resources Information Center

Jarrell, Stephen B.; Stanley, T. D.

2004-01-01

The meta-regression analysis reveals that there is a strong tendency for discrimination estimates to fall and wage discrimination exist against the woman. The biasing effect of researchers' gender of not correcting for selection bias has weakened and changes in labor market have made it less important.
Local kernel nonparametric discriminant analysis for adaptive extraction of complex structures

NASA Astrophysics Data System (ADS)

Li, Quanbao; Wei, Fajie; Zhou, Shenghan

2017-05-01

The linear discriminant analysis (LDA) is one of popular means for linear feature extraction. It usually performs well when the global data structure is consistent with the local data structure. Other frequently-used approaches of feature extraction usually require linear, independence, or large sample condition. However, in real world applications, these assumptions are not always satisfied or cannot be tested. In this paper, we introduce an adaptive method, local kernel nonparametric discriminant analysis (LKNDA), which integrates conventional discriminant analysis with nonparametric statistics. LKNDA is adept in identifying both complex nonlinear structures and the ad hoc rule. Six simulation cases demonstrate that LKNDA have both parametric and nonparametric algorithm advantages and higher classification accuracy. Quartic unilateral kernel function may provide better robustness of prediction than other functions. LKNDA gives an alternative solution for discriminant cases of complex nonlinear feature extraction or unknown feature extraction. At last, the application of LKNDA in the complex feature extraction of financial market activities is proposed.
Interactions between cadmium and decabrominated diphenyl ether on blood cells count in rats-Multiple factorial regression analysis.

PubMed

Curcic, Marijana; Buha, Aleksandra; Stankovic, Sanja; Milovanovic, Vesna; Bulat, Zorica; Đukić-Ćosić, Danijela; Antonijević, Evica; Vučinić, Slavica; Matović, Vesna; Antonijevic, Biljana

2017-02-01

The objective of this study was to assess toxicity of Cd and BDE-209 mixture on haematological parameters in subacutely exposed rats and to determine the presence and type of interactions between these two chemicals using multiple factorial regression analysis. Furthermore, for the assessment of interaction type, an isobologram based methodology was applied and compared with multiple factorial regression analysis. Chemicals were given by oral gavage to the male Wistar rats weighing 200-240g for 28days. Animals were divided in 16 groups (8/group): control vehiculum group, three groups of rats were treated with 2.5, 7.5 or 15mg Cd/kg/day. These doses were chosen on the bases of literature data and reflect relatively high Cd environmental exposure, three groups of rats were treated with 1000, 2000 or 4000mg BDE-209/kg/bw/day, doses proved to induce toxic effects in rats. Furthermore, nine groups of animals were treated with different mixtures of Cd and BDE-209 containing doses of Cd and BDE-209 stated above. Blood samples were taken at the end of experiment and red blood cells, white blood cells and platelets counts were determined. For interaction assessment multiple factorial regression analysis and fitted isobologram approach were used. In this study, we focused on multiple factorial regression analysis as a method for interaction assessment. We also investigated the interactions between Cd and BDE-209 by the derived model for the description of the obtained fitted isobologram curves. Current study indicated that co-exposure to Cd and BDE-209 can result in significant decrease in RBC count, increase in WBC count and decrease in PLT count, when compared with controls. Multiple factorial regression analysis used for the assessment of interactions type between Cd and BDE-209 indicated synergism for the effect on RBC count and no interactions i.e. additivity for the effects on WBC and PLT counts. On the other hand, isobologram based approach showed slight antagonism
Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

NASA Astrophysics Data System (ADS)

Kurniawan, Dian; Suparti; Sugito

2018-05-01

Population growth in Indonesia has increased every year. According to the population census conducted by the Central Bureau of Statistics (BPS) in 2010, the population of Indonesia has reached 237.6 million people. Therefore, to control the population growth rate, the government hold Family Planning or Keluarga Berencana (KB) program for couples of childbearing age. The purpose of this program is to improve the health of mothers and children in order to manifest prosperous society by controlling births while ensuring control of population growth. The data used in this study is the updated family data of Semarang city in 2016 that conducted by National Family Planning Coordinating Board (BKKBN). From these data, classifiers with kernel discriminant analysis will be obtained, and also classification accuracy will be obtained from that method. The result of the analysis showed that normal kernel discriminant analysis gives 71.05 % classification accuracy with 28.95 % classification error. Whereas triweight kernel discriminant analysis gives 73.68 % classification accuracy with 26.32 % classification error. Using triweight kernel discriminant for data preprocessing of family planning participation of childbearing age couples in Semarang City of 2016 can be stated better than with normal kernel discriminant.
The effect of perceived discrimination on the health of immigrant workers in Spain

PubMed Central

2011-01-01

Background Discrimination is an important determinant of health inequalities, and immigrants may be more vulnerable to certain types of discrimination than the native-born. This study analyses the relationship between immigrants' perceived discrimination and various self-reported health indicators. Methods A cross-sectional survey was conducted (2008) amongst a non-random sample of 2434 immigrants from Ecuador, Morocco, Romania and Colombia in four Spanish cities: Barcelona, Huelva, Madrid and Valencia. A factorial analysis of variables revealed three dimensions of perceived discrimination (due to immigrant status, due to physical appearance, and workplace-related). The association of these dimensions with self-rated health, mental health (GHQ-12), change in self-rated health between origin and host country, and other self-reported health outcomes was analysed. Logistic regression was used adjusting for potential confounders (aOR-95%CI). Subjects with worsening self-reported health status potentially attributable to perceived discrimination was estimated (population attributable proportion, PAP %). Results 73.3% of men and 69.3% of women immigrants reported discrimination due to immigrant status. Moroccans showed the highest prevalence of perceived discrimination. Immigrants reporting discrimination were at significantly higher risk of reporting health problems than those not reporting discrimination. Workplace-related discrimination was associated with poor mental health (aOR 2.97 95%CI 2.45-3.60), and the worsening of self-rated health (aOR 2.20 95%CI 1.73- 2.80). 40% (95% CI 24-53) PAP of those reporting worse self-rated health could be attributable to discrimination due to immigrant status. Conclusions Discrimination may constitute a risk factor for health in immigrant workers in Spain and could explain some health inequalities among immigrant populations in Spanish society. PMID:21849020
Linear discriminant analysis with misallocation in training samples

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator); Mckeon, J.

1982-01-01

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.
[Discrimination of Red Tide algae by fluorescence spectra and principle component analysis].

PubMed

Su, Rong-guo; Hu, Xu-peng; Zhang, Chuan-song; Wang, Xiu-lin

2007-07-01

Fluorescence discrimination technology for 11 species of the Red Tide algae at genus level was constructed by principle component analysis and non-negative least squares. Rayleigh and Raman scattering peaks of 3D fluorescence spectra were eliminated by Delaunay triangulation method. According to the results of Fisher linear discrimination, the first principle component score and the second component score of 3D fluorescence spectra were chosen as discriminant feature and the feature base was established. The 11 algae species were tested, and more than 85% samples were accurately determinated, especially for Prorocentrum donghaiense, Skeletonema costatum, Gymnodinium sp., which have frequently brought Red tide in the East China Sea. More than 95% samples were right discriminated. The results showed that the genus discriminant feature of 3D fluorescence spectra of Red Tide algae given by principle component analysis could work well.
Spatial-temporal discriminant analysis for ERP-based brain-computer interface.

PubMed

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

2013-03-01

Linear discriminant analysis (LDA) has been widely adopted to classify event-related potential (ERP) in brain-computer interface (BCI). Good classification performance of the ERP-based BCI usually requires sufficient data recordings for effective training of the LDA classifier, and hence a long system calibration time which however may depress the system practicability and cause the users resistance to the BCI system. In this study, we introduce a spatial-temporal discriminant analysis (STDA) to ERP classification. As a multiway extension of the LDA, the STDA method tries to maximize the discriminant information between target and nontarget classes through finding two projection matrices from spatial and temporal dimensions collaboratively, which reduces effectively the feature dimensionality in the discriminant analysis, and hence decreases significantly the number of required training samples. The proposed STDA method was validated with dataset II of the BCI Competition III and dataset recorded from our own experiments, and compared to the state-of-the-art algorithms for ERP classification. Online experiments were additionally implemented for the validation. The superior classification performance in using few training samples shows that the STDA is effective to reduce the system calibration time and improve the classification accuracy, thereby enhancing the practicability of ERP-based BCI.
Some observations on the use of discriminant analysis in ecology

USGS Publications Warehouse

Williams, B.K.

1983-01-01

The application of discriminant analysis in ecological investigations is discussed. The appropriate statistical assumptions for discriminant analysis are illustrated, and both classification and group separation approaches are outlined. Three assumptions that are crucial in ecological studies are discussed at length, and the consequences of their violation are developed. These assumptions are: equality of dispersions, identifiability of prior probabilities, and precise and accurate estimation of means and dispersions. The use of discriminant functions for purposes of interpreting ecological relationships is also discussed. It is suggested that the common practice of imputing ecological 'meaning' to the signs and magnitudes of coefficients be replaced by an assessment of 'structure coefficients.' Finally, the potential and limitations of representation of data in canonical space are considered, and some cautionary points are made concerning ecological interpretation of patterns in canonical space.
Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

NASA Astrophysics Data System (ADS)

Nasution, D. H.; Bangun, P.; Sitepu, H. R.

2018-04-01

In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.
Sequential Ideal-Observer Analysis of Visual Discriminations.

ERIC Educational Resources Information Center

Geisler, Wilson S.

1989-01-01

A new analysis, based on the concept of the ideal observer in signal detection theory, is described. It allows: tracing of the flow of discrimination information through the initial physiological stages of visual processing for arbitrary spatio-chromatic stimuli, and measurement of the information content of said visual stimuli. (TJH)
Feature extraction with deep neural networks by a generalized discriminant analysis.

PubMed

Stuhlsatz, André; Lippel, Jens; Zielke, Thomas

2012-04-01

We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used.
Real-time image annotation by manifold-based biased Fisher discriminant analysis

NASA Astrophysics Data System (ADS)

Ji, Rongrong; Yao, Hongxun; Wang, Jicheng; Sun, Xiaoshuai; Liu, Xianming

2008-01-01

Automatic Linguistic Annotation is a promising solution to bridge the semantic gap in content-based image retrieval. However, two crucial issues are not well addressed in state-of-art annotation algorithms: 1. The Small Sample Size (3S) problem in keyword classifier/model learning; 2. Most of annotation algorithms can not extend to real-time online usage due to their low computational efficiencies. This paper presents a novel Manifold-based Biased Fisher Discriminant Analysis (MBFDA) algorithm to address these two issues by transductive semantic learning and keyword filtering. To address the 3S problem, Co-Training based Manifold learning is adopted for keyword model construction. To achieve real-time annotation, a Bias Fisher Discriminant Analysis (BFDA) based semantic feature reduction algorithm is presented for keyword confidence discrimination and semantic feature reduction. Different from all existing annotation methods, MBFDA views image annotation from a novel Eigen semantic feature (which corresponds to keywords) selection aspect. As demonstrated in experiments, our manifold-based biased Fisher discriminant analysis annotation algorithm outperforms classical and state-of-art annotation methods (1.K-NN Expansion; 2.One-to-All SVM; 3.PWC-SVM) in both computational time and annotation accuracy with a large margin.
[Comparison of Discriminant Analysis and Decision Trees for the Detection of Subclinical Keratoconus].

PubMed

Kleinhans, Sonja; Herrmann, Eva; Kohnen, Thomas; Bühren, Jens

2017-08-15

Background Iatrogenic keratectasia is one of the most dreaded complications of refractive surgery. In most cases, keratectasia develops after refractive surgery of eyes suffering from subclinical stages of keratoconus with few or no signs. Unfortunately, there has been no reliable procedure for the early detection of keratoconus. In this study, we used binary decision trees (recursive partitioning) to assess their suitability for discrimination between normal eyes and eyes with subclinical keratoconus. Patients and Methods The method of decision tree analysis was compared with discriminant analysis which has shown good results in previous studies. Input data were 32 eyes of 32 patients with newly diagnosed keratoconus in the contralateral eye and preoperative data of 10 eyes of 5 patients with keratectasia after laser in-situ keratomileusis (LASIK). The control group was made up of 245 normal eyes after LASIK and 12-month follow-up without any signs of iatrogenic keratectasia. Results Decision trees gave better accuracy and specificity than did discriminant analysis. The sensitivity of decision trees was lower than the sensitivity of discriminant analysis. Conclusion On the basis of the patient population of this study, decision trees did not prove to be superior to linear discriminant analysis for the detection of subclinical keratoconus. Georg Thieme Verlag KG Stuttgart · New York.
Radiative Penguin Decays at the B Factories

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

Koneke, Karsten; /MIT, LNS

2007-11-16

In this article, I review the most recent results in radiative penguin decays from the B factories Belle and BABAR. Most notably, I will talk about the recent new observations in the decays B {yields} ({rho}/{omega}) {gamma}, a new analysis technique in b {yields} s{gamma}, and first measurements of radiative penguin decays in the B{sup 0}{sub s} meson system. Finally, I will summarize the current status and future prospects of radiative penguin B physics at the B factories.
Factorial analysis of trihalomethanes formation in drinking water.

PubMed

Chowdhury, Shakhawat; Champagne, Pascale; McLellan, P James

2010-06-01

Disinfection of drinking water reduces pathogenic infection, but may pose risks to human health through the formation of disinfection byproducts. The effects of different factors on the formation of trihalomethanes were investigated using a statistically designed experimental program, and a predictive model for trihalomethanes formation was developed. Synthetic water samples with different factor levels were produced, and trihalomethanes concentrations were measured. A replicated fractional factorial design with center points was performed, and significant factors were identified through statistical analysis. A second-order trihalomethanes formation model was developed from 92 experiments, and the statistical adequacy was assessed through appropriate diagnostics. This model was validated using additional data from the Drinking Water Surveillance Program database and was applied to the Smiths Falls water supply system in Ontario, Canada. The model predictions were correlated strongly to the measured trihalomethanes, with correlations of 0.95 and 0.91, respectively. The resulting model can assist in analyzing risk-cost tradeoffs in the design and operation of water supply systems.
Factory daughters, the family, and nuptiality in Java.

PubMed

Wolf, D L

1990-01-01

The commercialization of agriculture, increasing landlessness, and an expanding labor class in rural areas of Java are all the result of industrialization. This work discusses the effect of female employment on marriage patterns of women working in rural factories. The central point is that employment has not only increased the financial autonomy of these women, but also increased the level of control they have over the choice of marriage partners. The data set used for analysis consisted of the observations of all factory workers and all non-factory females age 15-24 located in an agricultural village. The observations were make over a 15 month period between 1981-83. A follow up visit was made in 1986 and the following conclusions were then made: 1) the village study gave detailed data, but the data set was not large enough, thus a follow up study that encompasses more people is called for; 2) young rural female factory workers are more likely to chose their marriage partners than those engaged in traditional village labor. Of those that married and worked in factories, their fertility rate was significantly lower, compared to non-factory workers. Factory workers also had different family structures, because they spent less time living in extended families because of a larger income for the couple. This study indicates that increased economic control results in increased life decision control. This changed the daughter's economic relationship with her family and gives her more control in marriage decisions.
Discrimination against Latina/os: A Meta-Analysis of Individual-Level Resources and Outcomes

ERIC Educational Resources Information Center

Lee, Debbiesiu L.; Ahn, Soyeon

2012-01-01

This meta-analysis synthesizes the findings of 60 independent samples from 51 studies examining racial/ethnic discrimination against Latina/os in the United States. The purpose was to identify individual-level resources and outcomes that most strongly relate to discrimination. Discrimination against Latina/os significantly results in outcomes…
Making Connections: After the Factories Revisited.

ERIC Educational Resources Information Center

Rosenfeld, Stuart A.; Bergman, Edward M.

This analysis of employment patterns in the American South extends a 1985 report, "After the Factories: Changing Employment Patterns in the Rural South," which was based on the years between 1977-1982. The 1985 report included Texas, but this analysis includes only the 12 Southern Growth Policies Board (SGPB) member states. This new…

Comparison of discriminant analysis methods: Application to occupational exposure to particulate matter

NASA Astrophysics Data System (ADS)

Ramos, M. Rosário; Carolino, E.; Viegas, Carla; Viegas, Sandra

2016-06-01

Health effects associated with occupational exposure to particulate matter have been studied by several authors. In this study were selected six industries of five different areas: Cork company 1, Cork company 2, poultry, slaughterhouse for cattle, riding arena and production of animal feed. The measurements tool was a portable device for direct reading. This tool provides information on the particle number concentration for six different diameters, namely 0.3 µm, 0.5 µm, 1 µm, 2.5 µm, 5 µm and 10 µm. The focus on these features is because they might be more closely related with adverse health effects. The aim is to identify the particles that better discriminate the industries, with the ultimate goal of classifying industries regarding potential negative effects on workers' health. Several methods of discriminant analysis were applied to data of occupational exposure to particulate matter and compared with respect to classification accuracy. The selected methods were linear discriminant analyses (LDA); linear quadratic discriminant analysis (QDA), robust linear discriminant analysis with selected estimators (MLE (Maximum Likelihood Estimators), MVE (Minimum Volume Elipsoid), "t", MCD (Minimum Covariance Determinant), MCD-A, MCD-B), multinomial logistic regression and artificial neural networks (ANN). The predictive accuracy of the methods was accessed through a simulation study. ANN yielded the highest rate of classification accuracy in the data set under study. Results indicate that the particle number concentration of diameter size 0.5 µm is the parameter that better discriminates industries.
Spectral Regression Discriminant Analysis for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Pan, Y.; Wu, J.; Huang, H.; Liu, J.

2012-08-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learning methods are popular for dimensionality reduction, such as Locally Linear Embedding, Isomap, and Laplacian Eigenmap. However, a disadvantage of many manifold learning methods is that their computations usually involve eigen-decomposition of dense matrices which is expensive in both time and memory. In this paper, we introduce a new dimensionality reduction method, called Spectral Regression Discriminant Analysis (SRDA). SRDA casts the problem of learning an embedding function into a regression framework, which avoids eigen-decomposition of dense matrices. Also, with the regression based framework, different kinds of regularizes can be naturally incorporated into our algorithm which makes it more flexible. It can make efficient use of data points to discover the intrinsic discriminant structure in the data. Experimental results on Washington DC Mall and AVIRIS Indian Pines hyperspectral data sets demonstrate the effectiveness of the proposed method.
[Phoneme analysis and phoneme discrimination of juvenile speech therapy school students].

PubMed

Franz, S; Rosanowski, F; Eysholdt, U; Hoppe, U

2011-05-01

Phoneme analysis and phoneme discrimination, important factors in acquiring spoken and written language, have been evaluated in juvenile speech therapy school students. The results have been correlated with the results of a school achievement test. The following questions were of interest: Do students in the lower verbal skill segment show pathological phoneme analysis and phoneme discrimination skills? Do the results of the school achievement test differ from the results by students visiting German "Hauptschule"? How does phoneme analysis and phoneme discrimination performance correlate to other tested parameters? 74 students of a speech therapy school ranging from 7 (th) to 9 (th) grade were examined (ages 12;10-17;04) with the Heidelberg Phoneme Discrimination Test H-LAD and the school achievement test "Prüfsystem für Schul- und Bildungsberatung PSB-R 6-13". Compared to 4 (th) graders the juvenile speech therapy school students showed worse results in the H-LAD test with good differentiation in the lower measuring range. In the PSB-R 6-13 test the examined students did worse compared to students visiting German "Hauptschule" for all grades except 9 (th) grade. Comparing H-LAD and PSB-R 6-13 shows a significant correlation for the sub-tests covering language competence and intelligence but not for the concentration tests. Pathological phoneme analysis and phoneme discrimination skills suggest elevated need for counseling, but this needs to corroborated through additional linguistic parameters and measuring non-verbal intelligence. Further trails are needed in order to clarify whether the results can lead to sophisticated therapy algorithms for educational purposes. © Georg Thieme Verlag KG Stuttgart · New York.
Manufacturing data analytics using a virtual factory representation.

PubMed

Jain, Sanjay; Shao, Guodong; Shin, Seung-Jun

2017-01-01

Large manufacturers have been using simulation to support decision-making for design and production. However, with the advancement of technologies and the emergence of big data, simulation can be utilised to perform and support data analytics for associated performance gains. This requires not only significant model development expertise, but also huge data collection and analysis efforts. This paper presents an approach within the frameworks of Design Science Research Methodology and prototyping to address the challenge of increasing the use of modelling, simulation and data analytics in manufacturing via reduction of the development effort. The use of manufacturing simulation models is presented as data analytics applications themselves and for supporting other data analytics applications by serving as data generators and as a tool for validation. The virtual factory concept is presented as the vehicle for manufacturing modelling and simulation. Virtual factory goes beyond traditional simulation models of factories to include multi-resolution modelling capabilities and thus allowing analysis at varying levels of detail. A path is proposed for implementation of the virtual factory concept that builds on developments in technologies and standards. A virtual machine prototype is provided as a demonstration of the use of a virtual representation for manufacturing data analytics.
Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

ERIC Educational Resources Information Center

Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan

2016-01-01

Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…
Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.
Enamel surface topography analysis for diet discrimination. A methodology to enhance and select discriminative parameters

NASA Astrophysics Data System (ADS)

Francisco, Arthur; Blondel, Cécile; Brunetière, Noël; Ramdarshan, Anusha; Merceron, Gildas

2018-03-01

Tooth wear and, more specifically, dental microwear texture is a dietary proxy that has been used for years in vertebrate paleoecology and ecology. DMTA, dental microwear texture analysis, relies on a few parameters related to the surface complexity, anisotropy and heterogeneity of the enamel facets at the micrometric scale. Working with few but physically meaningful parameters helps in comparing published results and in defining levels for classification purposes. Other dental microwear approaches are based on ISO parameters and coupled with statistical tests to find the more relevant ones. The present study roughly utilizes most of the aforementioned parameters in their more or less modified form. But more than parameters, we here propose a new approach: instead of a single parameter characterizing the whole surface, we sample the surface and thus generate 9 derived parameters in order to broaden the parameter set. The identification of the most discriminative parameters is performed with an automated procedure which is an extended and refined version of the workflows encountered in some studies. The procedure in its initial form includes the most common tools, like the ANOVA and the correlation analysis, along with the required mathematical tests. The discrimination results show that a simplified form of the procedure is able to more efficiently identify the desired number of discriminative parameters. Also highlighted are some trends like the relevance of working with both height and spatial parameters, as well as the potential benefits of dimensionless surfaces. On a set of 45 surfaces issued from 45 specimens of three modern ruminants with differences in feeding preferences (grazing, leaf-browsing and fruit-eating), it is clearly shown that the level of wear discrimination is improved with the new methodology compared to the other ones.
Discriminative factor analysis of juvenile delinquency in South Korea.

PubMed

Kim, Hyun Sil; Kim, Hun Soo

2006-12-01

The present study was intended to compare difference in research variables between delinquent adolescents and student adolescents, and to analyze discriminative factors of delinquent behaviors among Korean adolescents. The research design of this study was a questionnaire survey. Questionnaires were administered to 2,167 adolescents (1,196 students and 971 delinquents), sampled from 8 middle and high school and 6 juvenile corrective institutions, using the proportional stratified random sampling method. Statistical methods employed were Chi-square, t-test, and logistic regression analysis. The discriminative factors of delinquent behaviors were smoking, alcohol use, other drug use, being sexually abused, viewing time of media violence and pornography. Among these discriminative factors, the factor most strongly associated with delinquency was smoking (odds ratio: 32.32). That is, smoking adolescent has a 32-fold higher possibility of becoming a delinquent adolescent than a non-smoking adolescent. Our findings, that smoking was the strongest discriminative factor of delinquent behavior, suggest that educational strategies to prevent adolescent smoking may reduce the rate of juvenile delinquency. Antismoking educational efforts are therefore urgently needed in South Korea.
Harassment and discrimination in medical training: a systematic review and meta-analysis.

PubMed

Fnais, Naif; Soobiah, Charlene; Chen, Maggie Hong; Lillie, Erin; Perrier, Laure; Tashkhandi, Mariam; Straus, Sharon E; Mamdani, Muhammad; Al-Omran, Mohammed; Tricco, Andrea C

2014-05-01

Harassment and discrimination include a wide range of behaviors that medical trainees perceive as being humiliating, hostile, or abusive. To understand the significance of such mistreatment and to explore potential preventive strategies, the authors conducted a systematic review and meta-analysis to examine the prevalence, risk factors, and sources of harassment and discrimination among medical trainees. In 2011, the authors identified relevant studies by searching MEDLINE and EMBASE, scanning reference lists of relevant studies, and contacting experts. They included studies that reported the prevalence, risk factors, and sources of harassment and discrimination among medical trainees. Two reviewers independently screened all articles and abstracted study and participant characteristics and study results. The authors assessed the methodological quality in individual studies using the Newcastle-Ottawa Scale. They also conducted a meta-analysis. The authors included 57 cross-sectional and 2 cohort studies in their review. The meta-analysis of 51 studies demonstrated that 59.4% of medical trainees had experienced at least one form of harassment or discrimination during their training (95% confidence interval [CI]: 52.0%-66.7%). Verbal harassment was the most commonly cited form of harassment (prevalence: 63.0%; 95% CI: 54.8%-71.2%). Consultants were the most commonly cited source of harassment and discrimination, followed by patients or patients' families (34.4% and 21.9%, respectively). This review demonstrates the surprisingly high prevalence of harassment and discrimination among medical trainees that has not declined over time. The authors recommend both drafting policies and promoting cultural change within academic institutions to prevent future abuse.
Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

PubMed

Cao, Longlong; Guo, Shuixia; Xue, Zhimin; Hu, Yong; Liu, Haihong; Mwansisya, Tumbwene E; Pu, Weidan; Yang, Bo; Liu, Chang; Feng, Jianfeng; Chen, Eric Y H; Liu, Zhening

2014-02-01

Aberrant brain functional connectivity patterns have been reported in major depressive disorder (MDD). It is unknown whether they can be used in discriminant analysis for diagnosis of MDD. In the present study we examined the efficiency of discriminant analysis of MDD by individualized computer-assisted diagnosis. Based on resting-state functional magnetic resonance imaging data, a new approach was adopted to investigate functional connectivity changes in 39 MDD patients and 37 well-matched healthy controls. By using the proposed feature selection method, we identified significant altered functional connections in patients. They were subsequently applied to our analysis as discriminant features using a support vector machine classification method. Furthermore, the relative contribution of functional connectivity was estimated. After subset selection of high-dimension features, the support vector machine classifier reached up to approximately 84% with leave-one-out training during the discrimination process. Through summarizing the classification contribution of functional connectivities, we obtained four obvious contribution modules: inferior orbitofrontal module, supramarginal gyrus module, inferior parietal lobule-posterior cingulated gyrus module and middle temporal gyrus-inferior temporal gyrus module. The experimental results demonstrated that the proposed method is effective in discriminating MDD patients from healthy controls. Functional connectivities might be useful as new biomarkers to assist clinicians in computer auxiliary diagnosis of MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.
Operating a production pilot factory serving several scientific domains

NASA Astrophysics Data System (ADS)

Sfiligoi, I.; Würthwein, F.; Andrews, W.; Dost, J. M.; MacNeill, I.; McCrea, A.; Sheripon, E.; Murphy, C. W.

2011-12-01

Pilot infrastructures are becoming prominent players in the Grid environment. One of the major advantages is represented by the reduced effort required by the user communities (also known as Virtual Organizations or VOs) due to the outsourcing of the Grid interfacing services, i.e. the pilot factory, to Grid experts. One such pilot factory, based on the glideinWMS pilot infrastructure, is being operated by the Open Science Grid at University of California San Diego (UCSD). This pilot factory is serving multiple VOs from several scientific domains. Currently the three major clients are the analysis operations of the HEP experiment CMS, the community VO HCC, which serves mostly math, biology and computer science users, and the structural biology VO NEBioGrid. The UCSD glidein factory allows the served VOs to use Grid resources distributed over 150 sites in North and South America, in Europe, and in Asia. This paper presents the steps taken to create a production quality pilot factory, together with the challenges encountered along the road.
Robust L1-norm two-dimensional linear discriminant analysis.

PubMed

Li, Chun-Na; Shao, Yuan-Hai; Deng, Nai-Yang

2015-05-01

In this paper, we propose an L1-norm two-dimensional linear discriminant analysis (L1-2DLDA) with robust performance. Different from the conventional two-dimensional linear discriminant analysis with L2-norm (L2-2DLDA), where the optimization problem is transferred to a generalized eigenvalue problem, the optimization problem in our L1-2DLDA is solved by a simple justifiable iterative technique, and its convergence is guaranteed. Compared with L2-2DLDA, our L1-2DLDA is more robust to outliers and noises since the L1-norm is used. This is supported by our preliminary experiments on toy example and face datasets, which show the improvement of our L1-2DLDA over L2-2DLDA. Copyright © 2015 Elsevier Ltd. All rights reserved.
Robust linear discriminant analysis with distance based estimators

NASA Astrophysics Data System (ADS)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina

2017-11-01

Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.
Sequence Factorial and Its Applications

ERIC Educational Resources Information Center

Asiru, Muniru A.

2012-01-01

In this note, we introduce sequence factorial and use this to study generalized M-bonomial coefficients. For the sequence of natural numbers, the twin concepts of sequence factorial and generalized M-bonomial coefficients, respectively, extend the corresponding concepts of factorial of an integer and binomial coefficients. Some latent properties…
Plant Factory

NASA Astrophysics Data System (ADS)

Ikeda, Hideo

Recently, much attention is paid on the plant factory, as it enable to grow plants stably under extraordinary climate condition such as high and/or low air temperature and less rain. Lots of questions such as decreasing investing cost, realizing stable plant production and developing new growing technique should be solved for making popular this growing system. However, I think that we can introduce a highly developed Japanese industrial now-how to plant factory system and can produce a business chance to the world market.
Discriminant Analysis of Time Series in the Presence of Within-Group Spectral Variability.

PubMed

Krafty, Robert T

2016-07-01

Many studies record replicated time series epochs from different groups with the goal of using frequency domain properties to discriminate between the groups. In many applications, there exists variation in cyclical patterns from time series in the same group. Although a number of frequency domain methods for the discriminant analysis of time series have been explored, there is a dearth of models and methods that account for within-group spectral variability. This article proposes a model for groups of time series in which transfer functions are modeled as stochastic variables that can account for both between-group and within-group differences in spectra that are identified from individual replicates. An ensuing discriminant analysis of stochastic cepstra under this model is developed to obtain parsimonious measures of relative power that optimally separate groups in the presence of within-group spectral variability. The approach possess favorable properties in classifying new observations and can be consistently estimated through a simple discriminant analysis of a finite number of estimated cepstral coefficients. Benefits in accounting for within-group spectral variability are empirically illustrated in a simulation study and through an analysis of gait variability.
A Computational Discriminability Analysis on Twin Fingerprints

NASA Astrophysics Data System (ADS)

Liu, Yu; Srihari, Sargur N.

Sharing similar genetic traits makes the investigation of twins an important study in forensics and biometrics. Fingerprints are one of the most commonly found types of forensic evidence. The similarity between twins’ prints is critical establish to the reliability of fingerprint identification. We present a quantitative analysis of the discriminability of twin fingerprints on a new data set (227 pairs of identical twins and fraternal twins) recently collected from a twin population using both level 1 and level 2 features. Although the patterns of minutiae among twins are more similar than in the general population, the similarity of fingerprints of twins is significantly different from that between genuine prints of the same finger. Twins fingerprints are discriminable with a 1.5%~1.7% higher EER than non-twins. And identical twins can be distinguished by examine fingerprint with a slightly higher error rate than fraternal twins.
[Discriminant Analysis of Lavender Essential Oil by Attenuated Total Reflectance Infrared Spectroscopy].

PubMed

Tang, Jun; Wang, Qing; Tong, Hong; Liao, Xiang; Zhang, Zheng-fang

2016-03-01

This work aimed to use attenuated total reflectance Fourier transform infrared spectroscopy to identify the lavender essential oil by establishing a Lavender variety and quality analysis model. So, 96 samples were tested. For all samples, the raw spectra were pretreated as second derivative, and to determine the 1 750-900 cm(-1) wavelengths for pattern recognition analysis on the basis of the variance calculation. The results showed that principal component analysis (PCA) can basically discriminate lavender oil cultivar and the first three principal components mainly represent the ester, alcohol and terpenoid substances. When the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was established, the 68 samples were used for the calibration set. Determination coefficients of OPLS-DA regression curve were 0.959 2, 0.976 4, and 0.958 8 respectively for three varieties of lavender essential oil. Three varieties of essential oil's the root mean square error of prediction (RMSEP) in validation set were 0.142 9, 0.127 3, and 0.124 9, respectively. The discriminant rate of calibration set and the prediction rate of validation set had reached 100%. The model has the very good recognition capability to detect the variety and quality of lavender essential oil. The result indicated that a model which provides a quick, intuitive and feasible method had been built to discriminate lavender oils.
Neutrino factory

DOE PAGES

Bogomilov, M.; Matev, R.; Tsenov, R.; ...

2014-12-08

The properties of the neutrino provide a unique window on physics beyond that described by the standard model. The study of subleading effects in neutrino oscillations, and the race to discover CP-invariance violation in the lepton sector, has begun with the recent discovery that theta(13) > 0. The measured value of theta(13) is large, emphasizing the need for a facility at which the systematic uncertainties can be reduced to the percent level. The neutrino factory, in which intense neutrino beams are produced from the decay of muons, has been shown to outperform all realistic alternatives and to be capable ofmore » making measurements of the requisite precision. Its unique discovery potential arises from the fact that only at the neutrino factory is it practical to produce high-energy electron (anti) neutrino beams of the required intensity. This paper presents the conceptual design of the neutrino factory accelerator facility developed by the European Commission Framework Programme 7 EURO nu. Design Study consortium. EURO nu coordinated the European contributions to the International Design Study for the Neutrino Factory (the IDS-NF) collaboration. The EURO nu baseline accelerator facility will provide 10(21) muon decays per year from 12.6 GeV stored muon beams serving a single neutrino detector situated at a source-detector distance of between 1 500 km and 2 500 km. A suite of near detectors will allow definitive neutrino-scattering experiments to be performed.« less
Discrimination of red and white rice bran from Indonesia using HPLC fingerprint analysis combined with chemometrics.

PubMed

Sabir, Aryani; Rafi, Mohamad; Darusman, Latifah K

2017-04-15

HPLC fingerprint analysis combined with chemometrics was developed to discriminate between the red and the white rice bran grown in Indonesia. The major component in rice bran is γ-oryzanol which consisted of 4 main compounds, namely cycloartenol ferulate, cyclobranol ferulate, campesterol ferulate and β-sitosterol ferulate. Separation of these four compounds along with other compounds was performed using C18 and methanol-acetonitrile with gradient elution system. By using these intensity variations, principal component and discriminant analysis were performed to discriminate the two samples. Discriminant analysis was successfully discriminated the red from the white rice bran with predictive ability of the model showed a satisfactory classification for the test samples. The results of this study indicated that the developed method was suitable as quality control method for rice bran in terms of identification and discrimination of the red and the white rice bran. Copyright © 2016 Elsevier Ltd. All rights reserved.

Discriminant function analysis as tool for subsurface geologist

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

Chesser, K.

1987-05-01

Sedimentary structures such as cross-bedding control porosity, permeability, and other petrophysical properties in sandstone reservoirs. Understanding the distribution of such structures in the subsurface not only aids in the prediction of reservoir properties but also provides information about depositional environments. Discriminant function analysis (DFA) is a simple yet powerful method incorporating petrophysical data from wireline logs, core analyses, or other sources into groups that have been previously defined through direct observation of sedimentary structures in cores. Once data have been classified into meaningful groups, the geologist can predict the distribution of specific sedimentary structures or important reservoir properties in areasmore » where cores are unavailable. DFA is efficient. Given several variables, DFA will choose the best combination to discriminate among groups. The initial classification function can be computed from relatively few observations, and additional data may be included as necessary. Furthermore, DFA provides quantitative goodness-of-fit estimates for each observation. Such estimates can be used as mapping parameters or to assess risk in petroleum ventures. Petrophysical data from the Skinner sandstone of Strauss field in southeastern Kansas tested the ability of DFA to discriminate between cross-bedded and ripple-bedded sandstones. Petroleum production in Strauss field is largely restricted to the more permeable cross-bedded sandstones. DFA based on permeability correctly placed 80% of samples into cross-bedded or ripple-bedded groups. Addition of formation factor to the discriminant function increased correct classifications to 83% - a small but statistically significant gain.« less
Synthesis and analysis of discriminators under influence of broadband non-Gaussian noise

NASA Astrophysics Data System (ADS)

Artyushenko, V. M.; Volovach, V. I.

2018-01-01

We considered the problems of the synthesis and analysis of discriminators, when the useful signal is exposed to non-Gaussian additive broadband noise. It is shown that in this case, the discriminator of the tracking meter should contain the nonlinear transformation unit, the characteristics of which are determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian broadband noise and mismatch errors. The parameters of the discriminatory and phase characteristics of the discriminators working under the above conditions are obtained. It is shown that the efficiency of non-linear processing depends on the ratio of power of FM noise to the power of Gaussian noise. The analysis of the information loss of signal transformation caused by the linear section of discriminatory characteristics of the unit of nonlinear transformations of the discriminator is carried out. It is shown that the average slope of the nonlinear transformation characteristic is determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian noise and mismatch errors.
Additive Factors Analysis of Inhibitory Processing in the Stop-Signal Paradigm

ERIC Educational Resources Information Center

van den Wildenberg, W.P.M.; van der Molen, M.W.

2004-01-01

This article reports an additive factors analysis of choice reaction and selective stop processes manipulated in a stop-signal paradigm. Three experiments were performed in which stimulus discriminability (SD) and stimulus-response compatibility (SRC) were manipulated in a factorial fashion. In each experiment, the effects of SD and SRC were…
Chemical Discrimination of Cortex Phellodendri amurensis and Cortex Phellodendri chinensis by Multivariate Analysis Approach.

PubMed

Sun, Hui; Wang, Huiyu; Zhang, Aihua; Yan, Guangli; Han, Ying; Li, Yuan; Wu, Xiuhong; Meng, Xiangcai; Wang, Xijun

2016-01-01

As herbal medicines have an important position in health care systems worldwide, their current assessment, and quality control are a major bottleneck. Cortex Phellodendri chinensis (CPC) and Cortex Phellodendri amurensis (CPA) are widely used in China, however, how to identify species of CPA and CPC has become urgent. In this study, multivariate analysis approach was performed to the investigation of chemical discrimination of CPA and CPC. Principal component analysis showed that two herbs could be separated clearly. The chemical markers such as berberine, palmatine, phellodendrine, magnoflorine, obacunone, and obaculactone were identified through the orthogonal partial least squared discriminant analysis, and were identified tentatively by the accurate mass of quadruple-time-of-flight mass spectrometry. A total of 29 components can be used as the chemical markers for discrimination of CPA and CPC. Of them, phellodenrine is significantly higher in CPC than that of CPA, whereas obacunone and obaculactone are significantly higher in CPA than that of CPC. The present study proves that multivariate analysis approach based chemical analysis greatly contributes to the investigation of CPA and CPC, and showed that the identified chemical markers as a whole should be used to discriminate the two herbal medicines, and simultaneously the results also provided chemical information for their quality assessment. Multivariate analysis approach was performed to the investigate the herbal medicineThe chemical markers were identified through multivariate analysis approachA total of 29 components can be used as the chemical markers. UPLC-Q/TOF-MS-based multivariate analysis method for the herbal medicine samples Abbreviations used: CPC: Cortex Phellodendri chinensis, CPA: Cortex Phellodendri amurensis, PCA: Principal component analysis, OPLS-DA: Orthogonal partial least squares discriminant analysis, BPI: Base peaks ion intensity.
A sequential factorial analysis approach to characterize the effects of uncertainties for supporting air quality management

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Veawab, A.

2013-03-01

This study proposes a sequential factorial analysis (SFA) approach for supporting regional air quality management under uncertainty. SFA is capable not only of examining the interactive effects of input parameters, but also of analyzing the effects of constraints. When there are too many factors involved in practical applications, SFA has the advantage of conducting a sequence of factorial analyses for characterizing the effects of factors in a systematic manner. The factor-screening strategy employed in SFA is effective in greatly reducing the computational effort. The proposed SFA approach is applied to a regional air quality management problem for demonstrating its applicability. The results indicate that the effects of factors are evaluated quantitatively, which can help decision makers identify the key factors that have significant influence on system performance and explore the valuable information that may be veiled beneath their interrelationships.
Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of LANDSAT digital data

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.
Discrimination of Cynanchum wilfordii and Cynanchum auriculatum by terahertz spectroscopic analysis.

PubMed

Ham, Woo Sik; Kim, Jinju; Park, Dae Joon; Ryu, Han-Cheol; Jang, Young Pyo

2018-02-12

Precise identification of botanical origin of plant species is crucial for the quality control of herbal medicine. In Korea, the root part of Cynanchum auriculatum has been misused for C. wilfordii in the herbal drug market due to their morphological similarities. Currently, DNA analysis using the polymerase chain reaction (PCR) method is employed to discriminate between these species. In order to develop a new analytical tool for the rapid discrimination of C. wilfordii and C. auriculatum, terahertz (THz) spectroscopy was employed. Authentic samples of C. wilfordii and C. auriculatum were provided from the National Institute and standardized pellets for each species were prepared to get optimum results with terahertz time-domain spectroscopy (THz-TDS) in frequency range 0.2-1.20 THz. The C. wilfordii pellet showed longer time delay compare to the sample of C. auriculatum and this was due to the difference in permittivity. The pellet samples of C. wilfordii and C. auriculatum showed a permittivity difference of about 0.08 at 0.2-1.20 THz. The experimental results indicated that THz-TDS analysis can be an effective and rapid method for the discrimination of C. wilfordii and C. auriculatum, and this application can be expanded for the discrimination of other similar herbal medicines. Copyright © 2018 John Wiley & Sons, Ltd.
Regional Moment Tensor Source-Type Discrimination Analysis

DTIC Science & Technology

2015-11-16

Research Laboratory Space Vehicles Directorate 3550 Aberdeen Avenue SE Kirtland AFB, NM 87117-5776 AFRL /RVBYE 11. SPONSOR/MONITOR’S REPORT...OCP 8725 John J. Kingman Rd, Suite 0944 Ft Belvoir, VA 22060-6218 1 cy AFRL /RVIL Kirtland AFB, NM 87117-5776 2 cys Official Record Copy... AFRL -RV-PS- AFRL -RV-PS- TR-2016-0014 TR-2016-0014 REGIONAL MOMENT TENSOR SOURCE-TYPE DISCRIMINATION ANALYSIS Douglas S. Dreger, et al
Social Status Correlates of Reporting Racial Discrimination and Gender Discrimination among Racially Diverse Women

PubMed Central

Ro, Annie E.; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in Northern California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design. PMID:19485231
Social status correlates of reporting gender discrimination and racial discrimination among racially diverse women.

PubMed

Ro, Annie E; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in North California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design.
In-Factory Learning - Qualification For The Factory Of The Future

NASA Astrophysics Data System (ADS)

Quint, Fabian; Mura, Katharina; Gorecky, Dominic

2015-07-01

The Industry 4.0 vision anticipates that internet technologies will find their way into future factories replacing traditional components by dynamic and intelligent cyber-physical systems (CPS) that combine the physical objects with their digital representation. Reducing the gap between the real and digital world makes the factory environment more flexible, more adaptive, but also more complex for the human workers. Future workers require interdisciplinary competencies from engineering, information technology, and computer science in order to understand and manage the diverse interrelations between physical objects and their digital counterpart. This paper proposes a mixed-reality based learning environment, which combines physical objects and visualisation of digital content via Augmented Reality. It uses reality-based interaction in order to make the dynamic interrelations between real and digital factory visible and tangible. We argue that our learning system does not work as a stand-alone solution, but should fit into existing academic and advanced training curricula.
Hierarchical Discriminant Analysis.

PubMed

Lu, Di; Ding, Chuntao; Xu, Jinliang; Wang, Shangguang

2018-01-18

The Internet of Things (IoT) generates lots of high-dimensional sensor intelligent data. The processing of high-dimensional data (e.g., data visualization and data classification) is very difficult, so it requires excellent subspace learning algorithms to learn a latent subspace to preserve the intrinsic structure of the high-dimensional data, and abandon the least useful information in the subsequent processing. In this context, many subspace learning algorithms have been presented. However, in the process of transforming the high-dimensional data into the low-dimensional space, the huge difference between the sum of inter-class distance and the sum of intra-class distance for distinct data may cause a bias problem. That means that the impact of intra-class distance is overwhelmed. To address this problem, we propose a novel algorithm called Hierarchical Discriminant Analysis (HDA). It minimizes the sum of intra-class distance first, and then maximizes the sum of inter-class distance. This proposed method balances the bias from the inter-class and that from the intra-class to achieve better performance. Extensive experiments are conducted on several benchmark face datasets. The results reveal that HDA obtains better performance than other dimensionality reduction algorithms.
Kin discrimination within honey bee (Apis mellifera) colonies: An analysis of the evidence.

PubMed

Breed, M D; Welch, C K; Cruz, R

1994-12-01

Compelling evolutionary arguments lead to the prediction that honey bee workers should discriminate between supersisters and half-sisters within colonies. We review the theoretical support for discrimination during swarming, queen rearing, feeding, and grooming. A survey of the data that tests whether such discrimination takes place shows that, despite substantial effort in a number of laboratories, there is no conclusive evidence for intracolony discrimination in any of the postulated contexts. The strongest suggestive data is in the critical context of queen rearing, but flaws in experimental design or analysis make the best available tests inconclusive. We present new data that shows that cues exist on which discriminations can be made among adult workers in nestmate recognition interactions and in feeding interactions, but our data does not differentiate between subfamily recognition and recognition associated with color phenotypes. We conclude that while selection may favor discrimination between supersisters and half-sisters, as a practical matter such discriminations play no role, or only a minor role, in the biology of the honey bee. Copyright © 1994. Published by Elsevier B.V.
Midlands Teaching Factory, LTD.

ERIC Educational Resources Information Center

Midlands Technical Coll., Columbia, SC.

In 1987, Midlands Technical College (MTC), in Columbia, South Carolina, initiated a Computer Integrated Manufacturing (CIM) project, the Midlands Teaching Factory, LTD, which integrated various college departments with the goal of manufacturing a high quality, saleable product. The faculty developed a teaching factory model which was designed to…
Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images

PubMed Central

Khansari, Maziyar M; O’Neill, William; Penn, Richard; Chau, Felix; Blair, Norman P; Shahidi, Mahnaz

2016-01-01

The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method’s discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring. PMID:27446692
Principal Component Analysis for pulse-shape discrimination of scintillation radiation detectors

NASA Astrophysics Data System (ADS)

Alharbi, T.

2016-01-01

In this paper, we report on the application of Principal Component analysis (PCA) for pulse-shape discrimination (PSD) of scintillation radiation detectors. The details of the method are described and the performance of the method is experimentally examined by discriminating between neutrons and gamma-rays with a liquid scintillation detector in a mixed radiation field. The performance of the method is also compared against that of the conventional charge-comparison method, demonstrating the superior performance of the method particularly at low light output range. PCA analysis has the important advantage of automatic extraction of the pulse-shape characteristics which makes the PSD method directly applicable to various scintillation detectors without the need for the adjustment of a PSD parameter.
Multi-class ERP-based BCI data analysis using a discriminant space self-organizing map.

PubMed

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

Emotional or non-emotional image stimulus is recently applied to event-related potential (ERP) based brain computer interfaces (BCI). Though the classification performance is over 80% in a single trial, a discrimination between those ERPs has not been considered. In this research we tried to clarify the discriminability of four-class ERP-based BCI target data elicited by desk, seal, spider images and letter intensifications. A conventional self organizing map (SOM) and newly proposed discriminant space SOM (ds-SOM) were applied, then the discriminabilites were visualized. We also classify all pairs of those ERPs by stepwise linear discriminant analysis (SWLDA) and verify the visualization of discriminabilities. As a result, the ds-SOM showed understandable visualization of the data with a shorter computational time than the traditional SOM. We also confirmed the clear boundary between the letter cluster and the other clusters. The result was coherent with the classification performances by SWLDA. The method might be helpful not only for developing a new BCI paradigm, but also for the big data analysis.
Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia) adhesion

PubMed Central

2010-01-01

Background The zebra mussel (Dreissena polymorpha) has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. Results In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A), current velocity (Factor B), dissolved oxygen (Factor C), and byssogenesis status (Factor D). Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR). The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. Conclusions The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment. PMID:20509938
The intersectionality of discrimination attributes and bullying among youth: an applied latent class analysis.

PubMed

Garnett, Bernice Raveche; Masyn, Katherine E; Austin, S Bryn; Miller, Matthew; Williams, David R; Viswanath, Kasisomayajula

2014-08-01

Discrimination is commonly experienced among adolescents. However, little is known about the intersection of multiple attributes of discrimination and bullying. We used a latent class analysis (LCA) to illustrate the intersections of discrimination attributes and bullying, and to assess the associations of LCA membership to depressive symptoms, deliberate self harm and suicidal ideation among a sample of ethnically diverse adolescents. The data come from the 2006 Boston Youth Survey where students were asked whether they had experienced discrimination based on four attributes: race/ethnicity, immigration status, perceived sexual orientation and weight. They were also asked whether they had been bullied or assaulted for these attributes. A total of 965 (78%) students contributed to the LCA analytic sample (45% Non-Hispanic Black, 29% Hispanic, 58% Female). The LCA revealed that a 4-class solution had adequate relative and absolute fit. The 4-classes were characterized as: low discrimination (51%); racial discrimination (33%); sexual orientation discrimination (7%); racial and weight discrimination with high bullying (intersectional class) (7%). In multivariate models, compared to the low discrimination class, individuals in the sexual orientation discrimination class and the intersectional class had higher odds of engaging in deliberate self-harm. Students in the intersectional class also had higher odds of suicidal ideation. All three discrimination latent classes had significantly higher depressive symptoms compared to the low discrimination class. Multiple attributes of discrimination and bullying co-occur among adolescents. Research should consider the co-occurrence of bullying and discrimination.
Don't ask for fair treatment? A gender analysis of ethnic discrimination, response to discrimination, and self-rated health among marriage migrants in South Korea.

PubMed

Kim, Yugyun; Son, Inseo; Wie, Dainn; Muntaner, Carles; Kim, Hyunwoo; Kim, Seung-Sup

2016-07-19

Ethnic discrimination is increasingly common nowadays in South Korea with the influx of migrants. Despite the growing body of evidences suggests that ethnic discrimination negatively impacts health, only few researches have been conducted on the association between ethnic discrimination and health outcomes among marriage migrants in Korea. This study sought to examine how ethnic discrimination and response to the discrimination are related to self-rated health and whether the association differs by victim's gender. We conducted two-step analysis using cross-sectional dataset from the 'National Survey of Multicultural Families 2012'. First, we examined the association between perceived ethnic discrimination and self-rated health among 14,406 marriage migrants in Korea. Second, among the marriage migrants who experienced ethnic discrimination (n=5,880), we examined how response to discrimination (i.e., whether or not asking for fair treatment) is related to poor self-rated health. All analyses were conducted after being stratified by the migrant's gender. This research found the significant association between ethnic discrimination and poor self-rated health among female marriage migrants (OR: 1.53, 95 % CI: 1.32, 1.76), but not among male marriage migrants (OR: 1.16, 95 % CI: 0.81, 1.66). In the restricted analysis with marriage migrants who experienced ethnic discrimination, compared to the group who did not ask for fair treatment, female marriage migrants who asked for fair treatment were more likely to report poor self-rated health (OR: 1.21, 95 % CI: 0.98, 1.50); however, male marriage migrants who asked for fair treatment were less likely to report poor self-rated health (OR: 0.65, 95 % CI: 0.36, 1.04) although both were not statistically significant. This is the first study to investigate gender difference in the association between response to ethnic discrimination and self-rated health in South Korea. We discussed that gender may play an important role

Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes.

PubMed

De Luca, Michele; Restuccia, Donatella; Clodoveo, Maria Lisa; Puoci, Francesco; Ragno, Gaetano

2016-07-01

Chemometric discrimination of extra virgin olive oils (EVOO) from whole and stoned olive pastes was carried out by using Fourier transform infrared (FTIR) data and partial least squares-discriminant analysis (PLS1-DA) approach. Four Italian commercial EVOO brands, all in both whole and stoned version, were considered in this study. The adopted chemometric methodologies were able to describe the different chemical features in phenolic and volatile compounds contained in the two types of oil by using unspecific IR spectral information. Principal component analysis (PCA) was employed in cluster analysis to capture data patterns and to highlight differences between technological processes and EVOO brands. The PLS1-DA algorithm was used as supervised discriminant analysis to identify the different oil extraction procedures. Discriminant analysis was extended to the evaluation of possible adulteration by addition of aliquots of oil from whole paste to the most valuable oil from stoned olives. The statistical parameters from external validation of all the PLS models were very satisfactory, with low root mean square error of prediction (RMSEP) and relative error (RE%). Copyright © 2016 Elsevier Ltd. All rights reserved.
L1-norm kernel discriminant analysis via Bayes error bound optimization for robust feature extraction.

PubMed

Zheng, Wenming; Lin, Zhouchen; Wang, Haixian

2014-04-01

A novel discriminant analysis criterion is derived in this paper under the theoretical framework of Bayes optimality. In contrast to the conventional Fisher's discriminant criterion, the major novelty of the proposed one is the use of L1 norm rather than L2 norm, which makes it less sensitive to the outliers. With the L1-norm discriminant criterion, we propose a new linear discriminant analysis (L1-LDA) method for linear feature extraction problem. To solve the L1-LDA optimization problem, we propose an efficient iterative algorithm, in which a novel surrogate convex function is introduced such that the optimization problem in each iteration is to simply solve a convex programming problem and a close-form solution is guaranteed to this problem. Moreover, we also generalize the L1-LDA method to deal with the nonlinear robust feature extraction problems via the use of kernel trick, and hereafter proposed the L1-norm kernel discriminant analysis (L1-KDA) method. Extensive experiments on simulated and real data sets are conducted to evaluate the effectiveness of the proposed method in comparing with the state-of-the-art methods.
The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis.

PubMed

Corvucci, Francesca; Nobili, Lara; Melucci, Dora; Grillenzoni, Francesca-Vittoria

2015-02-15

Honey traceability to food quality is required by consumers and food control institutions. Melissopalynologists traditionally use percentages of nectariferous pollens to discriminate the botanical origin and the entire pollen spectrum (presence/absence, type and quantities and association of some pollen types) to determinate the geographical origin of honeys. To improve melissopalynological routine analysis, principal components analysis (PCA) was used. A remarkable and innovative result was that the most significant pollens for the traditional discrimination of the botanical and geographical origin of honeys were the same as those individuated with the chemometric model. The reliability of assignments of samples to honey classes was estimated through explained variance (85%). This confirms that the chemometric model properly describes the melissopalynological data. With the aim to improve honey discrimination, FT-microRaman spectrography and multivariate analysis were also applied. Well performing PCA models and good agreement with known classes were achieved. Encouraging results were obtained for botanical discrimination. Copyright © 2014 Elsevier Ltd. All rights reserved.
Factorial Design: An Eight Factor Experiment Using Paper Helicopters

NASA Technical Reports Server (NTRS)

Kozma, Michael

1996-01-01

The goal of this paper is to present the analysis of the multi-factor experiment (factorial design) conducted in EG490, Junior Design at Loyola College in Maryland. The discussion of this paper concludes the experimental analysis and ties the individual class papers together.
Analysis and Classification of Entering Freshmen Mathematic Students Using Multiple Discriminate Function Analysis.

ERIC Educational Resources Information Center

Ahrens, Steve

Predictor variables that could be used effectively to place entering freshmen methematics students into courses of instruction in mathematics were investigated at West Virginia University. Multiple discriminant analysis was used with nearly 6,000 student records collected over a three-year period, and a series of predictive equations were…
Links between patterns of racial socialization and discrimination experiences and psychological adjustment: a cluster analysis.

PubMed

Ajayi, Alex A; Syed, Moin

2014-10-01

This study used a person-oriented analytic approach to identify meaningful patterns of barriers-focused racial socialization and perceived racial discrimination experiences in a sample of 295 late adolescents. Using cluster analysis, three distinct groups were identified: Low Barrier Socialization-Low Discrimination, High Barrier Socialization-Low Discrimination, and High Barrier Socialization-High Discrimination clusters. These groups were substantively unique in terms of the frequency of racial socialization messages about bias preparation and out-group mistrust its members received and their actual perceived discrimination experiences. Further, individuals in the High Barrier Socialization-High Discrimination cluster reported significantly higher depressive symptoms than those in the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. However, no differences in adjustment were observed between the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. Overall, the findings highlight important individual differences in how young people of color experience their race and how these differences have significant implications on psychological adjustment. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
Sequence Factorial of "g"-Gonal Numbers

ERIC Educational Resources Information Center

Asiru, Muniru A.

2013-01-01

The gamma function, which has the property to interpolate the factorial whenever the argument is an integer, is a special case (the case "g"?=?2) of the general term of the sequence factorial of "g"-gonal numbers. In relation to this special case, a formula for calculating the general term of the sequence factorial of any…
Optimization of the Neutrino Factory, revisited

NASA Astrophysics Data System (ADS)

Agarwalla, Sanjib K.; Huber, Patrick; Tang, Jian; Winter, Walter

2011-01-01

We perform the baseline and energy optimization of the Neutrino Factory including the latest simulation results on the magnetized iron detector (MIND). We also consider the impact of τ decays, generated by νμ → ντ or ν e → ντ appearance, on the mass hierarchy, CP violation, and θ 13 discovery reaches, which we find to be negligible for the considered detector. For the baseline-energy optimization for small sin2 2 θ 13, we qualitatively recover the results with earlier simulations of the MIND detector. We find optimal baselines of about 2500km to 5000km for the CP violation measurement, where now values of E μ as low as about 12 GeV may be possible. However, for large sin2 2 θ 13, we demonstrate that the lower threshold and the backgrounds reconstructed at lower energies allow in fact for muon energies as low as 5 GeV at considerably shorter baselines, such as FNAL-Homestake. This implies that with the latest MIND analysis, low-and high-energy versions of the Neutrino Factory are just two different versions of the same experiment optimized for different parts of the parameter space. Apart from a green-field study of the updated detector performance, we discuss specific implementations for the two-baseline Neutrino Factory, where the considered detector sites are taken to be currently discussed underground laboratories. We find that reasonable setups can be found for the Neutrino Factory source in Asia, Europe, and North America, and that a triangular-shaped storage ring is possible in all cases based on geometrical arguments only.
Child Protection Decision Making: A Factorial Analysis Using Case Vignettes

ERIC Educational Resources Information Center

Stokes, Jacqueline; Schmidt, Glen

2012-01-01

This study explored decision making by child protection social workers in the province of British Columbia, Canada. A factorial survey method was used in which case vignettes were constructed by randomly assigning a number of key characteristics associated with decision making in child protection. Child protection social workers (n = 118) assessed…
Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis

PubMed Central

Cui, Hengjian; Li, Runze

2014-01-01

This work is concerned with marginal sure independence feature screening for ultra-high dimensional discriminant analysis. The response variable is categorical in discriminant analysis. This enables us to use conditional distribution function to construct a new index for feature screening. In this paper, we propose a marginal feature screening procedure based on empirical conditional distribution function. We establish the sure screening and ranking consistency properties for the proposed procedure without assuming any moment condition on the predictors. The proposed procedure enjoys several appealing merits. First, it is model-free in that its implementation does not require specification of a regression model. Second, it is robust to heavy-tailed distributions of predictors and the presence of potential outliers. Third, it allows the categorical response having a diverging number of classes in the order of O(nκ) with some κ ≥ 0. We assess the finite sample property of the proposed procedure by Monte Carlo simulation studies and numerical comparison. We further illustrate the proposed methodology by empirical analyses of two real-life data sets. PMID:26392643
Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening

PubMed Central

Pan, Rui; Wang, Hansheng; Li, Runze

2016-01-01

This paper is concerned with the problem of feature screening for multi-class linear discriminant analysis under ultrahigh dimensional setting. We allow the number of classes to be relatively large. As a result, the total number of relevant features is larger than usual. This makes the related classification problem much more challenging than the conventional one, where the number of classes is small (very often two). To solve the problem, we propose a novel pairwise sure independence screening method for linear discriminant analysis with an ultrahigh dimensional predictor. The proposed procedure is directly applicable to the situation with many classes. We further prove that the proposed method is screening consistent. Simulation studies are conducted to assess the finite sample performance of the new procedure. We also demonstrate the proposed methodology via an empirical analysis of a real life example on handwritten Chinese character recognition. PMID:28127109
Discrimination of healthy and osteoarthritic articular cartilage by Fourier transform infrared imaging and Fisher’s discriminant analysis

PubMed Central

Mao, Zhi-Hua; Yin, Jian-Hua; Zhang, Xue-Xi; Wang, Xiao; Xia, Yang

2016-01-01

Fourier transform infrared spectroscopic imaging (FTIRI) technique can be used to obtain the quantitative information of content and spatial distribution of principal components in cartilage by combining with chemometrics methods. In this study, FTIRI combining with principal component analysis (PCA) and Fisher’s discriminant analysis (FDA) was applied to identify the healthy and osteoarthritic (OA) articular cartilage samples. Ten 10-μm thick sections of canine cartilages were imaged at 6.25μm/pixel in FTIRI. The infrared spectra extracted from the FTIR images were imported into SPSS software for PCA and FDA. Based on the PCA result of 2 principal components, the healthy and OA cartilage samples were effectively discriminated by the FDA with high accuracy of 94% for the initial samples (training set) and cross validation, as well as 86.67% for the prediction group. The study showed that cartilage degeneration became gradually weak with the increase of the depth. FTIRI combined with chemometrics may become an effective method for distinguishing healthy and OA cartilages in future. PMID:26977354
A Profile-Based Framework for Factorial Similarity and the Congruence Coefficient.

PubMed

Hartley, Anselma G; Furr, R Michael

2017-01-01

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

PubMed

Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

2017-10-12

Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.
Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

PubMed Central

Lim, Jongguk; Kim, Giyoung; Mo, Changyeun; Oh, Kyoungmin; Yoo, Hyeonchae; Ham, Hyeonheui; Kim, Moon S.

2017-01-01

The purpose of this study is to use near-infrared reflectance (NIR) spectroscopy equipment to nondestructively and rapidly discriminate Fusarium-infected hulled barley. Both normal hulled barley and Fusarium-infected hulled barley were scanned by using a NIR spectrometer with a wavelength range of 1175 to 2170 nm. Multiple mathematical pretreatments were applied to the reflectance spectra obtained for Fusarium discrimination and the multivariate analysis method of partial least squares discriminant analysis (PLS-DA) was used for discriminant prediction. The PLS-DA prediction model developed by applying the second-order derivative pretreatment to the reflectance spectra obtained from the side of hulled barley without crease achieved 100% accuracy in discriminating the normal hulled barley and the Fusarium-infected hulled barley. These results demonstrated the feasibility of rapid discrimination of the Fusarium-infected hulled barley by combining multivariate analysis with the NIR spectroscopic technique, which is utilized as a nondestructive detection method. PMID:28974012
Computer experimental analysis of the CHP performance of a 100 kW e SOFC Field Unit by a factorial design

NASA Astrophysics Data System (ADS)

Calì, M.; Santarelli, M. G. L.; Leone, P.

Gas Turbine Technologies (GTT) and Politecnico di Torino, both located in Torino (Italy), have been involved in the design and installation of a SOFC laboratory in order to analyse the operation, in cogenerative configuration, of the CHP 100 kW e SOFC Field Unit, built by Siemens-Westinghouse Power Corporation (SWPC), which is at present (May 2005) starting its operation and which will supply electric and thermal power to the GTT factory. In order to take the better advantage from the analysis of the on-site operation, and especially to correctly design the scheduled experimental tests on the system, we developed a mathematical model and run a simulated experimental campaign, applying a rigorous statistical approach to the analysis of the results. The aim of this work is the computer experimental analysis, through a statistical methodology (2 k factorial experiments), of the CHP 100 performance. First, the mathematical model has been calibrated with the results acquired during the first CHP100 demonstration at EDB/ELSAM in Westerwoort. After, the simulated tests have been performed in the form of computer experimental session, and the measurement uncertainties have been simulated with perturbation imposed to the model independent variables. The statistical methodology used for the computer experimental analysis is the factorial design (Yates' Technique): using the ANOVA technique the effect of the main independent variables (air utilization factor U ox, fuel utilization factor U F, internal fuel and air preheating and anodic recycling flow rate) has been investigated in a rigorous manner. Analysis accounts for the effects of parameters on stack electric power, thermal recovered power, single cell voltage, cell operative temperature, consumed fuel flow and steam to carbon ratio. Each main effect and interaction effect of parameters is shown with particular attention on generated electric power and stack heat recovered.
Advanced Signal Processing Analysis of Laser-Induced Breakdown Spectroscopy Data for the Discrimination of Obsidian Sources

DTIC Science & Technology

2012-02-09

different sources [12,13], but the analytical techniques needed for such analysis (XRD, INAA , & ICP-MS) are time consuming and require expensive...partial least-squares discriminant analysis (PLSDA) that used the SIMPLS solving method [33]. In the experi- ment design, a leave-one-sample-out (LOSO) para...REPORT Advanced signal processing analysis of laser-induced breakdown spectroscopy data for the discrimination of obsidian sources 14. ABSTRACT 16
Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

PubMed

Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

2015-02-01

Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides
[Prevalence and influence factors of hypertension among mechanic factory workers].

PubMed

Pang, Li-Juan; Chen, Li-Zhang; Fu, Ben-Yan

2005-06-01

To determine the status and influence factors of hypertension on mechanic factory workers and to provide reference for further hypertension prevention and control. A cross-sectional study on 1205 workers (exposed to different noise levels) in Hunan was carried out by using questionaire and measuring the blood pressure of the workers and the noise exposure level in the workplace. The prevalence and the influence factors of hypertension among mechanic factory workers were analysed. The hypertension prevalence was 12.1%. Logistic regression analysis showed the body weight index (BMI), age, and history of hypertension in parents and accumulative noise dose levels influenced the hypertension prevalence. Controlling the body weight, reducing alcohol consumption, decreasing the sound pressure level in workshops and advocating healthy diet may reduce the prevalence rate of hypertension among mechanic factory workers.
Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

PubMed

Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-03

Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

Discrimination of complex synthetic echoes by an echolocating bottlenose dolphin

NASA Astrophysics Data System (ADS)

Helweg, David A.; Moore, Patrick W.; Dankiewicz, Lois A.; Zafran, Justine M.; Brill, Randall L.

2003-02-01

Bottlenose dolphins (Tursiops truncatus) detect and discriminate underwater objects by interrogating the environment with their native echolocation capabilities. Study of dolphins' ability to detect complex (multihighlight) signals in noise suggest echolocation object detection using an approximate 265-μs energy integration time window sensitive to the echo region of highest energy or containing the highlight with highest energy. Backscatter from many real objects contains multiple highlights, distributed over multiple integration windows and with varying amplitude relationships. This study used synthetic echoes with complex highlight structures to test whether high-amplitude initial highlights would interfere with discrimination of low-amplitude trailing highlights. A dolphin was trained to discriminate two-highlight synthetic echoes using differences in the center frequencies of the second highlights. The energy ratio (ΔdB) and the timing relationship (ΔT) between the first and second highlights were manipulated. An iso-sensitivity function was derived using a factorial design testing ΔdB at -10, -15, -20, and -25 dB and ΔT at 10, 20, 40, and 80 μs. The results suggest that the animal processed multiple echo highlights as separable analyzable features in the discrimination task, perhaps perceived through differences in spectral rippling across the duration of the echoes.
New generation electron-positron factories

NASA Astrophysics Data System (ADS)

Zobov, Mikhail

2011-09-01

In 2010 we celebrate 50 years since commissioning of the first particle storage ring ADA in Frascati (Italy) that also became the first electron-positron collider in 1964. After that date the particle colliders have increased their intensity, luminosity and energy by several orders of magnitude. Namely, because of the high stored beam currents and high rate of useful physics events (luminosity) the modern electron-positron colliders are called "factories". However, the fundamental physics has required luminosities by 1-2 orders of magnitudes higher with respect to those presently achieved. This task can be accomplished by designing a new generation of factories exploiting the potential of a new collision scheme based on the Crab Waist (CW) collision concept recently proposed and successfully tested at Frascati. In this paper we discuss the performance and limitations of the present generation electron-positron factories and give a brief overview of new ideas and collision schemes proposed for further collider luminosity increase. In more detail we describe the CW collision concept and the results of the crab waist collision tests in DAϕNE, the Italian ϕ-factory. Finally, we briefly describe most advanced projects of the next generation factories based on the CW concept: SuperB in Italy, SuperKEKB in Japan and SuperC-Tau in Russia.
Prediction of Recidivism in Juvenile Offenders Based on Discriminant Analysis.

ERIC Educational Resources Information Center

Proefrock, David W.

The recent development of strong statistical techniques has made accurate predictions of recidivism possible. To investigate the utility of discriminant analysis methodology in making predictions of recidivism in juvenile offenders, the court records of 271 male and female juvenile offenders, aged 12-16, were reviewed. A cross validation group…
Skills for the 21st Century Supervisor: What Factory Personnel Think.

ERIC Educational Resources Information Center

Hotek, Douglas R.

2002-01-01

Discusses supervisory skills that factory personnel believe are important for leading and improving employee performance in complex manufacturing environments. Highlights include a historical perspective; manufacturing technologies; results of Pareto analysis, comparative analysis, and analysis of variance; and a Taxonomy of Supervisory Skills.…
The Discriminant Analysis Flare Forecasting System (DAFFS)

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, Graham; Wagner, Eric; Hill, Frank; Marble, Andrew R.

2016-05-01

The Discriminant Analysis Flare Forecasting System (DAFFS) has been developed under NOAA/Small Business Innovative Research funds to quantitatively improve upon the NOAA/SWPC flare prediction. In the Phase-I of this project, it was demonstrated that DAFFS could indeed improve by the requested 25% most of the standard flare prediction data products from NOAA/SWPC. In the Phase-II of this project, a prototype has been developed and is presently running autonomously at NWRA.DAFFS uses near-real-time data from NOAA/GOES, SDO/HMI, and the NSO/GONG network to issue both region- and full-disk forecasts of solar flares, based on multi-variable non-parametric Discriminant Analysis. Presently, DAFFS provides forecasts which match those provided by NOAA/SWPC in terms of thresholds and validity periods (including 1-, 2-, and 3- day forecasts), although issued twice daily. Of particular note regarding DAFFS capabilities are the redundant system design, automatically-generated validation statistics and the large range of customizable options available. As part of this poster, a description of the data used, algorithm, performance and customizable options will be presented, as well as a demonstration of the DAFFS prototype.DAFFS development at NWRA is supported by NOAA/SBIR contracts WC-133R-13-CN-0079 and WC-133R-14-CN-0103, with additional support from NASA contract NNH12CG10C, plus acknowledgment to the SDO/HMI and NSO/GONG facilities and NOAA/SWPC personnel for data products, support, and feedback. DAFFS is presently ready for Phase-III development.
Rapid prototyping 3D virtual world interfaces within a virtual factory environment

NASA Technical Reports Server (NTRS)

Kosta, Charles Paul; Krolak, Patrick D.

1993-01-01

On-going work into user requirements analysis using CLIPS (NASA/JSC) expert systems as an intelligent event simulator has led to research into three-dimensional (3D) interfaces. Previous work involved CLIPS and two-dimensional (2D) models. Integral to this work was the development of the University of Massachusetts Lowell parallel version of CLIPS, called PCLIPS. This allowed us to create both a Software Bus and a group problem-solving environment for expert systems development. By shifting the PCLIPS paradigm to use the VEOS messaging protocol we have merged VEOS (HlTL/Seattle) and CLIPS into a distributed virtual worlds prototyping environment (VCLIPS). VCLIPS uses the VEOS protocol layer to allow multiple experts to cooperate on a single problem. We have begun to look at the control of a virtual factory. In the virtual factory there are actors and objects as found in our Lincoln Logs Factory of the Future project. In this artificial reality architecture there are three VCLIPS entities in action. One entity is responsible for display and user events in the 3D virtual world. Another is responsible for either simulating the virtual factory or communicating with the real factory. The third is a user interface expert. The interface expert maps user input levels, within the current prototype, to control information for the factory. The interface to the virtual factory is based on a camera paradigm. The graphics subsystem generates camera views of the factory on standard X-Window displays. The camera allows for view control and object control. Control or the factory is accomplished by the user reaching into the camera views to perform object interactions. All communication between the separate CLIPS expert systems is done through VEOS.
Baby factories taint surrogacy in Nigeria.

PubMed

Makinde, Olusesan Ayodeji; Makinde, Olufunmbi Olukemi; Olaleye, Olalekan; Brown, Brandon; Odimegwu, Clifford O

2016-01-01

The practice of reproductive medicine in Nigeria is facing new challenges with the proliferation of 'baby factories'. Baby factories are buildings, hospitals or orphanages that have been converted into places for young girls and women to give birth to children for sale on the black market, often to infertile couples, or into trafficking rings. This practice illegally provides outcomes (children) similar to surrogacy. While surrogacy has not been well accepted in this environment, the proliferation of baby factories further threatens its acceptance. The involvement of medical and allied health workers in the operation of baby factories raises ethical concerns. The lack of a properly defined legal framework and code of practice for surrogacy makes it difficult to prosecute baby factory owners, especially when they are health workers claiming to be providing services to clients. In this environment, surrogacy and other assisted reproductive techniques urgently require regulation in order to define when ethico-legal lines have been crossed in providing surrogacy or surrogacy-like services. Copyright © 2015 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.
Discrimination of Aurantii Fructus Immaturus and Fructus Poniciri Trifoliatae Immaturus by Flow Injection UV Spectroscopy (FIUV) and 1H NMR using Partial Least-squares Discriminant Analysis (PLS-DA)

USDA-ARS?s Scientific Manuscript database

Two simple fingerprinting methods, flow-injection UV spectroscopy (FIUV) and 1H nuclear magnetic resonance (NMR), for discrimination of Aurantii FructusImmaturus and Fructus Poniciri TrifoliataeImmaturususing were described. Both methods were combined with partial least-squares discriminant analysis...
Kinetic models in industrial biotechnology - Improving cell factory performance.

PubMed

Almquist, Joachim; Cvijovic, Marija; Hatzimanikatis, Vassily; Nielsen, Jens; Jirstrand, Mats

2014-07-01

An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Practitioner Representations of Environmental Uncertainty: An Application of Discriminant Analysis.

ERIC Educational Resources Information Center

Acharya, Lalit

Multiple discriminant analysis was used to analyze the structure of a perceived environmental uncertainty variable employed previously in research on public relations roles. Data came from a subset (N=229) of a national sample of public relations practitioners belonging to the Public Relations Society of America, who completed a set of scaled…
Forensic discrimination of vaginal epithelia by DNA methylation analysis through pyrosequencing.

PubMed

Antunes, Joana; Silva, Deborah S B S; Balamurugan, Kuppareddi; Duncan, George; Alho, Clarice S; McCord, Bruce

2016-10-01

The accurate identification of body fluids from crime scenes can aid in the discrimination between criminal and innocent intent. This research aimed to determine if the levels of DNA methylation in the locus PFN3A could be used to discriminate vaginal epithelia from other body fluids. In this work we bisulfite-modified and amplified DNA samples from blood, saliva, semen, and vaginal epithelia using primers for PFN3A. Through pyrosequencing we were able to show that vaginal epithelia present distinct methylation levels when compared to other body fluids. Mixtures of different body fluids present methylation values that correlate with single-source body fluid samples and the primers for PFN3A are specific for primates. This report successfully demonstrated that the analysis of methylation in the PFN3A locus can be used for vaginal epithelia discrimination in forensic samples. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A Bayesian-based multilevel factorial analysis method for analyzing parameter uncertainty of hydrological model

NASA Astrophysics Data System (ADS)

Liu, Y. R.; Li, Y. P.; Huang, G. H.; Zhang, J. L.; Fan, Y. R.

2017-10-01

In this study, a Bayesian-based multilevel factorial analysis (BMFA) method is developed to assess parameter uncertainties and their effects on hydrological model responses. In BMFA, Differential Evolution Adaptive Metropolis (DREAM) algorithm is employed to approximate the posterior distributions of model parameters with Bayesian inference; factorial analysis (FA) technique is used for measuring the specific variations of hydrological responses in terms of posterior distributions to investigate the individual and interactive effects of parameters on model outputs. BMFA is then applied to a case study of the Jinghe River watershed in the Loess Plateau of China to display its validity and applicability. The uncertainties of four sensitive parameters, including soil conservation service runoff curve number to moisture condition II (CN2), soil hydraulic conductivity (SOL_K), plant available water capacity (SOL_AWC), and soil depth (SOL_Z), are investigated. Results reveal that (i) CN2 has positive effect on peak flow, implying that the concentrated rainfall during rainy season can cause infiltration-excess surface flow, which is an considerable contributor to peak flow in this watershed; (ii) SOL_K has positive effect on average flow, implying that the widely distributed cambisols can lead to medium percolation capacity; (iii) the interaction between SOL_AWC and SOL_Z has noticeable effect on the peak flow and their effects are dependent upon each other, which discloses that soil depth can significant influence the processes of plant uptake of soil water in this watershed. Based on the above findings, the significant parameters and the relationship among uncertain parameters can be specified, such that hydrological model's capability for simulating/predicting water resources of the Jinghe River watershed can be improved.
Implicit Age Cues in Resumes: Subtle Effects on Hiring Discrimination

PubMed Central

Derous, Eva; Decoster, Jeroen

2017-01-01

Anonymous resume screening, as assumed, does not dissuade age discriminatory effects. Building on job market signaling theory, this study investigated whether older applicants may benefit from concealing explicitly mentioned age signals on their resumes (date of birth) or whether more implicit/subtle age cues on resumes (older-sounding names/old-fashioned extracurricular activities) may lower older applicants’ hirability ratings. An experimental study among 610 HR professionals using a mixed factorial design showed hiring discrimination of older applicants based on implicit age cues in resumes. This effect was more pronounced for older raters. Concealing one’s date of birth led to overall lower ratings. Study findings add to the limited knowledge on the effects of implicit age cues on hiring discrimination in resume screening and the usefulness of anonymous resume screening in the context of age. Implications for research and practice are discussed. PMID:28848463
Economic evaluation of factorial randomised controlled trials: challenges, methods and recommendations

PubMed Central

Gray, Alastair

2017-01-01

Increasing numbers of economic evaluations are conducted alongside randomised controlled trials. Such studies include factorial trials, which randomise patients to different levels of two or more factors and can therefore evaluate the effect of multiple treatments alone and in combination. Factorial trials can provide increased statistical power or assess interactions between treatments, but raise additional challenges for trial‐based economic evaluations: interactions may occur more commonly for costs and quality‐adjusted life‐years (QALYs) than for clinical endpoints; economic endpoints raise challenges for transformation and regression analysis; and both factors must be considered simultaneously to assess which treatment combination represents best value for money. This article aims to examine issues associated with factorial trials that include assessment of costs and/or cost‐effectiveness, describe the methods that can be used to analyse such studies and make recommendations for health economists, statisticians and trialists. A hypothetical worked example is used to illustrate the challenges and demonstrate ways in which economic evaluations of factorial trials may be conducted, and how these methods affect the results and conclusions. Ignoring interactions introduces bias that could result in adopting a treatment that does not make best use of healthcare resources, while considering all interactions avoids bias but reduces statistical power. We also introduce the concept of the opportunity cost of ignoring interactions as a measure of the bias introduced by not taking account of all interactions. We conclude by offering recommendations for planning, analysing and reporting economic evaluations based on factorial trials, taking increased analysis costs into account. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28470760
A multiple-locus variable-number tandem repeat analysis (MLVA) of Listeria monocytogenes isolated from Norwegian salmon-processing factories and from listeriosis patients.

PubMed

Lunestad, B T; Truong, T T T; Lindstedt, B-A

2013-10-01

The objective of this study was to characterize Listeria monocytogenes isolated from farmed Atlantic salmon (Salmo salar) and the processing environment in three different Norwegian factories, and compare these to clinical isolates by multiple-locus variable-number tandem repeat analysis (MLVA). The 65 L. monocytogenes isolates obtained gave 15 distinct MLVA profiles. There was great heterogeneity in the distribution of MLVA profiles in factories and within each factory. Nine of the 15 MLVA profiles found in the fish-associated isolates were found to match human profiles. The MLVA profile 07-07-09-10-06 was the most common strain in Norwegian listeriosis patients. L. monocytogenes with this profile has previously been associated with at least two known listeriosis outbreaks in Norway, neither determined to be due to fish consumption. However, since this profile was also found in fish and in the processing environment, fish should be considered as a possible food vehicle during sporadic cases and outbreaks of listeriosis.
Slime Factory.

ERIC Educational Resources Information Center

Fowler, Marilyn L.

1992-01-01

Describes a classroom activity using slime, a colloid: it behaves like both a solid and liquid. Explains how slime can be produced from guar gum. An activity where students work in teams and become a slime factory is presented. (PR)
Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

NASA Astrophysics Data System (ADS)

Phinyomark, A.; Hu, H.; Phukpattaranont, P.; Limsakul, C.

2012-01-01

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier.
Meta-analysis of field experiments shows no change in racial discrimination in hiring over time.

PubMed

Quillian, Lincoln; Pager, Devah; Hexel, Ole; Midtbøen, Arnfinn H

2017-10-10

This study investigates change over time in the level of hiring discrimination in US labor markets. We perform a meta-analysis of every available field experiment of hiring discrimination against African Americans or Latinos ( n = 28). Together, these studies represent 55,842 applications submitted for 26,326 positions. We focus on trends since 1989 ( n = 24 studies), when field experiments became more common and improved methodologically. Since 1989, whites receive on average 36% more callbacks than African Americans, and 24% more callbacks than Latinos. We observe no change in the level of hiring discrimination against African Americans over the past 25 years, although we find modest evidence of a decline in discrimination against Latinos. Accounting for applicant education, applicant gender, study method, occupational groups, and local labor market conditions does little to alter this result. Contrary to claims of declining discrimination in American society, our estimates suggest that levels of discrimination remain largely unchanged, at least at the point of hire.
Biomass analysis at palm oil factory as an electric power plant

NASA Astrophysics Data System (ADS)

Yusniati; Parinduri, Luthfi; Krianto Sulaiman, Oris

2018-04-01

Biomassa found in palm oil mill industryis a by-product such as palm shell, fiber, empty fruit bunches and pome. The material can be used as an alternative fuel for fossil fuel. On PTPN IVpalm oil millDolokSinumbah with a capacity of 30 tons tbs/hour of palm fruit fiber and palm shells has been utilized as boiler fuel to produce steam to supplyboilers power plant. With this utilization, the use of generators that using fossil fuel can be reduced, this would provide added value for the company. From the analysis, the fiber and shell materials were sufficient to supply 18 tons/hoursteam for the boiler. Shell material even excess as much as 441,5 tons per month. By utilizing the 2 types of biomass that is available alone, the electricity needs of the factory of 734 Kwh can be met. While other materials such as empty bunches and pome can be utilized to increase the added value and profitability for the palm oil mill.
Supernova Dust Factory in M74

NASA Image and Video Library

2006-06-09

Astronomers using NASA Spitzer Space Telescope have spotted a dust factory 30 million light-years away in the spiral galaxy M74. The factory is located at the scene of a massive star explosive death, or supernova.

Discrimination among populations of sockeye salmon fry with Fourier analysis of otolith banding patterns formed during incubation

USGS Publications Warehouse

Finn, James E.; Burger, Carl V.; Holland-Bartels, Leslie E.

1997-01-01

We used otolith banding patterns formed during incubation to discriminate among hatchery- and wild-incubated fry of sockeye salmon Oncorhynchus nerka from Tustumena Lake, Alaska. Fourier analysis of otolith luminance profiles was used to describe banding patterns: the amplitudes of individual Fourier harmonics were discriminant variables. Correct classification of otoliths to either hatchery or wild origin was 83.1% (cross-validation) and 72.7% (test data) with the use of quadratic discriminant function analysts on 10 Fourier amplitudes. Overall classification rates among the six test groups (one hatchery and five wild groups) were 46.5% (cross-validation) and 39.3% (test data) with the use of linear discriminant function analysis on 16 Fourier amplitudes. Although classification rates for wild-incubated fry from any one site never exceeded 67% (cross-validation) or 60% (test data), location-specific information was evident for all groups because the probability of classifying an individual to its true incubation location was significantly greater than chance. Results indicate phenotypic differences in otolith microstructure among incubation sites separated by less than 10 km. Analysis of otolith luminance profiles is a potentially useful technique for discriminating among and between various populations of hatchery and wild fish.
Chance-corrected classification for use in discriminant analysis: Ecological applications

USGS Publications Warehouse

Titus, K.; Mosher, J.A.; Williams, B.K.

1984-01-01

A method for evaluating the classification table from a discriminant analysis is described. The statistic, kappa, is useful to ecologists in that it removes the effects of chance. It is useful even with equal group sample sizes although the need for a chance-corrected measure of prediction becomes greater with more dissimilar group sample sizes. Examples are presented.
Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques.

PubMed

Tahir, Haroon Elrasheid; Xiaobo, Zou; Xiaowei, Huang; Jiyong, Shi; Mariod, Abdalbasit Adam

2016-09-01

Aroma profiles of six honey varieties of different botanical origins were investigated using colorimetric sensor array, gas chromatography-mass spectrometry (GC-MS) and descriptive sensory analysis. Fifty-eight aroma compounds were identified, including 2 norisoprenoids, 5 hydrocarbons, 4 terpenes, 6 phenols, 7 ketones, 9 acids, 12 aldehydes and 13 alcohols. Twenty abundant or active compounds were chosen as key compounds to characterize honey aroma. Discrimination of the honeys was subsequently implemented using multivariate analysis, including hierarchical clustering analysis (HCA) and principal component analysis (PCA). Honeys of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS and colorimetric sensor array were able to discriminate the honeys effectively with the advantages of being rapid, simple and low-cost. Moreover, partial least squares regression (PLSR) was applied to indicate the relationship between sensory descriptors and aroma compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.
Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.
Mobile Monitoring and Embedded Control System for Factory Environment

PubMed Central

Lian, Kuang-Yow; Hsiao, Sung-Jung; Sung, Wen-Tsai

2013-01-01

This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones. PMID:24351642
Mobile monitoring and embedded control system for factory environment.

PubMed

Lian, Kuang-Yow; Hsiao, Sung-Jung; Sung, Wen-Tsai

2013-12-17

This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones.
Factorials of real negative and imaginary numbers - A new perspective.

PubMed

Thukral, Ashwani K

2014-01-01

Presently, factorials of real negative numbers and imaginary numbers, except for zero and negative integers are interpolated using the Euler's gamma function. In the present paper, the concept of factorials has been generalised as applicable to real and imaginary numbers, and multifactorials. New functions based on Euler's factorial function have been proposed for the factorials of real negative and imaginary numbers. As per the present concept, the factorials of real negative numbers, are complex numbers. The factorials of real negative integers have their imaginary part equal to zero, thus are real numbers. Similarly, the factorials of imaginary numbers are complex numbers. The moduli of the complex factorials of real negative numbers, and imaginary numbers are equal to their respective real positive number factorials. Fractional factorials and multifactorials have been defined in a new perspective. The proposed concept has also been extended to Euler's gamma function for real negative numbers and imaginary numbers, and beta function.
Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.
Machine vision methods for use in grain variety discrimination and quality analysis

NASA Astrophysics Data System (ADS)

Winter, Philip W.; Sokhansanj, Shahab; Wood, Hugh C.

1996-12-01

Decreasing cost of computer technology has made it feasible to incorporate machine vision technology into the agriculture industry. The biggest attraction to using a machine vision system is the computer's ability to be completely consistent and objective. One use is in the variety discrimination and quality inspection of grains. Algorithms have been developed using Fourier descriptors and neural networks for use in variety discrimination of barley seeds. RGB and morphology features have been used in the quality analysis of lentils, and probability distribution functions and L,a,b color values for borage dockage testing. These methods have been shown to be very accurate and have a high potential for agriculture. This paper presents the techniques used and results obtained from projects including: a lentil quality discriminator, a barley variety classifier, a borage dockage tester, a popcorn quality analyzer, and a pistachio nut grading system.
Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.
Meta-analysis of studies assessing the efficacy of projective techniques in discriminating child sexual abuse.

PubMed

West, M M

1998-11-01

This meta-analysis of 12 studies assesses the efficacy of projective techniques to discriminate between sexually abused children and nonsexually abused children. A literature search was conducted to identify published studies that used projective instruments with sexually abused children. Those studies that reported statistics that allowed for an effect size to be calculated, were then included in the meta-analysis. There were 12 studies that fit the criteria. The projectives reviewed include The Rorschach, The Hand Test, The Thematic Apperception Test (TAT), the Kinetic Family Drawings, Human Figure Drawings, Draw Your Favorite Kind of Day, The Rosebush: A Visualization Strategy, and The House-Tree-Person. The results of this analysis gave an over-all effect size of d = .81, which is a large effect. Six studies included only a norm group of nondistressed, nonabused children with the sexual abuse group. The average effect size was d = .87, which is impressive. Six studies did include a clinical group of distressed nonsexually abused subjects and the effect size lowered to d = .76, which is a medium to large effect. This indicates that projective instruments can discriminate distressed children from nondistressed subjects, quite well. In the studies that included a clinical group of distressed children who were not sexually abused, the lower effect size indicates that the instruments were less able to discriminate the type of distress. This meta-analysis gives evidence that projective techniques have the ability to discriminate between children who have been sexually abused and those who were not abused sexually. However, further research that is designed to include clinical groups of distressed children is needed in order to determine how well the projectives can discriminate the type of distress.
Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zhu, Ying; Tan, Tuck Lee

2016-04-01

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects.
Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy.

PubMed

Zhu, Ying; Tan, Tuck Lee

2016-04-15

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects. Copyright © 2016 Elsevier B.V. All rights reserved.
The Economic Status of Migrant Wives: An Application of Discriminant Analysis.

ERIC Educational Resources Information Center

Rytina, Nancy F.

1981-01-01

Lower work rate of migrant wives after moving is a function of moving for husbands' job opportunities and being in the childrearing stage of life. Discriminant analysis reveals that socioeconomic characteristics are lower for nonworking than migrant wives. Working migrant wives have more education and higher status jobs than nonmigrants.…
Is it really organic?--multi-isotopic analysis as a tool to discriminate between organic and conventional plants.

PubMed

Laursen, K H; Mihailova, A; Kelly, S D; Epov, V N; Bérail, S; Schjoerring, J K; Donard, O F X; Larsen, E H; Pedentchouk, N; Marca-Bell, A D; Halekoh, U; Olesen, J E; Husted, S

2013-12-01

Novel procedures for analytical authentication of organic plant products are urgently needed. Here we present the first study encompassing stable isotopes of hydrogen, carbon, nitrogen, oxygen, magnesium and sulphur as well as compound-specific nitrogen and oxygen isotope analysis of nitrate for discrimination of organically and conventionally grown plants. The study was based on wheat, barley, faba bean and potato produced in rigorously controlled long-term field trials comprising 144 experimental plots. Nitrogen isotope analysis revealed the use of animal manure, but was unable to discriminate between plants that were fertilised with synthetic nitrogen fertilisers or green manures from atmospheric nitrogen fixing legumes. This limitation was bypassed using oxygen isotope analysis of nitrate in potato tubers, while hydrogen isotope analysis allowed complete discrimination of organic and conventional wheat and barley grains. It is concluded, that multi-isotopic analysis has the potential to disclose fraudulent substitutions of organic with conventionally cultivated plants. Copyright © 2013 Elsevier Ltd. All rights reserved.
Symptoms of musculoskeletal disorders among ammunition factory workers in Turkey.

PubMed

Pinar, Tevfik; Cakmak, Z Aytul; Saygun, Meral; Akdur, Recep; Ulu, Nuriye; Keles, Isik; Saylam, Hamdi Saim

2013-01-01

The aim of this study was to assess the prevalence of symptoms of work-related musculoskeletal disorders (MSDs) and to determine the risk factors among ammunition factory workers in Turkey. This cross-sectional study was performed on 955 ammunition factory workers. Potential risk factors were investigated with a questionnaire and multivariate logistic regression analysis was performed. During the previous year, 39.3% of ammunition workers experienced symptoms of work-related MSDs. Logistic regression analysis showed smoking (odds ratio [OR] = 1.372), chronic diseases (OR = 1.795), body mass index (BMI; overweight) (OR = 1.631), working year (OR = 1.509), cold temperature (OR = 1.838), and work load (OR = 2.210) were significant independent risk factors for the development of symptoms of MSDs. It was found that both work-related conditions and personal and environmental factors are important for the development of occupational MSDs.
The discrimination of man-made explosions from earthquakes using seismo-acoustic analysis in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Che, Il-Young; Jeon, Jeong-Soo

2010-05-01

Korea Institute of Geoscience and Mineral Resources (KIGAM) operates an infrasound network consisting of seven seismo-acoustic arrays in South Korea. Development of the arrays began in 1999, partially in collaboration with Southern Methodist University, with the goal of detecting distant infrasound signals from natural and anthropogenic phenomena in and around the Korean Peninsula. The main operational purpose of this network is to discriminate man-made seismic events from seismicity including thousands of seismic events per year in the region. The man-made seismic events are major cause of error in estimating the natural seismicity, especially where the seismic activity is weak or moderate such as in the Korean Peninsula. In order to discriminate the man-made explosions from earthquakes, we have applied the seismo-acoustic analysis associating seismic and infrasonic signals generated from surface explosion. The observations of infrasound at multiple arrays made it possible to discriminate surface explosion, because small or moderate size earthquake is not sufficient to generate infrasound. Till now we have annually discriminated hundreds of seismic events in seismological catalog as surface explosions by the seismo-acoustic analysis. Besides of the surface explosions, the network also detected infrasound signals from other sources, such as bolide, typhoons, rocket launches, and underground nuclear test occurred in and around the Korean Peninsula. In this study, ten years of seismo-acoustic data are reviewed with recent infrasonic detection algorithm and association method that finally linked to the seismic monitoring system of the KIGAM to increase the detection rate of surface explosions. We present the long-term results of seismo-acoustic analysis, the detection capability of the multiple arrays, and implications for seismic source location. Since the seismo-acoustic analysis is proved as a definite method to discriminate surface explosion, the analysis will be
Gait characterization in golden retriever muscular dystrophy dogs using linear discriminant analysis.

PubMed

Fraysse, Bodvaël; Barthélémy, Inès; Qannari, El Mostafa; Rouger, Karl; Thorin, Chantal; Blot, Stéphane; Le Guiner, Caroline; Chérel, Yan; Hogrel, Jean-Yves

2017-04-12

Accelerometric analysis of gait abnormalities in golden retriever muscular dystrophy (GRMD) dogs is of limited sensitivity, and produces highly complex data. The use of discriminant analysis may enable simpler and more sensitive evaluation of treatment benefits in this important preclinical model. Accelerometry was performed twice monthly between the ages of 2 and 12 months on 8 healthy and 20 GRMD dogs. Seven accelerometric parameters were analysed using linear discriminant analysis (LDA). Manipulation of the dependent and independent variables produced three distinct models. The ability of each model to detect gait alterations and their pattern change with age was tested using a leave-one-out cross-validation approach. Selecting genotype (healthy or GRMD) as the dependent variable resulted in a model (Model 1) allowing a good discrimination between the gait phenotype of GRMD and healthy dogs. However, this model was not sufficiently representative of the disease progression. In Model 2, age in months was added as a supplementary dependent variable (GRMD_2 to GRMD_12 and Healthy_2 to Healthy_9.5), resulting in a high overall misclassification rate (83.2%). To improve accuracy, a third model (Model 3) was created in which age was also included as an explanatory variable. This resulted in an overall misclassification rate lower than 12%. Model 3 was evaluated using blinded data pertaining to 81 healthy and GRMD dogs. In all but one case, the model correctly matched gait phenotype to the actual genotype. Finally, we used Model 3 to reanalyse data from a previous study regarding the effects of immunosuppressive treatments on muscular dystrophy in GRMD dogs. Our model identified significant effect of immunosuppressive treatments on gait quality, corroborating the original findings, with the added advantages of direct statistical analysis with greater sensitivity and more comprehensible data representation. Gait analysis using LDA allows for improved analysis of
The specter of discrimination: Fear of interpersonal racial discrimination among adolescents in Chicago.

PubMed

Herda, Daniel

2016-01-01

This analysis examines fear of interpersonal racial discrimination among Black, Hispanic, and White adolescents. The extent and correlates of these concerns are examined using survey data from the Project for Human Development in Chicago Neighborhoods. Borrowing from the fear-of-crime literature, the contact hypothesis, and group threat theory, several hypotheses are developed linking discrimination fear to direct personal experience with discrimination, indirect or vicarious experience, and environmental signals of discrimination. Results show that about half of Blacks and Hispanics have feared discrimination in the past year. Multivariate results indicate that fear is most likely if one has experienced victimization first-hand and when one's parent is affected by discrimination. Further, a larger presence neighborhood outgroups produces greater fear. Overall, discrimination fear constitutes an additional obstacle for minority adolescents as they transition to adulthood. The phenomenon warrants increased scholarly attention and represents a fruitful avenue for future research. Copyright © 2015 Elsevier Inc. All rights reserved.
Linear discriminant analysis of dermoscopic parameters for the differentiation of early melanomas from Clark naevi.

PubMed

Oka, Hiroshi; Tanaka, Masaru; Kobayashi, Seiichiro; Argenziano, Giuseppe; Soyer, H Peter; Nishikawa, Takeji

2004-04-01

As a first step to develop a screening system for pigmented skin lesions, we performed digital discriminant analyses between early melanomas and Clark naevi. A total of 59 cases of melanoma, including 23 melanoma in situ and 36 thin invasive melanomas (Breslow thickness < or =0.75 mm), and 188 clinically equivocal, histopathologically diagnosed Clark naevi were used in our study. After calculating 62 mathematical variables related to the colour, texture, asymmetry and circularity based on the dermoscopic findings of the pigmented skin lesions, we performed multivariate stepwise discriminant analysis using these variables to differentiate melanomas from naevi. The sensitivities and specificities of our model were 94.4 and 98.4%, respectively, for discriminating between melanomas (Breslow thickness < or =0.75 mm) and Clark naevi, and 73.9 and 85.6%, respectively, for discriminating between melanoma in situ and Clark naevi. Our algorithm accurately discriminated invasive melanomas from Clark naevi, but not melanomas in situ from Clark naevi.

Perceived Discrimination and Health: A Meta-Analytic Review

PubMed Central

Pascoe, Elizabeth A.; Richman, Laura Smart

2009-01-01

Perceived discrimination has been studied with regard to its impact on several types of health effects. This meta-analysis provides a comprehensive account of the relationships between multiple forms of perceived discrimination and both mental and physical health outcomes. In addition, this meta-analysis examines potential mechanisms by which perceiving discrimination may affect health, including through psychological and physiological stress responses and health behaviors. Analysis of 134 samples suggests that when weighting each study’s contribution by sample size, perceived discrimination has a significant negative effect on both mental and physical health. Perceived discrimination also produces significantly heightened stress responses and is related to participation in unhealthy and nonparticipation in healthy behaviors. These findings suggest potential pathways linking perceived discrimination to negative health outcomes. PMID:19586161
Discriminating topology in galaxy distributions using network analysis

NASA Astrophysics Data System (ADS)

Hong, Sungryong; Coutinho, Bruno C.; Dey, Arjun; Barabási, Albert-L.; Vogelsberger, Mark; Hernquist, Lars; Gebhardt, Karl

2016-07-01

The large-scale distribution of galaxies is generally analysed using the two-point correlation function. However, this statistic does not capture the topology of the distribution, and it is necessary to resort to higher order correlations to break degeneracies. We demonstrate that an alternate approach using network analysis can discriminate between topologically different distributions that have similar two-point correlations. We investigate two galaxy point distributions, one produced by a cosmological simulation and the other by a Lévy walk. For the cosmological simulation, we adopt the redshift z = 0.58 slice from Illustris and select galaxies with stellar masses greater than 108 M⊙. The two-point correlation function of these simulated galaxies follows a single power law, ξ(r) ˜ r-1.5. Then, we generate Lévy walks matching the correlation function and abundance with the simulated galaxies. We find that, while the two simulated galaxy point distributions have the same abundance and two-point correlation function, their spatial distributions are very different; most prominently, filamentary structures, absent in Lévy fractals. To quantify these missing topologies, we adopt network analysis tools and measure diameter, giant component, and transitivity from networks built by a conventional friends-of-friends recipe with various linking lengths. Unlike the abundance and two-point correlation function, these network quantities reveal a clear separation between the two simulated distributions; therefore, the galaxy distribution simulated by Illustris is not a Lévy fractal quantitatively. We find that the described network quantities offer an efficient tool for discriminating topologies and for comparing observed and theoretical distributions.
[Detection of occupational hazards in a large shipbuilding factory].

PubMed

Du, Weijia; Wang, Zhi; Zhang, Hai; Zhou, Liping; Huang, Minzhi; Liu, Yimin

2014-03-01

To provide evidence for the prevention and treatment of occupational diseases by the analysis of existing major occupational hazards and health conditions of workers in a large shipbuilding factory. Field investigation of occupational conditions was conducted to examine the existence of occupational hazards from 2009 to 2012 in a large shipbuilding factory, and then the results of physical examination among its workers were analyzed. Other than the metal dust (total dust), the levels of other dusts and manganese dioxide were beyond the national standard to various degrees, and through a sampling point detection, it was found that the levels of manganese dioxide exceeded the standard by 42.8%. The maximum time-weighted average concentration in individuals was 27.927 mg/m(3), much higher than the national standard limit. For harmful gas detection in individuals, xylene was 38.4%above the standard level (the highest concentration reached 1447.7 mg/m(3)); moreover, both toluene and ethylbenzene exceeded the national standard at different levels. Among the noise-exposed workers, 71%worked in the environment where the daily noise was above the limit of the national standard (85 dB). Physical examinations in 2010 and 2012 showed that the abnormal rate of audiometry in workers was higher than 15%. Dust (total dust), manganese dioxide, benzene, and noise are the main occupational hazards among the workers in the large shipbuilding factory, and strict protection and control for these hazards should be implemented for the workers in the factory.
Hard and soft age discrimination: the dual nature of workplace discrimination.

PubMed

Stypinska, Justyna; Turek, Konrad

2017-03-01

The paper concentrates on the problem of age discrimination in the labour market and the way it can be conceptualised and measured in a multi-disciplinary way. The approach proposed here combines two understandings of age discrimination-a sociological and legal one, what allows for a fuller and expanded understanding of ageism in the workplace. At the heart of the study is a survey carried out in Poland with a sample of 1000 men and women aged 45-65 years. The study takes a deeper and innovative look into the issue of age discrimination in employment. Confirmatory factor analysis with WLSMV estimation and logistic regressions were used to test the hypotheses. The study shows that age discrimination in labour market can take on different forms: hard and soft, where the hard type of age discrimination mirrors the legally prohibited types of behaviours and those which relate to the actual decisions of employers which can impact on the employee's career development. The soft discrimination corresponds with those occurrences, which are not inscribed in the legal system per se, are occurring predominantly in the interpersonal sphere, but can nevertheless have negative consequences. Soft discrimination was experienced more often (28.6% of respondents) than hard discrimination (15.7%) with higher occurrences among women, persons in precarious job situation or residents of urban areas. The role of education was not confirmed to influence the levels of perceived age discrimination.
Quantum computation with realistic magic-state factories

NASA Astrophysics Data System (ADS)

O'Gorman, Joe; Campbell, Earl T.

2017-03-01

Leading approaches to fault-tolerant quantum computation dedicate a significant portion of the hardware to computational factories that churn out high-fidelity ancillas called magic states. Consequently, efficient and realistic factory design is of paramount importance. Here we present the most detailed resource assessment to date of magic-state factories within a surface code quantum computer, along the way introducing a number of techniques. We show that the block codes of Bravyi and Haah [Phys. Rev. A 86, 052329 (2012), 10.1103/PhysRevA.86.052329] have been systematically undervalued; we track correlated errors both numerically and analytically, providing fidelity estimates without appeal to the union bound. We also introduce a subsystem code realization of these protocols with constant time and low ancilla cost. Additionally, we confirm that magic-state factories have space-time costs that scale as a constant factor of surface code costs. We find that the magic-state factory required for postclassical factoring can be as small as 6.3 million data qubits, ignoring ancilla qubits, assuming 10-4 error gates and the availability of long-range interactions.
General tensor discriminant analysis and gabor features for gait recognition.

PubMed

Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

2007-10-01

The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine
Field hyperspectral data analysis for discriminating spectral behavior of tea plantations under various management practices

NASA Astrophysics Data System (ADS)

Kumar, Amit; Manjunath, K. R.; Meenakshi; Bala, Renu; Sud, R. K.; Singh, R. D.; Panigrahy, Sushma

2013-08-01

The quality and yield of tea depends upon management of tea plantations, which takes into account the factors like type, age of plantation, growth stage, pruning status, light conditions, and disease incidence. Recognizing the importance of hyperspectral data in detecting minute spectral variations in vegetation, the present study was conducted to explore applicability of such data in evaluating these factors. Also stepwise discriminant analysis and principal component analysis were conducted to identify the appropriate bands for accessing the above mentioned factors. The Green region followed by NIR region was found as most appropriate best band for discriminating different types of tea plants, and the tea in sunlit and shade condition. For discriminating age of plantation, growth stage of tea, and diseased and healthy bush, Blue region was most appropriate. The Red and NIR regions were best bands to discriminate pruned and unpruned tea. The study concluded that field hyperspectral data can be efficiently used to know the plantation that need special care and may be an indicator of tea productivity. The spectral signature of these characteristics of tea plantations may also be used to classify the hyperspectral satellite data to derive these parameters at regional scale.
On the energy and baseline optimization to study effects related to the /δ-phase (CP-/T-violation) in neutrino oscillations at a neutrino factory

NASA Astrophysics Data System (ADS)

Bueno, A.; Campanelli, M.; Navas-Concha, S.; Rubbia, A.

2002-06-01

In this paper we discuss the detection of CP- and T-violation effects in the framework of a neutrino factory. We introduce three quantities, which are good discriminants for a non-vanishing complex phase ( δ) in the 3×3 neutrino mixing matrix: Δδ, ΔCP and ΔT. We find that these three discriminants (in vacuum) all scale with L/ Eν, where L is the baseline and Eν the neutrino energy. Matter effects modify the scaling, but these effects are large enough to spoil the sensitivity only for baselines larger than 5000 km. So, in the hypothesis of constant neutrino factory power (i.e., number of muons inversely proportional to muon energy), the sensitivity on the δ-phase is independent of the baseline chosen. Specially interesting is the direct measurement of T-violation from the "wrong-sign" electron channel (i.e., the ΔT discriminant), which involves a comparison of the νe→ νμ and νμ→ νe oscillation rates. However, the νμ→ νe measurement requires magnetic discrimination of the electron charge, experimentally very challenging in a neutrino detector. Since the direction of the electron curvature has to be estimated before the start of the electromagnetic shower, low-energy neutrino beams and hence short baselines, are preferred. In this paper we show, as an example, the exclusion regions in the Δm212- δ plane using the ΔCP and ΔT discriminants for two concrete cases keeping the same L/ Eν ratio (730 km/7.5 GeV and 2900 km/30 GeV). We obtain a similar excluded region provided that the electron detection efficiency is ˜20% and the charge confusion 0.1%. The Δm212 compatible with the LMA solar data can be tested with a flux of 5×10 21 muons. We compare these results with the fit of the visible energy distributions.
Spike detection, characterization, and discrimination using feature analysis software written in LabVIEW.

PubMed

Stewart, C M; Newlands, S D; Perachio, A A

2004-12-01

Rapid and accurate discrimination of single units from extracellular recordings is a fundamental process for the analysis and interpretation of electrophysiological recordings. We present an algorithm that performs detection, characterization, discrimination, and analysis of action potentials from extracellular recording sessions. The program was entirely written in LabVIEW (National Instruments), and requires no external hardware devices or a priori information about action potential shapes. Waveform events are detected by scanning the digital record for voltages that exceed a user-adjustable trigger. Detected events are characterized to determine nine different time and voltage levels for each event. Various algebraic combinations of these waveform features are used as axis choices for 2-D Cartesian plots of events. The user selects axis choices that generate distinct clusters. Multiple clusters may be defined as action potentials by manually generating boundaries of arbitrary shape. Events defined as action potentials are validated by visual inspection of overlain waveforms. Stimulus-response relationships may be identified by selecting any recorded channel for comparison to continuous and average cycle histograms of binned unit data. The algorithm includes novel aspects of feature analysis and acquisition, including higher acquisition rates for electrophysiological data compared to other channels. The program confirms that electrophysiological data may be discriminated with high-speed and efficiency using algebraic combinations of waveform features derived from high-speed digital records.
Discrimination of whisky brands and counterfeit identification by UV-Vis spectroscopy and multivariate data analysis.

PubMed

Martins, Angélica Rocha; Talhavini, Márcio; Vieira, Maurício Leite; Zacca, Jorge Jardim; Braga, Jez Willian Batista

2017-08-15

The discrimination of whisky brands and counterfeit identification were performed by UV-Vis spectroscopy combined with partial least squares for discriminant analysis (PLS-DA). In the proposed method all spectra were obtained with no sample preparation. The discrimination models were built with the employment of seven whisky brands: Red Label, Black Label, White Horse, Chivas Regal (12years), Ballantine's Finest, Old Parr and Natu Nobilis. The method was validated with an independent test set of authentic samples belonging to the seven selected brands and another eleven brands not included in the training samples. Furthermore, seventy-three counterfeit samples were also used to validate the method. Results showed correct classification rates for genuine and false samples over 98.6% and 93.1%, respectively, indicating that the method can be helpful for the forensic analysis of whisky samples. Copyright © 2017 Elsevier Ltd. All rights reserved.
The International Design Study for the Neutrino Factory

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

Long, K.

2008-02-21

The International Design Study for a future Neutrino Factory and super-beam facility (the ISS) established the physics case for a high-precision programme of long-baseline neutrino-oscillation measurements. The ISS also identified baseline specifications for the Neutrino Factory accelerator complex and the neutrino detector systems. This paper summarises the objectives of the International Design Study for the Neutrino Factory (the IDS-NF). The IDS-NF will build on the work of the ISS to deliver a Reference Design Report for the Neutrino Factory by 2012/13 and an Interim Design Report by 2010/11.
Longitudinal Discriminant Analysis of Hemoglobin Level for Predicting Preeclampsia

PubMed Central

Nasiri, Malihe; Faghihzadeh, Soghrat; Alavi Majd, Hamid; Zayeri, Farid; Kariman, Noorosadat; Safavi Ardebili, Nastaran

2015-01-01

Background: Preeclampsia is one of the most serious complications during pregnancy with important effects on health of mother and fetus that causes maternal and fetal morbidity and mortality. This study was performed to evaluate whether high levels of hemoglobin may increase the risk of preeclampsia. Objectives: The present study aimed to predict preeclampsia by the hemoglobin profiles through longitudinal discriminant analysis and comparing the error rate of discrimination in longitudinal and cross sectional data. Patients and Methods: In a prospective cohort study from October 2010 to July 2011, 650 pregnant women referred to the prenatal clinic of Milad Hospital in Tehran were evaluated in 3 stages. The hemoglobin level of each woman was measured in the first, second, and third trimester of pregnancy by an expert technician. The subjects were followed up to delivery and preeclampsia was the main outcome under study. The covariance pattern and linear-mixed effects models are common methods that were applied for discriminant analysis of longitudinal data. Also Student t, Mann-Whitney U, and chi-square tests were used for comparing the demographic and clinical characteristics between two groups. Statistical analyses were performed using the SAS software version 9.1. Results: The prevalence rate of preeclampsia was 7.2% (47 women). The women with preeclampsia had a higher mean of hemoglobin values and the difference was 0.46 g/dL (P = 0.003). Also the mean of hemoglobin in the first trimester was higher than that of the second trimester, and was lower than that of the third trimester and the differences were significant (P = 0.015 and P < 0.001, respectively). The sensitivity for longitudinal data and cross-sectional data in three trimesters was 90%, 67%, 72%, and 54% and the specificity was 88%, 55%, 63%, and 50%, respectively. Conclusions: The levels of hemoglobin can be used to predict preeclampsia and monitoring the pregnant women and its regular measure in 3
A reference architecture for the component factory

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Caldiera, Gianluigi; Cantone, Giovanni

1992-01-01

Software reuse can be achieved through an organization that focuses on utilization of life cycle products from previous developments. The component factory is both an example of the more general concepts of experience and domain factory and an organizational unit worth being considered independently. The critical features of such an organization are flexibility and continuous improvement. In order to achieve these features we can represent the architecture of the factory at different levels of abstraction and define a reference architecture from which specific architectures can be derived by instantiation. A reference architecture is an implementation and organization independent representation of the component factory and its environment. The paper outlines this reference architecture, discusses the instantiation process, and presents some examples of specific architectures by comparing them in the framework of the reference model.
Acoustic scale modelling of factories, part II: 1-50 Cale model investigations of factory sound fields

NASA Astrophysics Data System (ADS)

Hodgson, M. R.; Orlowski, R. J.

1987-03-01

In this second part of a report on factory scale modelling use of a 1:50 scale variable model as a research tool is described. Details of the model are presented. The results of measurements of reverberation time and sound propagation, made in various model configurations, are used to investigate the main factors influencing factory sound fields, and the applicability of the Sabine theory to factories. The parameters investigated are the enclosure geometry (aspect ratio, volume and roof pitch), surface absorption and fittings (density, size, surface area, vertical distribution and specific types). Despite certain limitations and uncertainties resulting, for example, from surprising results associated with surface absorption, models are shown to be effective research tools. The inapplicability of the Sabine theory is confirmed and elucidated.
Discriminant forest classification method and system

DOEpatents

Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

2012-11-06

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.
Sexing California gulls using morphometrics and discriminant function analysis

USGS Publications Warehouse

Herring, Garth; Ackerman, Joshua T.; Eagles-Smith, Collin A.; Takekawa, John Y.

2010-01-01

A discriminant function analysis (DFA) model was developed with DNA sex verification so that external morphology could be used to sex 203 adult California Gulls (Larus californicus) in San Francisco Bay (SFB). The best model was 97% accurate and included head-to-bill length, culmen depth at the gonys, and wing length. Using an iterative process, the model was simplified to a single measurement (head-to-bill length) that still assigned sex correctly 94% of the time. A previous California Gull sex determination model developed for a population in Wyoming was then assessed by fitting SFB California Gull measurement data to the Wyoming model; this new model failed to converge on the same measurements as those originally used by the Wyoming model. Results from the SFB discriminant function model were compared to the Wyoming model results (by using SFB data with the Wyoming model); the SFB model was 7% more accurate for SFB California gulls. The simplified DFA model (head-to-bill length only) provided highly accurate results (94%) and minimized the measurements and time required to accurately sex California Gulls.
Factorial structure and convergent and discriminant validity of the E (Empathy) scale.

PubMed

Tran, Ulrich S; Laireiter, Anton-Rupert; Schmitt, David P; Neuner, Christine; Leibetseder, Max; Szente-Voracek, Sara Leyla; Voracek, Martin

2013-10-01

The Empathy (E) scale has been proposed as a theoretically and psychometrically more satisfying alternative to existing self-report measures of empathy. Its four scales (facets) cover both components (cognitive vs. emotional) and both reality statuses (fictitious vs. real-life) of empathy in pairwise combinations. Confirmatory factor analyses of the E-scale in an Austrian community sample (N = 794) suggested that one prior assumption, namely the mutual orthogonality of these facets, may partly need revision; particularly, the E-scale facets seemed to reflect more strongly differences in the reality statuses than in the components of empathy. Utilizing numerous informative psychological traits, the scale's convergent and discriminant validity were examined. E-scale scores were consistently predicted by sex-related and relationship-related constructs and measures of antisocial attitudes and behavior. Among the Big Five personality dimensions, openness emerged as a major positive correlate of empathy. Sex and age were demographic correlates of E-scale scores (higher in women and the younger). Findings were discussed with regards to the definition and measurement of empathy.
Prostate lesion detection and localization based on locality alignment discriminant analysis

NASA Astrophysics Data System (ADS)

Lin, Mingquan; Chen, Weifu; Zhao, Mingbo; Gibson, Eli; Bastian-Jordan, Matthew; Cool, Derek W.; Kassam, Zahra; Chow, Tommy W. S.; Ward, Aaron; Chiu, Bernard

2017-03-01

Prostatic adenocarcinoma is one of the most commonly occurring cancers among men in the world, and it also the most curable cancer when it is detected early. Multiparametric MRI (mpMRI) combines anatomic and functional prostate imaging techniques, which have been shown to produce high sensitivity and specificity in cancer localization, which is important in planning biopsies and focal therapies. However, in previous investigations, lesion localization was achieved mainly by manual segmentation, which is time-consuming and prone to observer variability. Here, we developed an algorithm based on locality alignment discriminant analysis (LADA) technique, which can be considered as a version of linear discriminant analysis (LDA) localized to patches in the feature space. Sensitivity, specificity and accuracy generated by the proposed algorithm in five prostates by LADA were 52.2%, 89.1% and 85.1% respectively, compared to 31.3%, 85.3% and 80.9% generated by LDA. The delineation accuracy attainable by this tool has a potential in increasing the cancer detection rate in biopsies and in minimizing collateral damage of surrounding tissues in focal therapies.
Discriminative analysis of lip motion features for speaker identification and speech-reading.

PubMed

Cetingül, H Ertan; Yemez, Yücel; Erzin, Engin; Tekalp, A Murat

2006-10-01

There have been several studies that jointly use audio, lip intensity, and lip geometry information for speaker identification and speech-reading applications. This paper proposes using explicit lip motion information, instead of or in addition to lip intensity and/or geometry information, for speaker identification and speech-reading within a unified feature selection and discrimination analysis framework, and addresses two important issues: 1) Is using explicit lip motion information useful, and, 2) if so, what are the best lip motion features for these two applications? The best lip motion features for speaker identification are considered to be those that result in the highest discrimination of individual speakers in a population, whereas for speech-reading, the best features are those providing the highest phoneme/word/phrase recognition rate. Several lip motion feature candidates have been considered including dense motion features within a bounding box about the lip, lip contour motion features, and combination of these with lip shape features. Furthermore, a novel two-stage, spatial, and temporal discrimination analysis is introduced to select the best lip motion features for speaker identification and speech-reading applications. Experimental results using an hidden-Markov-model-based recognition system indicate that using explicit lip motion information provides additional performance gains in both applications, and lip motion features prove more valuable in the case of speech-reading application.
Semi-supervised learning for ordinal Kernel Discriminant Analysis.

PubMed

Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

2016-12-01

Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spectral identification of melon seeds variety based on k-nearest neighbor and Fisher discriminant analysis

NASA Astrophysics Data System (ADS)

Li, Cuiling; Jiang, Kai; Zhao, Xueguan; Fan, Pengfei; Wang, Xiu; Liu, Chuan

2017-10-01

Impurity of melon seeds variety will cause reductions of melon production and economic benefits of farmers, this research aimed to adopt spectral technology combined with chemometrics methods to identify melon seeds variety. Melon seeds whose varieties were "Yi Te Bai", "Yi Te Jin", "Jing Mi NO.7", "Jing Mi NO.11" and " Yi Li Sha Bai "were used as research samples. A simple spectral system was developed to collect reflective spectral data of melon seeds, including a light source unit, a spectral data acquisition unit and a data processing unit, the detection wavelength range of this system was 200-1100nm with spectral resolution of 0.14 7.7nm. The original reflective spectral data was pre-treated with de-trend (DT), multiple scattering correction (MSC), first derivative (FD), normalization (NOR) and Savitzky-Golay (SG) convolution smoothing methods. Principal Component Analysis (PCA) method was adopted to reduce the dimensions of reflective spectral data and extract principal components. K-nearest neighbour (KNN) and Fisher discriminant analysis (FDA) methods were used to develop discriminant models of melon seeds variety based on PCA. Spectral data pretreatments improved the discriminant effects of KNN and FDA, FDA generated better discriminant results than KNN, both KNN and FDA methods produced discriminant accuracies reaching to 90.0% for validation set. Research results showed that using spectral technology in combination with KNN and FDA modelling methods to identify melon seeds variety was feasible.
An Analysis of Discrimination by Real Estate Brokers.

ERIC Educational Resources Information Center

Yinger, John

This paper focuses on designing policies to eliminate discrimination in the sale of single-family houses by analyzing the behavior of the agents who actually do most of the discriminating, namely real estate agents. Discriminatory practices are said to be supported by policies of house builders, lending institutions, and government, and by the…
An electroglottographical analysis-based discriminant function model differentiating multiple sclerosis patients from healthy controls.

PubMed

Vavougios, George D; Doskas, Triantafyllos; Konstantopoulos, Kostas

2018-05-01

Dysarthrophonia is a predominant symptom in many neurological diseases, affecting the quality of life of the patients. In this study, we produced a discriminant function equation that can differentiate MS patients from healthy controls, using electroglottographic variables not analyzed in a previous study. We applied stepwise linear discriminant function analysis in order to produce a function and score derived from electroglottographic variables extracted from a previous study. The derived discriminant function's statistical significance was determined via Wilk's λ test (and the associated p value). Finally, a 2 × 2 confusion matrix was used to determine the function's predictive accuracy, whereas the cross-validated predictive accuracy is estimated via the "leave-one-out" classification process. Discriminant function analysis (DFA) was used to create a linear function of continuous predictors. DFA produced the following model (Wilk's λ = 0.043, χ2 = 388.588, p < 0.0001, Tables 3 and 4): D (MS vs controls) = 0.728*DQx1 mean monologue + 0.325*CQx monologue + 0.298*DFx1 90% range monologue + 0.443*DQx1 90% range reading - 1.490*DQx1 90% range monologue. The derived discriminant score (S1) was used subsequently in order to form the coordinates of a ROC curve. Thus, a cutoff score of - 0.788 for S1 corresponded to a perfect classification (100% sensitivity and 100% specificity, p = 1.67e -22 ). Consistent with previous findings, electroglottographic evaluation represents an easy to implement and potentially important assessment in MS patients, achieving adequate classification accuracy. Further evaluation is needed to determine its use as a biomarker.
Characterization of local complex structures in a recurrence plot to improve nonlinear dynamic discriminant analysis.

PubMed

Ding, Hang

2014-01-01

Structures in recurrence plots (RPs), preserving the rich information of nonlinear invariants and trajectory characteristics, have been increasingly analyzed in dynamic discrimination studies. The conventional analysis of RPs is mainly focused on quantifying the overall diagonal and vertical line structures through a method, called recurrence quantification analysis (RQA). This study extensively explores the information in RPs by quantifying local complex RP structures. To do this, an approach was developed to analyze the combination of three major RQA variables: determinism, laminarity, and recurrence rate (DLR) in a metawindow moving over a RP. It was then evaluated in two experiments discriminating (1) ideal nonlinear dynamic series emulated from the Lorenz system with different control parameters and (2) data sets of human heart rate regulations with normal sinus rhythms (n = 18) and congestive heart failure (n = 29). Finally, the DLR was compared with seven major RQA variables in terms of discriminatory power, measured by standardized mean difference (DSMD). In the two experiments, DLR resulted in the highest discriminatory power with DSMD = 2.53 and 0.98, respectively, which were 7.41 and 2.09 times the best performance from RQA. The study also revealed that the optimal RP structures for the discriminations were neither typical diagonal structures nor vertical structures. These findings indicate that local complex RP structures contain some rich information unexploited by RQA. Therefore, future research to extensively analyze complex RP structures would potentially improve the effectiveness of the RP analysis in dynamic discrimination studies.
Liquid contrabands classification based on energy dispersive X-ray diffraction and hybrid discriminant analysis

NASA Astrophysics Data System (ADS)

YangDai, Tianyi; Zhang, Li

2016-02-01

Energy dispersive X-ray diffraction (EDXRD) combined with hybrid discriminant analysis (HDA) has been utilized for classifying the liquid materials for the first time. The XRD spectra of 37 kinds of liquid contrabands and daily supplies were obtained using an EDXRD test bed facility. The unique spectra of different samples reveal XRD's capability to distinguish liquid contrabands from daily supplies. In order to create a system to detect liquid contrabands, the diffraction spectra were subjected to HDA which is the combination of principal components analysis (PCA) and linear discriminant analysis (LDA). Experiments based on the leave-one-out method demonstrate that HDA is a practical method with higher classification accuracy and lower noise sensitivity than the other methods in this application. The study shows the great capability and potential of the combination of XRD and HDA for liquid contrabands classification.
Discriminative Ocular Artifact Correction for Feature Learning in EEG Analysis.

PubMed

Xinyang Li; Cuntai Guan; Haihong Zhang; Kai Keng Ang

2017-08-01

Electrooculogram (EOG) artifact contamination is a common critical issue in general electroencephalogram (EEG) studies as well as in brain-computer interface (BCI) research. It is especially challenging when dedicated EOG channels are unavailable or when there are very few EEG channels available for independent component analysis based ocular artifact removal. It is even more challenging to avoid loss of the signal of interest during the artifact correction process, where the signal of interest can be multiple magnitudes weaker than the artifact. To address these issues, we propose a novel discriminative ocular artifact correction approach for feature learning in EEG analysis. Without extra ocular movement measurements, the artifact is extracted from raw EEG data, which is totally automatic and requires no visual inspection of artifacts. Then, artifact correction is optimized jointly with feature extraction by maximizing oscillatory correlations between trials from the same class and minimizing them between trials from different classes. We evaluate this approach on a real-world EEG dataset comprising 68 subjects performing cognitive tasks. The results showed that the approach is capable of not only suppressing the artifact components but also improving the discriminative power of a classifier with statistical significance. We also demonstrate that the proposed method addresses the confounding issues induced by ocular movements in cognitive EEG study.
Discrimination of cultivation ages and cultivars of ginseng leaves using Fourier transform infrared spectroscopy combined with multivariate analysis

PubMed Central

Kwon, Yong-Kook; Ahn, Myung Suk; Park, Jong Suk; Liu, Jang Ryol; In, Dong Su; Min, Byung Whan; Kim, Suk Weon

2013-01-01

To determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng. PMID:24558311
The Physics of the B Factories

NASA Astrophysics Data System (ADS)

Bevan, A. J.; Golob, B.; Mannel, Th.; Prell, S.; Yabsley, B. D.; Aihara, H.; Anulli, F.; Arnaud, N.; Aushev, T.; Beneke, M.; Beringer, J.; Bianchi, F.; Bigi, I. I.; Bona, M.; Brambilla, N.; Brodzicka, J.; Chang, P.; Charles, M. J.; Cheng, C. H.; Cheng, H.-Y.; Chistov, R.; Colangelo, P.; Coleman, J. P.; Drutskoy, A.; Druzhinin, V. P.; Eidelman, S.; Eigen, G.; Eisner, A. M.; Faccini, R.; Flood, K. T.; Gambino, P.; Gaz, A.; Gradl, W.; Hayashii, H.; Higuchi, T.; Hulsbergen, W. D.; Hurth, T.; Iijima, T.; Itoh, R.; Jackson, P. D.; Kass, R.; Kolomensky, Yu. G.; Kou, E.; Križan, P.; Kronfeld, A.; Kumano, S.; Kwon, Y. J.; Latham, T. E.; Leith, D. W. G. S.; Lüth, V.; Martinez-Vidal, F.; Meadows, B. T.; Mussa, R.; Nakao, M.; Nishida, S.; Ocariz, J.; Olsen, S. L.; Pakhlov, P.; Pakhlova, G.; Palano, A.; Pich, A.; Playfer, S.; Poluektov, A.; Porter, F. C.; Robertson, S. H.; Roney, J. M.; Roodman, A.; Sakai, Y.; Schwanda, C.; Schwartz, A. J.; Seidl, R.; Sekula, S. J.; Steinhauser, M.; Sumisawa, K.; Swanson, E. S.; Tackmann, F.; Trabelsi, K.; Uehara, S.; Uno, S.; van de Water, R.; Vasseur, G.; Verkerke, W.; Waldi, R.; Wang, M. Z.; Wilson, F. F.; Zupan, J.; Zupanc, A.; Adachi, I.; Albert, J.; Banerjee, Sw.; Bellis, M.; Ben-Haim, E.; Biassoni, P.; Cahn, R. N.; Cartaro, C.; Chauveau, J.; Chen, C.; Chiang, C. C.; Cowan, R.; Dalseno, J.; Davier, M.; Davies, C.; Dingfelder, J. C.; Echenard, B.; Epifanov, D.; Fulsom, B. G.; Gabareen, A. M.; Gary, J. W.; Godang, R.; Graham, M. T.; Hafner, A.; Hamilton, B.; Hartmann, T.; Hayasaka, K.; Hearty, C.; Iwasaki, Y.; Khodjamirian, A.; Kusaka, A.; Kuzmin, A.; Lafferty, G. D.; Lazzaro, A.; Li, J.; Lindemann, D.; Long, O.; Lusiani, A.; Marchiori, G.; Martinelli, M.; Miyabayashi, K.; Mizuk, R.; Mohanty, G. B.; Muller, D. R.; Nakazawa, H.; Ongmongkolkul, P.; Pacetti, S.; Palombo, F.; Pedlar, T. K.; Piilonen, L. E.; Pilloni, A.; Poireau, V.; Prothmann, K.; Pulliam, T.; Rama, M.; Ratcliff, B. N.; Roudeau, P.; Schrenk, S.; Schroeder, T.; Schubert, K. R.; Shen, C. P.; Shwartz, B.; Soffer, A.; Solodov, E. P.; Somov, A.; Starič, M.; Stracka, S.; Telnov, A. V.; Todyshev, K. Yu.; Tsuboyama, T.; Uglov, T.; Vinokurova, A.; Walsh, J. J.; Watanabe, Y.; Won, E.; Wormser, G.; Wright, D. H.; Ye, S.; Zhang, C. C.; Abachi, S.; Abashian, A.; Abe, K.; Abe, N.; Abe, R.; Abe, T.; Abrams, G. S.; Adam, I.; Adamczyk, K.; Adametz, A.; Adye, T.; Agarwal, A.; Ahmed, H.; Ahmed, M.; Ahmed, S.; Ahn, B. S.; Ahn, H. S.; Aitchison, I. J. R.; Akai, K.; Akar, S.; Akatsu, M.; Akemoto, M.; Akhmetshin, R.; Akre, R.; Alam, M. S.; Albert, J. N.; Aleksan, R.; Alexander, J. P.; Alimonti, G.; Allen, M. T.; Allison, J.; Allmendinger, T.; Alsmiller, J. R. G.; Altenburg, D.; Alwyn, K. E.; An, Q.; Anderson, J.; Andreassen, R.; Andreotti, D.; Andreotti, M.; Andress, J. C.; Angelini, C.; Anipko, D.; Anjomshoaa, A.; Anthony, P. L.; Antillon, E. A.; Antonioli, E.; Aoki, K.; Arguin, J. F.; Arinstein, K.; Arisaka, K.; Asai, K.; Asai, M.; Asano, Y.; Asgeirsson, D. J.; Asner, D. M.; Aso, T.; Aspinwall, M. L.; Aston, D.; Atmacan, H.; Aubert, B.; Aulchenko, V.; Ayad, R.; Azemoon, T.; Aziz, T.; Azzolini, V.; Azzopardi, D. E.; Baak, M. A.; Back, J. J.; Bagnasco, S.; Bahinipati, S.; Bailey, D. S.; Bailey, S.; Bailly, P.; van Bakel, N.; Bakich, A. M.; Bala, A.; Balagura, V.; Baldini-Ferroli, R.; Ban, Y.; Banas, E.; Band, H. R.; Banerjee, S.; Baracchini, E.; Barate, R.; Barberio, E.; Barbero, M.; Bard, D. J.; Barillari, T.; Barlow, N. R.; Barlow, R. J.; Barrett, M.; Bartel, W.; Bartelt, J.; Bartoldus, R.; Batignani, G.; Battaglia, M.; Bauer, J. M.; Bay, A.; Beaulieu, M.; Bechtle, P.; Beck, T. W.; Becker, J.; Becla, J.; Bedny, I.; Behari, S.; Behera, P. K.; Behn, E.; Behr, L.; Beigbeder, C.; Beiline, D.; Bell, R.; Bellini, F.; Bellodi, G.; Belous, K.; Benayoun, M.; Benelli, G.; Benitez, J. F.; Benkebil, M.; Berger, N.; Bernabeu, J.; Bernard, D.; Bernet, R.; Bernlochner, F. U.; Berryhill, J. W.; Bertsche, K.; Besson, P.; Best, D. S.; Bettarini, S.; Bettoni, D.; Bhardwaj, V.; Bhimji, W.; Bhuyan, B.; Biagini, M. E.; Biasini, M.; van Bibber, K.; Biesiada, J.; Bingham, I.; Bionta, R. M.; Bischofberger, M.; Bitenc, U.; Bizjak, I.; Blanc, F.; Blaylock, G.; Blinov, V. E.; Bloom, E.; Bloom, P. C.; Blount, N. L.; Blouw, J.; Bly, M.; Blyth, S.; Boeheim, C. T.; Bomben, M.; Bondar, A.; Bondioli, M.; Bonneaud, G. R.; Bonvicini, G.; Booke, M.; Booth, J.; Borean, C.; Borgland, A. W.; Borsato, E.; Bosi, F.; Bosisio, L.; Botov, A. A.; Bougher, J.; Bouldin, K.; Bourgeois, P.; Boutigny, D.; Bowerman, D. A.; Boyarski, A. M.; Boyce, R. F.; Boyd, J. T.; Bozek, A.; Bozzi, C.; Bračko, M.; Brandenburg, G.; Brandt, T.; Brau, B.; Brau, J.; Breon, A. B.; Breton, D.; Brew, C.; Briand, H.; Bright-Thomas, P. G.; Brigljević, V.; Britton, D. I.; Brochard, F.; Broomer, B.; Brose, J.; Browder, T. E.; Brown, C. L.; Brown, C. M.; Brown, D. N.; Browne, M.; Bruinsma, M.; Brunet, S.; Bucci, F.; Buchanan, C.; Buchmueller, O. L.; Bünger, C.; Bugg, W.; Bukin, A. D.; Bula, R.; Bulten, H.; Burchat, P. R.; Burgess, W.; Burke, J. P.; Button-Shafer, J.; Buzykaev, A. R.; Buzzo, A.; Cai, Y.; Calabrese, R.; Calcaterra, A.; Calderini, G.; Camanzi, B.; Campagna, E.; Campagnari, C.; Capra, R.; Carassiti, V.; Carpinelli, M.; Carroll, M.; Casarosa, G.; Casey, B. C. K.; Cason, N. M.; Castelli, G.; Cavallo, N.; Cavoto, G.; Cecchi, A.; Cenci, R.; Cerizza, G.; Cervelli, A.; Ceseracciu, A.; Chai, X.; Chaisanguanthum, K. S.; Chang, M. C.; Chang, Y. H.; Chang, Y. W.; Chao, D. S.; Chao, M.; Chao, Y.; Charles, E.; Chavez, C. A.; Cheaib, R.; Chekelian, V.; Chen, A.; Chen, E.; Chen, G. P.; Chen, H. F.; Chen, J.-H.; Chen, J. C.; Chen, K. F.; Chen, P.; Chen, S.; Chen, W. T.; Chen, X.; Chen, X. R.; Chen, Y. Q.; Cheng, B.; Cheon, B. G.; Chevalier, N.; Chia, Y. M.; Chidzik, S.; Chilikin, K.; Chistiakova, M. V.; Cizeron, R.; Cho, I. S.; Cho, K.; Chobanova, V.; Choi, H. H. F.; Choi, K. S.; Choi, S. K.; Choi, Y.; Choi, Y. K.; Christ, S.; Chu, P. H.; Chun, S.; Chuvikov, A.; Cibinetto, G.; Cinabro, D.; Clark, A. R.; Clark, P. J.; Clarke, C. K.; Claus, R.; Claxton, B.; Clifton, Z. C.; Cochran, J.; Cohen-Tanugi, J.; Cohn, H.; Colberg, T.; Cole, S.; Colecchia, F.; Condurache, C.; Contri, R.; Convert, P.; Convery, M. R.; Cooke, P.; Copty, N.; Cormack, C. M.; Dal Corso, F.; Corwin, L. A.; Cossutti, F.; Cote, D.; Cotta Ramusino, A.; Cottingham, W. N.; Couderc, F.; Coupal, D. P.; Covarelli, R.; Cowan, G.; Craddock, W. W.; Crane, G.; Crawley, H. B.; Cremaldi, L.; Crescente, A.; Cristinziani, M.; Crnkovic, J.; Crosetti, G.; Cuhadar-Donszelmann, T.; Cunha, A.; Curry, S.; D'Orazio, A.; Dû, S.; Dahlinger, G.; Dahmes, B.; Dallapiccola, C.; Danielson, N.; Danilov, M.; Das, A.; Dash, M.; Dasu, S.; Datta, M.; Daudo, F.; Dauncey, P. D.; David, P.; Davis, C. L.; Day, C. T.; De Mori, F.; De Domenico, G.; De Groot, N.; De la Vaissière, C.; de la Vaissière, Ch.; de Lesquen, A.; De Nardo, G.; de Sangro, R.; De Silva, A.; DeBarger, S.; Decker, F. J.; del Amo Sanchez, P.; Del Buono, L.; Del Gamba, V.; del Re, D.; Della Ricca, G.; Denig, A. G.; Derkach, D.; Derrington, I. M.; DeStaebler, H.; Destree, J.; Devmal, S.; Dey, B.; Di Girolamo, B.; Marco, E. Di; Dickopp, M.; Dima, M. O.; Dittrich, S.; Dittongo, S.; Dixon, P.; Dneprovsky, L.; Dohou, F.; Doi, Y.; Doležal, Z.; Doll, D. A.; Donald, M.; Dong, L.; Dong, L. Y.; Dorfan, J.; Dorigo, A.; Dorsten, M. P.; Dowd, R.; Dowdell, J.; Drásal, Z.; Dragic, J.; Drummond, B. W.; Dubitzky, R. S.; Dubois-Felsmann, G. P.; Dubrovin, M. S.; Duh, Y. C.; Duh, Y. T.; Dujmic, D.; Dungel, W.; Dunwoodie, W.; Dutta, D.; Dvoretskii, A.; Dyce, N.; Ebert, M.; Eckhart, E. A.; Ecklund, S.; Eckmann, R.; Eckstein, P.; Edgar, C. L.; Edwards, A. J.; Egede, U.; Eichenbaum, A. M.; Elmer, P.; Emery, S.; Enari, Y.; Enomoto, R.; Erdos, E.; Erickson, R.; Ernst, J. A.; Erwin, R. J.; Escalier, M.; Eschenburg, V.; Eschrich, I.; Esen, S.; Esteve, L.; Evangelisti, F.; Everton, C. W.; Eyges, V.; Fabby, C.; Fabozzi, F.; Fahey, S.; Falbo, M.; Fan, S.; Fang, F.; Fanin, C.; Farbin, A.; Farhat, H.; Fast, J. E.; Feindt, M.; Fella, A.; Feltresi, E.; Ferber, T.; Fernholz, R. E.; Ferrag, S.; Ferrarotto, F.; Ferroni, F.; Field, R. C.; Filippi, A.; Finocchiaro, G.; Fioravanti, E.; Firmino da Costa, J.; Fischer, P.-A.; Fisher, A. S.; Fisher, P. H.; Flacco, C. J.; Flack, R. L.; Flaecher, H. U.; Flanagan, J.; Flanigan, J. M.; Ford, K. E.; Ford, W. T.; Forster, I. J.; Forti, A. C.; Forti, F.; Fortin, D.; Foster, B.; Foulkes, S. D.; Fouque, G.; Fox, J.; Franchini, P.; Franco Sevilla, M.; Franek, B.; Frank, E. D.; Fransham, K. B.; Fratina, S.; Fratini, K.; Frey, A.; Frey, R.; Friedl, M.; Fritsch, M.; Fry, J. R.; Fujii, H.; Fujikawa, M.; Fujita, Y.; Fujiyama, Y.; Fukunaga, C.; Fukushima, M.; Fullwood, J.; Funahashi, Y.; Funakoshi, Y.; Furano, F.; Furman, M.; Furukawa, K.; Futterschneider, H.; Gabathuler, E.; Gabriel, T. A.; Gabyshev, N.; Gaede, F.; Gagliardi, N.; Gaidot, A.; Gaillard, J.-M.; Gaillard, J. R.; Galagedera, S.; Galeazzi, F.; Gallo, F.; Gamba, D.; Gamet, R.; Gan, K. K.; Gandini, P.; Ganguly, S.; Ganzhur, S. F.; Gao, Y. Y.; Gaponenko, I.; Garmash, A.; Garra Tico, J.; Garzia, I.; Gaspero, M.; Gastaldi, F.; Gatto, C.; Gaur, V.; Geddes, N. I.; Geld, T. L.; Genat, J.-F.; George, K. A.; George, M.; George, S.; Georgette, Z.; Gershon, T. J.; Gill, M. S.; Gillard, R.; Gilman, J. D.; Giordano, F.; Giorgi, M. A.; Giraud, P.-F.; Gladney, L.; Glanzman, T.; Glattauer, R.; Go, A.; Goetzen, K.; Goh, Y. M.; Gokhroo, G.; Goldenzweig, P.; Golubev, V. B.; Gopal, G. P.; Gordon, A.; Gorišek, A.; Goriletsky, V. I.; Gorodeisky, R.; Gosset, L.; Gotow, K.; Gowdy, S. J.; Graffin, P.; Grancagnolo, S.; Grauges, E.; Graziani, G.; Green, M. G.; Greene, M. G.; Grenier, G. J.; Grenier, P.; Griessinger, K.; Grillo, A. A.; Grinyov, B. V.; Gritsan, A. V.; Grosdidier, G.; Grosse Perdekamp, M.; Grosso, P.; Grothe, M.; Groysman, Y.; Grünberg, O.; Guido, E.; Guler, H.; Gunawardane, N. J. W.; Guo, Q. H.; Guo, R. S.; Guo, Z. J.; Guttman, N.; Ha, H.; Ha, H. C.; Haas, T.; Haba, J.; Hachtel, J.; Hadavand, H. K.; Hadig, T.; Hagner, C.; Haire, M.; Haitani, F.; Haji, T.; Haller, G.; Halyo, V.; Hamano, K.; Hamasaki, H.; Hamel de Monchenault, G.; Hamilton, J.; Hamilton, R.; Hamon, O.; Han, B. Y.; Han, Y. L.; Hanada, H.; Hanagaki, K.; Handa, F.; Hanson, J. E.; Hanushevsky, A.; Hara, K.; Hara, T.; Harada, Y.; Harrison, P. F.; Harrison, T. J.; Harrop, B.; Hart, A. J.; Hart, P. A.; Hartfiel, B. L.; Harton, J. L.; Haruyama, T.; Hasan, A.; Hasegawa, Y.; Hast, C.; Hastings, N. C.; Hasuko, K.; Hauke, A.; Hawkes, C. M.; Hayashi, K.; Hazumi, M.; Hee, C.; Heenan, E. 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E.; Walker, D.; Walkowiak, W.; Wallom, D.; Wang, C. C.; Wang, C. H.; Wang, J.; Wang, J. G.; Wang, K.; Wang, L.; Wang, L. L.; Wang, P.; Wang, T. J.; Wang, W. F.; Wang, X. L.; Wang, Y. F.; Wappler, F. R.; Watanabe, M.; Watson, A. T.; Watson, J. E.; Watson, N. K.; Watt, M.; Weatherall, J. H.; Weaver, M.; Weber, T.; Wedd, R.; Wei, J. T.; Weidemann, A. W.; Weinstein, A. J. R.; Wenzel, W. A.; West, C. A.; West, C. G.; West, T. J.; White, E.; White, R. M.; Wicht, J.; Widhalm, L.; Wiechczynski, J.; Wienands, U.; Wilden, L.; Wilder, M.; Williams, D. C.; Williams, G.; Williams, J. C.; Williams, K. M.; Williams, M. I.; Willocq, S. Y.; Wilson, J. R.; Wilson, M. G.; Wilson, R. J.; Winklmeier, F.; Winstrom, L. O.; Winter, M. A.; Wisniewski, W. J.; Wittgen, M.; Wittlin, J.; Wittmer, W.; Wixted, R.; Woch, A.; Wogsland, B. J.; Won, E.; Wong, Q. K.; Wray, B. C.; Wren, A. C.; Wright, D. M.; Wu, C. H.; Wu, J.; Wu, S. L.; Wulsin, H. W.; Xella, S. M.; Xie, Q. L.; Xie, Y.; Xu, Z. Z.; Yéche, Ch.; Yamada, Y.; Yamaga, M.; Yamaguchi, A.; Yamaguchi, H.; Yamaki, T.; Yamamoto, H.; Yamamoto, N.; Yamamoto, R. K.; Yamamoto, S.; Yamanaka, T.; Yamaoka, H.; Yamaoka, J.; Yamaoka, Y.; Yamashita, Y.; Yamauchi, M.; Yan, D. S.; Yan, Y.; Yanai, H.; Yanaka, S.; Yang, H.; Yang, R.; Yang, S.; Yarritu, A. K.; Yashchenko, S.; Yashima, J.; Yasin, Z.; Yasu, Y.; Ye, S. W.; Yeh, P.; Yi, J. I.; Yi, K.; Yi, M.; Yin, Z. W.; Ying, J.; Yocky, G.; Yokoyama, K.; Yokoyama, M.; Yokoyama, T.; Yoshida, K.; Yoshida, M.; Yoshimura, Y.; Young, C. C.; Yu, C. X.; Yu, Z.; Yuan, C. Z.; Yuan, Y.; Yumiceva, F. X.; Yusa, Y.; Yushkov, A. N.; Yuta, H.; Zacek, V.; Zain, S. B.; Zallo, A.; Zambito, S.; Zander, D.; Zang, S. L.; Zanin, D.; Zaslavsky, B. G.; Zeng, Q. L.; Zghiche, A.; Zhang, B.; Zhang, J.; Zhang, J.; Zhang, L.; Zhang, L. M.; Zhang, S. Q.; Zhang, Z. P.; Zhao, H. W.; Zhao, M.; Zhao, Z. G.; Zheng, Y.; Zheng, Y. H.; Zheng, Z. P.; Zhilich, V.; Zhou, P.; Zhu, R. Y.; Zhu, Y. S.; Zhu, Z. M.; Zhulanov, V.; Ziegler, T.; Ziegler, V.; Zioulas, G.; Zisman, M.; Zito, M.; Zürcher, D.; Zwahlen, N.; Zyukova, O.; Živko, T.; Žontar, D.

2014-11-01

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C. Please note that version 3 on the archive is the auxiliary version of the Physics of the B Factories book. This uses the notation alpha, beta, gamma for the angles of the Unitarity Triangle. The nominal version uses the notation phi_1, phi_2 and phi_3. Please cite this work as Eur. Phys. J. C74 (2014) 3026.
Effective application of multiple locus variable number of tandem repeats analysis to tracing Staphylococcus aureus in food-processing environment.

PubMed

Rešková, Z; Koreňová, J; Kuchta, T

2014-04-01

A total of 256 isolates of Staphylococcus aureus were isolated from 98 samples (34 swabs and 64 food samples) obtained from small or medium meat- and cheese-processing plants in Slovakia. The strains were genotypically characterized by multiple locus variable number of tandem repeats analysis (MLVA), involving multiplex polymerase chain reaction (PCR) with subsequent separation of the amplified DNA fragments by an automated flow-through gel electrophoresis. With the panel of isolates, MLVA produced 31 profile types, which was a sufficient discrimination to facilitate the description of spatial and temporal aspects of contamination. Further data on MLVA discrimination were obtained by typing a subpanel of strains by multiple locus sequence typing (MLST). MLVA coupled to automated electrophoresis proved to be an effective, comparatively fast and inexpensive method for tracing S. aureus contamination of food-processing factories. Subspecies genotyping of microbial contaminants in food-processing factories may facilitate identification of spatial and temporal aspects of the contamination. This may help to properly manage the process hygiene. With S. aureus, multiple locus variable number of tandem repeats analysis (MLVA) proved to be an effective method for the purpose, being sufficiently discriminative, yet comparatively fast and inexpensive. The application of automated flow-through gel electrophoresis to separation of DNA fragments produced by multiplex PCR helped to improve the accuracy and speed of the method. © 2013 The Society for Applied Microbiology.
Discrimination of inflammatory bowel disease using Raman spectroscopy and linear discriminant analysis methods

NASA Astrophysics Data System (ADS)

Ding, Hao; Cao, Ming; DuPont, Andrew W.; Scott, Larry D.; Guha, Sushovan; Singhal, Shashideep; Younes, Mamoun; Pence, Isaac; Herline, Alan; Schwartz, David; Xu, Hua; Mahadevan-Jansen, Anita; Bi, Xiaohong

2016-03-01

Inflammatory bowel disease (IBD) is an idiopathic disease that is typically characterized by chronic inflammation of the gastrointestinal tract. Recently much effort has been devoted to the development of novel diagnostic tools that can assist physicians for fast, accurate, and automated diagnosis of the disease. Previous research based on Raman spectroscopy has shown promising results in differentiating IBD patients from normal screening cases. In the current study, we examined IBD patients in vivo through a colonoscope-coupled Raman system. Optical diagnosis for IBD discrimination was conducted based on full-range spectra using multivariate statistical methods. Further, we incorporated several feature selection methods in machine learning into the classification model. The diagnostic performance for disease differentiation was significantly improved after feature selection. Our results showed that improved IBD diagnosis can be achieved using Raman spectroscopy in combination with multivariate analysis and feature selection.
Gender identification of Caspian Terns using external morphology and discriminant function analysis

USGS Publications Warehouse

Ackerman, Joshua T.; Takekawa, John Y.; Bluso, J.D.; Yee, J.L.; Eagles-Smith, Collin A.

2008-01-01

Caspian Tern (Sterna caspia) plumage characteristics are sexually monochromatic and gender cannot easily be distinguished in the field without extensive behavioral observations. We assessed sexual size dimorphism and developed a discriminant function to assign gender in Caspian Terns based on external morphology. We collected and measured Caspian Terns in San Francisco Bay, California, and confirmed their gender based on necropsy and genetic analysis. Of the eight morphological measurements we examined, only bill depth at the gonys and head plus bill length differed between males and females with males being larger than females. A discriminant function using both bill depth at the gonys and head plus bill length accurately assigned gender of 83% of terns for which gender was known. We improved the accuracy of our discriminant function to 90% by excluding individuals that had less than a 75% posterior probability of correctly being assigned to gender. Caspian Terns showed little sexual size dimorphism in many morphometries, but our results indicate they can be reliably assigned to gender in the field using two morphological measurements.
HIV-related stigma and self-disclosure: the mediating and moderating role of anticipated discrimination among people living with HIV/AIDS in Akure Nigeria.

PubMed

Olley, B O; Ogunde, M J; Oso, P O; Ishola, A

2016-01-01

Although links between HIV-related stigma and self-disclosure of HIV status among people living with HIV have been well established, it is unclear whether levels of perceived discrimination are differentially associated with self-disclosure. The present study using a multi-factorial survey design investigated the role of stigma and other self-related factors (e.g., anticipated discrimination, self-esteem, HIV-related factors [e.g., drug use combination; knowledge of duration of HIV diagnosis] and socio-demographic factors [e.g., multiple spouse; age, gender, educational level] and psychological distress [depression]) in self-disclosure among People living with HIV/AIDs has been added (PLWHA) on follow-up management in State Specialist Hospital Akure, Nigeria. One hundred and thirty nine HIV/AIDS patients (49 males and 90 females) participated in the study. Mean age and mean time in months since diagnosis were 39.56 ± 10.26 and 37.78 ± 48.34, respectively. Four variables: multiple spouse, anticipated discrimination, HIV-related stigma and self-esteem were related to self-disclosure at (p < .05). Product-term regression analyses demonstrated that perceived discrimination mediated the relationship between self-esteem (Sobel test: z = 2.09, Aroian = 2.06, p < .001), perceived stigma (Sobel test: z = 2.78, Aroaian = 2.75 p < .01) and self-disclosure. Interaction term analysis between HIV-related stigma t (5, 137) = 1.69, p > .05, self-esteem t (5, 137) = .59, p > .05 and anticipated discrimination were non-significant, suggesting a non-moderation effect of discrimination and disclosure. The results indicate that anticipated discrimination may impact HIV-related stigma to reduce self-disclosure among the PLWHAs in Akure, Nigeria. Interventions should incorporate anticipated discrimination in educational programs of HIV stigma in encouraging self-disclosure among PLWHAs.
An examination of effect estimation in factorial and standardly-tailored designs

PubMed Central

Allore, Heather G; Murphy, Terrence E

2012-01-01

individual component effects from the family of factorial designs and this limitation for standardly-tailored designs. We use the phrase ‘factorial designs’ to describe full-factorial designs and their derivatives including the fractional factorial, partial factorial, incomplete factorial and modified reciprocal designs. We suggest two potential directions for designing multicomponent interventions to facilitate unbiased estimates of individual interventional components. Results Full factorial designs and their variants are the most common multicomponent trial design described in the literature and differ meaningfully from standardly-tailored designs. Factorial and standardly-tailored designs result in similar estimates of net effect with different levels of precision. Unbiased estimation of individual component effects from a standardly-tailored design will require new methodology. Limitations Although clinically relevant in geriatrics, previous applications of standardly-tailored designs have not provided unbiased estimates of the effects of individual interventional components. Discussion Future directions to estimate individual component effects from standardly-tailored designs include applying D-optimal designs and creating independent linear combinations of risk factors analogous to factor analysis. Conclusion Methods are needed to extract unbiased estimates of the effects of individual interventional components from standardly-tailored designs. PMID:18375650
Testing for Factorial Invariance in the Context of Construct Validation

ERIC Educational Resources Information Center

Dimitrov, Dimiter M.

2010-01-01

This article describes the logic and procedures behind testing for factorial invariance across groups in the context of construct validation. The procedures include testing for configural, measurement, and structural invariance in the framework of multiple-group confirmatory factor analysis (CFA). The "forward" (sequential constraint imposition)…
Implementing Clinical Research Using Factorial Designs: A Primer.

PubMed

Baker, Timothy B; Smith, Stevens S; Bolt, Daniel M; Loh, Wei-Yin; Mermelstein, Robin; Fiore, Michael C; Piper, Megan E; Collins, Linda M

2017-07-01

Factorial experiments have rarely been used in the development or evaluation of clinical interventions. However, factorial designs offer advantages over randomized controlled trial designs, the latter being much more frequently used in such research. Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components. Such advantages have led methodologists to advocate for the greater use of factorial designs in research on clinical interventions (Collins, Dziak, & Li, 2009). However, researchers considering the use of such designs in clinical research face a series of choices that have consequential implications for the interpretability and value of the experimental results. These choices include: whether to use a factorial design, selection of the number and type of factors to include, how to address the compatibility of the different factors included, whether and how to avoid confounds between the type and number of interventions a participant receives, and how to interpret interactions. The use of factorial designs in clinical intervention research poses choices that differ from those typically considered in randomized clinical trial designs. However, the great information yield of the former encourages clinical researchers' increased and careful execution of such designs. Copyright © 2017. Published by Elsevier Ltd.
Race, Sex, and Discrimination in School Settings: A Multilevel Analysis of Associations With Delinquency.

PubMed

Chambers, Brittany D; Erausquin, Jennifer Toller

2018-02-01

Adolescence is a critical phase of development and experimentation with delinquent behaviors. There is a growing body of literature exploring individual and structural impacts of discrimination on health outcomes and delinquent behaviors. However, there is limited research assessing how school diversity and discrimination impact students' delinquent behaviors. In response, the purpose of this study was to assess if individual- and school-level indicators of discrimination and diversity were associated with student delinquent behaviors among African American and White students. We analyzed Wave I (1994-1995) data from the National Longitudinal Study of Adolescent Health. Our analysis was limited to 8947 African American and White students (73% White, 48% male, and 88% parent ≥ high school education). We used multilevel zero-inflated negative binomial regression to test the association of individual- and school characteristics and discrimination with the number of self-reported delinquent behaviors. Race, sex, perceived peer inclusion, and teacher discrimination were predictors of students' delinquent behaviors. The average school perceived peer inclusion and percentage of African Americans in teaching roles were associated with delinquent behaviors. Findings from this study highlight the potential for intervention at the interpersonal and school levels to reduce delinquency among African American and White students. © 2018, American School Health Association.
1. VIEW TO SOUTHEAST (NORTHWEST CORNER OF EDIBLE FATS FACTORY) ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

1. VIEW TO SOUTHEAST (NORTHWEST CORNER OF EDIBLE FATS FACTORY) - Wilson's Oil House, Lard Refinery, & Edible Fats Factory, Edible Fats Factory, 2801 Southwest Fifteenth Street, Oklahoma City, Oklahoma County, OK
3. VIEW TO SOUTHWEST (NORTHEAST CORNER OF EDIBLE FATS FACTORY) ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

3. VIEW TO SOUTHWEST (NORTHEAST CORNER OF EDIBLE FATS FACTORY) - Wilson's Oil House, Lard Refinery, & Edible Fats Factory, Edible Fats Factory, 2801 Southwest Fifteenth Street, Oklahoma City, Oklahoma County, OK
The Physics of the B Factories

DOE PAGES

Bevan, A. J.; Golob, B.; Mannel, Th.; ...

2014-11-19

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C.
4. SOUTHEAST CORNER OF EDIBLE FATS FACTORY (CONNECTING BUILDING ON ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

4. SOUTHEAST CORNER OF EDIBLE FATS FACTORY (CONNECTING BUILDING ON THE LEFT) - Wilson's Oil House, Lard Refinery, & Edible Fats Factory, Edible Fats Factory, 2801 Southwest Fifteenth Street, Oklahoma City, Oklahoma County, OK

Intrapopulation variability shaping isotope discrimination and turnover: experimental evidence in arctic foxes.

PubMed

Lecomte, Nicolas; Ahlstrøm, Oystein; Ehrich, Dorothée; Fuglei, Eva; Ims, Rolf A; Yoccoz, Nigel G

2011-01-01

Tissue-specific stable isotope signatures can provide insights into the trophic ecology of consumers and their roles in food webs. Two parameters are central for making valid inferences based on stable isotopes, isotopic discrimination (difference in isotopic ratio between consumer and its diet) and turnover time (renewal process of molecules in a given tissue usually measured when half of the tissue composition has changed). We investigated simultaneously the effects of age, sex, and diet types on the variation of discrimination and half-life in nitrogen and carbon stable isotopes (δ¹⁵N and δ¹³C, respectively) in five tissues (blood cells, plasma, muscle, liver, nail, and hair) of a top predator, the arctic fox Vulpes lagopus. We fed 40 farmed foxes (equal numbers of adults and yearlings of both sexes) with diet capturing the range of resources used by their wild counterparts. We found that, for a single species, six tissues, and three diet types, the range of discrimination values can be almost as large as what is known at the scale of the whole mammalian or avian class. Discrimination varied depending on sex, age, tissue, and diet types, ranging from 0.3‰ to 5.3‰ (mean = 2.6‰) for δ¹⁵N and from 0.2‰ to 2.9‰ (mean = 0.9‰) for δ¹³C. We also found an impact of population structure on δ¹⁵N half-life in blood cells. Varying across individuals, δ¹⁵N half-life in plasma (6 to 10 days) was also shorter than for δ¹³C (14 to 22 days), though δ¹⁵N and δ¹³C half-lives are usually considered as equal. Overall, our multi-factorial experiment revealed that at least six levels of isotopic variations could co-occur in the same population. Our experimental analysis provides a framework for quantifying multiple sources of variation in isotopic discrimination and half-life that needs to be taken into account when designing and analysing ecological field studies.
Everyday Discrimination and Mood and Substance Use Disorders: A Latent Profile Analysis with African Americans and Caribbean Blacks

PubMed Central

Clark, Trenette T.; Salas-Wright, Christopher P.; Vaughn, Michael G.; Whitfield, Keith E.

2016-01-01

Perceived discrimination is a major source of health-related stress. The purpose of this study was to model the heterogeneity of everyday-discrimination experiences among African American and Caribbean Blacks and to identify differences in the prevalence of mood and substance use outcomes, including generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder among the identified subgroups. The study uses data from the National Survey of American Life obtained from a sample of African American and Caribbean Black respondents (N = 4,462) between 18 and 65 years. We used latent profile analysis and multinomial regression analyses to identify and validate latent subgroups and test hypotheses, yielding 4 classes of perceived everyday discrimination: Low Discrimination, Disrespect and Condescension, General Discrimination, and Chronic Discrimination. Findings show significant differences exist between the Low Discrimination and General Discrimination classes for major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Moreover, we find significant differences exist between the Low Discrimination and Chronic Discrimination classes for the four disorders examined. Compared with the Chronic Discrimination class, members of the other classes were significantly less likely to meet criteria for generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Findings suggest elevated levels of discrimination increase risk for mood and substance-use disorders. Importantly, results suggest the prevalence of mood and substance-use disorders is a function of the type and frequency of discrimination that individuals experience. PMID:25254321
Discriminant analysis for predictor of falls in stroke patients by using the Berg Balance Scale.

PubMed

Maeda, Noriaki; Urabe, Yukio; Murakami, Masahito; Itotani, Keisuke; Kato, Junichi

2015-05-01

An observational study was carried out to estimate the strength of the relationships among balance, mobility and falls in hemiplegic stroke inpatients. The objective was to examine factors that may aid in the prediction of the likelihood of falls in stroke patients. A total of 53 stroke patients (30 male, 23 female) aged 67.0 ± 11.1 years were interviewed regarding their fall history. Physical performance was assessed using the Berg Balance Scale (BBS) and the Functional Independence Measure (FIM) scale. Variables that differed between fallers and non-fallers were identified, and a discriminant function analysis was carried out to determine the combination of variables that effectively predicted fall status. Of the 53 stroke patients, 19 were fallers. Compared with the non-fallers, the fallers scored low on the FIM, and differed with respect to age, time from stroke onset, length of hospital stay, Brunnstrom recovery stage and admission BBS score. Discriminant analysis for predicting falls in stroke patients showed that admission BBS score was significantly related to the likelihood of falls. Moreover, discriminant analysis showed that the use of a significant BBS score to classify fallers and non-fallers had an accuracy of 81.1%. The discriminating criterion between the two groups was a score of 31 points on the BBS. The results of this study suggest that BBS score is a strong predictor of falls in stroke patients. As balance is closely related to the risk of falls in hospitalised stroke patients, BBS might be useful in the prediction of falls.
The convergent and discriminant validity of burnout measures in sport: a multi-trait/multi-method analysis.

PubMed

Cresswell, Scott L; Eklund, Robert C

2006-02-01

Athlete burnout research has been hampered by the lack of an adequate measurement tool. The Athlete Burnout Questionnaire (ABQ) and the Maslach Burnout Inventory General Survey (MBI-GS) are two recently developed self-report instruments designed to assess burnout. The convergent and discriminant validity of the ABQ and MBI-GS were assessed through multi-trait/multi-method analysis with a sporting population. Overall, the ABQ and the MBI-GS displayed acceptable convergent validity with matching subscales highly correlated, and satisfactory internal discriminant validity with lower correlations between non-matching subscales. Both scales also indicated an adequate discrimination between the concepts of burnout and depression. These findings add support to previous findings in non-sporting populations that depression and burnout are separate constructs. Based on the psychometric results, construct validity analysis and practical considerations, the results support the use of the ABQ to assess athlete burnout.
Discriminant analysis in wildlife research: Theory and applications

USGS Publications Warehouse

Williams, B.K.; Capen, D.E.

1981-01-01

Discriminant analysis, a method of analyzing grouped multivariate data, is often used in ecological investigations. It has both a predictive and an explanatory function, the former aiming at classification of individuals of unknown group membership. The goal of the latter function is to exhibit group separation by means of linear transforms, and the corresponding method is called canonical analysis. This discussion focuses on the application of canonical analysis in ecology. In order to clarify its meaning, a parametric approach is taken instead of the usual data-based formulation. For certain assumptions the data-based canonical variates are shown to result from maximum likelihood estimation, thus insuring consistency and asymptotic efficiency. The distorting effects of covariance heterogeneity are examined, as are certain difficulties which arise in interpreting the canonical functions. A 'distortion metric' is defined, by means of which distortions resulting from the canonical transformation can be assessed. Several sampling problems which arise in ecological applications are considered. It is concluded that the method may prove valuable for data exploration, but is of limited value as an inferential procedure.
How discriminating are discriminative instruments?

PubMed

Hankins, Matthew

2008-05-27

The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL). The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness), but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta) is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.
Factorial analysis of diesel engine performance using different types of biofuels.

PubMed

Tashtoush, Ghassan M; Al-Widyan, Mohamad I; Albatayneh, Aiman M

2007-09-01

In this study, several bio-source-fuels like fresh and waste vegetable oil and waste animal fat were tested at different injector pressures (120, 140, 190, 210 bar) in a direct-injection, naturally aspirated, single-cylinder diesel engine with a design injection pressure of 190 bar. Using 2k factorial analysis, the effect of injection pressure (Pi) and fuel type on three engine parameters, namely, combustion efficiency (etac), mass fuel consumption (mf), and engine speed (N) was examined. It was found that Pi and fuel type significantly affected both etac and mf while they had a slight effect on engine speed. Moreover, with diesel and biodiesels, the etac increased to a maximum at 190 bar but declined at the higher Pi value. In contrast, higher Pi had a favorable effect on etac over the whole Pi range with all the other more viscous fuels tested. In addition, the mass fuel consumption consistently decreased with an increase in Pi for all the fuels including the baseline diesel fuel, with which the engine consistently attained higher etac and higher rpm compared to all the other fuels tested.
Sexual Dimorphism and Aging in the Human Hyppocampus: Identification, Validation, and Impact of Differentially Expressed Genes by Factorial Microarray and Network Analysis.

PubMed

Guebel, Daniel V; Torres, Néstor V

2016-01-01

Motivation: In the brain of elderly-healthy individuals, the effects of sexual dimorphism and those due to normal aging appear overlapped. Discrimination of these two dimensions would powerfully contribute to a better understanding of the etiology of some neurodegenerative diseases, such as "sporadic" Alzheimer. Methods: Following a system biology approach, top-down and bottom-up strategies were combined. First, public transcriptome data corresponding to the transition from adulthood to the aging stage in normal, human hippocampus were analyzed through an optimized microarray post-processing (Q-GDEMAR method) together with a proper experimental design (full factorial analysis). Second, the identified genes were placed in context by building compatible networks. The subsequent ontology analyses carried out on these networks clarify the main functionalities involved. Results: Noticeably we could identify large sets of genes according to three groups: those that exclusively depend on the sex, those that exclusively depend on the age, and those that depend on the particular combinations of sex and age (interaction). The genes identified were validated against three independent sources (a proteomic study of aging, a senescence database, and a mitochondrial genetic database). We arrived to several new inferences about the biological functions compromised during aging in two ways: by taking into account the sex-independent effects of aging, and considering the interaction between age and sex where pertinent. In particular, we discuss the impact of our findings on the functions of mitochondria, autophagy, mitophagia, and microRNAs. Conclusions: The evidence obtained herein supports the occurrence of significant neurobiological differences in the hippocampus, not only between adult and elderly individuals, but between old-healthy women and old-healthy men. Hence, to obtain realistic results in further analysis of the transition from the normal aging to incipient Alzheimer
Sexual Dimorphism and Aging in the Human Hyppocampus: Identification, Validation, and Impact of Differentially Expressed Genes by Factorial Microarray and Network Analysis

PubMed Central

Guebel, Daniel V.; Torres, Néstor V.

2016-01-01

Motivation: In the brain of elderly-healthy individuals, the effects of sexual dimorphism and those due to normal aging appear overlapped. Discrimination of these two dimensions would powerfully contribute to a better understanding of the etiology of some neurodegenerative diseases, such as “sporadic” Alzheimer. Methods: Following a system biology approach, top-down and bottom-up strategies were combined. First, public transcriptome data corresponding to the transition from adulthood to the aging stage in normal, human hippocampus were analyzed through an optimized microarray post-processing (Q-GDEMAR method) together with a proper experimental design (full factorial analysis). Second, the identified genes were placed in context by building compatible networks. The subsequent ontology analyses carried out on these networks clarify the main functionalities involved. Results: Noticeably we could identify large sets of genes according to three groups: those that exclusively depend on the sex, those that exclusively depend on the age, and those that depend on the particular combinations of sex and age (interaction). The genes identified were validated against three independent sources (a proteomic study of aging, a senescence database, and a mitochondrial genetic database). We arrived to several new inferences about the biological functions compromised during aging in two ways: by taking into account the sex-independent effects of aging, and considering the interaction between age and sex where pertinent. In particular, we discuss the impact of our findings on the functions of mitochondria, autophagy, mitophagia, and microRNAs. Conclusions: The evidence obtained herein supports the occurrence of significant neurobiological differences in the hippocampus, not only between adult and elderly individuals, but between old-healthy women and old-healthy men. Hence, to obtain realistic results in further analysis of the transition from the normal aging to incipient
Productivity or discrimination? An economic analysis of excess-weight penalty in the Swedish labor market.

PubMed

Dackehag, Margareta; Gerdtham, Ulf-G; Nordin, Martin

2015-07-01

This article investigates the excess-weight penalty in income for men and women in the Swedish labor market, using longitudinal data. It compares two identification strategies, OLS and individual fixed effects, and distinguishes between two main sources of excess-weight penalties, lower productivity because of bad health and discrimination. For men, the analysis finds a significant obesity penalty related to discrimination when applying individual fixed effects. We do not find any significant excess-weight penalty for women.
Triacylglycerol stereospecific analysis and linear discriminant analysis for milk speciation.

PubMed

Blasi, Francesca; Lombardi, Germana; Damiani, Pietro; Simonetti, Maria Stella; Giua, Laura; Cossignani, Lina

2013-05-01

Product authenticity is an important topic in dairy sector. Dairy products sold for public consumption must be accurately labelled in accordance with the contained milk species. Linear discriminant analysis (LDA), a common chemometric procedure, has been applied to fatty acid% composition to classify pure milk samples (cow, ewe, buffalo, donkey, goat). All original grouped cases were correctly classified, while 90% of cross-validated grouped cases were correctly classified. Another objective of this research was the characterisation of cow-ewe milk mixtures in order to reveal a common fraud in dairy field, that is the addition of cow to ewe milk. Stereospecific analysis of triacylglycerols (TAG), a method based on chemical-enzymatic procedures coupled with chromatographic techniques, has been carried out to detect fraudulent milk additions, in particular 1, 3, 5% cow milk added to ewe milk. When only TAG composition data were used for the elaboration, 75% of original grouped cases were correctly classified, while totally correct classified samples were obtained when both total and intrapositional TAG data were used. Also the results of cross validation were better when TAG stereospecific analysis data were considered as LDA variables. In particular, 100% of cross-validated grouped cases were obtained when 5% cow milk mixtures were considered.
Optical spectroscopic analysis for the discrimination of extra-virgin olive-oil (Conference Presentation)

NASA Astrophysics Data System (ADS)

McReynolds, Naomi; Auñón Garcia, Juan M.; Guengerich, Zoe; Smith, Terry K.; Dholakia, Kishan

2017-02-01

We present an optical spectroscopic technique, making use of both Raman signals and fluorescence spectroscopy, for the identification of five brands of commercially available extra-virgin olive-oil (EVOO). We demonstrate our technique on both a `bulk-optics' free-space system and a compact device. Using the compact device, which is capable of recording both Raman and fluorescence signals, we achieved an average sensitivity and specificity of 98.4% and 99.6% for discrimination, respectively. Our approach demonstrates that both Raman and fluorescence spectroscopy can be used for portable discrimination of EVOOs which obviates the need to use centralised laboratories and opens up the prospect of in-field testing. This technique may enable detection of EVOO that has undergone counterfeiting or adulteration. One of the main challenges facing Raman spectroscopy for use in quality control of EVOOs is that the oxidation of EVOO, which naturally occurs due to aging, causes shifts in Raman spectra with time, which implies regular retraining would be necessary. We present a potential method of analysis to minimize the effect that aging has on discrimination efficiency; we show that by discarding the first principal component, which contains information on the variations due to oxidation, we can improve discrimination efficiency thus improving the robustness of our technique.
Analysis of the discriminative methods for diagnosis of benign and malignant solitary pulmonary nodules based on serum markers.

PubMed

Wang, Wanping; Liu, Mingyue; Wang, Jing; Tian, Rui; Dong, Junqiang; Liu, Qi; Zhao, Xianping; Wang, Yuanfang

2014-01-01

Screening indexes of tumor serum markers for benign and malignant solitary pulmonary nodules (SPNs) were analyzed to find the optimum method for diagnosis. Enzyme-linked immunosorbent assays, an automatic immune analyzer and radioimmunoassay methods were used to examine the levels of 8 serum markers in 164 SPN patients, and the sensitivity for differential diagnosis of malignant or benign SPN was compared for detection using a single plasma marker or a combination of markers. The results for serological indicators that closely relate to benign and malignant SPNs were screened using the Fisher discriminant analysis and a non-conditional logistic regression analysis method, respectively. The results were then verified by the k-means clustering analysis method. The sensitivity when using a combination of serum markers to detect SPN was higher than that using a single marker. By Fisher discriminant analysis, cytokeratin 19 fragments (CYFRA21-1), carbohydrate antigen 125 (CA125), squamous cell carcinoma antigen (SCC) and breast cancer antigen (CA153), which relate to the benign and malignant SPNs, were screened. Through non-conditional logistic regression analysis, CYFRA21-1, SCC and CA153 were obtained. Using the k-means clustering analysis, the cophenetic correlation coefficient (0.940) obtained by the Fisher discriminant analysis was higher than that obtained with logistic regression analysis (0.875). This study indicated that the Fisher discriminant analysis functioned better in screening out serum markers to recognize the benign and malignant SPN. The combined detection of CYFRA21-1, CA125, SCC and CA153 is an effective way to distinguish benign and malignant SPN, and will find an important clinical application in the early diagnosis of SPN. © 2014 S. Karger GmbH, Freiburg.
Discriminant analysis of some east Tennessee forest herb niches. Environmental Sciences Division Publication No. 752

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

Mann, L.K.; Shugart, H.H.; Kitchings, J.T.

1978-03-01

The purpose of this study was to evaluate the effectiveness of using discriminant analysis in assessing plant niches. As a component of research by the Environmental Research Park Project at Oak Ridge, Tennessee, five sites were inventoried for herbaceous species. From this inventory, four sympatric species of Galium and seventeen co-occurring herbaceous species were selected for discriminant analysis. The four species of Galium were treated as two data sets: one was composed of information collected at one site (a mesic hardwood area) and the other contained data from two cedar sites of shallow soil over limestone bedrock. The seventeen herbaceousmore » species all occurred in the mesic hardwood area.« less
On KEK B-Factory

NASA Astrophysics Data System (ADS)

Sugawara, H.

2009-07-01

There are two principles which the management of a research institute like KEK must respect when dealing with such big project as B-Factory. One is the scientific merit of the project and the other is the organizational consideration which includes financial, human, technical and historical elements. Ideally, the two principles are to be fully taken into account. But, in many cases, one or the other is only partially fulfilled due to unavoidable circumstances. The lack of flexibility to respond to all possible situations is more dangerous and may lead to a disaster as in the case of SSC. I will describe the process which lead to the successful construction, operation and physics presentations of KEK B-Factory following faithfully the official records.
Engineering the smart factory

NASA Astrophysics Data System (ADS)

Harrison, Robert; Vera, Daniel; Ahmad, Bilal

2016-10-01

The fourth industrial revolution promises to create what has been called the smart factory. The vision is that within such modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralised decisions. This paper provides a view of this initiative from an automation systems perspective. In this context it considers how future automation systems might be effectively configured and supported through their lifecycles and how integration, application modelling, visualisation and reuse of such systems might be best achieved. The paper briefly describes limitations in current engineering methods, and new emerging approaches including the cyber physical systems (CPS) engineering tools being developed by the automation systems group (ASG) at Warwick Manufacturing Group, University of Warwick, UK.
Asymptotic Normality Through Factorial Cumulants and Partition Identities

PubMed Central

Bobecka, Konstancja; Hitczenko, Paweł; López-Blázquez, Fernando; Rempała, Grzegorz; Wesołowski, Jacek

2013-01-01

In the paper we develop an approach to asymptotic normality through factorial cumulants. Factorial cumulants arise in the same manner from factorial moments as do (ordinary) cumulants from (ordinary) moments. Another tool we exploit is a new identity for ‘moments’ of partitions of numbers. The general limiting result is then used to (re-)derive asymptotic normality for several models including classical discrete distributions, occupancy problems in some generalized allocation schemes and two models related to negative multinomial distribution. PMID:24591773
Defect Analysis Of Quality Palm Kernel Meal Using Statistical Quality Control In Kernels Factory

NASA Astrophysics Data System (ADS)

Sembiring, M. T.; Marbun, N. J.

2018-04-01

The production quality has an important impact retain the totality of characteristics of a product or service to pay attention to its capabilities to meet the needs that have been established. Quality criteria Palm Kernel Meal (PKM) set Factory kernel is as follows: oil content: max 8.50%, water content: max 12,00% and impurity content: max 4.00% While the average quality of the oil content of 8.94%, the water content of 5.51%, and 8.45% impurity content. To identify the defective product quality PKM produced, then used a method of analysis using Statistical Quality Control (SQC). PKM Plant Quality Kernel shows the oil content was 0.44% excess of a predetermined maximum value, and 4.50% impurity content. With excessive PKM content of oil and dirt cause disability content of production for oil, amounted to 854.6078 kg PKM and 8643.193 kg impurity content of PKM. Analysis of the results of cause and effect diagram and SQC, the factors that lead to poor quality of PKM is Ampere second press oil expeller and hours second press oil expeller.
Detection of non-milk fat in milk fat by gas chromatography and linear discriminant analysis.

PubMed

Gutiérrez, R; Vega, S; Díaz, G; Sánchez, J; Coronado, M; Ramírez, A; Pérez, J; González, M; Schettino, B

2009-05-01

Gas chromatography was utilized to determine triacylglycerol profiles in milk and non-milk fat. The values of triacylglycerol were subjected to linear discriminant analysis to detect and quantify non-milk fat in milk fat. Two groups of milk fat were analyzed: A) raw milk fat from the central region of Mexico (n = 216) and B) ultrapasteurized milk fat from 3 industries (n = 36), as well as pork lard (n = 2), bovine tallow (n = 2), fish oil (n = 2), peanut (n = 2), corn (n = 2), olive (n = 2), and soy (n = 2). The samples of raw milk fat were adulterated with non-milk fats in proportions of 0, 5, 10, 15, and 20% to form 5 groups. The first function obtained from the linear discriminant analysis allowed the correct classification of 94.4% of the samples with levels <10% of adulteration. The triacylglycerol values of the ultrapasteurized milk fats were evaluated with the discriminant function, demonstrating that one industry added non-milk fat to its product in 80% of the samples analyzed.
Factorial Experiments: Efficient Tools for Evaluation of Intervention Components

PubMed Central

Collins, Linda M.; Dziak, John J.; Kugler, Kari C.; Trail, Jessica B.

2014-01-01

Background An understanding of the individual and combined effects of a set of intervention components is important for moving the science of preventive medicine interventions forward. This understanding can often be achieved in an efficient and economical way via a factorial experiment, in which two or more independent variables are manipulated. The factorial experiment is a complement to the randomized controlled trial (RCT); the two designs address different research questions. Purpose This article offers an introduction to factorial experiments aimed at investigators trained primarily in the RCT. Method The factorial experiment is compared and contrasted with other experimental designs used commonly in intervention science to highlight where each is most efficient and appropriate. Results Several points are made: factorial experiments make very efficient use of experimental subjects when the data are properly analyzed; a factorial experiment can have excellent statistical power even if it has relatively few subjects per experimental condition; and when conducting research to select components for inclusion in a multicomponent intervention, interactions should be studied rather than avoided. Conclusions Investigators in preventive medicine and related areas should begin considering factorial experiments alongside other approaches. Experimental designs should be chosen from a resource management perspective, which states that the best experimental design is the one that provides the greatest scientific benefit without exceeding available resources. PMID:25092122

Factorial experiments: efficient tools for evaluation of intervention components.

PubMed

Collins, Linda M; Dziak, John J; Kugler, Kari C; Trail, Jessica B

2014-10-01

An understanding of the individual and combined effects of a set of intervention components is important for moving the science of preventive medicine interventions forward. This understanding can often be achieved in an efficient and economical way via a factorial experiment, in which two or more independent variables are manipulated. The factorial experiment is a complement to the RCT; the two designs address different research questions. To offer an introduction to factorial experiments aimed at investigators trained primarily in the RCT. The factorial experiment is compared and contrasted with other experimental designs used commonly in intervention science to highlight where each is most efficient and appropriate. Several points are made: factorial experiments make very efficient use of experimental subjects when the data are properly analyzed; a factorial experiment can have excellent statistical power even if it has relatively few subjects per experimental condition; and when conducting research to select components for inclusion in a multicomponent intervention, interactions should be studied rather than avoided. Investigators in preventive medicine and related areas should begin considering factorial experiments alongside other approaches. Experimental designs should be chosen from a resource management perspective, which states that the best experimental design is the one that provides the greatest scientific benefit without exceeding available resources. Copyright © 2014 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Everyday discrimination and mood and substance use disorders: a latent profile analysis with African Americans and Caribbean Blacks.

PubMed

Clark, Trenette T; Salas-Wright, Christopher P; Vaughn, Michael G; Whitfield, Keith E

2015-01-01

Perceived discrimination is a major source of health-related stress. The purpose of this study was to model the heterogeneity of everyday-discrimination experiences among African American and Caribbean Blacks and to identify differences in the prevalence of mood and substance use outcomes, including generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder among the identified subgroups. The study uses data from the National Survey of American Life obtained from a sample of African American and Caribbean Black respondents (N=4,462) between 18 and 65 years. We used latent profile analysis and multinomial regression analyses to identify and validate latent subgroups and test hypotheses, yielding 4 classes of perceived everyday discrimination: Low Discrimination, Disrespect and Condescension, General Discrimination, and Chronic Discrimination. Findings show significant differences exist between the Low Discrimination and General Discrimination classes for major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Moreover, we find significant differences exist between the Low Discrimination and Chronic Discrimination classes for the four disorders examined. Compared with the Chronic Discrimination class, members of the other classes were significantly less likely to meet criteria for generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Findings suggest elevated levels of discrimination increase risk for mood and substance-use disorders. Importantly, results suggest the prevalence of mood and substance-use disorders is a function of the type and frequency of discrimination that individuals experience. Copyright © 2014 Elsevier Ltd. All rights reserved.
Sex determination of the Acadian Flycatcher using discriminant analysis

USGS Publications Warehouse

Wilson, R.R.

1999-01-01

I used five morphometric variables from 114 individuals captured in Arkansas to develop a discriminant model to predict the sex of Acadian Flycatchers (Empidonax virescens). Stepwise discriminant function analyses selected wing chord and tail length as the most parsimonious subset of variables for discriminating sex. This two-variable model correctly classified 80% of females and 97% of males used to develop the model. Validation of the model using 19 individuals from Louisiana and Virginia resulted in 100% correct classification of males and females. This model provides criteria for sexing monomorphic Acadian Flycatchers during the breeding season and possibly during the winter.
Complexity-reduced implementations of complete and null-space-based linear discriminant analysis.

PubMed

Lu, Gui-Fu; Zheng, Wenming

2013-10-01

Dimensionality reduction has become an important data preprocessing step in a lot of applications. Linear discriminant analysis (LDA) is one of the most well-known dimensionality reduction methods. However, the classical LDA cannot be used directly in the small sample size (SSS) problem where the within-class scatter matrix is singular. In the past, many generalized LDA methods has been reported to address the SSS problem. Among these methods, complete linear discriminant analysis (CLDA) and null-space-based LDA (NLDA) provide good performances. The existing implementations of CLDA are computationally expensive. In this paper, we propose a new and fast implementation of CLDA. Our proposed implementation of CLDA, which is the most efficient one, is equivalent to the existing implementations of CLDA in theory. Since CLDA is an extension of null-space-based LDA (NLDA), our implementation of CLDA also provides a fast implementation of NLDA. Experiments on some real-world data sets demonstrate the effectiveness of our proposed new CLDA and NLDA algorithms. Copyright © 2013 Elsevier Ltd. All rights reserved.
The 9-item Bergen Burnout Inventory: factorial validity across organizations and measurements of longitudinal data.

PubMed

Feldt, Taru; Rantanen, Johanna; Hyvönen, Katriina; Mäkikangas, Anne; Huhtala, Mari; Pihlajasaari, Pia; Kinnunen, Ulla

2014-01-01

The present study tested the factorial validity of the 9-item Bergen Burnout Inventory (BBI-9). The BBI-9 is comprised of three core dimensions: (1) exhaustion at work; (2) cynicism toward the meaning of work; and (3) sense of inadequacy at work. The study further investigated whether the three-factor structure of the BBI-9 remains the same across different organizations (group invariance) and measurement time points (time invariance). The factorial group invariance was tested using a cross-sectional design with data pertaining to managers (n=742), and employees working in a bank (n=162), an engineering office (n=236), a public sector organization divided into three service areas: administration (n=102), education and culture (n=581), and social affairs and health (n=1,505). Factorial time invariance was tested using longitudinal data pertaining to managers, with three measurements over a four-year follow-up period. The confirmatory factor analysis revealed that the three-factor structure of the BBI-9 was invariant across cross-sectional samples. The factorial invariance was also supported across measurement times. To conclude, the factorial structure of the BBI-9 was found to remain the same regardless of the sample properties and measurement times.
Linear Discriminant Analysis on a Spreadsheet.

ERIC Educational Resources Information Center

Busbey, Arthur Bresnahan III

1989-01-01

Described is a software package, "Trapeze," within which a routine called LinDis can be used. Discussed are teaching methods, the linear discriminant model and equations, the LinDis worksheet, and an example. The set up for this routine is included. (CW)
Estimating erosion risk on forest lands using improved methods of discriminant analysis

Treesearch

J. Lewis; R. M. Rice

1990-01-01

A population of 638 timber harvest areas in northwestern California was sampled for data related to the occurrence of critical amounts of erosion (>153 m3 within 0.81 ha). Separate analyses were done for forest roads and logged areas. Linear discriminant functions were computed in each analysis to contrast site conditions at critical plots with randomly selected...
Photosynthesis energy factory: analysis, synthesis, and demonstration. Final report

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

Not Available

This quantitative assessment of the potential of a combined dry-land Energy Plantation, wood-fired power plant, and algae wastewater treatment system demonstrates the cost-effectiveness of recycling certain by-products and effluents from one subsystem to another. Designed to produce algae up to the limit of the amount of carbon in municipal wastewater, the algae pond provides a positive cash credit, resulting mainly from the wastewater treatment credit, which may be used to reduce the cost of the Photosynthesis Energy Factory (PEF)-generated electricity. The algae pond also produces fertilizer, which reduces the cost of the biomass produced on the Energy Plantation, and somemore » gas. The cost of electricity was as low as 35 mills per kilowatt-hour for a typical municipally-owned PEF consisting of a 65-MWe power plant, a 144-acre algae pond, and a 33,000-acre Energy Plantation. Using only conventional or near-term technology, the most cost-effective algae pond for a PEF is the carbon-limited secondary treatment system. This system does not recycle CO/sub 2/ from the flue gas. Analysis of the Energy Plantation subsystem at 15 sites revealed that plantations of 24,000 to 36,000 acres produce biomass at the lowest cost per ton. The following sites are recommended for more detailed evaluation as potential demonstration sites: Pensacola, Florida; Jamestown, New York; Knoxville, Tennessee; Martinsville, Virginia, and Greenwood, South Carolina. A major possible extension of the PEF concept is to include the possibility for irrigation.« less
Racial Discrimination and Asian Mental Health: A Meta-Analysis

ERIC Educational Resources Information Center

Lee, Debbiesiu L.; Ahn, Soyeon

2011-01-01

Although research on racial discrimination and mental health has proliferated, findings are varied and dispersed. This study explored the critical question of how Asians, in particular, deal with discrimination and how this relates to Asian mental health. With 99 correlations from 23 independent studies, the overall relationship between racial…
A simple model for factory distribution: Historical effect in an industry city

NASA Astrophysics Data System (ADS)

Uehara, Takashi; Sato, Kazunori; Morita, Satoru; Maeda, Yasunobu; Yoshimura, Jin; Tainaka, Kei-ichi

2016-02-01

The construction and discontinuance processes of factories are complicated problems in sociology. We focus on the spatial and temporal changes of factories at Hamamatsu city in Japan. Real data indicate that the clumping degree of factories decreases as the density of factory increases. To represent the spatial and temporal changes of factories, we apply "contact process" which is one of cellular automata. This model roughly explains the dynamics of factory distribution. We also find "historical effect" in spatial distribution. Namely, the recent factories have been dispersed due to the past distribution during the period of economic bubble. This effect may be related to heavy shock in Japanese stock market.
Rapid discrimination of different Apiaceae species based on HPTLC fingerprints and targeted flavonoids determination using multivariate image analysis.

PubMed

Shawky, Eman; Abou El Kheir, Rasha M

2018-02-11

Species of Apiaceae are used in folk medicine as spices and in officinal medicinal preparations of drugs. They are an excellent source of phenolics exhibiting antioxidant activity, which are of great benefit to human health. Discrimination among Apiaceae medicinal herbs remains an intricate challenge due to their morphological similarity. In this study, a combined "untargeted" and "targeted" approach to investigate different Apiaceae plants species was proposed by using the merging of high-performance thin layer chromatography (HPTLC)-image analysis and pattern recognition methods which were used for fingerprinting and classification of 42 different Apiaceae samples collected from Egypt. Software for image processing was applied for fingerprinting and data acquisition. HPTLC fingerprint assisted by principal component analysis (PCA) and hierarchical cluster analysis (HCA)-heat maps resulted in a reliable untargeted approach for discrimination and classification of different samples. The "targeted" approach was performed by developing and validating an HPTLC method allowing the quantification of eight flavonoids. The combination of quantitative data with PCA and HCA-heat-maps allowed the different samples to be discriminated from each other. The use of chemometrics tools for evaluation of fingerprints reduced expense and analysis time. The proposed method can be adopted for routine discrimination and evaluation of the phytochemical variability in different Apiaceae species extracts. Copyright © 2018 John Wiley & Sons, Ltd.
Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI.

PubMed

Keith, Verna M; Nguyen, Ann W; Taylor, Robert Joseph; Mouzon, Dawne M; Chatters, Linda M

2017-05-01

Data from the 2001-2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.
Factorial structure and psychometric properties of a brief version of the Reminiscence Functions Scale with Chinese older adults.

PubMed

Lou, Vivian W Q; Choy, Jacky C P

2014-05-01

The current study aims to examine the factorial structure and psychometric properties of a brief version of the Reminiscence Functions Scale (RFS), a 14-item assessment tool of reminiscence functions, with Chinese older adults. The scale, covering four reminiscence functions (boredom reduction, bitterness revival, problem solving, and identity) was translated from English into Chinese and administered to older adults (N=675). Confirmatory factor analysis and hierarchical confirmatory factor analysis were conducted to examine its factorial structure, and its psychometric properties and criterion validity were examined. Confirmatory factor analysis supports a second-order model comprising one second-order factor and four first-order factors of RFS. The Cronbach's alpha of the subscales ranged from 0.75 to 0.90. The brief RFS contains a second-order factorial structure. Its psychometric properties support it as a sound instrument for measuring reminiscence functions among Chinese older adults.
Batch process fault detection and identification based on discriminant global preserving kernel slow feature analysis.

PubMed

Zhang, Hanyuan; Tian, Xuemin; Deng, Xiaogang; Cao, Yuping

2018-05-16

As an attractive nonlinear dynamic data analysis tool, global preserving kernel slow feature analysis (GKSFA) has achieved great success in extracting the high nonlinearity and inherently time-varying dynamics of batch process. However, GKSFA is an unsupervised feature extraction method and lacks the ability to utilize batch process class label information, which may not offer the most effective means for dealing with batch process monitoring. To overcome this problem, we propose a novel batch process monitoring method based on the modified GKSFA, referred to as discriminant global preserving kernel slow feature analysis (DGKSFA), by closely integrating discriminant analysis and GKSFA. The proposed DGKSFA method can extract discriminant feature of batch process as well as preserve global and local geometrical structure information of observed data. For the purpose of fault detection, a monitoring statistic is constructed based on the distance between the optimal kernel feature vectors of test data and normal data. To tackle the challenging issue of nonlinear fault variable identification, a new nonlinear contribution plot method is also developed to help identifying the fault variable after a fault is detected, which is derived from the idea of variable pseudo-sample trajectory projection in DGKSFA nonlinear biplot. Simulation results conducted on a numerical nonlinear dynamic system and the benchmark fed-batch penicillin fermentation process demonstrate that the proposed process monitoring and fault diagnosis approach can effectively detect fault and distinguish fault variables from normal variables. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
The Clone Factory

ERIC Educational Resources Information Center

Stoddard, Beryl

2005-01-01

Have humans been cloned? Is it possible? Immediate interest is sparked when students are asked these questions. In response to their curiosity, the clone factory activity was developed to help them understand the process of cloning. In this activity, students reenact the cloning process, in a very simplified simulation. After completing the…
Analysis of Mannitol, as Tracer of Bacterial Infections in Cane and Beet Sugar Factories

USDA-ARS?s Scientific Manuscript database

Mannitol, formed mainly by Leuconostoc mesenteroides bacteria, is a sensitive marker of sugarcane and sugarbeet deterioration that can predict multiple processing problems. The delivery of consignments of deteriorated sugarcane or sugar beets to factories can detrimentally affect multiple process u...
Analysis of Mannitol, as Tracer of Bacterial Infections in Cane and Beet Sugar Factories

USDA-ARS?s Scientific Manuscript database

Mannitol, formed mainly by Leuconostoc mesenteroides bacteria, is a sensitive marker of sugarcane and sugarbeet deterioration that can predict multiple processing problems. The delivery of consignments of deteriorated sugarcane or sugar beets to factories can detrimentally affect multiple process un...
Testing Factorial Invariance in Multilevel Data: A Monte Carlo Study

ERIC Educational Resources Information Center

Kim, Eun Sook; Kwok, Oi-man; Yoon, Myeongsun

2012-01-01

Testing factorial invariance has recently gained more attention in different social science disciplines. Nevertheless, when examining factorial invariance, it is generally assumed that the observations are independent of each other, which might not be always true. In this study, we examined the impact of testing factorial invariance in multilevel…
Determinants of Chronic Respiratory Symptoms among Pharmaceutical Factory Workers

PubMed Central

Enquselassie, Fikre; Tefera, Yifokire; Gizaw, Muluken; Wakuma, Samson; Woldemariam, Messay

2018-01-01

Background Chronic respiratory symptoms including chronic cough, chronic phlegm, wheezing, shortness of breath, and chest pain are manifestations of respiratory problems which are mainly evolved as a result of occupational exposures. This study aims to assess determinants of chronic respiratory symptoms among pharmaceutical factory workers. Methods A case control study was carried out among 453 pharmaceutical factory workers with 151 cases and 302 controls. Data was collected using pretested and structured questionnaire. The data was analyzed using descriptive statistics and bivariate and multivariate analysis. Result Previous history of chronic respiratory diseases (AOR = 3.36, 95% CI = 1.85–6.12), family history of chronic respiratory diseases (AOR = 2.55, 95% CI = 1.51–4.32), previous dusty working environment (AOR = 2.26, 95% CI = 1.07–4.78), ever smoking (AOR = 3.66, 95% CI = 1.05–12.72), and service years (AOR = 1.86, 95% CI = 1.16–2.99) showed statistically significant association with chronic respiratory symptoms. Conclusion Previous history of respiratory diseases, family history of chronic respiratory diseases, previous dusty working environment, smoking, and service years were determinants of chronic respiratory symptoms. Public health endeavors to prevent the burden of chronic respiratory symptoms among pharmaceutical factory workers should target the reduction of adverse workplace exposures and discouragement of smoking. PMID:29666655
Phonological experience modulates voice discrimination: Evidence from functional brain networks analysis.

PubMed

Hu, Xueping; Wang, Xiangpeng; Gu, Yan; Luo, Pei; Yin, Shouhang; Wang, Lijun; Fu, Chao; Qiao, Lei; Du, Yi; Chen, Antao

2017-10-01

Numerous behavioral studies have found a modulation effect of phonological experience on voice discrimination. However, the neural substrates underpinning this phenomenon are poorly understood. Here we manipulated language familiarity to test the hypothesis that phonological experience affects voice discrimination via mediating the engagement of multiple perceptual and cognitive resources. The results showed that during voice discrimination, the activation of several prefrontal regions was modulated by language familiarity. More importantly, the same effect was observed concerning the functional connectivity from the fronto-parietal network to the voice-identity network (VIN), and from the default mode network to the VIN. Our findings indicate that phonological experience could bias the recruitment of cognitive control and information retrieval/comparison processes during voice discrimination. Therefore, the study unravels the neural substrates subserving the modulation effect of phonological experience on voice discrimination, and provides new insights into studying voice discrimination from the perspective of network interactions. Copyright © 2017. Published by Elsevier Inc.

The Virtual Factory Teaching System (VFTS): Project Review and Results.

ERIC Educational Resources Information Center

Kazlauskas, E. J.; Boyd, E. F., III; Dessouky, M. M.

This paper presents a review of the Virtual Factory Teaching (VFTS) project, a Web-based, multimedia collaborative learning network. The system allows students, working alone or in teams, to build factories, forecast demand for products, plan production, establish release rules for new work into the factory, and set scheduling rules for…
[Etiological analysis and establishment of a discriminant model for lower respiratory tract infections in hospitalized patients].

PubMed

Chen, Y S; Lin, X H; Li, H R; Hua, Z D; Lin, M Q; Huang, W S; Yu, T; Lyu, H Y; Mao, W P; Liang, Y Q; Peng, X R; Chen, S J; Zheng, H; Lian, S Q; Hu, X L; Yao, X Q

2017-12-12

Objective: To analyze the pathogens of lower respiratory tract infection(LRTI) including bacterial, viral and mixed infection, and to establish a discriminant model based on clinical features in order to predict the pathogens. Methods: A total of 243 hospitalized patients with lower respiratory tract infections were enrolled in Fujian Provincial Hospital from April 2012 to September 2015. The clinical data and airway (sputum and/or bronchoalveolar lavage) samples were collected. Microbes were identified by traditional culture (for bacteria), loop-mediated isothermal amplification(LAMP) and gene sequencing (for bacteria and atypical pathogen), or Real-time quantitative polymerase chain reaction (Real-time PCR)for viruses. Finally, a discriminant model was established by using the discriminant analysis methods to help to predict bacterial, viral and mixed infections. Results: Pathogens were detected in 53.9% (131/243) of the 243 cases.Bacteria accounted for 23.5%(57/243, of which 17 cases with the virus, 1 case with Mycoplasma pneumoniae and virus), mainly Pseudomonas Aeruginosa and Klebsiella Pneumonia. Atypical pathogens for 4.9% (12/243, of which 3 cases with the virus, 1 case of bacteria and viruses), all were mycoplasma pneumonia. Viruses for 34.6% (84/243, of which 17 cases of bacteria, 3 cases with Mycoplasma pneumoniae, 1 case with Mycoplasma pneumoniae and bacteria) of the cases, mainly Influenza A virus and Human Cytomegalovirus, and other virus like adenovirus, human parainfluenza virus, respiratory syncytial virus, human metapneumovirus, human boca virus were also detected fewly. Seven parameters including mental status, using antibiotics prior to admission, complications, abnormal breath sounds, neutrophil alkaline phosphatase (NAP) score, pneumonia severity index (PSI) score and CRUB-65 score were enrolled after univariate analysis, and discriminant analysis was used to establish the discriminant model by applying the identified pathogens as the
The Old Factory

ERIC Educational Resources Information Center

Roman, Harry T.

2007-01-01

Technology education is not just about things, systems, and processes. It can also be about history, people, technological change, and impacts on society. In this design challenge, one uses technology education principles and ideas to convert an old factory into a museum and learning center. The challenge with this historical resource is to think…
Gaussian Discriminant Analysis for Optimal Delineation of Mild Cognitive Impairment in Alzheimer's Disease.

PubMed

Fang, Chen; Li, Chunfei; Cabrerizo, Mercedes; Barreto, Armando; Andrian, Jean; Rishe, Naphtali; Loewenstein, David; Duara, Ranjan; Adjouadi, Malek

2018-04-12

Over the past few years, several approaches have been proposed to assist in the early diagnosis of Alzheimer's disease (AD) and its prodromal stage of mild cognitive impairment (MCI). Using multimodal biomarkers for this high-dimensional classification problem, the widely used algorithms include Support Vector Machines (SVM), Sparse Representation-based classification (SRC), Deep Belief Networks (DBN) and Random Forest (RF). These widely used algorithms continue to yield unsatisfactory performance for delineating the MCI participants from the cognitively normal control (CN) group. A novel Gaussian discriminant analysis-based algorithm is thus introduced to achieve a more effective and accurate classification performance than the aforementioned state-of-the-art algorithms. This study makes use of magnetic resonance imaging (MRI) data uniquely as input to two separate high-dimensional decision spaces that reflect the structural measures of the two brain hemispheres. The data used include 190 CN, 305 MCI and 133 AD subjects as part of the AD Big Data DREAM Challenge #1. Using 80% data for a 10-fold cross-validation, the proposed algorithm achieved an average F1 score of 95.89% and an accuracy of 96.54% for discriminating AD from CN; and more importantly, an average F1 score of 92.08% and an accuracy of 90.26% for discriminating MCI from CN. Then, a true test was implemented on the remaining 20% held-out test data. For discriminating MCI from CN, an accuracy of 80.61%, a sensitivity of 81.97% and a specificity of 78.38% were obtained. These results show significant improvement over existing algorithms for discriminating the subtle differences between MCI participants and the CN group.
Variations in students' perceived reasons for, sources of, and forms of in-school discrimination: A latent class analysis.

PubMed

Byrd, Christy M; Carter Andrews, Dorinda J

2016-08-01

Although there exists a healthy body of literature related to discrimination in schools, this research has primarily focused on racial or ethnic discrimination as perceived and experienced by students of color. Few studies examine students' perceptions of discrimination from a variety of sources, such as adults and peers, their descriptions of the discrimination, or the frequency of discrimination in the learning environment. Middle and high school students in a Midwestern school district (N=1468) completed surveys identifying whether they experienced discrimination from seven sources (e.g., peers, teachers, administrators), for seven reasons (e.g., gender, race/ethnicity, religion), and in eight forms (e.g., punished more frequently, called names, excluded from social groups). The sample was 52% White, 15% Black/African American, 14% Multiracial, and 17% Other. Latent class analysis was used to cluster individuals based on reported sources of, reasons for, and forms of discrimination. Four clusters were found, and ANOVAs were used to test for differences between clusters on perceptions of school climate, relationships with teachers, perceptions that the school was a "good school," and engagement. The Low Discrimination cluster experienced the best outcomes, whereas an intersectional cluster experienced the most discrimination and the worst outcomes. The results confirm existing research on the negative effects of discrimination. Additionally, the paper adds to the literature by highlighting the importance of an intersectional approach to examining students' perceptions of in-school discrimination. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
Hazarding health: experiences of body, work, and risk among factory women in Malaysia.

PubMed

Root, Robin

2009-10-01

In the 1970s, Malaysia launched an export-oriented development strategy as a means of financing the nation's modernization. The success of the strategy hinged significantly on intensive recruitment of women for factory employment. I draw on descriptive qualitative research, including interviews (51), surveys (106), and ethnography in Malaysia to investigate factory women's experiences of work and work-related health risks. Discourse analysis surfaced a latent consciousness of bodily changes in relation to work. A grounded theory analysis showed a compromised access to occupational risk knowledge that may bear negatively on women's well-being and the role women's new labor identities played in mediating the meanings of work and risks. Given the predominance of women workers in low-end manufacturing globally, I aimed to contribute to theoretical and applied understandings of gender, globalization, and health.
Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

NASA Technical Reports Server (NTRS)

Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

1984-01-01

An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.
Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of Landsat digital data. [mapping of hydrothermally altered volcanic rocks

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed using Johnson's HICLUS program. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.
Workplace discrimination: experiences of practicing physicians.

PubMed

Coombs, Alice A Tolbert; King, Roderick K

2005-04-01

In response to a growing concern regarding physician discrimination in the workplace, this study was developed to: (1) describe the types of discrimination that exist for the practicing physician and (2) determine which groups of physicians are more likely to experience the various forms of discrimination. Surveys were mailed to 1930 practicing physicians in Massachusetts. Participants were asked if they had encountered discrimination, how significant the discrimination was against a specific group, the frequency of personal discrimination, and the type of discrimination. Factor analysis identified four types of discrimination: career advancement, punitive behaviors, practice barriers and hiring barriers. A total of 445 responses were received (a 24% response rate). Sixty-three percent of responding physicians had experienced some form of discrimination. Respondents were women (46%), racial/ethnic minorities (42%) and international medical graduates (IMGs) (40%). In addition, 26% of those classified as white were also IMGs. Over 60% of respondents believed discrimination against IMGs was very or somewhat significant. Almost 27% of males acknowledged that gender bias against females was very or somewhat significant. IMGs were more likely to indicate that discrimination against IMGs was significant in their current organization. Of U.S. medical graduates (USMGs) 44% reported that discrimination against IMGs in their current organization was significant. Nonwhites were more likely to report that discrimination based on race/ethnicity was significant. Nearly 29% of white respondents also believed that such discrimination was very or somewhat significant. Physicians practicing in academic, research, and private practice sectors experience discrimination based on gender, ethnic/racial, and IMG status.
Textural Maturity Analysis and Sedimentary Environment Discrimination Based on Grain Shape Data

NASA Astrophysics Data System (ADS)

Tunwal, M.; Mulchrone, K. F.; Meere, P. A.

2017-12-01

Morphological analysis of clastic sedimentary grains is an important source of information regarding the processes involved in their formation, transportation and deposition. However, a standardised approach for quantitative grain shape analysis is generally lacking. In this contribution we report on a study where fully automated image analysis techniques were applied to loose sediment samples collected from glacial, aeolian, beach and fluvial environments. A range of shape parameters are evaluated for their usefulness in textural characterisation of populations of grains. The utility of grain shape data in ranking textural maturity of samples within a given sedimentary environment is evaluated. Furthermore, discrimination of sedimentary environment on the basis of grain shape information is explored. The data gathered demonstrates a clear progression in textural maturity in terms of roundness, angularity, irregularity, fractal dimension, convexity, solidity and rectangularity. Textural maturity can be readily categorised using automated grain shape parameter analysis. However, absolute discrimination between different depositional environments on the basis of shape parameters alone is less certain. For example, the aeolian environment is quite distinct whereas fluvial, glacial and beach samples are inherently variable and tend to overlap each other in terms of textural maturity. This is most likely due to a collection of similar processes and sources operating within these environments. This study strongly demonstrates the merit of quantitative population-based shape parameter analysis of texture and indicates that it can play a key role in characterising both loose and consolidated sediments. This project is funded by the Irish Petroleum Infrastructure Programme (www.pip.ie)
Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics.

PubMed

Melucci, Dora; Bendini, Alessandra; Tesini, Federica; Barbieri, Sara; Zappi, Alessandro; Vichi, Stefania; Conte, Lanfranco; Gallina Toschi, Tullia

2016-08-01

At present, the geographical origin of extra virgin olive oils can be ensured by documented traceability, although chemical analysis may add information that is useful for possible confirmation. This preliminary study investigated the effectiveness of flash gas chromatography electronic nose and multivariate data analysis to perform rapid screening of commercial extra virgin olive oils characterized by a different geographical origin declared in the label. A comparison with solid phase micro extraction coupled to gas chromatography mass spectrometry was also performed. The new method is suitable to verify the geographic origin of extra virgin olive oils based on principal components analysis and discriminant analysis applied to the volatile profile of the headspace as a fingerprint. The selected variables were suitable in discriminating between "100% Italian" and "non-100% Italian" oils. Partial least squares discriminant analysis also allowed prediction of the degree of membership of unknown samples to the classes examined. Copyright © 2016. Published by Elsevier Ltd.
Behavioral lifestyle and mental health status of Japanese factory workers.

PubMed

Ezoe, S; Morimoto, K

1994-01-01

Lifestyle factors, sometimes associated with physical health and mortality, have also been known to be associated with mental health status. This study seeks to correlate behavioral lifestyles with major components of mental health among Japanese factory workers. We administered the 28-item version of the General Health Questionnaire (GHQ-28) and a questionnaire concerning eight personal health practices to 2,132 male and 668 female factory workers at a camera-manufacturing company in Japan. There were strong negative relationships of a higher total number of favorable lifestyles as indicated by the Health Practice Index (HPI) to psychological distress and its components: somatic symptoms, anxiety-insomnia, and social dysfunction. After controlling for the effects of confounding factors that included age, marital status, and somatic condition, multiple logistic regression analysis indicated that five of the eight health factors among male workers--mental stress, nutritional balance, eating breakfast regularly, physical exercise, and working hours--were significantly related to the grade of psychological distress or its three components. Among female workers, five health practices, i.e., mental stress, physical exercise, sleeping hours, working hours, and cigarette smoking, were significantly associated with the grade of psychological distress or its three components. Good health practices might be individually and as a whole associated with better mental health status in factory workers.
The Learning Factory.

ERIC Educational Resources Information Center

Alef, Edward R.; Berg, Daniel

This book looks at the administration of an academic institution as a learning factory which needs to be run like a business, competing with other businesses offering the same service. The book begins with a discussion of the concepts of the continuing education learning market, the playing fields and rules of the games, as well as the idea of…
Application of otolith shape analysis for stock discrimination and species identification of five goby species (Perciformes: Gobiidae) in the northern Chinese coastal waters

NASA Astrophysics Data System (ADS)

Yu, Xin; Cao, Liang; Liu, Jinhu; Zhao, Bo; Shan, Xiujuan; Dou, Shuozeng

2014-09-01

We tested the use of otolith shape analysis to discriminate between species and stocks of five goby species ( Ctenotrypauchen chinensis, Odontamblyopus lacepedii, Amblychaeturichthys hexanema, Chaeturichthys stigmatias, and Acanthogobius hasta) found in northern Chinese coastal waters. The five species were well differentiated with high overall classification success using shape indices (83.7%), elliptic Fourier coefficients (98.6%), or the combination of both methods (94.9%). However, shape analysis alone was only moderately successful at discriminating among the four stocks (Liaodong Bay, LD; Bohai Bay, BH; Huanghe (Yellow) River estuary HRE, and Jiaozhou Bay, JZ stocks) of A. hasta (50%-54%) and C. stigmatias (65.7%-75.8%). For these two species, shape analysis was moderately successful at discriminating the HRE or JZ stocks from other stocks, but failed to effectively identify the LD and BH stocks. A large number of otoliths were misclassified between the HRE and JZ stocks, which are geographically well separated. The classification success for stock discrimination was higher using elliptic Fourier coefficients alone (70.2%) or in combination with shape indices (75.8%) than using only shape indices (65.7%) in C. stigmatias whereas there was little difference among the three methods for A. hasta. Our results supported the common belief that otolith shape analysis is generally more effective for interspecific identification than intraspecific discrimination. Moreover, compared with shape indices analysis, Fourier analysis improves classification success during inter- and intra-species discrimination by otolith shape analysis, although this did not necessarily always occur in all fish species.
27 CFR 40.47 - Other businesses within factory.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 27 Alcohol, Tobacco Products and Firearms 2 2012-04-01 2011-04-01 true Other businesses within... AND TUBES, AND PROCESSED TOBACCO Administrative Provisions § 40.47 Other businesses within factory. (a) General. The appropriate TTB officer may authorize such other businesses within the factory of a...
27 CFR 40.47 - Other businesses within factory.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 27 Alcohol, Tobacco Products and Firearms 2 2014-04-01 2014-04-01 false Other businesses within... AND TUBES, AND PROCESSED TOBACCO Administrative Provisions § 40.47 Other businesses within factory. (a) General. The appropriate TTB officer may authorize such other businesses within the factory of a...
Early discrimination of nasopharyngeal carcinoma based on tissue deoxyribose nucleic acid surface-enhanced Raman spectroscopy analysis

NASA Astrophysics Data System (ADS)

Qiu, Sufang; Li, Chao; Lin, Jinyong; Xu, Yuanji; Lu, Jun; Huang, Qingting; Zou, Changyan; Chen, Chao; Xiao, Nanyang; Lin, Duo; Chen, Rong; Pan, Jianji; Feng, Shangyuan

2016-12-01

Surface-enhanced Raman spectroscopy (SERS) was employed to detect deoxyribose nucleic acid (DNA) variations associated with the development of nasopharyngeal carcinoma (NPC). Significant SERS spectral differences between the DNA extracted from early NPC, advanced NPC, and normal nasopharyngeal tissue specimens were observed at 678, 729, 788, 1337, 1421, 1506, and 1573 cm-1, which reflects the genetic variations in NPC. Principal component analysis combined with discriminant function analysis for early NPC discrimination yielded a diagnostic accuracy of 86.8%, 92.3%, and 87.9% for early NPC, advanced NPC, and normal nasopharyngeal tissue DNA, respectively. In this exploratory study, we demonstrated the potential of SERS for early detection of NPC based on the DNA molecular study of biopsy tissues.
Local classification: Locally weighted-partial least squares-discriminant analysis (LW-PLS-DA).

PubMed

Bevilacqua, Marta; Marini, Federico

2014-08-01

The possibility of devising a simple, flexible and accurate non-linear classification method, by extending the locally weighted partial least squares (LW-PLS) approach to the cases where the algorithm is used in a discriminant way (partial least squares discriminant analysis, PLS-DA), is presented. In particular, to assess which category an unknown sample belongs to, the proposed algorithm operates by identifying which training objects are most similar to the one to be predicted and building a PLS-DA model using these calibration samples only. Moreover, the influence of the selected training samples on the local model can be further modulated by adopting a not uniform distance-based weighting scheme which allows the farthest calibration objects to have less impact than the closest ones. The performances of the proposed locally weighted-partial least squares-discriminant analysis (LW-PLS-DA) algorithm have been tested on three simulated data sets characterized by a varying degree of non-linearity: in all cases, a classification accuracy higher than 99% on external validation samples was achieved. Moreover, when also applied to a real data set (classification of rice varieties), characterized by a high extent of non-linearity, the proposed method provided an average correct classification rate of about 93% on the test set. By the preliminary results, showed in this paper, the performances of the proposed LW-PLS-DA approach have proved to be comparable and in some cases better than those obtained by other non-linear methods (k nearest neighbors, kernel-PLS-DA and, in the case of rice, counterpropagation neural networks). Copyright © 2014 Elsevier B.V. All rights reserved.
The 9-item Bergen Burnout Inventory: Factorial Validity Across Organizations and Measurements of Longitudinal Data

PubMed Central

Feldt, Taru; RANTANEN, Johanna; HYVÖNEN, Katriina; MÄKIKANGAS, Anne; HUHTALA, Mari; PIHLAJASAARI, Pia; KINNUNEN, Ulla

2013-01-01

The present study tested the factorial validity of the 9-item Bergen Burnout Inventory (BBI-9)1). The BBI-9 is comprised of three core dimensions: (1) exhaustion at work; (2) cynicism toward the meaning of work; and (3) sense of inadequacy at work. The study further investigated whether the three-factor structure of the BBI-9 remains the same across different organizations (group invariance) and measurement time points (time invariance). The factorial group invariance was tested using a cross-sectional design with data pertaining to managers (n=742), and employees working in a bank (n=162), an engineering office (n=236), a public sector organization divided into three service areas: administration (n=102), education and culture (n=581), and social affairs and health (n=1,505). Factorial time invariance was tested using longitudinal data pertaining to managers, with three measurements over a four-year follow-up period. The confirmatory factor analysis revealed that the three-factor structure of the BBI-9 was invariant across cross-sectional samples. The factorial invariance was also supported across measurement times. To conclude, the factorial structure of the BBI-9 was found to remain the same regardless of the sample properties and measurement times. PMID:24366535
Sex Discrimination in Higher Education Employment: An Empirical Analysis of the Case Law.

ERIC Educational Resources Information Center

Schoenfeld, Sage L.; Zirkel, Perry A.

1989-01-01

Analysis of 132 court decisions for the period of 1976-86 concerning sex discrimination of faculty and nonfaculty employees in higher education indicates that the overall odds favor the defendant-institutions over the plaintiff-employees by a four-to-one ratio. The most frequently litigated institutional action was salary, followed by hiring and…

Perceived age discrimination in older adults

PubMed Central

Rippon, Isla; Kneale, Dylan; de Oliveira, Cesar; Demakakos, Panayotes; Steptoe, Andrew

2014-01-01

Objectives: to examine perceived age discrimination in a large representative sample of older adults in England. Methods: this cross-sectional study of over 7,500 individuals used data from the fifth wave of the English Longitudinal Study of Ageing (ELSA), a longitudinal cohort study of men and women aged 52 years and older in England. Wave 5 asked respondents about the frequency of five everyday discriminatory situations. Participants who attributed any experiences of discrimination to their age were treated as cases of perceived age discrimination. Multivariable logistic regression analysis was used to estimate the odds ratios of experiencing perceived age discrimination in relation to selected sociodemographic factors. Results: approximately a third (33.3%) of all respondents experienced age discrimination, rising to 36.8% in those aged 65 and over. Perceived age discrimination was associated with older age, higher education, lower levels of household wealth and being retired or not in employment. The correlates of age discrimination across the five discriminatory situations were similar. Conclusion: understanding age discrimination is vital if we are to develop appropriate policies and to target future interventions effectively. These findings highlight the scale of the challenge of age discrimination for older adults in England and illustrate that those groups are particularly vulnerable to this form of discrimination. PMID:24077751
Perceived age discrimination in older adults.

PubMed

Rippon, Isla; Kneale, Dylan; de Oliveira, Cesar; Demakakos, Panayotes; Steptoe, Andrew

2014-05-01

to examine perceived age discrimination in a large representative sample of older adults in England. this cross-sectional study of over 7,500 individuals used data from the fifth wave of the English Longitudinal Study of Ageing (ELSA), a longitudinal cohort study of men and women aged 52 years and older in England. Wave 5 asked respondents about the frequency of five everyday discriminatory situations. Participants who attributed any experiences of discrimination to their age were treated as cases of perceived age discrimination. Multivariable logistic regression analysis was used to estimate the odds ratios of experiencing perceived age discrimination in relation to selected sociodemographic factors. approximately a third (33.3%) of all respondents experienced age discrimination, rising to 36.8% in those aged 65 and over. Perceived age discrimination was associated with older age, higher education, lower levels of household wealth and being retired or not in employment. The correlates of age discrimination across the five discriminatory situations were similar. understanding age discrimination is vital if we are to develop appropriate policies and to target future interventions effectively. These findings highlight the scale of the challenge of age discrimination for older adults in England and illustrate that those groups are particularly vulnerable to this form of discrimination.
Discrimination of Geographical Origin of Asian Garlic Using Isotopic and Chemical Datasets under Stepwise Principal Component Analysis.

PubMed

Liu, Tsang-Sen; Lin, Jhen-Nan; Peng, Tsung-Ren

2018-01-16

Isotopic compositions of δ 2 H, δ 18 O, δ 13 C, and δ 15 N and concentrations of 22 trace elements from garlic samples were analyzed and processed with stepwise principal component analysis (PCA) to discriminate garlic's country of origin among Asian regions including South Korea, Vietnam, Taiwan, and China. Results indicate that there is no single trace-element concentration or isotopic composition that can accomplish the study's purpose and the stepwise PCA approach proposed does allow for discrimination between countries on a regional basis. Sequentially, Step-1 PCA distinguishes garlic's country of origin among Taiwanese, South Korean, and Vietnamese samples; Step-2 PCA discriminates Chinese garlic from South Korean garlic; and Step-3 and Step-4 PCA, Chinese garlic from Vietnamese garlic. In model tests, countries of origin of all audit samples were correctly discriminated by stepwise PCA. Consequently, this study demonstrates that stepwise PCA as applied is a simple and effective approach to discriminating country of origin among Asian garlics. © 2018 American Academy of Forensic Sciences.
Workplace discrimination: experiences of practicing physicians.

PubMed Central

Coombs, Alice A. Tolbert; King, Roderick K.

2005-01-01

BACKGROUND: In response to a growing concern regarding physician discrimination in the workplace, this study was developed to: (1) describe the types of discrimination that exist for the practicing physician and (2) determine which groups of physicians are more likely to experience the various forms of discrimination. METHODS: Surveys were mailed to 1930 practicing physicians in Massachusetts. Participants were asked if they had encountered discrimination, how significant the discrimination was against a specific group, the frequency of personal discrimination, and the type of discrimination. Factor analysis identified four types of discrimination: career advancement, punitive behaviors, practice barriers and hiring barriers. RESULTS: A total of 445 responses were received (a 24% response rate). Sixty-three percent of responding physicians had experienced some form of discrimination. Respondents were women (46%), racial/ethnic minorities (42%) and international medical graduates (IMGs) (40%). In addition, 26% of those classified as white were also IMGs. Over 60% of respondents believed discrimination against IMGs was very or somewhat significant. Almost 27% of males acknowledged that gender bias against females was very or somewhat significant. IMGs were more likely to indicate that discrimination against IMGs was significant in their current organization. Of U.S. medical graduates (USMGs) 44% reported that discrimination against IMGs in their current organization was significant. Nonwhites were more likely to report that discrimination based on race/ethnicity was significant. Nearly 29% of white respondents also believed that such discrimination was very or somewhat significant. CONCLUSIONS: Physicians practicing in academic, research, and private practice sectors experience discrimination based on gender, ethnic/racial, and IMG status. Images Figure 3 Figure 4 Figure 5 PMID:15868767
Structural and functional analysis of virus factories purified from Rabbit vesivirus-infected Vero cells.

PubMed

Casais, Rosa; Molleda, Lorenzo González; Machín, Angeles; del Barrio, Gloria; Manso, Alberto García; Dalton, Kevin P; Coto, Ana; Alonso, José Manuel Martín; Prieto, Miguel; Parra, Francisco

2008-10-01

Rabbit vesivirus infection induces membrane modifications and accumulation of vesicular structures in the cytoplasm of infected Vero cells. Crude RaV replication complexes (RCs) have been purified and their structural and functional properties have been characterized. We show that calnexin, an ER-resident protein, RaV non-structural proteins 2AB-, 2C-, 3A-, 3B- and 3CD-like as well as viral RNAs co-localize within membranous structures which are able to replicate the endogenous RNA templates. The purified virus factories protected their viral RNA contents from microccocal nuclease degradation and were inaccessible to exogenously added synthetic transcripts. In addition, we have shown that RCs can be used to investigate uridylylation of native endogenous VPg. In contrast to the observation that the virus factories were inaccessible to RNAs, RCs were accessible to added recombinant VPg which was subsequently nucleotidylylated. Nevertheless no elongation of an RNA chain attached to native or recombinant VPg could be demonstrated.
Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

PubMed

Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

2017-07-01

Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
The contribution of cluster and discriminant analysis to the classification of complex aquifer systems.

PubMed

Panagopoulos, G P; Angelopoulou, D; Tzirtzilakis, E E; Giannoulopoulos, P

2016-10-01

This paper presents an innovated method for the discrimination of groundwater samples in common groups representing the hydrogeological units from where they have been pumped. This method proved very efficient even in areas with complex hydrogeological regimes. The proposed method requires chemical analyses of water samples only for major ions, meaning that it is applicable to most of cases worldwide. Another benefit of the method is that it gives a further insight of the aquifer hydrogeochemistry as it provides the ions that are responsible for the discrimination of the group. The procedure begins with cluster analysis of the dataset in order to classify the samples in the corresponding hydrogeological unit. The feasibility of the method is proven from the fact that the samples of volcanic origin were separated into two different clusters, namely the lava units and the pyroclastic-ignimbritic aquifer. The second step is the discriminant analysis of the data which provides the functions that distinguish the groups from each other and the most significant variables that define the hydrochemical composition of the aquifer. The whole procedure was highly successful as the 94.7 % of the samples were classified to the correct aquifer system. Finally, the resulted functions can be safely used to categorize samples of either unknown or doubtful origin improving thus the quality and the size of existing hydrochemical databases.
Seismic signature analysis for discrimination of people from animals

NASA Astrophysics Data System (ADS)

Damarla, Thyagaraju; Mehmood, Asif; Sabatier, James M.

2013-05-01

Cadence analysis has been the main focus for discriminating between the seismic signatures of people and animals. However, cadence analysis fails when multiple targets are generating the signatures. We analyze the mechanism of human walking and the signature generated by a human walker, and compare it with the signature generated by a quadruped. We develop Fourier-based analysis to differentiate the human signatures from the animal signatures. We extract a set of basis vectors to represent the human and animal signatures using non-negative matrix factorization, and use them to separate and classify both the targets. Grazing animals such as deer, cows, etc., often produce sporadic signals as they move around from patch to patch of grass and one must characterize them so as to differentiate their signatures from signatures generated by a horse steadily walking along a path. These differences in the signatures are used in developing a robust algorithm to distinguish the signatures of animals from humans. The algorithm is tested on real data collected in a remote area.
Efficiency in Complexity: Composition and Dynamic Nature of Mimivirus Replication Factories

PubMed Central

Milrot, Elad; Mutsafi, Yael; Ben-Dor, Shifra; Levin, Yishai; Savidor, Alon; Kartvelishvily, Elena

2016-01-01

ABSTRACT The recent discovery of multiple giant double-stranded DNA (dsDNA) viruses blurred the consensual distinction between viruses and cells due to their size, as well as to their structural and genetic complexity. A dramatic feature revealed by these viruses as well as by many positive-strand RNA viruses is their ability to rapidly form elaborate intracellular organelles, termed “viral factories,” where viral progeny are continuously generated. Here we report the first isolation of viral factories at progressive postinfection time points. The isolated factories were subjected to mass spectrometry-based proteomics, bioinformatics, and imaging analyses. These analyses revealed that numerous viral proteins are present in the factories but not in mature virions, thus implying that multiple and diverse proteins are required to promote the efficiency of viral factories as “production lines” of viral progeny. Moreover, our results highlight the dynamic and highly complex nature of viral factories, provide new and general insights into viral infection, and substantiate the intriguing notion that viral factories may represent the living state of viruses. IMPORTANCE Large dsDNA viruses such as vaccinia virus and the giant mimivirus, as well as many positive-strand RNA viruses, generate elaborate cytoplasmic organelles in which the multiple and diverse transactions required for viral replication and assembly occur. These organelles, which were termed “viral factories,” are attracting much interest due to the increasing realization that the rapid and continuous production of viral progeny is a direct outcome of the elaborate structure and composition of the factories, which act as efficient production lines. To get new insights into the nature and function of viral factories, we devised a method that allows, for the first time, the isolation of these organelles. Analyses of the isolated factories generated at different times postinfection by mass spectrometry
Assessment of Tooth Wear Among Glass Factory Workers: WHO 2013 Oral Health Survey

PubMed Central

Bhat, Nagesh; Asawa, Kailash; Tak, Mridula; Bapat, Salil; Gupta, Vivek Vardhan

2015-01-01

Background Glass factory workers are often exposed to the hazardous environment that leads to deleterious oral health and subsequently, general health. We planned to determine the effects of the particulates present in the milieu on the tooth wear among workers. Aim To assess tooth wear among glass factory workers in Jaipur, Rajasthan, India. Settings and Design A descriptive cross-sectional survey was conducted among 936 glass workers in Jaipur, Rajasthan, India from January-June 2014. Materials and Methods A survey proforma was designed for tooth wear evaluation with the help of WHO Oral Health Assessment form 2013 (for adults). Information regarding oral health practices, adverse habits and dietary habits, demographic details was gathered and clinical parameters were recorded. Statistical Analysis The Chi–square test, t–test, One-way Analysis of Variance and a Stepwise multiple linear regression analysis. Results The most prevalent form of erosion was enamel erosion (589, 62.93%) with few subjects of deeper dentinal erosion and the difference was statistically significant (p=0.001). Dental erosion was found to be higher among males compared to females. Years of experience and educational status were identified as best predictors for dental erosion. Conclusion It was concluded that there was considerable evidence of dental erosion found among the factory workers. Due to ignorance on social, cultural and health aspects, professional approach with regular dental care services for detection of early symptoms and planning of preventive strategies is warranted. PMID:26436050
Effects of Perceived Discrimination on Depressive Symptoms Among Black Men Residing in the United States: A Meta-Analysis

PubMed Central

Britt-Spells, Angelitta M.; Slebodnik, Maribeth; Sands, Laura P.; Rollock, David

2016-01-01

Research reports that perceived discrimination is positively associated with depressive symptoms. The literature is limited when examining this relationship among Black men. This meta-analysis systematically examines the current literature and investigates the relationship of perceived discrimination on depressive symptoms among Black men residing in the United States. Using a random-effects model, study findings indicate a positive association between perceived discrimination and depressive symptoms among Black men (r = .29). Several potential moderators were also examined in this study; however, there were no significant moderation effects detected. Recommendations and implications for future research and practice are discussed. PMID:26742988
Gaming in the Classroom: An Innovative Way to Teach Factorial Designs

ERIC Educational Resources Information Center

Stansbury, Jessica A.; Munro, Geoffrey D.

2013-01-01

This study tested the effectiveness of video game use for instruction of factorial designs in a research methods course. Students designed and conducted a mini study, playing "Dance, Dance, Revolution", using video game scores as the dependent variable. A mixed-design analysis of variance revealed a significantly greater increase from pretest to…
Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options.

PubMed

Quanbao, Jiang; Shuzhuo, Li; Marcus W, Feldman

2011-08-01

The large number of missing females in China, a consequence of gender discrimination, is having and will continue to have a profound effect on the country's population development. In this paper, we analyze the causes of this gender discrimination in terms of institutions, culture and, economy, and suggest public policies that might help eliminate gender discrimination. Using a population simulation model, we study the effect of public policies on the sex ratio at birth and excess female child mortality, and the effect of gender discrimination on China's population development. We find that gender discrimination will decrease China's population size, number of births, and working age population, accelerate population aging and exacerbate the male marriage squeeze. These results provide theoretical support for suggesting that the government enact and implement public policies aimed at eliminating gender discrimination.
A Classroom of Polymer Factories.

ERIC Educational Resources Information Center

Harris, Mary E.; Van Natta, Sandra

1998-01-01

Provides an activity in which students create small classroom factories and investigate several aspects of production including design, engineering, quality control, waste management, packaging, shipment, and communication. (DDR)
Attractor structure discriminates sleep states: recurrence plot analysis applied to infant breathing patterns.

PubMed

Terrill, Philip Ian; Wilson, Stephen James; Suresh, Sadasivam; Cooper, David M; Dakin, Carolyn

2010-05-01

Breathing patterns are characteristically different between infant active sleep (AS) and quiet sleep (QS), and statistical quantifications of interbreath interval (IBI) data have previously been used to discriminate between infant sleep states. It has also been identified that breathing patterns are governed by a nonlinear controller. This study aims to investigate whether nonlinear quantifications of infant IBI data are characteristically different between AS and QS, and whether they may be used to discriminate between these infant sleep states. Polysomnograms were obtained from 24 healthy infants at six months of age. Periods of AS and QS were identified, and IBI data extracted. Recurrence quantification analysis (RQA) was applied to each period, and recurrence calculated for a fixed radius in the range of 0-8 in steps of 0.02, and embedding dimensions of 4, 6, 8, and 16. When a threshold classifier was trained, the RQA variable recurrence was able to correctly classify 94.3% of periods in a test dataset. It was concluded that RQA of IBI data is able to accurately discriminate between infant sleep states. This is a promising step toward development of a minimal-channel automatic sleep state classification system.
Different faces of discrimination: perceived discrimination among homeless adults with mental illness in healthcare settings.

PubMed

Skosireva, Anna; O'Campo, Patricia; Zerger, Suzanne; Chambers, Catharine; Gapka, Susan; Stergiopoulos, Vicky

2014-09-07

Research on discrimination in healthcare settings has primarily focused on health implications of race-based discrimination among ethno-racial minority groups. Little is known about discrimination experiences of other marginalized populations, particularly groups facing multiple disadvantages who may be subjected to other/multiple forms of discrimination. (1) To examine the prevalence of perceived discrimination due to homelessness/poverty, mental illness/alcohol/drug related problems, and race/ethnicity/skin color while seeking healthcare in the past year among racially diverse homeless adults with mental illness; (2) To identify whether perceiving certain types of discrimination is associated with increased likelihood of perceiving other kinds of discrimination; and (3) To examine association of these perceived discrimination experiences with socio-demographic characteristics, self-reported measures of psychiatric symptomatology and substance use, and Emergency Department utilization. We used baseline data from the Toronto site of the At Home/Chez Soi randomized controlled trial of Housing First for homeless adults with mental illness (n = 550). Bivariate statistics and multivariable logistic regression models were used for the analysis. Perceived discrimination related to homelessness/poverty (30.4%) and mental illness/alcohol/substance use (32.5%) is prevalent among ethnically diverse homeless adults with mental illness in healthcare settings. Only 15% of the total participants reported discrimination due to race/ethnicity/skin color. After controlling for relevant confounders and presence of psychosis, all types of discrimination in healthcare settings were associated with more frequent ED use, a greater - 3 - severity of lifetime substance abuse, and mental health problems. Perceiving discrimination of one type was associated with increased likelihood of perceiving other kinds of discrimination. Understanding the experience of discrimination in healthcare
The Role of Discrimination in Care Postponement Among Trans-Feminine Individuals in the U.S. National Transgender Discrimination Survey.

PubMed

Glick, Jennifer L; Theall, Katherine P; Andrinopoulos, Katherine M; Kendall, Carl

2018-04-01

This study examines the associations between discrimination experiences (types and locations) and care postponement among trans-feminine individuals in the United States. This secondary, cross-sectional study utilized a subset of the data from the National Transgender Discrimination Survey (n = 2248), specifically for trans-feminine individuals. In this analysis, we examined the relationship between discrimination and primary care postponement. Twenty-six percent (26.25%) of the study sample reported delaying preventive care due to fear of discrimination; 23.98%-46.66% of respondents reported past experiences of discrimination (setting dependent). Discrimination in health and non-health settings and different types of discrimination-being denied services, verbally harassed, or physically assaulted-were all significantly associated with delaying care; respondents reporting discrimination were up to 20 times more likely to postpone care. While discrimination at a health location had the strongest association with care postponement (adjusted odds ratio = 9.65, confidence interval = 7.60-12.24), discrimination in all non-health-related locations was also important. Individuals reporting discrimination in greater numbers of locations and multiple types of discrimination were more likely to postpone care. To promote preventive care-seeking, these results affirm the importance of interventions that promote discrimination-free environments for gender minorities.
Item validity vs. item discrimination index: a redundancy?

NASA Astrophysics Data System (ADS)

Panjaitan, R. L.; Irawati, R.; Sujana, A.; Hanifah, N.; Djuanda, D.

2018-03-01

In several literatures about evaluation and test analysis, it is common to find that there are calculations of item validity as well as item discrimination index (D) with different formula for each. Meanwhile, other resources said that item discrimination index could be obtained by calculating the correlation between the testee’s score in a particular item and the testee’s score on the overall test, which is actually the same concept as item validity. Some research reports, especially undergraduate theses tend to include both item validity and item discrimination index in the instrument analysis. It seems that these concepts might overlap for both reflect the test quality on measuring the examinees’ ability. In this paper, examples of some results of data processing on item validity and item discrimination index were compared. It would be discussed whether item validity and item discrimination index can be represented by one of them only or it should be better to present both calculations for simple test analysis, especially in undergraduate theses where test analyses were included.
Development and Validation of Discriminant Analysis Models for Student Loan Defaultees and Non-Defaultees.

ERIC Educational Resources Information Center

Myers, Greeley; Siera, Steven

1980-01-01

Default on guaranteed student loans has been increasing. The use of discriminant analysis as a technique to identify "good" v "bad" student loans based on information available from the loan application is discussed. Research to test the ability of models to such predictions is reported. (Author/MLW)
A new method for fingerprinting sediments source contributions using distances from discriminant function analysis

USDA-ARS?s Scientific Manuscript database

Mixing models have been used to predict sediment source contributions. The inherent problem of the mixing models limited the number of sediment sources. The objective of this study is to develop and evaluate a new method using Discriminant Function Analysis (DFA) to fingerprint sediment source contr...

Perceived Discrimination and Health: A Meta-Analytic Review

ERIC Educational Resources Information Center

Pascoe, Elizabeth A.; Richman, Laura Smart

2009-01-01

Perceived discrimination has been studied with regard to its impact on several types of health effects. This meta-analysis provides a comprehensive account of the relationships between multiple forms of perceived discrimination and both mental and physical health outcomes. In addition, this meta-analysis examines potential mechanisms by which…
Engineering Robustness of Microbial Cell Factories.

PubMed

Gong, Zhiwei; Nielsen, Jens; Zhou, Yongjin J

2017-10-01

Metabolic engineering and synthetic biology offer great prospects in developing microbial cell factories capable of converting renewable feedstocks into fuels, chemicals, food ingredients, and pharmaceuticals. However, prohibitively low production rate and mass concentration remain the major hurdles in industrial processes even though the biosynthetic pathways are comprehensively optimized. These limitations are caused by a variety of factors unamenable for host cell survival, such as harsh industrial conditions, fermentation inhibitors from biomass hydrolysates, and toxic compounds including metabolic intermediates and valuable target products. Therefore, engineered microbes with robust phenotypes is essential for achieving higher yield and productivity. In this review, the recent advances in engineering robustness and tolerance of cell factories is described to cope with these issues and briefly introduce novel strategies with great potential to enhance the robustness of cell factories, including metabolic pathway balancing, transporter engineering, and adaptive laboratory evolution. This review also highlights the integration of advanced systems and synthetic biology principles toward engineering the harmony of overall cell function, more than the specific pathways or enzymes. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A simple randomisation procedure for validating discriminant analysis: a methodological note.

PubMed

Wastell, D G

1987-04-01

Because the goal of discriminant analysis (DA) is to optimise classification, it designedly exaggerates between-group differences. This bias complicates validation of DA. Jack-knifing has been used for validation but is inappropriate when stepwise selection (SWDA) is employed. A simple randomisation test is presented which is shown to give correct decisions for SWDA. The general superiority of randomisation tests over orthodox significance tests is discussed. Current work on non-parametric methods of estimating the error rates of prediction rules is briefly reviewed.
Mu Opioid Mediated Discriminative-Stimulus Effects of Tramadol: An Individual Subjects Analysis

PubMed Central

Strickland, Justin C.; Rush, Craig R.; Stoops, William W.

2015-01-01

Drug discrimination procedures use dose-dependent generalization, substitution, and pretreatment with selective agonists and antagonists to evaluate receptor systems mediating interoceptive effects of drugs. Despite the extensive use of these techniques in the nonhuman animal literature, few studies have used human subjects. Specifically, human studies have not routinely used antagonist administration as a pharmacological tool to elucidate the mechanisms mediating the discriminative stimulus effects of drugs. This study evaluated the discriminative-stimulus effects of tramadol, an atypical analgesic with monoamine and mu opioid activity. Three human subjects first learned to discriminate 100 mg tramadol from placebo. A range of tramadol doses (25 to 150 mg) and hydromorphone (4 mg) with and without naltrexone pretreatment (50 mg) were then administered to subjects after acquiring the discrimination. Tramadol produced dose-dependent increases in drug-appropriate responding and hydromorphone partially or fully substituted for tramadol in all subjects. These effects were attenuated by naltrexone. Individual subject records indicated a relationship between mu opioid activity (i.e., miosis) and drug discrimination performance. Our findings indicate that mu opioid activity may mediate the discriminative-stimulus effects of tramadol in humans. The correspondence of generalization, substitution, and pretreatment findings with the animal literature supports the neuropharmacological specificity of the drug discrimination procedure. PMID:25664525
Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options

PubMed Central

Quanbao, Jiang; Marcus W., Feldman

2013-01-01

The large number of missing females in China, a consequence of gender discrimination, is having and will continue to have a profound effect on the country's population development. In this paper, we analyze the causes of this gender discrimination in terms of institutions, culture and, economy, and suggest public policies that might help eliminate gender discrimination. Using a population simulation model, we study the effect of public policies on the sex ratio at birth and excess female child mortality, and the effect of gender discrimination on China's population development. We find that gender discrimination will decrease China's population size, number of births, and working age population, accelerate population aging and exacerbate the male marriage squeeze. These results provide theoretical support for suggesting that the government enact and implement public policies aimed at eliminating gender discrimination. PMID:24363477
Using Job Analytic Perceptions to Predict Stressor Levels among Factory Supervisors.

ERIC Educational Resources Information Center

Love, Kevin G.; And Others

Job stress is recognized as a primary roadblock to achieving job satisfaction. In order to investigate the linkage between important job characteristics and stressor levels, 378 factory supervisors (aged 45-54; 89 percent male; 93 percent white with an average of 21 years with the company) completed a two-part job analysis questionnaire. In the…
Discriminant analysis to predict the occurrence of ELMS in H-mode discharges

NASA Astrophysics Data System (ADS)

Kardaun, O. J. W. F.; Itoh, S.-I.; Itoh, K.; Kardaun, J. W. P. F.

1993-08-01

After an exposition of its theoretical background, discriminant analysis is applied to the H-mode confinement database to find the region in plasma parameter space in which H-mode with small ELM's (Edge Localized Modes) is likely to occur. The boundary of this region is determined by the condition that the probability of appearance of such a type of H-mode, as a function of the plasma parameters, should be larger than some threshold value and larger than the corresponding probability for other types of H-mode (i.e., H-mode without ELM's or with giant ELM's). In practice, the discrimination has been performed for the ASDEX, JET and JFT-2M tokamaks using four instantaneous plasma parameters (injected power Pinj, magnetic field Bt, plasma current Ip and line averaged electron density ne) and taking also memory effects of the plasma and the distance between the plasma and the wall into account, while using variables that are normalized with respect to machine size. Generally speaking, it is found that there is a substantial overlap between the region of H-mode with small ELM's and the region of the two other types of H-mode. However, the ELM-free and the giant ELM H-modes relatively rarely appear in the region, that, according to the analysis, is allocated to small ELM's. A reliable production of H-mode with only small ELM's seems well possible by choosing this regime in parameter space. In the present study, it was not attempted to arrive at a unified discrimination across the machines. So, projection from one machine to another remains difficult, and a reliable determination of the region where small ELM's occur still requires a training sample from the device under consideration.
Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-07-01

In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor
Myc Dynamically and Preferentially Relocates to a Transcription Factory Occupied by Igh

PubMed Central

Osborne, Cameron S; Chakalova, Lyubomira; Mitchell, Jennifer A; Horton, Alice; Wood, Andrew L; Bolland, Daniel J; Corcoran, Anne E; Fraser, Peter

2007-01-01

Transcription in mammalian nuclei is highly compartmentalized in RNA polymerase II-enriched nuclear foci known as transcription factories. Genes in cis and trans can share the same factory, suggesting that genes migrate to preassembled transcription sites. We used fluorescent in situ hybridization to investigate the dynamics of gene association with transcription factories during immediate early (IE) gene induction in mouse B lymphocytes. Here, we show that induction involves rapid gene relocation to transcription factories. Importantly, we find that the Myc proto-oncogene on Chromosome 15 is preferentially recruited to the same transcription factory as the highly transcribed Igh gene located on Chromosome 12. Myc and Igh are the most frequent translocation partners in plasmacytoma and Burkitt lymphoma. Our results show that transcriptional activation of IE genes involves rapid relocation to preassembled transcription factories. Furthermore, the data imply a direct link between the nonrandom interchromosomal organization of transcribed genes at transcription factories and the incidence of specific chromosomal translocations. PMID:17622196
Factory overload testing of a large power transformer

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

Douglas, D.H.; Lawrence, C.O.; Templeton, J.B.

1985-09-01

A factory overload test of up to 150% of the nameplate rating was run on a 224 MVA autotransformer. The results of this test were of great value and were used in identifying transformer overload limitations, in evaluating loading guide oil and winding equations, exponents and time constants, and in helping to perfect a factory overload test procedure.
Rapid discrimination of bergamot essential oil by paper spray mass spectrometry and chemometric analysis.

PubMed

Taverna, Domenico; Di Donna, Leonardo; Mazzotti, Fabio; Tagarelli, Antonio; Napoli, Anna; Furia, Emilia; Sindona, Giovanni

2016-09-01

A novel approach for the rapid discrimination of bergamot essential oil from other citrus fruits oils is presented. The method was developed using paper spray mass spectrometry (PS-MS) allowing for a rapid molecular profiling coupled with a statistic tool for a precise and reliable discrimination between the bergamot complex matrix and other similar matrices, commonly used for its reconstitution. Ambient mass spectrometry possesses the ability to record mass spectra of ordinary samples, in their native environment, without sample preparation or pre-separation by creating ions outside the instrument. The present study reports a PS-MS method for the determination of oxygen heterocyclic compounds such as furocoumarins, psoralens and flavonoids present in the non-volatile fraction of citrus fruits essential oils followed by chemometric analysis. The volatile fraction of Bergamot is one of the most known and fashionable natural products, which found applications in flavoring industry as ingredient in beverages and flavored foodstuff. The development of the presented method employed bergamot, sweet orange, orange, cedar, grapefruit and mandarin essential oils. PS-MS measurements were carried out in full scan mode for a total run time of 2 min. The capability of PS-MS profiling to act as marker for the classification of bergamot essential oils was evaluated by using multivariate statistical analysis. Two pattern recognition techniques, linear discriminant analysis and soft independent modeling of class analogy, were applied to MS data. The cross-validation procedure has shown excellent results in terms of the prediction ability because both models have correctly classified all samples for each category. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Hazardous factories: Nigerian evidence.

PubMed

Oloyede, Olajide

2005-06-01

The past 15 years have seen an increasing governmental and corporate concern for the environment worldwide. For governments, information about the environmental performance of the industrial sector is required to inform macro-level decisions about environmental targets such as those required to meet UN directives. However, in many African, Asian, and Latin American countries, researching and reporting company environmental performance is limited. This article serves as a contribution to filling the gap by presenting evidence of physical and chemical risk in Nigerian factories. One hundred and three factories with a total of 5,021 workers were studied. One hundred and twenty physical and chemical hazards were identified and the result shows a high number of workers exposed to such hazards. The study also reveals that workers' awareness level of chemical hazards was high. Yet the danger was perceived in behavioral terms, especially by manufacturing firms, which tend to see environmental investment in an increasingly global economy as detrimental to profitability.
Associations of racial discrimination and parental discrimination coping messages with African American adolescent racial identity.

PubMed

Richardson, Bridget L; Macon, Tamarie A; Mustafaa, Faheemah N; Bogan, Erin D; Cole-Lewis, Yasmin; Chavous, Tabbye M

2015-06-01

Research links racial identity to important developmental outcomes among African American adolescents, but less is known about the contextual experiences that shape youths' racial identity. In a sample of 491 African American adolescents (48% female), associations of youth-reported experiences of racial discrimination and parental messages about preparation for racial bias with adolescents' later racial identity were examined. Cluster analysis resulted in four profiles of adolescents varying in reported frequency of racial discrimination from teachers and peers at school and frequency of parental racial discrimination coping messages during adolescents' 8th grade year. Boys were disproportionately over-represented in the cluster of youth experiencing more frequent discrimination but receiving fewer parental discrimination coping messages, relative to the overall sample. Also examined were clusters of adolescents' 11th grade racial identity attitudes about the importance of race (centrality), personal group affect (private regard), and perceptions of societal beliefs about African Americans (public regard). Girls and boys did not differ in their representation in racial identity clusters, but 8th grade discrimination/parent messages clusters were associated with 11th grade racial identity cluster membership, and these associations varied across gender groups. Boys experiencing more frequent discrimination but fewer parental coping messages were over-represented in the racial identity cluster characterized by low centrality, low private regard, and average public regard. The findings suggest that adolescents who experience racial discrimination but receive fewer parental supports for negotiating and coping with discrimination may be at heightened risk for internalizing stigmatizing experiences. Also, the findings suggest the need to consider the context of gender in adolescents' racial discrimination and parental racial socialization.
The differentiation of camel breeds based on meat measurements using discriminant analysis.

PubMed

Al-Atiyat, Raed Mahmoud; Suliman, Gamal; AlSuhaibani, Entissar; El-Waziry, Ahmad; Al-Owaimer, Abdullah; Basmaeil, Saeid

2016-06-01

The meat productivity of camel in the tropics is still under investigation for identification of better meat breed or type. Therefore, four one-humped Saudi Arabian (SA) camel breeds, Majaheem, Maghateer, Hamrah, and Safrah were experimented in order to differentiate them from each other based on meat measurements. The measurements were biometrical meat traits measured on six intact males from each breed. The results showed higher values of the Majaheem breed than that obtained for the other breeds except few cases such dressing percentage and rib-eye area. In differentiation analysis, the most discriminating meat variables were myofibrillar protein index, meat color components (L* and a*, b*), and cooking loss. Consequently, the Safrah and the Majaheem breeds presented the largest dissimilarity as evidenced by their multivariate means. The canonical discriminant analysis allowed an additional understanding of the differentiation between breeds. Furthermore, two large clusters, one formed by Hamrah and Maghateer in one group along with Safrah. These classifications may assign each breed into one cluster considering they are better as meat producers. The Majaheem was clustered alone in another cluster that might be a result of being better as milk producers. Nevertheless, the productivity type of the camel breeds of SA needs further morphology and genetic descriptions.
Applying linear discriminant analysis to predict groundwater redox conditions conducive to denitrification

NASA Astrophysics Data System (ADS)

Wilson, S. R.; Close, M. E.; Abraham, P.

2018-01-01

Diffuse nitrate losses from agricultural land pollute groundwater resources worldwide, but can be attenuated under reducing subsurface conditions. In New Zealand, the ability to predict where groundwater denitrification occurs is important for understanding the linkage between land use and discharges of nitrate-bearing groundwater to streams. This study assesses the application of linear discriminant analysis (LDA) for predicting groundwater redox status for Southland, a major dairy farming region in New Zealand. Data cases were developed by assigning a redox status to samples derived from a regional groundwater quality database. Pre-existing regional-scale geospatial databases were used as training variables for the discriminant functions. The predictive accuracy of the discriminant functions was slightly improved by optimising the thresholds between sample depth classes. The models predict 23% of the region as being reducing at shallow depths (<15 m), and 37% at medium depths (15-75 m). Predictions were made at a sub-regional level to determine whether improvements could be made with discriminant functions trained by local data. The results indicated that any gains in predictive success were offset by loss of confidence in the predictions due to the reduction in the number of samples used. The regional scale model predictions indicate that subsurface reducing conditions predominate at low elevations on the coastal plains where poorly drained soils are widespread. Additional indicators for subsurface denitrification are a high carbon content of the soil, a shallow water table, and low-permeability clastic sediments. The coastal plains are an area of widespread groundwater discharge, and the soil and hydrology characteristics require the land to be artificially drained to render the land suitable for farming. For the improvement of water quality in coastal areas, it is therefore important that land and water management efforts focus on understanding hydrological
Corona discharge radical emission spectroscopy: a multi-channel detector with nose-type function for discrimination analysis.

PubMed

Tian, Yunfei; Wu, Peng; Wu, Xi; Jiang, Xiaoming; Xu, Kailai; Hou, Xiandeng

2013-04-21

A simple and economical multi-channel optical sensor using corona discharge radical emission spectroscopy is developed and explored as an optical nose for discrimination analysis of volatile organic compounds, wines, and even isomers.
Influence of variable selection on partial least squares discriminant analysis models for explosive residue classification

NASA Astrophysics Data System (ADS)

De Lucia, Frank C., Jr.; Gottfried, Jennifer L.

2011-02-01

Using a series of thirteen organic materials that includes novel high-nitrogen energetic materials, conventional organic military explosives, and benign organic materials, we have demonstrated the importance of variable selection for maximizing residue discrimination with partial least squares discriminant analysis (PLS-DA). We built several PLS-DA models using different variable sets based on laser induced breakdown spectroscopy (LIBS) spectra of the organic residues on an aluminum substrate under an argon atmosphere. The model classification results for each sample are presented and the influence of the variables on these results is discussed. We found that using the whole spectra as the data input for the PLS-DA model gave the best results. However, variables due to the surrounding atmosphere and the substrate contribute to discrimination when the whole spectra are used, indicating this may not be the most robust model. Further iterative testing with additional validation data sets is necessary to determine the most robust model.
Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.
Integrating PCLIPS into ULowell's Lincoln Logs: Factory of the future

NASA Technical Reports Server (NTRS)

Mcgee, Brenda J.; Miller, Mark D.; Krolak, Patrick; Barr, Stanley J.

1990-01-01

We are attempting to show how independent but cooperating expert systems, executing within a parallel production system (PCLIPS), can operate and control a completely automated, fault tolerant prototype of a factory of the future (The Lincoln Logs Factory of the Future). The factory consists of a CAD system for designing the Lincoln Log Houses, two workcells, and a materials handling system. A workcell consists of two robots, part feeders, and a frame mounted vision system.
[Heavy metals distribution characteristics and risk assessment of water below an electroplating factory].

PubMed

Hang, Xiao-Shuai; Wang, Huo-Yan; Zhou, Jian-Min

2008-10-01

Surface water and shallow groundwater within the flow of an electroplating factory was analyzed in order to study the resulting impact. The analysis method of ICP-AES was used to analyze content of zinc, manganese, chromium, copper and nickel in surface water and groundwater samples. The results indicate acidic pollutants of zinc, manganese, chromium, copper and nickel were discharged from the factory with concentrations of 1.34, 3.77, 28.1, 6.40 and 9.37 mg x L(-1), respectively; and pH was 2.32. They all exceeded permissible levels according to Integrated Wastewater Discharge Standard except zinc. Factory discharge is responsible for the longitudinal distribution characteristics of heavy metals in the stream water downstream from the factory. Heavy metals variations in the well water do not suggest they were affected by heavy metals in the stream, indicating that the migration rates of heavy metals in soils were relatively low. Risk assessment shows surface water quality significantly deteriorated. Nickel and manganese in the stream water exceeded the standard levels seriously, and chromium and copper in some samples were also above Grade III standard levels according to Environmental Quality Standard for Surface Water. Moreover, all studied heavy metals in 14 groundwater samples measured within drinking water standard, except manganese in 4 groundwater samples, which were Grade IV according to Quality Standard for Ground water.

Discrimination of Temperature and Strain in Brillouin Optical Time Domain Analysis Using a Multicore Optical Fiber

PubMed Central

Zaghloul, Mohamed A. S.; Wang, Mohan; Milione, Giovanni; Li, Ming-Jun; Li, Shenping; Huang, Yue-Kai; Wang, Ting; Chen, Kevin P.

2018-01-01

Brillouin optical time domain analysis is the sensing of temperature and strain changes along an optical fiber by measuring the frequency shift changes of Brillouin backscattering. Because frequency shift changes are a linear combination of temperature and strain changes, their discrimination is a challenge. Here, a multicore optical fiber that has two cores is fabricated. The differences between the cores’ temperature and strain coefficients are such that temperature (strain) changes can be discriminated with error amplification factors of 4.57 °C/MHz (69.11 μϵ/MHz), which is 2.63 (3.67) times lower than previously demonstrated. As proof of principle, using the multicore optical fiber and a commercial Brillouin optical time domain analyzer, the temperature (strain) changes of a thermally expanding metal cylinder are discriminated with an error of 0.24% (3.7%). PMID:29649148
Discrimination of Temperature and Strain in Brillouin Optical Time Domain Analysis Using a Multicore Optical Fiber.

PubMed

Zaghloul, Mohamed A S; Wang, Mohan; Milione, Giovanni; Li, Ming-Jun; Li, Shenping; Huang, Yue-Kai; Wang, Ting; Chen, Kevin P

2018-04-12

Brillouin optical time domain analysis is the sensing of temperature and strain changes along an optical fiber by measuring the frequency shift changes of Brillouin backscattering. Because frequency shift changes are a linear combination of temperature and strain changes, their discrimination is a challenge. Here, a multicore optical fiber that has two cores is fabricated. The differences between the cores' temperature and strain coefficients are such that temperature (strain) changes can be discriminated with error amplification factors of 4.57 °C/MHz (69.11 μ ϵ /MHz), which is 2.63 (3.67) times lower than previously demonstrated. As proof of principle, using the multicore optical fiber and a commercial Brillouin optical time domain analyzer, the temperature (strain) changes of a thermally expanding metal cylinder are discriminated with an error of 0.24% (3.7%).
The Limits of Outcomes Analysis; A Comment on "Sex Discrimination in Higher Employment: An Empirical Analysis of the Case Law."

ERIC Educational Resources Information Center

Lee, Barbara A.

1990-01-01

Questions assumptions by Schoenfeld and Zirkel in a study reviewing gender discrimination cases against institutions of higher education. Critiques the methodology used in that study, cautions about the overall utility of "outcomes analysis," and reports more promising routes of empirical legal research. (15 references) (MLF)
Assessment of Tooth Wear Among Glass Factory Workers: WHO 2013 Oral Health Survey.

PubMed

Chaturvedi, Pulkit; Bhat, Nagesh; Asawa, Kailash; Tak, Mridula; Bapat, Salil; Gupta, Vivek Vardhan

2015-08-01

Glass factory workers are often exposed to the hazardous environment that leads to deleterious oral health and subsequently, general health. We planned to determine the effects of the particulates present in the milieu on the tooth wear among workers. To assess tooth wear among glass factory workers in Jaipur, Rajasthan, India. A descriptive cross-sectional survey was conducted among 936 glass workers in Jaipur, Rajasthan, India from January-June 2014. A survey proforma was designed for tooth wear evaluation with the help of WHO Oral Health Assessment form 2013 (for adults). Information regarding oral health practices, adverse habits and dietary habits, demographic details was gathered and clinical parameters were recorded. The Chi-square test, t-test, One-way Analysis of Variance and a Stepwise multiple linear regression analysis. The most prevalent form of erosion was enamel erosion (589, 62.93%) with few subjects of deeper dentinal erosion and the difference was statistically significant (p=0.001). Dental erosion was found to be higher among males compared to females. Years of experience and educational status were identified as best predictors for dental erosion. It was concluded that there was considerable evidence of dental erosion found among the factory workers. Due to ignorance on social, cultural and health aspects, professional approach with regular dental care services for detection of early symptoms and planning of preventive strategies is warranted.
Otolith shape analysis for stock discrimination of two Collichthys genus croaker (Pieces: Sciaenidae,) from the northern Chinese coast

NASA Astrophysics Data System (ADS)

Zhao, Bo; Liu, Jinhu; Song, Junjie; Cao, Liang; Dou, Shuozeng

2017-08-01

The otolith morphology of two croaker species (Collichthys lucidus and Collichthys niveatus) from three areas (Liaodong Bay, LD; Huanghe (Yellow) River estuary, HRE; Jiaozhou Bay, JZ) along the northern Chinese coast were investigated for species identification and stock discrimination. The otolith contour shape described by elliptic Fourier coefficients (EFC) were analysed using principal components analysis (PCA) and stepwise canonical discriminant analysis (CDA) to identify species and stocks. The two species were well differentiated, with an overall classification success rate of 97.8%. And variations in the otolith shapes were significant enough to discriminate among the three geographical samples of C. lucidus (67.7%) or C. niveatus (65.2%). Relatively high mis-assignment occurred between the geographically adjacent LD and HRE samples, which implied that individual mixing may exist between the two samples. This study yielded information complementary to that derived from genetic studies and provided information for assessing the stock structure of C. lucidus and C. niveatus in the Bohai Sea and the Yellow Sea.
Gearing up to the factory of the future

NASA Astrophysics Data System (ADS)

Godfrey, D. E.

1985-01-01

The features of factories and manufacturing techniques and tools of the near future are discussed. The spur to incorporate new technologies on the factory floor will originate in management, who must guide the interfacing of computer-enhanced equipment with traditional manpower, materials and machines. Electronic control with responsiveness and flexibility will be the key concept in an integrated approach to processing materials. Microprocessor controlled laser and fluid cutters add accuracy to cutting operations. Unattended operation will become feasible when automated inspection is added to a work station through developments in robot vision. Optimum shop management will be achieved through AI programming of parts manufacturing, optimized work flows, and cost accounting. The automation enhancements will allow designers to affect directly parts being produced on the factory floor.
Congruences for central factorial numbers modulo powers of prime.

PubMed

Wang, Haiqing; Liu, Guodong

2016-01-01

Central factorial numbers are more closely related to the Stirling numbers than the other well-known special numbers, and they play a major role in a variety of branches of mathematics. In the present paper we prove some interesting congruences for central factorial numbers.
The NWRA Classification Infrastructure: description and extension to the Discriminant Analysis Flare Forecasting System (DAFFS)

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, Graham; Wagner, Eric

2018-04-01

A classification infrastructure built upon Discriminant Analysis (DA) has been developed at NorthWest Research Associates for examining the statistical differences between samples of two known populations. Originating to examine the physical differences between flare-quiet and flare-imminent solar active regions, we describe herein some details of the infrastructure including: parametrization of large datasets, schemes for handling "null" and "bad" data in multi-parameter analysis, application of non-parametric multi-dimensional DA, an extension through Bayes' theorem to probabilistic classification, and methods invoked for evaluating classifier success. The classifier infrastructure is applicable to a wide range of scientific questions in solar physics. We demonstrate its application to the question of distinguishing flare-imminent from flare-quiet solar active regions, updating results from the original publications that were based on different data and much smaller sample sizes. Finally, as a demonstration of "Research to Operations" efforts in the space-weather forecasting context, we present the Discriminant Analysis Flare Forecasting System (DAFFS), a near-real-time operationally-running solar flare forecasting tool that was developed from the research-directed infrastructure.
Optical Spectroscopic Analysis for the Discrimination of Extra-Virgin Olive Oil.

PubMed

McReynolds, Naomi; Auñón Garcia, Juan M; Guengerich, Zoe; Smith, Terry K; Dholakia, Kishan

2016-11-01

We demonstrate the ability to discriminate between five brands of commercially available extra-virgin olive oil (EVOO) using Raman spectroscopy or fluorescence spectroscopy. Data was taken on both a 'bulk optics' free space system and on a compact handheld device, each capable of taking both Raman and fluorescence data. With the compact Raman device we achieved an average sensitivity and specificity of 98.4% and 99.6% for discrimination, respectively. Our approach illustrates that both Raman and fluorescence spectroscopy can be used for portable discrimination of EVOOs. This technique may enable detection of EVOO that has undergone counterfeiting or adulteration. The main challenge with this technique is that oxidation of EVOO causes a shift in the Raman signal over time. It would therefore be necessary to retrain the database regularly. We demonstrate preliminary data to address this issue, which may enable successful discrimination over time. We show that by discarding the first principal component, which contains information on the variations due to oxidation, we can improve discrimination efficiency. © The Author(s) 2016.
Theoretical Development, Factorial Validity, and Reliability of the Online Graduate Mentoring Scale

ERIC Educational Resources Information Center

Crawford, Linda M.; Randolph, Justus J.; Yob, Iris M.

2014-01-01

In this study, we sought to confirm the theoretical framework underlying an Online Graduate Mentoring Scale by establishing the scale's factorial validity and reliability. Analysis of data received from doctoral students and alumni/ae of the College of Education of one large, online, accredited university reduced the initial theoretical…
Discrimination of surface wear on obsidian tools using LSCM and RelA: pilot study results (area-scale analysis of obsidian tool surfaces).

PubMed

Stemp, W James; Chung, Steven

2011-01-01

This pilot study tests the reliability of laser scanning confocal microscopy (LSCM) to quantitatively measure wear on experimental obsidian tools. To our knowledge, this is the first use of confocal microscopy to study wear on stone flakes made from an amorphous silicate like obsidian. Three-dimensional surface roughness or texture area scans on three obsidian flakes used on different contact materials (hide, shell, wood) were documented using the LSCM to determine whether the worn surfaces could be discriminated using area-scale analysis, specifically relative area (RelA). When coupled with the F-test, this scale-sensitive fractal analysis could not only discriminate the used from unused surfaces on individual tools, but was also capable of discriminating the wear histories of tools used on different contact materials. Results indicate that such discriminations occur at different scales. Confidence levels for the discriminations at different scales were established using the F-test (mean square ratios or MSRs). In instances where discrimination of surface roughness or texture was not possible above the established confidence level based on MSRs, photomicrographs and RelA assisted in hypothesizing why this was so. Copyright © 2011 Wiley Periodicals, Inc.
Total fume and metal concentrations during welding in selected factories in Jeddah, Saudi Arabia.

PubMed

Balkhyour, Mansour Ahmed; Goknil, Mohammad Khalid

2010-07-01

Welding is a major industrial process used for joining metals. Occupational exposure to welding fumes is a serious occupational health problem all over the world. The degree of risk to welder's health from fumes depends on composition, concentration, and the length of exposure. The aim of this study was to investigate workers' welding fume exposure levels in some industries in Jeddah, Saudi Arabia. In each factory, the air in the breathing zone within 0.5 m from welders was sampled during 8-hour shifts. Total particulates, manganese, copper, and molybdenum concentrations of welding fumes were determined. Mean values of eight-hour average particulate concentrations measured during welding at the welders breathing zone were 6.3 mg/m(3) (Factory 1), 5.3 mg/m(3) (Factory 2), 11.3 mg/m(3) (Factory 3), 6.8 mg/m(3) (Factory 4), 4.7 mg/m(3) (Factory 5), and 3.0 mg/m(3) (Factory 6). Mean values of airborne manganese, copper, and molybdenum levels measured during welding were in the range of 0.010 mg/m(3)-0.477 mg/m(3), 0.001 mg/m(3)-0.080 mg/m(3) and 0.001 mg/m(3)-0.058 mg/m(3) respectively. Mean values of calculated equivalent exposure values were: 1.50 (Factory 1), 1.56 (Factory 2), 5.14 (Factory 3), 2.21 (Factory 4), 2.89 (Factory 5), and 1.20 (Factory 6). The welders in factories 1, 2, 3, and 4 were exposed to welding fume concentration above the SASO limit value, which may increase the risk of respiratory health problems.
Discrimination in relation to parenthood reported by community psychiatric service users in the UK: a framework analysis.

PubMed

Jeffery, Debra; Clement, Sarah; Corker, Elizabeth; Howard, Louise M; Murray, Joanna; Thornicroft, Graham

2013-04-20

Experienced discrimination refers to an individual's perception that they have been treated unfairly due to an attribute and is an important recent focus within stigma research. A significant proportion of mental health service users report experiencing mental illness-based discrimination in relation to parenthood. Existing studies in this area have not gone beyond prevalence, therefore little is known about the nature of experienced discrimination in relation to parenthood, and how is it constituted. This study aims to generate a typology of community psychiatric service users' reports of mental illness-based discrimination in relation to becoming or being a parent. A secondary aim is to assess the prevalence of these types of experienced discrimination. In a telephone survey 2026 community psychiatric service users in ten UK Mental Health service provider organisations (Trusts) were asked about discrimination experienced in the previous 12 months using the Discrimination and Stigma Scale (DISC). The sample were asked if, due to their mental health problem, they had been treated unfairly in starting a family, or in their role as a parent, and gave examples of this. Prevalence is reported and the examples of experienced discrimination in relation to parenthood were analysed using the framework method of qualitative analysis. Three hundred and four participants (73% female) reported experienced discrimination, with prevalences of 22.5% and 28.3% for starting a family and for the parenting role respectively. Participants gave 89 examples of discrimination about starting a family and 228 about parenting, and these occurred in social and professional contexts. Ten themes were identified. These related to being seen as an unfit parent; people not being understanding; being stopped from having children; not being allowed to see their children; not getting the support needed; children being affected; children avoiding their parents; children's difficulties being blamed
Incense and joss stick making in small household factories, Thailand.

PubMed

Siripanich, S; Siriwong, W; Keawrueang, P; Borjan, M; Robson, M

2014-07-01

Incense and joss stick are generally used in the world. Most products were made in small household factories. There are many environmental and occupational hazards in these factories. To evaluate the workplace environmental and occupational hazards in small household incense and joss stick factories in Roi-Et, Thailand. Nine small household factories in rural areas of Roi-Et, Thailand, were studied. Dust concentration and small aerosol particles were counted through real time exposure monitoring. The inductively coupled plasma optical emission spectrometry (ICP-OES) was used for quantitative measurement of heavy metal residue in incense products. Several heavy metals were found in dissolved dye and joss sticks. Those included barium, manganese, and lead. Rolling and shaking processes produced the highest concentration of dust and aerosols. Only 3.9% of female workers used personal protection equipment. Dust and chemicals were major threats in small household incense and joss stick factories in Thailand. Increasing awareness towards using personal protection equipment and emphasis on elimination of environmental workplace hazards should be considered to help the workers of this industry.
Commercial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu-Natal, South Africa

NASA Astrophysics Data System (ADS)

Peerbhay, Kabir Yunus; Mutanga, Onisimo; Ismail, Riyad

2013-05-01

Discriminating commercial tree species using hyperspectral remote sensing techniques is critical in monitoring the spatial distributions and compositions of commercial forests. However, issues related to data dimensionality and multicollinearity limit the successful application of the technology. The aim of this study was to examine the utility of the partial least squares discriminant analysis (PLS-DA) technique in accurately classifying six exotic commercial forest species (Eucalyptus grandis, Eucalyptus nitens, Eucalyptus smithii, Pinus patula, Pinus elliotii and Acacia mearnsii) using airborne AISA Eagle hyperspectral imagery (393-900 nm). Additionally, the variable importance in the projection (VIP) method was used to identify subsets of bands that could successfully discriminate the forest species. Results indicated that the PLS-DA model that used all the AISA Eagle bands (n = 230) produced an overall accuracy of 80.61% and a kappa value of 0.77, with user's and producer's accuracies ranging from 50% to 100%. In comparison, incorporating the optimal subset of VIP selected wavebands (n = 78) in the PLS-DA model resulted in an improved overall accuracy of 88.78% and a kappa value of 0.87, with user's and producer's accuracies ranging from 70% to 100%. Bands located predominantly within the visible region of the electromagnetic spectrum (393-723 nm) showed the most capability in terms of discriminating between the six commercial forest species. Overall, the research has demonstrated the potential of using PLS-DA for reducing the dimensionality of hyperspectral datasets as well as determining the optimal subset of bands to produce the highest classification accuracies.
Toroidal magnetized iron neutrino detector for a neutrino factory

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

Bross, A.; Wands, R.; Bayes, R.

2013-08-01

A neutrino factory has unparalleled physics reach for the discovery and measurement of CP violation in the neutrino sector. A far detector for a neutrino factory must have good charge identification with excellent background rejection and a large mass. An elegant solution is to construct a magnetized iron neutrino detector (MIND) along the lines of MINOS, where iron plates provide a toroidal magnetic field and scintillator planes provide 3D space points. In this report, the current status of a simulation of a toroidal MIND for a neutrino factory is discussed in light of the recent measurements of largemore » $$\\theta_{13}$$. The response and performance using the 10 GeV neutrino factory configuration are presented. It is shown that this setup has equivalent $$\\delta_{CP}$$ reach to a MIND with a dipole field and is sensitive to the discovery of CP violation over 85% of the values of $$\\delta_{CP}$$.« less
Arcnet(R) On-Fiber -- A Viable Factory Automation Alternative

NASA Astrophysics Data System (ADS)

Karlin, Geof; Tucker, Carol S.

1987-01-01

Manufacturers need to improve their operating methods and increase their productivity so they can compete successfully in the marketplace. This goal can be achieved through factory automation, and the key to this automation is successful data base management and factory integration. However, large scale factory automation and integration requires effective communications, and this has given rise to an interest in various Local Area Networks or LANs. In a completely integrated and automated factory, the entire organization must have access to the data base, and all departments and functions must be able to communicate with each other. Traditionally, these departments and functions use incompatible equipment, and the ability to make such equipment communicate presents numerous problems. ARCNET, a token-passing LAN which has a significant presence in the office environment today, coupled with fiber optic cable, the cable of the future, provide an effective, low-cost solution to a number of these problems.
Discrimination in lexical decision

PubMed Central

Feldman, Laurie Beth; Ramscar, Michael; Hendrix, Peter; Baayen, R. Harald

2017-01-01

In this study we present a novel set of discrimination-based indicators of language processing derived from Naive Discriminative Learning (ndl) theory. We compare the effectiveness of these new measures with classical lexical-distributional measures—in particular, frequency counts and form similarity measures—to predict lexical decision latencies when a complete morphological segmentation of masked primes is or is not possible. Data derive from a re-analysis of a large subset of decision latencies from the English Lexicon Project, as well as from the results of two new masked priming studies. Results demonstrate the superiority of discrimination-based predictors over lexical-distributional predictors alone, across both the simple and primed lexical decision tasks. Comparable priming after masked corner and cornea type primes, across two experiments, fails to support early obligatory segmentation into morphemes as predicted by the morpho-orthographic account of reading. Results fit well with ndl theory, which, in conformity with Word and Paradigm theory, rejects the morpheme as a relevant unit of analysis. Furthermore, results indicate that readers with greater spelling proficiency and larger vocabularies make better use of orthographic priors and handle lexical competition more efficiently. PMID:28235015
Discrimination in lexical decision.

PubMed

Milin, Petar; Feldman, Laurie Beth; Ramscar, Michael; Hendrix, Peter; Baayen, R Harald

2017-01-01

In this study we present a novel set of discrimination-based indicators of language processing derived from Naive Discriminative Learning (ndl) theory. We compare the effectiveness of these new measures with classical lexical-distributional measures-in particular, frequency counts and form similarity measures-to predict lexical decision latencies when a complete morphological segmentation of masked primes is or is not possible. Data derive from a re-analysis of a large subset of decision latencies from the English Lexicon Project, as well as from the results of two new masked priming studies. Results demonstrate the superiority of discrimination-based predictors over lexical-distributional predictors alone, across both the simple and primed lexical decision tasks. Comparable priming after masked corner and cornea type primes, across two experiments, fails to support early obligatory segmentation into morphemes as predicted by the morpho-orthographic account of reading. Results fit well with ndl theory, which, in conformity with Word and Paradigm theory, rejects the morpheme as a relevant unit of analysis. Furthermore, results indicate that readers with greater spelling proficiency and larger vocabularies make better use of orthographic priors and handle lexical competition more efficiently.
[Study on the classification of dominant pathogens related to febrile respiratory syndrome, based on the method of Bayes discriminant analysis].

PubMed

Li, X C; Li, J S; Meng, L; Bai, Y N; Yu, D S; Liu, X N; Liu, X F; Jiang, X J; Ren, X W; Yang, X T; Shen, X P; Zhang, J W

2017-08-10

Objective: To understand the dominant pathogens of febrile respiratory syndrome (FRS) patients in Gansu province and to establish the Bayes discriminant function in order to identify the patients infected with the dominant pathogens. Methods: FRS patients were collected in various sentinel hospitals of Gansu province from 2009 to 2015 and the dominant pathogens were determined by describing the composition of pathogenic profile. Significant clinical variables were selected by stepwise discriminant analysis to establish the Bayes discriminant function. Results: In the detection of pathogens for FRS, both influenza virus and rhinovirus showed higher positive rates than those caused by other viruses (13.79%, 8.63%), that accounting for 54.38%, 13.73% of total viral positive patients. Most frequently detected bacteria would include Streptococcus pneumoniae , and haemophilus influenza (44.41%, 18.07%) that accounting for 66.21% and 24.55% among the bacterial positive patients. The original-validated rate of discriminant function, established by 11 clinical variables, was 73.1%, with the cross-validated rate as 70.6%. Conclusion: Influenza virus, Rhinovirus, Streptococcus pneumoniae and Haemophilus influenzae were the dominant pathogens of FRS in Gansu province. Results from the Bayes discriminant analysis showed both higher accuracy in the classification of dominant pathogens, and applicative value for FRS.

Analysis of Optimal Sequential State Discrimination for Linearly Independent Pure Quantum States.

PubMed

Namkung, Min; Kwon, Younghun

2018-04-25

Recently, J. A. Bergou et al. proposed sequential state discrimination as a new quantum state discrimination scheme. In the scheme, by the successful sequential discrimination of a qubit state, receivers Bob and Charlie can share the information of the qubit prepared by a sender Alice. A merit of the scheme is that a quantum channel is established between Bob and Charlie, but a classical communication is not allowed. In this report, we present a method for extending the original sequential state discrimination of two qubit states to a scheme of N linearly independent pure quantum states. Specifically, we obtain the conditions for the sequential state discrimination of N = 3 pure quantum states. We can analytically provide conditions when there is a special symmetry among N = 3 linearly independent pure quantum states. Additionally, we show that the scenario proposed in this study can be applied to quantum key distribution. Furthermore, we show that the sequential state discrimination of three qutrit states performs better than the strategy of probabilistic quantum cloning.
Factorial Structure of Rosenberg's Self-Esteem Scale among Crack-Cocaine Drug Users.

ERIC Educational Resources Information Center

Wang, Jichuan; Siegal, Harvey A.; Falck, Russell S.; Carlson, Robert G.

2001-01-01

Used nine different confirmatory factor analysis models to test the factorial structure of Rosenberg's (M. Rosenberg, 1965) self-esteem scale with a sample of 430 crack-cocaine users. Results partly support earlier research to show a single global self-esteem factor underlying responses to the Rosenberg scale, method effects associated with item…
[Discrimination of Rice Syrup Adulterant of Acacia Honey Based Using Near-Infrared Spectroscopy].

PubMed

Zhang, Yan-nan; Chen, Lan-zhen; Xue, Xiao-feng; Wu, Li-ming; Li, Yi; Yang, Juan

2015-09-01

At present, the rice syrup as a low price of the sweeteners was often adulterated into acacia honey and the adulterated honeys were sold in honey markets, while there is no suitable and fast method to identify honey adulterated with rice syrup. In this study, Near infrared spectroscopy (NIR) combined with chemometric methods were used to discriminate authenticity of honey. 20 unprocessed acacia honey samples from the different honey producing areas, mixed? with different proportion of rice syrup, were prepared of seven different concentration gradient? including 121 samples. The near infrared spectrum (NIR) instrument and spectrum processing software have been applied in the? spectrum? scanning and data conversion on adulterant samples, respectively. Then it was analyzed by Principal component analysis (PCA) and canonical discriminant analysis methods in order to discriminating adulterated honey. The results showed that after principal components analysis, the first two principal components accounted for 97.23% of total variation, but the regionalism of the score plot of the first two PCs was not obvious, so the canonical discriminant analysis was used to make the further discrimination, all samples had been discriminated correctly, the first two discriminant functions accounted for 91.6% among the six canonical discriminant functions, Then the different concentration of adulterant samples can be discriminated correctly, it illustrate that canonical discriminant analysis method combined with NIR spectroscopy is not only feasible but also practical for rapid and effective discriminate of the rice syrup adulterant of acacia honey.
Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

PubMed

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.
Diagnosing basal cell carcinoma in vivo by near-infrared Raman spectroscopy: a Principal Components Analysis discrimination algorithm

NASA Astrophysics Data System (ADS)

Silveira, Landulfo, Jr.; Silveira, Fabrício L.; Bodanese, Benito; Pacheco, Marcos Tadeu T.; Zângaro, Renato A.

2012-02-01

This work demonstrated the discrimination among basal cell carcinoma (BCC) and normal human skin in vivo using near-infrared Raman spectroscopy. Spectra were obtained in the suspected lesion prior resectional surgery. After tissue withdrawn, biopsy fragments were submitted to histopathology. Spectra were also obtained in the adjacent, clinically normal skin. Raman spectra were measured using a Raman spectrometer (830 nm) with a fiber Raman probe. By comparing the mean spectra of BCC with the normal skin, it has been found important differences in the 800-1000 cm-1 and 1250-1350 cm-1 (vibrations of C-C and amide III, respectively, from lipids and proteins). A discrimination algorithm based on Principal Components Analysis and Mahalanobis distance (PCA/MD) could discriminate the spectra of both tissues with high sensitivity and specificity.
Assessment of parameter uncertainty in hydrological model using a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis method

NASA Astrophysics Data System (ADS)

Zhang, Junlong; Li, Yongping; Huang, Guohe; Chen, Xi; Bao, Anming

2016-07-01

Without a realistic assessment of parameter uncertainty, decision makers may encounter difficulties in accurately describing hydrologic processes and assessing relationships between model parameters and watershed characteristics. In this study, a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis (MCMC-MFA) method is developed, which can not only generate samples of parameters from a well constructed Markov chain and assess parameter uncertainties with straightforward Bayesian inference, but also investigate the individual and interactive effects of multiple parameters on model output through measuring the specific variations of hydrological responses. A case study is conducted for addressing parameter uncertainties in the Kaidu watershed of northwest China. Effects of multiple parameters and their interactions are quantitatively investigated using the MCMC-MFA with a three-level factorial experiment (totally 81 runs). A variance-based sensitivity analysis method is used to validate the results of parameters' effects. Results disclose that (i) soil conservation service runoff curve number for moisture condition II (CN2) and fraction of snow volume corresponding to 50% snow cover (SNO50COV) are the most significant factors to hydrological responses, implying that infiltration-excess overland flow and snow water equivalent represent important water input to the hydrological system of the Kaidu watershed; (ii) saturate hydraulic conductivity (SOL_K) and soil evaporation compensation factor (ESCO) have obvious effects on hydrological responses; this implies that the processes of percolation and evaporation would impact hydrological process in this watershed; (iii) the interactions of ESCO and SNO50COV as well as CN2 and SNO50COV have an obvious effect, implying that snow cover can impact the generation of runoff on land surface and the extraction of soil evaporative demand in lower soil layers. These findings can help enhance the hydrological model
Avoid Age Discrimination.

ERIC Educational Resources Information Center

Bernstein, Michael I.

1982-01-01

Steps a school board can take to minimize the risk of age discrimination suits include reviewing all written policies, forms, files, and collective bargaining agreements for age discriminatory items; preparing a detailed statistical analysis of the age of personnel; and reviewing reduction-in-force procedures. (Author/MLF)
Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis.

PubMed

André, Nathalie; Ferrand, Claude; Albinet, Cédric; Audiffren, Michel

2018-01-01

Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging.
Classification and prediction of pilot weather encounters: A discriminant function analysis.

PubMed

O'Hare, David; Hunter, David R; Martinussen, Monica; Wiggins, Mark

2011-05-01

Flight into adverse weather continues to be a significant hazard for General Aviation (GA) pilots. Weather-related crashes have a significantly higher fatality rate than other GA crashes. Previous research has identified lack of situational awareness, risk perception, and risk tolerance as possible explanations for why pilots would continue into adverse weather. However, very little is known about the nature of these encounters or the differences between pilots who avoid adverse weather and those who do not. Visitors to a web site described an experience with adverse weather and completed a range of measures of personal characteristics. The resulting data from 364 pilots were carefully screened and subject to a discriminant function analysis. Two significant functions were found. The first, accounting for 69% of the variance, reflected measures of risk awareness and pilot judgment while the second differentiated pilots in terms of their experience levels. The variables measured in this study enabled us to correctly discriminate between the three groups of pilots considerably better (53% correct classifications) than would have been possible by chance (33% correct classifications). The implications of these findings for targeting safety interventions are discussed.
Discriminative analysis with a limited number of MEG trials in depression.

PubMed

Lu, Qing; Jiang, Haiteng; Bi, Kun; Liu, Chu; Yao, Zhijian

2014-01-01

In studies when exploring distinct patterns of functional abnormalities inherent in depression, experiments are generally repeated over many trials, and then the data are averaged across those trials in order to improve the signal to noise ratio. Repeated stimuli will lead to unpredictable impairment on signals, due to material familiarity or subjects׳ fatigue. In this consideration, signal processing tools powerful on small numbers of trials are expected to alleviate the work load on subjects, especially for mental disease studies. Forty-four subjects, half-depressed patients and half-healthy subjects, were recruited for MEG scanning in response to sad facial stimuli. Multichannel matching pursuit (MMP) was implemented to manage the limited number of trials. The post-MMP MEG signals were utilized to calculate the power topography over the whole brain, as inputs for a Support Vector Machine (SVM) classifier. Standard ICA and conventional ensemble averaging plus Butterworth filtering were employed as well as benchmark studies for performance comparison. A limited number of trials were required via MMP to discriminate the depressive. Post-MMP discriminative analysis revealed a deficit theta pattern and an excessive alpha/beta pattern. The small sample size may impair the stability of the reported findings. The transient tiny variance of the signal was excluded from exploration. The deficit theta pattern together with the excessive alpha/beta pattern in depression may indicate the dysfunction of the limbic-cortical circuit in a 'top-down' process. The post-MMP discrimination helps alleviate the scanning burden, facilitating the possibility for neuroimaging supporting the affective disorder clinical diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.
1. GENERAL VIEW OF COMPLEX, SHOWING FACTORY BUILDING IN LEFT ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

1. GENERAL VIEW OF COMPLEX, SHOWING FACTORY BUILDING IN LEFT FOREGROUND, GRINDING PLATFORM AT REAR OF FACTORY, AND STABLE AREA AND OVERSEER'S HOUSE TO RIGHT - Caneel Bay Plantation, General Views, Cruz Bay, St. John, VI
Predicting groundwater redox status on a regional scale using linear discriminant analysis.

PubMed

Close, M E; Abraham, P; Humphries, B; Lilburne, L; Cuthill, T; Wilson, S

2016-08-01

Reducing conditions are necessary for denitrification, thus the groundwater redox status can be used to identify subsurface zones where potentially significant nitrate reduction can occur. Groundwater chemistry in two contrasting regions of New Zealand was classified with respect to redox status and related to mappable factors, such as geology, topography and soil characteristics using discriminant analysis. Redox assignment was carried out for water sampled from 568 and 2223 wells in the Waikato and Canterbury regions, respectively. For the Waikato region 64% of wells sampled indicated oxic conditions in the water; 18% indicated reduced conditions and 18% had attributes indicating both reducing and oxic conditions termed "mixed". In Canterbury 84% of wells indicated oxic conditions; 10% were mixed; and only 5% indicated reduced conditions. The analysis was performed over three different well depths, <25m, 25 to 100 and >100m. For both regions, the percentage of oxidised groundwater decreased with increasing well depth. Linear discriminant analysis was used to develop models to differentiate between the three redox states. Models were derived for each depth and region using 67% of the data, and then subsequently validated on the remaining 33%. The average agreement between predicted and measured redox status was 63% and 70% for the Waikato and Canterbury regions, respectively. The models were incorporated into GIS and the prediction of redox status was extended over the whole region, excluding mountainous land. This knowledge improves spatial prediction of reduced groundwater zones, and therefore, when combined with groundwater flow paths, improves estimates of denitrification. Copyright © 2016 Elsevier B.V. All rights reserved.
The Japanese Positron Factory

NASA Astrophysics Data System (ADS)

Okada, S.; Sunaga, H.; Kaneko, H.; Takizawa, H.; Kawasuso, A.; Yotsumoto, K.; Tanaka, R.

1999-06-01

The Positron Factory has been planned at Japan Atomic Energy Research Institute (JAERI). The factory is expected to produce linac-based monoenergetic positron beams having world-highest intensities of more than 1010e+/sec, which will be applied for R&D of materials science, biotechnology and basic physics & chemistry. In this article, results of the design studies are demonstrated for the following essential components of the facilities: 1) Conceptual design of a high-power electron linac with 100 MeV in beam energy and 100 kW in averaged beam power, 2) Performance tests of the RF window in the high-power klystron and of the electron beam window, 3) Development of a self-driven rotating electron-to-positron converter and the performance tests, 4) Proposal of multi-channel beam generation system for monoenergetic positrons, with a series of moderator assemblies based on a newly developed Monte Carlo simulation and the demonstrative experiment, 5) Proposal of highly efficient moderator structures, 6) Conceptual design of a local shield to suppress the surrounding radiation and activation levels.
DKIST enclosure modeling and verification during factory assembly and testing

NASA Astrophysics Data System (ADS)

Larrakoetxea, Ibon; McBride, William; Marshall, Heather K.; Murga, Gaizka

2014-08-01

The Daniel K. Inouye Solar Telescope (DKIST, formerly the Advanced Technology Solar Telescope, ATST) is unique as, apart from protecting the telescope and its instrumentation from the weather, it holds the entrance aperture stop and is required to position it with millimeter-level accuracy. The compliance of the Enclosure design with the requirements, as of Final Design Review in January 2012, was supported by mathematical models and other analyses which included structural and mechanical analyses (FEA), control models, ventilation analysis (CFD), thermal models, reliability analysis, etc. During the Enclosure Factory Assembly and Testing the compliance with the requirements has been verified using the real hardware and the models created during the design phase have been revisited. The tests performed during shutter mechanism subsystem (crawler test stand) functional and endurance testing (completed summer 2013) and two comprehensive system-level factory acceptance testing campaigns (FAT#1 in December 2013 and FAT#2 in March 2014) included functional and performance tests on all mechanisms, off-normal mode tests, mechanism wobble tests, creation of the Enclosure pointing map, control system tests, and vibration tests. The comparison of the assumptions used during the design phase with the properties measured during the test campaign provides an interesting reference for future projects.
Discrimination and chemical phylogenetic study of seven species of Dendrobium using infrared spectroscopy combined with cluster analysis

NASA Astrophysics Data System (ADS)

Luo, Congpei; He, Tao; Chun, Ze

2013-04-01

Dendrobium is a commonly used and precious herb in Traditional Chinese Medicine. The high biodiversity of Dendrobium and the therapeutic needs require tools for the correct and fast discrimination of different Dendrobium species. This study investigates Fourier transform infrared spectroscopy followed by cluster analysis for discrimination and chemical phylogenetic study of seven Dendrobium species. Despite the general pattern of the IR spectra, different intensities, shapes, peak positions were found in the IR spectra of these samples, especially in the range of 1800-800 cm-1. The second derivative transformation and alcoholic extracting procedure obviously enlarged the tiny spectral differences among these samples. The results indicated each Dendrobium species had a characteristic IR spectra profile, which could be used to discriminate them. The similarity coefficients among the samples were analyzed based on their second derivative IR spectra, which ranged from 0.7632 to 0.9700, among the seven Dendrobium species, and from 0.5163 to 0.9615, among the ethanol extracts. A dendrogram was constructed based on cluster analysis the IR spectra for studying the chemical phylogenetic relationships among the samples. The results indicated that D. denneanum and D. crepidatum could be the alternative resources to substitute D. chrysotoxum, D. officinale and D. nobile which were officially recorded in Chinese Pharmacopoeia. In conclusion, with the advantages of high resolution, speediness and convenience, the experimental approach can successfully discriminate and construct the chemical phylogenetic relationships of the seven Dendrobium species.
Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis

PubMed Central

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods: In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. Results: The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Conclusion: Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended. PMID:26793655
Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

PubMed

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.
Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-11-01

In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of
From Equal to Equivalent Pay: Salary Discrimination in Academia

ERIC Educational Resources Information Center

Greenfield, Ester

1977-01-01

Examines the federal statutes barring sex discrimination in employment and argues that the work of any two professors is comparable but not equal. Suggests using regression analysis to prove salary discrimination and discusses the legal justification for adopting regression analysis and the standard of comparable pay for comparable work.…
Microbially induced and microbially catalysed precipitation: two different carbonate factories

NASA Astrophysics Data System (ADS)

Meister, Patrick

2016-04-01

The landmark paper by Schlager (2003) has revealed three types of benthic carbonate production referred to as "carbonate factories", operative at different locations at different times in Earth history. The tropical or T-factory comprises the classical platforms and fringing reefs and is dominated by carbonate precipitation by autotrophic calcifying metazoans ("biotically controlled" precipitation). The cool or C-factory is also biotically controlled but via heterotrophic, calcifying metazoans in cold and deep waters at the continental margins. A further type is the mud-mound or M-factory, where carbonate precipitation is supported by microorganisms but not controlled by a specific enzymatic pathway ("biotically induced" precipitation). How exactly the microbes influence precipitation is still poorly understood. Based on recent experimental and field studies, the microbial influence on modern mud mound and microbialite growth includes two fundamentally different processes: (1) Metabolic activity of microbes may increase the saturation state with respect to a particular mineral phase, thereby indirectly driving the precipitation of the mineral phase: microbially induced precipitation. (2) In a situation, where a solution is already supersaturated but precipitation of the mineral is inhibited by a kinetic barrier, microbes may act as a catalyser, i.e. they lower the kinetic barrier: microbially catalysed precipitation. Such a catalytic effect can occur e.g. via secreted polymeric substances or specific chemical groups on the cell surface, at which the minerals nucleate or which facilitate mechanistically the bonding of new ions to the mineral surface. Based on these latest developments in microbialite formation, I propose to extend the scheme of benthic carbonate factories of Schlager et al. (2003) by introducing an additional branch distinguishing microbially induced from microbially catalysed precipitation. Although both mechanisms could be operative in a M-factory

Undergraduate students' initial conceptions of factorials

NASA Astrophysics Data System (ADS)

Lockwood, Elise; Erickson, Sarah

2017-05-01

Counting problems offer rich opportunities for students to engage in mathematical thinking, but they can be difficult for students to solve. In this paper, we present a study that examines student thinking about one concept within counting, factorials, which are a key aspect of many combinatorial ideas. In an effort to better understand students' conceptions of factorials, we conducted interviews with 20 undergraduate students. We present a key distinction between computational versus combinatorial conceptions, and we explore three aspects of data that shed light on students' conceptions (their initial characterizations, their definitions of 0!, and their responses to Likert-response questions). We present implications this may have for mathematics educators both within and separate from combinatorics.
Investigation of cadmium pollution in the spruce saplings near the metal production factory.

PubMed

Hashemi, Seyed Armin; Farajpour, Ghasem

2016-02-01

Toxic metals such as lead and cadmium are among the pollutants that are created by the metal production factories and disseminated in the nature. In order to study the quantity of cadmium pollution in the environment of the metal production factories, 50 saplings of the spruce species at the peripheries of the metal production factories were examined and the samples of the leaves, roots, and stems of saplings planted around the factory and the soil of the environment of the factory were studied to investigate pollution with cadmium. They were compared to the soil and saplings of the spruce trees planted outside the factory as observer region. The results showed that the quantity of pollution in the leaves, stems, and roots of the trees planted inside the factory environment were estimated at 1.1, 1.5, and 2.5 mg/kg, respectively, and this indicated a significant difference with the observer region (p < 0.05). The quantity of cadmium in the soil of the peripheries of the metal production factory was estimated at 6.8 mg/kg in the depth of 0-10 cm beneath the level of the soil. The length of roots in the saplings planted around the factory of metal production stood at 11 and 14.5 cm in the observer region which had a significant difference with the observer region (p < 0.05). The quantity of soil resources and spruce species' pollution with cadmium in the region has been influenced by the production processes in the factory. © The Author(s) 2013.
Sex determination from the mandibular ramus flexure of Koreans by discrimination function analysis using three-dimensional mandible models.

PubMed

Lin, Chenghe; Jiao, Benzheng; Liu, Shanshan; Guan, Feng; Chung, Nak-Eun; Han, Seung-Ho; Lee, U-Young

2014-03-01

It has been known that mandible ramus flexure is an important morphologic trait for sex determination. However, it will be unavailable when mandible is incomplete or fragmented. Therefore, the anthropometric analysis on incomplete or fragmented mandible becomes more important. The aim of this study is to investigate the sex-discriminant potential of mandible ramus flexure on the Korean three-dimensional (3D) mandible models with anthropometric analysis. The sample consists of 240 three dimensional mandibular models obtained from Korean population (M:F; 120:120, mean age 46.2 y), collected by The Catholic Institute for Applied Anatomy, The Catholic University of Korea. Anthropometric information about 11 metric was taken with Mimics, anthropometry libraries toolkit. These parameters were subjected to different discriminant function analyses using SPSS 17.0. Univariate analyses showed that the resubstitution accuracies for sex determination range from 50.4 to 77.1%. Mandibular flexure upper border (MFUB), maximum ramus vertical height (MRVH), and upper ramus vertical height (URVH) expressed the greatest dimorphism, 72.1 to 77.1%. Bivariate analyses indicated that the combination of MFUB and MRVH hold even higher resubstitution accuracy of 81.7%. Furthermore, the direct and stepwise discriminant analyses with the variables on the upper ramus above flexure could predict sex in 83.3 and 85.0%, respectively. When all variables of mandibular ramus flexure were input in stepwise discriminant analysis, the resubstitution accuracy arrived as high as 88.8%. Therefore, we concluded that the upper ramus above flexure hold the larger potentials than the mandibular ramus flexure itself to predict sexes, and that the equations in bivariate and multivariate analysis from our study will be helpful for sex determination on Korean population in forensic science and law. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
[Study on the genuineness and producing area of Panax notoginseng based on infrared spectroscopy combined with discriminant analysis].

PubMed

Liu, Fei; Wang, Yuan-zhong; Yang, Chun-yan; Jin, Hang

2015-01-01

The genuineness and producing area of Panax notoginseng were studied based on infrared spectroscopy combined with discriminant analysis. The infrared spectra of 136 taproots of P. notoginseng from 13 planting point in 11 counties were collected and the second derivate spectra were calculated by Omnic 8. 0 software. The infrared spectra and their second derivate spectra in the range 1 800 - 700 cm-1 were used to build model by stepwise discriminant analysis, which was in order to distinguish study on the genuineness of P. notoginseng. The model built based on the second derivate spectra showed the better recognition effect for the genuineness of P. notoginseng. The correct rate of returned classification reached to 100%, and the prediction accuracy was 93. 4%. The stability of model was tested by cross validation and the method was performed extrapolation validation. The second derivate spectra combined with the same discriminant analysis method were used to distinguish the producing area of P. notoginseng. The recognition effect of models built based on different range of spectrum and different numbers of samples were compared and found that when the model was built by collecting 8 samples from each planting point as training sample and the spectrum in the range 1 500 - 1 200 cm-1 , the recognition effect was better, with the correct rate of returned classification reached to 99. 0%, and the prediction accuracy was 76. 5%. The results indicated that infrared spectroscopy combined with discriminant analysis showed good recognition effect for the genuineness of P. notoginseng. The method might be a hopeful new method for identification of genuineness of P. notoginseng in practice. The method could recognize the producing area of P. notoginseng to some extent and could be a new thought for identification of the producing area of P. natoginseng.
Factory-Calibrated Continuous Glucose Sensors: The Science Behind the Technology.

PubMed

Hoss, Udo; Budiman, Erwin Satrya

2017-05-01

The use of commercially available continuous glucose monitors for diabetes management requires sensor calibrations, which until recently are exclusively performed by the patient. A new development is the implementation of factory calibration for subcutaneous glucose sensors, which eliminates the need for user calibrations and the associated blood glucose tests. Factory calibration means that the calibration process is part of the sensor manufacturing process and performed under controlled laboratory conditions. The ability to move from a user calibration to factory calibration is based on several technical requirements related to sensor stability and the robustness of the sensor manufacturing process. The main advantages of factory calibration over the conventional user calibration are: (a) more convenience for the user, since no more fingersticks are required for calibration and (b) elimination of use errors related to the execution of the calibration process, which can lead to sensor inaccuracies. The FreeStyle Libre ™ and FreeStyle Libre Pro ™ flash continuous glucose monitoring systems are the first commercially available sensor systems using factory-calibrated sensors. For these sensor systems, no user calibrations are required throughout the sensor wear duration.
Factory-Calibrated Continuous Glucose Sensors: The Science Behind the Technology

PubMed Central

Budiman, Erwin Satrya

2017-01-01

Abstract The use of commercially available continuous glucose monitors for diabetes management requires sensor calibrations, which until recently are exclusively performed by the patient. A new development is the implementation of factory calibration for subcutaneous glucose sensors, which eliminates the need for user calibrations and the associated blood glucose tests. Factory calibration means that the calibration process is part of the sensor manufacturing process and performed under controlled laboratory conditions. The ability to move from a user calibration to factory calibration is based on several technical requirements related to sensor stability and the robustness of the sensor manufacturing process. The main advantages of factory calibration over the conventional user calibration are: (a) more convenience for the user, since no more fingersticks are required for calibration and (b) elimination of use errors related to the execution of the calibration process, which can lead to sensor inaccuracies. The FreeStyle Libre™ and FreeStyle Libre Pro™ flash continuous glucose monitoring systems are the first commercially available sensor systems using factory-calibrated sensors. For these sensor systems, no user calibrations are required throughout the sensor wear duration. PMID:28541139
More Powerful Tests of Simple Interaction Contrasts in the Two-Way Factorial Design

ERIC Educational Resources Information Center

Hancock, Gregory R.; McNeish, Daniel M.

2017-01-01

For the two-way factorial design in analysis of variance, the current article explicates and compares three methods for controlling the Type I error rate for all possible simple interaction contrasts following a statistically significant interaction, including a proposed modification to the Bonferroni procedure that increases the power of…
Linear discriminant analysis based on L1-norm maximization.

PubMed

Zhong, Fujin; Zhang, Jiashu

2013-08-01

Linear discriminant analysis (LDA) is a well-known dimensionality reduction technique, which is widely used for many purposes. However, conventional LDA is sensitive to outliers because its objective function is based on the distance criterion using L2-norm. This paper proposes a simple but effective robust LDA version based on L1-norm maximization, which learns a set of local optimal projection vectors by maximizing the ratio of the L1-norm-based between-class dispersion and the L1-norm-based within-class dispersion. The proposed method is theoretically proved to be feasible and robust to outliers while overcoming the singular problem of the within-class scatter matrix for conventional LDA. Experiments on artificial datasets, standard classification datasets and three popular image databases demonstrate the efficacy of the proposed method.
Students Tackle Academics in Practical Context at Skateboard Factory

ERIC Educational Resources Information Center

Pearson, George

2012-01-01

High school student Nick Robertson came to Oasis Skateboard Factory (OSF) from a suburban Toronto district. He was surfing the web when he spotted a reference to Oasis Skateboard Factory, an alternative program in the Toronto District School Board. He says his first reaction was "Skateboards in school? It didn't seem possible." He…
Determination of five active compounds in Artemisia princeps and A. capillaris based on UPLC-DAD and discrimination of two species with multivariate analysis.

PubMed

Yang, Heejung; Lee, Dong Young; Jeon, Minji; Suh, Youngbae; Sung, Sang Hyun

2014-05-01

Five active compounds, chlorogenic acid, 3,5-di-O-caffeoylquinic acid, 4,5-di-O-caffeoylquinic acid, jaceosidin, and eupatilin, in Artemisia princeps (Compositae) were simultaneously determined by ultra-performance liquid chromatography connected to diode array detector. The morphological resemblance between A. princeps and A. capillaris makes it difficult to properly identify species properly. It occasionally leads to misuse or misapplication in Korean traditional medicine. In the study, the discrimination between A. princeps and A. capillaris was optimally performed by the developed validation method, which resulted in definitely a difference between two species. Also, it was developed the most reliable markers contributing to the discrimination of two species by the multivariate analysis methods, such as a principal component analysis and a partial least squares discrimination analysis.
Phylogenetic comparative methods complement discriminant function analysis in ecomorphology.

PubMed

Barr, W Andrew; Scott, Robert S

2014-04-01

In ecomorphology, Discriminant Function Analysis (DFA) has been used as evidence for the presence of functional links between morphometric variables and ecological categories. Here we conduct simulations of characters containing phylogenetic signal to explore the performance of DFA under a variety of conditions. Characters were simulated using a phylogeny of extant antelope species from known habitats. Characters were modeled with no biomechanical relationship to the habitat category; the only sources of variation were body mass, phylogenetic signal, or random "noise." DFA on the discriminability of habitat categories was performed using subsets of the simulated characters, and Phylogenetic Generalized Least Squares (PGLS) was performed for each character. Analyses were repeated with randomized habitat assignments. When simulated characters lacked phylogenetic signal and/or habitat assignments were random, <5.6% of DFAs and <8.26% of PGLS analyses were significant. When characters contained phylogenetic signal and actual habitats were used, 33.27 to 45.07% of DFAs and <13.09% of PGLS analyses were significant. False Discovery Rate (FDR) corrections for multiple PGLS analyses reduced the rate of significance to <4.64%. In all cases using actual habitats and characters with phylogenetic signal, correct classification rates of DFAs exceeded random chance. In simulations involving phylogenetic signal in both predictor variables and predicted categories, PGLS with FDR was rarely significant, while DFA often was. In short, DFA offered no indication that differences between categories might be explained by phylogenetic signal, while PGLS did. As such, PGLS provides a valuable tool for testing the functional hypotheses at the heart of ecomorphology. Copyright © 2013 Wiley Periodicals, Inc.
Discrimination in relation to parenthood reported by community psychiatric service users in the UK: a framework analysis

PubMed Central

2013-01-01

Background Experienced discrimination refers to an individual’s perception that they have been treated unfairly due to an attribute and is an important recent focus within stigma research. A significant proportion of mental health service users report experiencing mental illness-based discrimination in relation to parenthood. Existing studies in this area have not gone beyond prevalence, therefore little is known about the nature of experienced discrimination in relation to parenthood, and how is it constituted. This study aims to generate a typology of community psychiatric service users’ reports of mental illness-based discrimination in relation to becoming or being a parent. A secondary aim is to assess the prevalence of these types of experienced discrimination. Methods In a telephone survey 2026 community psychiatric service users in ten UK Mental Health service provider organisations (Trusts) were asked about discrimination experienced in the previous 12 months using the Discrimination and Stigma Scale (DISC). The sample were asked if, due to their mental health problem, they had been treated unfairly in starting a family, or in their role as a parent, and gave examples of this. Prevalence is reported and the examples of experienced discrimination in relation to parenthood were analysed using the framework method of qualitative analysis. Results Three hundred and four participants (73% female) reported experienced discrimination, with prevalences of 22.5% and 28.3% for starting a family and for the parenting role respectively. Participants gave 89 examples of discrimination about starting a family and 228 about parenting, and these occurred in social and professional contexts. Ten themes were identified. These related to being seen as an unfit parent; people not being understanding; being stopped from having children; not being allowed to see their children; not getting the support needed; children being affected; children avoiding their parents
Factorial and Item-Level Invariance of a Principal Perspectives Survey: German and U.S. Principals.

PubMed

Wang, Chuang; Hancock, Dawson R; Muller, Ulrich

This study examined the factorial and item-level invariance of a survey of principals' job satisfaction and perspectives about reasons and barriers to becoming a principal with a sample of US principals and another sample of German principals. Confirmatory factor analysis (CFA) and differential item functioning (DIF) analysis were employed at the test and item level, respectively. A single group CFA was conducted first, and the model was found to fit the data collected. The factorial invariance between the German and the US principals was tested through three steps: (a) configural invariance; (b) measurement invariance; and (c) structural invariance. The results suggest that the survey is a viable measure of principals' job satisfaction and perspectives about reasons and barriers to becoming a principal because principals from two different cultures shared a similar pattern on all three constructs. The DIF analysis further revealed that 22 out of the 28 items functioned similarly between German and US principals.
1. FACTORY BUILDING VIEWED FROM THE EAST, CURING AND STORAGE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

1. FACTORY BUILDING VIEWED FROM THE EAST, CURING AND STORAGE WING TO THE LEFT, BOILING HOUSE IN THE CENTER, GRINDING PLATFORM TO THE FAR RIGHT, ST. THOMAS ISLAND VISIBLE IN BACKGROUND - Caneel Bay Plantation, Sugar Factory, Cruz Bay, St. John, VI
Factorial, Convergent, and Discriminant Validity of TIMSS Math and Science Motivation Measures: A Comparison of Arab and Anglo-Saxon Countries

ERIC Educational Resources Information Center

Marsh, Herbert W.; Abduljabbar, Adel Salah; Abu-Hilal, Maher M.; Morin, Alexandre J. S.; Abdelfattah, Faisal; Leung, Kim Chau; Xu, Man K.; Nagengast, Benjamin; Parker, Philip

2013-01-01

For the international Trends in International Mathematics and Science Study (TIMSS2007) math and science motivation scales (self-concept, positive affect, and value), we evaluated the psychometric properties (factor structure, method effects, gender differences, and convergent and discriminant validity) in 4 Arab-speaking countries (Saudi Arabia,…
Discrimination and psychiatric disorder among Asian American immigrants: a national analysis by subgroups.

PubMed

Li, Miao

2014-12-01

Although considerable evidence suggests that discrimination negatively affects mental health for Asian American (AA) immigrants, few studies have disaggregated this heterogeneous community and/or differentiated effects of different forms of discrimination. Using the first nationally representative data on AA immigrants in US, this study examines whether perceived racial discrimination, perceived language discrimination, and vicarious racism experiences increase the risk of psychiatric disorder for different Asian immigrant groups in the past 12 months. Results from group specific logistic regressions show that both perceived racial and language discrimination have strong deleterious effects on mental health only for Filipinos, while Vietnamese and Chinese are more likely to be affected by vicarious racism experiences. No significant association was found between racial discrimination and the mental health outcome for Vietnamese and Chinese. Findings were discussed in the light of inter-racial contact pattern and acculturation status for each group.
Local linear discriminant analysis framework using sample neighbors.

PubMed

Fan, Zizhu; Xu, Yong; Zhang, David

2011-07-01

The linear discriminant analysis (LDA) is a very popular linear feature extraction approach. The algorithms of LDA usually perform well under the following two assumptions. The first assumption is that the global data structure is consistent with the local data structure. The second assumption is that the input data classes are Gaussian distributions. However, in real-world applications, these assumptions are not always satisfied. In this paper, we propose an improved LDA framework, the local LDA (LLDA), which can perform well without needing to satisfy the above two assumptions. Our LLDA framework can effectively capture the local structure of samples. According to different types of local data structure, our LLDA framework incorporates several different forms of linear feature extraction approaches, such as the classical LDA and principal component analysis. The proposed framework includes two LLDA algorithms: a vector-based LLDA algorithm and a matrix-based LLDA (MLLDA) algorithm. MLLDA is directly applicable to image recognition, such as face recognition. Our algorithms need to train only a small portion of the whole training set before testing a sample. They are suitable for learning large-scale databases especially when the input data dimensions are very high and can achieve high classification accuracy. Extensive experiments show that the proposed algorithms can obtain good classification results.
Discrimination between Alzheimer's Disease and Late Onset Bipolar Disorder Using Multivariate Analysis.

PubMed

Besga, Ariadna; Gonzalez, Itxaso; Echeburua, Enrique; Savio, Alexandre; Ayerdi, Borja; Chyzhyk, Darya; Madrigal, Jose L M; Leza, Juan C; Graña, Manuel; Gonzalez-Pinto, Ana Maria

2015-01-01

Late onset bipolar disorder (LOBD) is often difficult to distinguish from degenerative dementias, such as Alzheimer disease (AD), due to comorbidities and common cognitive symptoms. Moreover, LOBD prevalence in the elder population is not negligible and it is increasing. Both pathologies share pathophysiological neuroinflammation features. Improvements in differential diagnosis of LOBD and AD will help to select the best personalized treatment. The aim of this study is to assess the relative significance of clinical observations, neuropsychological tests, and specific blood plasma biomarkers (inflammatory and neurotrophic), separately and combined, in the differential diagnosis of LOBD versus AD. It was carried out evaluating the accuracy achieved by classification-based computer-aided diagnosis (CAD) systems based on these variables. A sample of healthy controls (HC) (n = 26), AD patients (n = 37), and LOBD patients (n = 32) was recruited at the Alava University Hospital. Clinical observations, neuropsychological tests, and plasma biomarkers were measured at recruitment time. We applied multivariate machine learning classification methods to discriminate subjects from HC, AD, and LOBD populations in the study. We analyzed, for each classification contrast, feature sets combining clinical observations, neuropsychological measures, and biological markers, including inflammation biomarkers. Furthermore, we analyzed reduced feature sets containing variables with significative differences determined by a Welch's t-test. Furthermore, a battery of classifier architectures were applied, encompassing linear and non-linear Support Vector Machines (SVM), Random Forests (RF), Classification and regression trees (CART), and their performance was evaluated in a leave-one-out (LOO) cross-validation scheme. Post hoc analysis of Gini index in CART classifiers provided a measure of each variable importance. Welch's t-test found one biomarker (Malondialdehyde) with
Development of muon ring coolers, neutrino factories and supersymmetric Higgs factory

NASA Astrophysics Data System (ADS)

Cline, David B.

2003-08-01

Over the past few years or so a key new development is the invention of ring coolers for muon cooling. In particular, these rings demonstrate robust cooling of the longitudinal phase space. We discuss the quadrupole or UCLA ring cooler and the prospects to make this a final cooler to reduce the transceiver emittance to the value required for a mu+mu- collider. This will lead to a Higgs factory for the A0/H0 in supersymmetry models.
Development of Muon Ring Coolers, Neutrino Factories and Supersymmetric Higgs Factory

NASA Astrophysics Data System (ADS)

Cline, David B.

2002-12-01

Over the past few years or so a key new development is the invention of Ring Coolers for muon cooling. In particular these rings demonstrate robust cooling of the longitudinal phase space. We discuss the Quadrupole or UCLA Ring Cooler and the prospects to make this a final cooler to reduce the tranceiver emittance to the value required for a μ+ μ- collider. This will lead to a Higgs Factory for the A0/H0 in supersymmetry models.

Baby Factories in Nigeria: Starting the Discussion Toward a National Prevention Policy.

PubMed

Makinde, Olusesan Ayodeji; Olaleye, Olalekan; Makinde, Olufunmbi Olukemi; Huntley, Svetlana S; Brown, Brandon

2017-01-01

Baby factories and baby harvesting are relatively new terms that involve breeding, trafficking, and abuse of infants and their biological mothers. Since it was first described in a United Nations Educational, Scientific and Cultural Organization report in Nigeria in 2006, several more baby factories have been discovered over the years. Infertile women are noted to be major patrons of these baby factories due to the stigmatization of childless couples in Southern Nigeria and issues around cultural acceptability of surrogacy and adoption. These practices have contributed to the growth in the industry which results in physical, psychological, and sexual violence to the victims. Tackling baby factories will involve a multifaceted approach that includes advocacy and enacting of legislation barring baby factories and infant trafficking and harsh consequences for their patrons. Also, programs to educate young girls on preventing unwanted pregnancies are needed. Methods of improving awareness and acceptability of adoption and surrogacy and reducing the administrative and legal bottlenecks associated with these options for infertile couples should be explored to diminish the importance of baby factories. © The Author(s) 2015.
Varietal discrimination of hop pellets by near and mid infrared spectroscopy.

PubMed

Machado, Julio C; Faria, Miguel A; Ferreira, Isabel M P L V O; Páscoa, Ricardo N M J; Lopes, João A

2018-04-01

Hop is one of the most important ingredients of beer production and several varieties are commercialized. Therefore, it is important to find an eco-real-time-friendly-low-cost technique to distinguish and discriminate hop varieties. This paper describes the development of a method based on vibrational spectroscopy techniques, namely near- and mid-infrared spectroscopy, for the discrimination of 33 commercial hop varieties. A total of 165 samples (five for each hop variety) were analysed by both techniques. Principal component analysis, hierarchical cluster analysis and partial least squares discrimination analysis were the chemometric tools used to discriminate positively the hop varieties. After optimizing the spectral regions and pre-processing methods a total of 94.2% and 96.6% correct hop varieties discrimination were obtained for near- and mid-infrared spectroscopy, respectively. The results obtained demonstrate the suitability of these vibrational spectroscopy techniques to discriminate different hop varieties and consequently their potential to be used as an authenticity tool. Compared with the reference procedures normally used for hops variety discrimination these techniques are quicker, cost-effective, non-destructive and eco-friendly. Copyright © 2017 Elsevier B.V. All rights reserved.
Lattice Commissioning Stretgy Simulation for the B Factory

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

Lee, M.; Whittum, D.; Yan, Y.

2011-08-26

To prepare for the PEP-II turn on, we have studied one commissioning strategy with simulated lattice errors. Features such as difference and absolute orbit analysis and correction are discussed. To prepare for the commissioning of the PEP-II injection line and high energy ring (HER), we have developed a system for on-line orbit analysis by merging two existing codes: LEGO and RESOLVE. With the LEGO-RESOLVE system, we can study the problem of finding quadrupole alignment and beam position (BPM) offset errors with simulated data. We have increased the speed and versatility of the orbit analysis process by using a command filemore » written in a script language designed specifically for RESOLVE. In addition, we have interfaced the LEGO-RESOLVE system to the control system of the B-Factory. In this paper, we describe online analysis features of the LEGO-RESOLVE system and present examples of practical applications.« less
Genetic Discrimination

MedlinePlus

... the News Canadian 41 st Parliament Passes New Law, S-201 "Genetic Non-Discrimination Act" Canadian lawmakers passed ... Title II). Read more Genetic Discrimination and Other Laws Genetic Discrimination and Other Laws includes the Health ...
Factorial Structure of the New Ecological Paradigm Scale in Two French Samples

ERIC Educational Resources Information Center

Fleury-Bahi, Ghozlane; Marcouyeux, Aurore; Renard, Elise; Roussiau, Nicolas

2015-01-01

The principal objective of this research is to test the factorial structure of the New Ecological Paradigm scale on a population of men and women residing in France. The tested model is a second-order factorial model. This factorial structure is evaluated on two separate samples to test the stability of the solution (a first sample of 253…
Assessing factorial invariance of two-way rating designs using three-way methods

PubMed Central

Kroonenberg, Pieter M.

2015-01-01

Assessing the factorial invariance of two-way rating designs such as ratings of concepts on several scales by different groups can be carried out with three-way models such as the Parafac and Tucker models. By their definitions these models are double-metric factorially invariant. The differences between these models lie in their handling of the links between the concept and scale spaces. These links may consist of unrestricted linking (Tucker2 model), invariant component covariances but variable variances per group and per component (Parafac model), zero covariances and variances different per group but not per component (Replicated Tucker3 model) and strict invariance (Component analysis on the average matrix). This hierarchy of invariant models, and the procedures by which to evaluate the models against each other, is illustrated in some detail with an international data set from attachment theory. PMID:25620936
B factory plans at Cornell

NASA Astrophysics Data System (ADS)

Berkelman, Karl

1989-12-01

Recent upgrade project at the Cornell Electron Storage Ring is discussed. Modification was made to make B mesons factory design possible. The CLEO detector has been rebuilt with a new superconducting magnet and a high resolution electromagnetic calorimeter made of cesium iodide scintillators.(AIP)
The prediction of human exons by oligonucleotide composition and discriminant analysis of spliceable open reading frames

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

Solovyev, V.V.; Salamov, A.A.; Lawrence, C.B.

1994-12-31

Discriminant analysis is applied to the problem of recognition 5`-, internal and 3`-exons in human DNA sequences. Specific recognition functions were developed for revealing exons of particular types. The method based on a splice site prediction algorithm that uses the linear Fisher discriminant to combine the information about significant triplet frequencies of various functional parts of splice site regions and preferences of oligonucleotide in protein coding and nation regions. The accuracy of our splice site recognition function is about 97%. A discriminant function for 5`-exon prediction includes hexanucleotide composition of upstream region, triplet composition around the ATG codon, ORF codingmore » potential, donor splice site potential and composition of downstream introit region. For internal exon prediction, we combine in a discriminant function the characteristics describing the 5`- intron region, donor splice site, coding region, acceptor splice site and Y-intron region for each open reading frame flanked by GT and AG base pairs. The accuracy of precise internal exon recognition on a test set of 451 exon and 246693 pseudoexon sequences is 77% with a specificity of 79% and a level of pseudoexon ORF prediction of 99.96%. The recognition quality computed at the level of individual nucleotides is 89%, for exon sequences and 98% for intron sequences. A discriminant function for 3`-exon prediction includes octanucleolide composition of upstream nation region, triplet composition around the stop codon, ORF coding potential, acceptor splice site potential and hexanucleotide composition of downstream region. We unite these three discriminant functions in exon predicting program FEX (find exons). FEX exactly predicts 70% of 1016 exons from the test of 181 complete genes with specificity 73%, and 89% exons are exactly or partially predicted. On the average, 85% of nucleotides were predicted accurately with specificity 91%.« less
Pion Production for Neutrino Factory-challenges

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

Breton, Florian; Le Couedic, Clement; Soler, F. J. P.

2011-10-06

One of the key issues in the design of a Neutrino Factory target station is the determination of the optimum kinetic energy of the proton beam due to the large uncertainties in simulations of protons impinging on nuclear targets. In this paper we have developed a procedure to correct GEANT4 simulations for the HARP data, and we have determined the yield of muons expected at the front-end of a Neutrino Factory as a function of target material (Be, C, Al, Ta and Pb) and energy (3-12 GeV).The maximum muon yield is found between 5 and 8 GeV for high Zmore » targets and 3 GeV for low Z targets.« less
Soybean varieties discrimination using non-imaging hyperspectral sensor

NASA Astrophysics Data System (ADS)

da Silva Junior, Carlos Antonio; Nanni, Marcos Rafael; Shakir, Muhammad; Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; Cezar, Everson; de Gois, Givanildo; Lima, Mendelson; Wojciechowski, Julio Cesar; Shiratsuchi, Luciano Shozo

2018-03-01

Infrared region of electromagnetic spectrum has remarkable applications in crop studies. Infrared along with Red band has been used to develop certain vegetation indices. These indices like NDVI, EVI provide important information on any crop physiological stages. The main objective of this research was to discriminate 4 different soybean varieties (BMX Potência, NA5909, FT Campo Mourão and Don Mario) using non-imaging hyperspectral sensor. The study was conducted in four agricultural areas in the municipality of Deodápolis (MS), Brazil. For spectral analysis, 2400 field samples were taken from soybean leaves by means of FieldSpec 3 JR spectroradiometer in the range from 350 to 2500 nm. The data were evaluated through multivariate analysis with the whole set of spectral curves isolated by blue, green, red and near infrared wavelengths along with the addition of vegetation indices like (Enhanced Vegetation Index - EVI, Normalized Difference Vegetation Index - NDVI, Green Normalized Difference Vegetation Index - GNDVI, Soil-adjusted Vegetation Index - SAVI, Transformed Vegetation Index - TVI and Optimized Soil-Adjusted Vegetation Index - OSAVI). A number of the analysis performed where, discriminant (60 and 80% of the data), simulated discriminant (40 and 20% of data), principal component (PC) and cluster analysis (CA). Discriminant and simulated discriminant analyze presented satisfactory results, with average global hit rates of 99.28 and 98.77%, respectively. The results obtained by PC and CA revealed considerable associations between the evaluated variables and the varieties, which indicated that each variety has a variable that discriminates it more effectively in relation to the others. There was great variation in the sample size (number of leaves) for estimating the mean of variables. However, it was possible to observe that 200 leaves allow to obtain a maximum error of 2% in relation to the mean.
Neural mechanisms of coarse-to-fine discrimination in the visual cortex.

PubMed

Purushothaman, Gopathy; Chen, Xin; Yampolsky, Dmitry; Casagrande, Vivien A

2014-12-01

Vision is a dynamic process that refines the spatial scale of analysis over time, as evidenced by a progressive improvement in the ability to detect and discriminate finer details. To understand coarse-to-fine discrimination, we studied the dynamics of spatial frequency (SF) response using reverse correlation in the primary visual cortex (V1) of the primate. In a majority of V1 cells studied, preferred SF either increased monotonically with time (group 1) or changed nonmonotonically, with an initial increase followed by a decrease (group 2). Monotonic shift in preferred SF occurred with or without an early suppression at low SFs. Late suppression at high SFs always accompanied nonmonotonic SF dynamics. Bayesian analysis showed that SF discrimination performance and best discriminable SF frequencies changed with time in different ways in the two groups of neurons. In group 1 neurons, SF discrimination performance peaked on both left and right flanks of the SF tuning curve at about the same time. In group 2 neurons, peak discrimination occurred on the right flank (high SFs) later than on the left flank (low SFs). Group 2 neurons were also better discriminators of high SFs. We examined the relationship between the time at which SF discrimination performance peaked on either flank of the SF tuning curve and the corresponding best discriminable SFs in both neuronal groups. This analysis showed that the population best discriminable SF increased with time in V1. These results suggest neural mechanisms for coarse-to-fine discrimination behavior and that this process originates in V1 or earlier. Copyright © 2014 the American Physiological Society.
The discrimination of geoforensic trace material from close proximity locations by organic profiling using HPLC and plant wax marker analysis by GC.

PubMed

McCulloch, G; Dawson, L A; Ross, J M; Morgan, R M

2018-07-01

There is a need to develop a wider empirical research base to expand the scope for utilising the organic fraction of soil in forensic geoscience, and to demonstrate the capability of the analytical techniques used in forensic geoscience to discriminate samples at close proximity locations. The determination of wax markers from soil samples by GC analysis has been used extensively in court and is known to be effective in discriminating samples from different land use types. A new HPLC method for the analysis of the organic fraction of forensic sediment samples has also been shown recently to add value in conjunction with existing inorganic techniques for the discrimination of samples derived from close proximity locations. This study compares the ability of these two organic techniques to discriminate samples derived from close proximity locations and finds the GC technique to provide good discrimination at this scale, providing quantification of known compounds, whilst the HPLC technique offered a shorter and simpler sample preparation method and provided very good discrimination between groups of samples of different provenance in most cases. The use of both data sets together gave further improved accuracy rates in some cases, suggesting that a combined organic approach can provide added benefits in certain case scenarios and crime reconstruction contexts. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Approaching the socialist factory and its workforce: considerations from fieldwork in (former) Yugoslavia

PubMed Central

Archer, Rory; Musić, Goran

2017-01-01

Abstract The socialist factory, as the ‘incubator’ of the new socialist (wo)man, is a productive entry point for the study of socialist modernization and its contradictions. By outlining some theoretical and methodological insights gathered through field-research in factories in former Yugoslavia, we seek to connect the state of labour history in the Balkans to recent breakthroughs made by labour historians of other socialist countries. The first part of this article sketches some of the specificities of the Yugoslav self-managed factory and its heterogeneous workforce. It presents the ambiguous relationship between workers and the factory and demonstrates the variety of life trajectories for workers in Yugoslav state-socialism (from model communists to alienated workers). The second part engages with the available sources for conducting research inside and outside the factory advocating an approach which combines factory and local archives, print media and oral history. PMID:28190894
Approaching the socialist factory and its workforce: considerations from fieldwork in (former) Yugoslavia.

PubMed

Archer, Rory; Musić, Goran

2017-01-01

The socialist factory, as the 'incubator' of the new socialist (wo)man, is a productive entry point for the study of socialist modernization and its contradictions. By outlining some theoretical and methodological insights gathered through field-research in factories in former Yugoslavia, we seek to connect the state of labour history in the Balkans to recent breakthroughs made by labour historians of other socialist countries. The first part of this article sketches some of the specificities of the Yugoslav self-managed factory and its heterogeneous workforce. It presents the ambiguous relationship between workers and the factory and demonstrates the variety of life trajectories for workers in Yugoslav state-socialism (from model communists to alienated workers). The second part engages with the available sources for conducting research inside and outside the factory advocating an approach which combines factory and local archives, print media and oral history.
Accurate palm vein recognition based on wavelet scattering and spectral regression kernel discriminant analysis

NASA Astrophysics Data System (ADS)

Elnasir, Selma; Shamsuddin, Siti Mariyam; Farokhi, Sajad

2015-01-01

Palm vein recognition (PVR) is a promising new biometric that has been applied successfully as a method of access control by many organizations, which has even further potential in the field of forensics. The palm vein pattern has highly discriminative features that are difficult to forge because of its subcutaneous position in the palm. Despite considerable progress and a few practical issues, providing accurate palm vein readings has remained an unsolved issue in biometrics. We propose a robust and more accurate PVR method based on the combination of wavelet scattering (WS) with spectral regression kernel discriminant analysis (SRKDA). As the dimension of WS generated features is quite large, SRKDA is required to reduce the extracted features to enhance the discrimination. The results based on two public databases-PolyU Hyper Spectral Palmprint public database and PolyU Multi Spectral Palmprint-show the high performance of the proposed scheme in comparison with state-of-the-art methods. The proposed approach scored a 99.44% identification rate and a 99.90% verification rate [equal error rate (EER)=0.1%] for the hyperspectral database and a 99.97% identification rate and a 99.98% verification rate (EER=0.019%) for the multispectral database.
Lameness detection challenges in automated milking systems addressed with partial least squares discriminant analysis.

PubMed

Garcia, E; Klaas, I; Amigo, J M; Bro, R; Enevoldsen, C

2014-12-01

Lameness causes decreased animal welfare and leads to higher production costs. This study explored data from an automatic milking system (AMS) to model on-farm gait scoring from a commercial farm. A total of 88 cows were gait scored once per week, for 2 5-wk periods. Eighty variables retrieved from AMS were summarized week-wise and used to predict 2 defined classes: nonlame and clinically lame cows. Variables were represented with 2 transformations of the week summarized variables, using 2-wk data blocks before gait scoring, totaling 320 variables (2 × 2 × 80). The reference gait scoring error was estimated in the first week of the study and was, on average, 15%. Two partial least squares discriminant analysis models were fitted to parity 1 and parity 2 groups, respectively, to assign the lameness class according to the predicted probability of being lame (score 3 or 4/4) or not lame (score 1/4). Both models achieved sensitivity and specificity values around 80%, both in calibration and cross-validation. At the optimum values in the receiver operating characteristic curve, the false-positive rate was 28% in the parity 1 model, whereas in the parity 2 model it was about half (16%), which makes it more suitable for practical application; the model error rates were, 23 and 19%, respectively. Based on data registered automatically from one AMS farm, we were able to discriminate nonlame and lame cows, where partial least squares discriminant analysis achieved similar performance to the reference method. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Vigilance in the discrimination-stress model for Black Americans.

PubMed

Himmelstein, Mary S; Young, Danielle M; Sanchez, Diana T; Jackson, James S

2015-01-01

Daily events of discrimination are important factors in understanding health disparities. Vigilant coping, or protecting against anticipated discrimination by monitoring and modifying behaviour, is an understudied mechanism that may link discrimination and health outcomes. This study investigates how responding to everyday discrimination with anticipatory vigilance relates to the health of Black men and women. Black adults (N = 221) from the Detroit area completed measures of discrimination, adverse life events, vigilance coping, stress, depressive symptoms and self-reported health. Vigilance coping strategies mediated the relationship between discrimination and stress. Multi-group path analysis revealed that stress in turn was associated with increased depression in men and women. Self-reported health consequences of stress differed between men and women. Vigilance coping mediates the link between discrimination and stress, and stress has consequences for health outcomes resulting from discrimination. More research is needed to understand other underlying contributors to discrimination, stress and poor health outcomes as well as to create potential interventions to ameliorate health outcomes in the face of discrimination-related stress.
Vigilance in the discrimination-stress model for Black Americans

PubMed Central

Himmelstein, Mary S.; Young, Danielle M.; Sanchez, Diana T.; Jackson, James S.

2015-01-01

Objective Daily events of discrimination are important factors in understanding health disparities. Vigilant coping, or protecting against anticipated discrimination by monitoring and modifying behaviour, is an understudied mechanism that may link discrimination and health outcomes. This study investigates how responding to everyday discrimination with anticipatory vigilance relates to the health of Black men and women. Methods Black adults (N = 221) from the Detroit area completed measures of discrimination, adverse life events, vigilance coping, stress, depressive symptoms and self-reported health. Results Vigilance coping strategies mediated the relationship between discrimination and stress. Multi-group path analysis revealed that stress in turn was associated with increased depression in men and women. Self-reported health consequences of stress differed between men and women. Conclusions Vigilance coping mediates the link between discrimination and stress, and stress has consequences for health outcomes resulting from discrimination. More research is needed to understand other underlying contributors to discrimination, stress and poor health outcomes as well as to create potential interventions to ameliorate health outcomes in the face of discrimination-related stress. PMID:25247925
Job strain among rubber-glove-factory workers in central Thailand.

PubMed

Sein, Muang Muang; Howteerakul, Nopporn; Suwannapong, Nawarat; Jirachewee, Jirachai

2010-01-01

Job strain has become a major concern because of its potential impacts on worker well-being and performance. This cross-sectional study aimed to assess the prevalence of, and examine factors associated with, job strain among workers in a rubber-glove factory, in a central province of Thailand. A total of 200 workers aged 18-55 yr, who had worked at the factory for at least 6 months, completed the Job Content Questionnaire (JCQ) (Thai Version). Two of 5 scales in the JCQ were used to measure job strain, i.e.; job control and psychological job demand. The prevalence of job strain was 27.5%. Multiple logistic regression analysis indicated two variables significantly associated with job strain: low supervisor social support (adjusted OR=3.08; 95%CI: 1.38-6.91) and high job insecurity (adjusted OR=2.25; 95%CI: 1.04-4.88). Effective training for supervisors, to create good relationships among workers and supervisors, and ensuring steady and secure jobs for good employees, are necessary.
Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis

PubMed Central

Ferrand, Claude; Audiffren, Michel

2018-01-01

Background Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Methods Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. Results A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. Conclusions This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging. PMID:29850247

"Mixing" as an ethnoetiology of HIV/AIDS in Malaysia's multinational factories.

PubMed

Root, Robin

2006-09-01

Minah Karan, the stigmatizing label appended to Malay factory women in the 1980s, signaled a dangerous female sexuality that risked spreading beyond the factory gates and infecting Malaysia's idea(l)s of its traditional kampung culture. This article narrates how Minah Karan, as the former antihero of development, was reconstituted in the 1990s, with the government's labeling of factories as "high-risk settings" for HIV/AIDS. This is an ethnoetiology based not on any evidential epidemiological data but on the racial and gendered "mixing" that transpires behind factory walls: a fear that the "mixing of the sexes" means ipso facto "sexual mixing" among the races. The article demonstrates how importation of the high-risk label articulates at the local level the new and contested linkages, economic, religious, and scientific, constitutive of globalization. The pragmatic nature and imperatives of this high-risk process are discerned in factory women's accounts of how they negotiate the interactional imperatives of factory work, because transnational structures of productivity violate the social boundaries that have long connoted political stability, moral integrity, ethnic community, and individual safety. The article concludes by questioning whether ethnoetiologies, especially when they concern sexual networks, become social etiologies, because this would locate ethnoetiologies as central to conventional public health praxis rather than as ethnographic exotica in the margins.
Neutrino Factory Plans at CERN

NASA Astrophysics Data System (ADS)

Riche, J. A.

2002-10-01

The considerable interest raised by the discovery of neutrino oscillations and recent progress in studies of muon colliders has triggered interest in considering a neutrino factory at CERN. This paper explains the reference scenario, indicates the other possible choices and mentions the R&D that are foreseen.
A Longitudinal Analysis of Hispanic Youth Acculturation and Cigarette Smoking: The Roles of Gender, Culture, Family, and Discrimination

PubMed Central

2013-01-01

Introduction: Risk for smoking initiation increases as Hispanic youth acculturate to U.S. society, and this association seems to be stronger for Hispanic girls than boys. To better understand the influence of culture, family, and everyday discrimination on cigarette smoking, we tested a process-oriented model of acculturation and cigarette smoking. Methods: Data came from Project RED (Reteniendo y Entendiendo Diversidad para Salud), which included 1,436 Hispanic students (54% girls) from Southern California. We used data from 9th to 11th grade (85% were 14 years old, and 86% were U.S. born) to test the influence of acculturation-related experiences on smoking over time. Results: Multigroup structural equation analysis suggested that acculturation was associated with increased familismo and lower traditional gender roles, and enculturation was linked more with familismo and respeto. Familismo, respeto, and traditional gender roles were linked with lower family conflict and increased family cohesion, and these links were stronger for girls. Familismo and respeto were further associated with lower discrimination. Conversely, fatalismo was linked with worse family functioning (especially for boys) and increased discrimination in both the groups. Discrimination was the only predictor of smoking for boys and girls. Conclusions: In all, the results of the current study indicate that reducing discrimination and helping youth cope with discrimination may prevent or reduce smoking in Hispanic boys and girls. This may be achieved by promoting familismo and respeto and by discouraging fatalistic beliefs. PMID:23109671
A longitudinal analysis of Hispanic youth acculturation and cigarette smoking: the roles of gender, culture, family, and discrimination.

PubMed

Lorenzo-Blanco, Elma I; Unger, Jennifer B; Ritt-Olson, Anamara; Soto, Daniel; Baezconde-Garbanati, Lourdes

2013-05-01

Risk for smoking initiation increases as Hispanic youth acculturate to U.S. society, and this association seems to be stronger for Hispanic girls than boys. To better understand the influence of culture, family, and everyday discrimination on cigarette smoking, we tested a process-oriented model of acculturation and cigarette smoking. Data came from Project RED (Reteniendo y Entendiendo Diversidad para Salud), which included 1,436 Hispanic students (54% girls) from Southern California. We used data from 9th to 11th grade (85% were 14 years old, and 86% were U.S. born) to test the influence of acculturation-related experiences on smoking over time. Multigroup structural equation analysis suggested that acculturation was associated with increased familismo and lower traditional gender roles, and enculturation was linked more with familismo and respeto. Familismo, respeto, and traditional gender roles were linked with lower family conflict and increased family cohesion, and these links were stronger for girls. Familismo and respeto were further associated with lower discrimination. Conversely, fatalismo was linked with worse family functioning (especially for boys) and increased discrimination in both the groups. Discrimination was the only predictor of smoking for boys and girls. In all, the results of the current study indicate that reducing discrimination and helping youth cope with discrimination may prevent or reduce smoking in Hispanic boys and girls. This may be achieved by promoting familismo and respeto and by discouraging fatalistic beliefs.
Using Pattern Recognition and Discriminance Analysis to Predict Critical Events in Large Signal Databases

NASA Astrophysics Data System (ADS)

Feller, Jens; Feller, Sebastian; Mauersberg, Bernhard; Mergenthaler, Wolfgang

2009-09-01

Many applications in plant management require close monitoring of equipment performance, in particular with the objective to prevent certain critical events. At each point in time, the information available to classify the criticality of the process, is represented through the historic signal database as well as the actual measurement. This paper presents an approach to detect and predict critical events, based on pattern recognition and discriminance analysis.
A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

PubMed

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.
DIFFERENTIATION OF AURANTII FRUCTUS IMMATURUS AND FRUCTUS PONICIRI TRIFOLIATAE IMMATURUS BY FLOW-INJECTION WITH ULTRAVIOLET SPECTROSCOPIC DETECTION AND PROTON NUCLEAR MAGNETIC RESONANCE USING PARTIAL LEAST-SQUARES DISCRIMINANT ANALYSIS.

PubMed

Zhang, Mengliang; Zhao, Yang; Harrington, Peter de B; Chen, Pei

2016-03-01

Two simple fingerprinting methods, flow-injection coupled to ultraviolet spectroscopy and proton nuclear magnetic resonance, were used for discriminating between Aurantii fructus immaturus and Fructus poniciri trifoliatae immaturus . Both methods were combined with partial least-squares discriminant analysis. In the flow-injection method, four data representations were evaluated: total ultraviolet absorbance chromatograms, averaged ultraviolet spectra, absorbance at 193, 205, 225, and 283 nm, and absorbance at 225 and 283 nm. Prediction rates of 100% were achieved for all data representations by partial least-squares discriminant analysis using leave-one-sample-out cross-validation. The prediction rate for the proton nuclear magnetic resonance data by partial least-squares discriminant analysis with leave-one-sample-out cross-validation was also 100%. A new validation set of data was collected by flow-injection with ultraviolet spectroscopic detection two weeks later and predicted by partial least-squares discriminant analysis models constructed by the initial data representations with no parameter changes. The classification rates were 95% with the total ultraviolet absorbance chromatograms datasets and 100% with the other three datasets. Flow-injection with ultraviolet detection and proton nuclear magnetic resonance are simple, high throughput, and low-cost methods for discrimination studies.
Unsupervised spike sorting based on discriminative subspace learning.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.
Origin discrimination of defatted pork via trace elements profiling, stable isotope ratios analysis, and multivariate statistical techniques.

PubMed

Park, Yu Min; Lee, Cheong Mi; Hong, Joon Ho; Jamila, Nargis; Khan, Naeem; Jung, Jong-Hyun; Jung, Young-Chul; Kim, Kyong Su

2018-09-01

This study verified the origin of 346 defatted Korean and non-Korean pork samples via trace elements profiling, and C and N stable isotope ratios analysis. The analyzed elements were 6 Li, 7 Li, 10 B, 11 B, 51 V , 50 Cr, 52 Cr, 53 Cr, 55 Mn, 58 Ni, 60 Ni, 59 Co, 63 Cu, 65 Cu, 64 Zn, 66 Zn, 69 Ga, 71 Ga, 75 As, 82 Se, 84 Sr, 86 Sr, 87 Sr, 88 Sr, 85 Rb, 94 Mo, 95 Mo, 97 Mo, 107 Ag, 109 Ag, 110 Cd, 111 Cd, 113 Cd, 112 Cd, 114 Cd, 116 Cd, 133 Cs, 206 Pb, 207 Pb, and 208 Pb. Content (mg/kg) of 51 V (0.012), 50 Cr (0.882), 75 As (0.017), 85 Rb (57.7), and 87 Sr (46.3) were high in Korean pork samples whereas 6 Li, 7 Li, 59 Co, 55 Mn, 58 Ni, 84 Sr, 86 Sr, 88 Sr, 111 Cd, and 133 Cs were found higher in non-Korean samples. The results of discriminant analysis showed that the trace elements content and stable isotope ratios were significant for the discrimination of geographical origins with a perfect discrimination rate of 100%. Copyright © 2018 Elsevier Ltd. All rights reserved.
Discrimination of Bacillus anthracis from closely related microorganisms by analysis of 16S and 23S rRNA with oligonucleotide microchips

DOEpatents

Bavykin, Sergei G.; Mirzabekov, Andrei D.

2007-10-30

The present invention is directed to a novel method of discriminating a highly infectious bacterium Bacillus anthracis from a group of closely related microorganisms. Sequence variations in the 16S and 23S rRNA of the B. cereus subgroup including B. anthracis are utilized to construct an array that can detect these sequence variations through selective hybridizations. The identification and analysis of these sequence variations enables positive discrimination of isolates of the B. cereus group that includes B. anthracis. Discrimination of single base differences in rRNA was achieved with a microchip during analysis of B. cereus group isolates from both single and in mixed probes, as well as identification of polymorphic sites. Successful use of a microchip to determine the appropriate subgroup classification using eight reference microorganisms from the B. cereus group as a study set, was demonstrated.
The Skateboard Factory: Curriculum by Design--Oasis Skateboard Factory Q&A with Craig Morrison

ERIC Educational Resources Information Center

Pearson, George

2012-01-01

Since its opening three years ago, Oasis Skateboard Factory (OSF), founded by teacher Craig Morrison, has attracted considerable media exposure and received a Ken Spencer Award from the CEA for its innovative program. OSF is one of three programs offered by Oasis Alternative Secondary School, one of 22 alternative secondary schools of the Toronto…
Sex Discrimination--Court Narrows Gilbert--Some Pregnancy Discrimination Is Sex Related.

ERIC Educational Resources Information Center

Allen, Claudia G.; Powers, Jean C.

1978-01-01

Issues concerning sex discrimination based on pregnancy, presented in Nashville Gas Co. vs. Satty, and the Supreme Court's treatment of the issues are examined. The way in which the Satty opinion limits the scope of the General Electric Co. vs. Gilbert decision, and an analysis of the implications of the Satty decision are included. (JMD)
Factorial validity of the Job Expectations Questionnaire in a sample of Mexican workers.

PubMed

Villa-George, Fabiola Itzel; Moreno-Jiménez, Bernardo; Rodríguez-Muñoz, Alfredo; Villalpando Uribe, Jessica

2011-11-01

The aim of this study was to examine the factorial validity of the Job Expectations Questionnaire (Cuestionario de Expectativas Laborales CEL) in a sample of Mexican workers. Following a cross validation approach, two samples were used in the study. The first sample consisted of 380 professionals who mainly performed administrative work in the Health Services in Puebla-Mexico. The second sample comprised 400 health professionals from the Hospital de la Mujer in Puebla-Mexico. Exploratory factor analysis yielded a three-factor solution, accounting for 51.8% of the variance. The results of confirmatory factorial analysis indicate that the three-factor model provided the best fit with the data (CFI = .96, GFI = .95, NNFI = .95, RMSEA = .04), maintaining the structure with 12 items. The reliability of the questionnaire and the diverse subscales showed high internal consistency. Significant correlations were found between job expectations and autonomy, vigor, dedication, and absorption, providing evidence of its construct validity. The evaluation of the psychometric qualities confirms this questionnaire as a valid and specific instrument to measure job expectations.
Aft segment dome-to-stiffener factory joint insulation void elimination

NASA Technical Reports Server (NTRS)

Jensen, S. K.

1991-01-01

Since the detection of voids in the internal insulation of the dome-to-stiffener factory joint of the 15B aft segment, all aft segment dome-to-stiffener factory joints were x-rated and all were found to contain voids. Using a full-scale process simulation article (PSA), the objective was to demonstrate that the proposed changes in the insulation layup and vacuum bagging processes will greatly reduce or eliminate voids without adversely affecting the configuration of performance of the insulation which serves as a primary seal over the factory joint. The PSA-8 aft segment was insulated and cured using standard production processes.
The simulation of air recirculation and fire/explosion phenomena within a semiconductor factory.

PubMed

I, Yet-Pole; Chiu, Yi-Long; Wu, Shi-Jen

2009-04-30

The semiconductor industry is the collection of capital-intensive firms that employ a variety of hazardous chemicals and engage in the design and fabrication of semiconductor devices. Owing to its processing characteristics, the fully confined structure of the fabrication area (fab) and the vertical airflow ventilation design restrict the applications of traditional consequence analysis techniques that are commonly used in other industries. The adverse situation also limits the advancement of a fire/explosion prevention design for the industry. In this research, a realistic model of a semiconductor factory with a fab, sub-fabrication area, supply air plenum, and return air plenum structures was constructed and the computational fluid dynamics algorithm was employed to simulate the possible fire/explosion range and its severity. The semiconductor factory has fan module units with high efficiency particulate air filters that can keep the airflow uniform within the cleanroom. This condition was modeled by 25 fans, three layers of porous ceiling, and one layer of porous floor. The obtained results predicted very well the real airflow pattern in the semiconductor factory. Different released gases, leak locations, and leak rates were applied to investigate their influence on the hazard range and severity. Common mitigation measures such as a water spray system and a pressure relief panel were also provided to study their potential effectiveness to relieve thermal radiation and overpressure hazards within a fab. The semiconductor industry can use this simulation procedure as a reference on how to implement a consequence analysis for a flammable gas release accident within an air recirculation cleanroom.
Effect of factory effluents on physiological and biochemical contents of Gossypium hirsutum l.

PubMed

Muthusamy, A; Jayabalan, N

2001-10-01

The effect of sago and sugar factory effluents was studied on Gossypium hirsutum L. var. MCU 5 and MCU 11. Plants were irrigated with 0, 25, 50, 75 and 100% of effluents of both factories. At lower concentration (25%) of sugar factory effluents had stimulatory effect on all biochemical contents observed. Moreover, all concentration of sago factory effluents were found to have inhibitory effect on all biochemical contents except proline content which increased with increasing concentration of both the effluents. Plants growing on adjacent to sago and sugar factories or they irrigated with such type of polluted water, may accumulate the heavy metals found in both the effluents, at higher levels in plant products and if consumed may have similar effect on living organisms.
37. NORTH TO BINS ALONG NORTH WALL OF FACTORY BUILDING ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

37. NORTH TO BINS ALONG NORTH WALL OF FACTORY BUILDING WHICH REMAIN FILLED WITH NEW OLD STOCK AND USED PARTS FOR ELI WINDMILLS. THE ROPE AT THE LOWER FOREGROUND WAS USED IN ERECTING WINDMILLS AND TOWERS FOR CUSTOMERS. - Kregel Windmill Company Factory, 1416 Central Avenue, Nebraska City, Otoe County, NE
Racial discrimination mediates race differences in sleep problems: A longitudinal analysis.

PubMed

Fuller-Rowell, Thomas E; Curtis, David S; El-Sheikh, Mona; Duke, Adrienne M; Ryff, Carol D; Zgierska, Aleksandra E

2017-04-01

To examine changes in sleep problems over a 1.5-year period among Black or African American (AA) and White or European American (EA) college students and to consider the role of racial discrimination as a mediator of race differences in sleep problems over time. Students attending a large, predominantly White university (N = 133, 41% AA, 57% female, mean age = 18.8, SD = .90) reported on habitual sleep characteristics and experiences of racial discrimination at baseline and follow-up assessments. A latent variable for sleep problems was assessed from reports of sleep latency, duration, efficiency, and quality. Longitudinal models were used to examine race differences in sleep problems over time and the mediating role of perceived discrimination. Covariates included age, gender, parent education, parent income, body mass index, self-rated physical health, and depressive symptoms. Each of the individual sleep measures was also examined separately, and sensitivity analyses were conducted using alternative formulations of the sleep problems measure. AAs had greater increases in sleep problems than EAs. Perceived discrimination was also associated with increases in sleep problems over time and mediated racial disparities in sleep. This pattern of findings was similar when each of the sleep indicators was considered separately and held with alternative sleep problems measures. The findings highlight the importance of racial disparities in sleep across the college years and suggest that experiences of discrimination contribute to group disparities. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
The relation of racial identity, ethnic identity, and racial socialization to discrimination-distress: a meta-analysis of Black Americans.

PubMed

Lee, Debbiesiu L; Ahn, Soyeon

2013-01-01

This meta-analysis synthesized the results of 27 studies examining the relations of racial identity, ethnic identity, and racial socialization to discrimination-distress for Black Americans. The purpose was to uncover which constructs connected to racial identity, ethnic identity, and racial socialization most strongly correlate with racial discrimination and psychological distress. Discrimination significantly related to aspects of racial identity, including immersion-emersion, public regard, encounter, Afrocentricity/racial centrality/private regard, and internalization. Distress significantly correlated with preencounter/assimilation, encounter, public regard, immersion-emersion, and Afrocentricity/racial centrality/private regard. Several of these relationships were significantly moderated by the measure of racial identity or demographic variables (gender or age). Implications of these findings are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Relation between minimum-error discrimination and optimum unambiguous discrimination

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

Qiu Daowen; SQIG-Instituto de Telecomunicacoes, Departamento de Matematica, Instituto Superior Tecnico, Universidade Tecnica de Lisboa, Avenida Rovisco Pais PT-1049-001, Lisbon; Li Lvjun

2010-09-15

In this paper, we investigate the relationship between the minimum-error probability Q{sub E} of ambiguous discrimination and the optimal inconclusive probability Q{sub U} of unambiguous discrimination. It is known that for discriminating two states, the inequality Q{sub U{>=}}2Q{sub E} has been proved in the literature. The main technical results are as follows: (1) We show that, for discriminating more than two states, Q{sub U{>=}}2Q{sub E} may not hold again, but the infimum of Q{sub U}/Q{sub E} is 1, and there is no supremum of Q{sub U}/Q{sub E}, which implies that the failure probabilities of the two schemes for discriminating somemore » states may be narrowly or widely gapped. (2) We derive two concrete formulas of the minimum-error probability Q{sub E} and the optimal inconclusive probability Q{sub U}, respectively, for ambiguous discrimination and unambiguous discrimination among arbitrary m simultaneously diagonalizable mixed quantum states with given prior probabilities. In addition, we show that Q{sub E} and Q{sub U} satisfy the relationship that Q{sub U{>=}}(m/m-1)Q{sub E}.« less

Weight-based discrimination: an ubiquitary phenomenon?

PubMed

Sikorski, C; Spahlholz, J; Hartlev, M; Riedel-Heller, S G

2016-02-01

Despite strong indications of a high prevalence of weight-related stigmatization in individuals with obesity, limited attention has been given to the role of weight discrimination in examining the stigma obesity. Studies, up to date, rely on a limited basis of data sets and additional studies are needed to confirm the findings of previous studies. In particular, data for Europe are lacking, and are needed in light of a recent ruling of the European Court of Justice that addressed weight-based discrimination. The data were derived from a large representative telephone survey in Germany (n=3003). The dependent variable, weight-based discrimination, was assessed with a one-item question. The lifetime prevalence of weight discrimination across different sociodemographic variables was determined. Logistic regression models were used to assess the association of independent and dependent variables. A sub-group analysis was conducted analyzing all participants with a body mass index ⩾25 kg m(-)(2). The overall prevalence of weight-based discrimination was 7.3%. Large differences, however, were observed regarding weight status. In normal weight and overweight participants the prevalence was 5.6%, but this number doubled in participants with obesity class I (10.2%), and quadrupled in participants with obesity class II (18.7%) and underweight (19.7%). In participants with obesity class III, every third participant reported accounts of weight-based discrimination (38%). In regression models, after adjustment, the associations of weight status and female gender (odds ratio: 2.59, P<0.001) remained highly significant. Discrimination seems to be an ubiquitary phenomenon at least for some groups that are at special risk, such as heavier individuals and women. Our findings therefore emphasize the need for research and intervention on weight discrimination among adults with obesity, including anti-discrimination legislation.
Epidemiology of Skin Disease in an Automobile Factory*

PubMed Central

Newhouse, Muriel L.

1964-01-01

A survey was made of a random sample of workers from the machine shops, assembly lines, and stock and store departments of an automobile factory. Among the 1,223 men seen, representing 97% of the sample, the prevalence of non-infective skin diseases was 14·5%. Skin diseases were classified into four groups: `dermatitis' and `folliculitis' of occupational origin, endogenous `eczemas', and miscellaneous skin diseases. Slightly more than half of all the skin diseases seen were considered to be occupational in origin. In this population the prevalence of skin disease was more than four times that based on patients attending the factory medical department. An unsuspected cause of allergic dermatitis was found on the assembly lines, where the incidence of dermatitis was significantly higher than among the non-production workers. The prevalence of folliculitis was significantly higher among production than non-production workers. There was no significant difference in the prevalence of `eczema' or the miscellaneous skin diseases in the various occupational groups. Among European workers fair men were more prone to skin disease than darker men. In another factory, a West Indian and Asiatic group of workers had a significantly lower prevalence of skin diseases than a group of Europeans doing similar work. Folliculitis was more prevalent among the younger workers and those recently employed in the factory; there was no obvious association between age and length of service and the occurrence of other types of skin disease. PMID:14249898
Functional MRI Representational Similarity Analysis Reveals a Dissociation between Discriminative and Relative Location Information in the Human Visual System.

PubMed

Roth, Zvi N

2016-01-01

Neural responses in visual cortex are governed by a topographic mapping from retinal locations to cortical responses. Moreover, at the voxel population level early visual cortex (EVC) activity enables accurate decoding of stimuli locations. However, in many cases information enabling one to discriminate between locations (i.e., discriminative information) may be less relevant than information regarding the relative location of two objects (i.e., relative information). For example, when planning to grab a cup, determining whether the cup is located at the same retinal location as the hand is hardly relevant, whereas the location of the cup relative to the hand is crucial for performing the action. We have previously used multivariate pattern analysis techniques to measure discriminative location information, and found the highest levels in EVC, in line with other studies. Here we show, using representational similarity analysis, that availability of discriminative information in fMRI activation patterns does not entail availability of relative information. Specifically, we find that relative location information can be reliably extracted from activity patterns in posterior intraparietal sulcus (pIPS), but not from EVC, where we find the spatial representation to be warped. We further show that this variability in relative information levels between regions can be explained by a computational model based on an array of receptive fields. Moreover, when the model's receptive fields are extended to include inhibitory surround regions, the model can account for the spatial warping in EVC. These results demonstrate how size and shape properties of receptive fields in human visual cortex contribute to the transformation of discriminative spatial representations into relative spatial representations along the visual stream.
Functional MRI Representational Similarity Analysis Reveals a Dissociation between Discriminative and Relative Location Information in the Human Visual System

PubMed Central

Roth, Zvi N.

2016-01-01

Neural responses in visual cortex are governed by a topographic mapping from retinal locations to cortical responses. Moreover, at the voxel population level early visual cortex (EVC) activity enables accurate decoding of stimuli locations. However, in many cases information enabling one to discriminate between locations (i.e., discriminative information) may be less relevant than information regarding the relative location of two objects (i.e., relative information). For example, when planning to grab a cup, determining whether the cup is located at the same retinal location as the hand is hardly relevant, whereas the location of the cup relative to the hand is crucial for performing the action. We have previously used multivariate pattern analysis techniques to measure discriminative location information, and found the highest levels in EVC, in line with other studies. Here we show, using representational similarity analysis, that availability of discriminative information in fMRI activation patterns does not entail availability of relative information. Specifically, we find that relative location information can be reliably extracted from activity patterns in posterior intraparietal sulcus (pIPS), but not from EVC, where we find the spatial representation to be warped. We further show that this variability in relative information levels between regions can be explained by a computational model based on an array of receptive fields. Moreover, when the model's receptive fields are extended to include inhibitory surround regions, the model can account for the spatial warping in EVC. These results demonstrate how size and shape properties of receptive fields in human visual cortex contribute to the transformation of discriminative spatial representations into relative spatial representations along the visual stream. PMID:27242455
The role of critical ethnic awareness and social support in the discrimination-depression relationship among Asian Americans: path analysis.

PubMed

Kim, Isok

2014-01-01

This study used a path analytic technique to examine associations among critical ethnic awareness, racial discrimination, social support, and depressive symptoms. Using a convenience sample from online survey of Asian American adults (N = 405), the study tested 2 main hypotheses: First, based on the empowerment theory, critical ethnic awareness would be positively associated with racial discrimination experience; and second, based on the social support deterioration model, social support would partially mediate the relationship between racial discrimination and depressive symptoms. The result of the path analysis model showed that the proposed path model was a good fit based on global fit indices, χ²(2) = 4.70, p = .10; root mean square error of approximation = 0.06; comparative fit index = 0.97; Tucker-Lewis index = 0.92; and standardized root mean square residual = 0.03. The examinations of study hypotheses demonstrated that critical ethnic awareness was directly associated (b = .11, p < .05) with the racial discrimination experience, whereas social support had a significant indirect effect (b = .48; bias-corrected 95% confidence interval [0.02, 1.26]) between the racial discrimination experience and depressive symptoms. The proposed path model illustrated that both critical ethnic awareness and social support are important mechanisms for explaining the relationship between racial discrimination and depressive symptoms among this sample of Asian Americans. This study highlights the usefulness of the critical ethnic awareness concept as a way to better understand how Asian Americans might perceive and recognize racial discrimination experiences in relation to its mental health consequences.
Visible light assisted photoelectrocatalytic degradation of sugarcane factory wastewater by sprayed CZTS thin films

NASA Astrophysics Data System (ADS)

Hunge, Y. M.; Mahadik, M. A.; Patil, V. L.; Pawar, A. R.; Gadakh, S. R.; Moholkar, A. V.; Patil, P. S.; Bhosale, C. H.

2017-12-01

Highly crystalline Cu2ZnSnS4 (CZTS) thin films have been deposited onto glass and FTO coated glass substrates by simple chemical spray-pyrolysis technique. It is an important material for solar energy conversion through the both photovoltaics and photocatalysis. The effect of substrate temperatures on the physico-chemical properties of the CZTS films is studied. The XRD study shows the formation of single phase CZTS with kesterite structure. FE-SEM analysis reveals nano flakes architecture with pin-hole and crake free surface with more adherent. The film deposited at optimized substrate temperature exhibits optical band gap energy of 1.90 eV, which lies in the visible region of the solar spectrum and useful for photocatalysis application. The photoelectrocatalytic activities of the large surface area (10 × 10 cm2) deposited CZTS thin film photocatalysts were evaluated for the degradation of sugarcane factory wastewater under visible light irradiation. The results show that the CZTS thin film photocatalyst exhibited about 90% degradation of sugar cane factory wastewater. The mineralization of sugarcane factory wastewater is studied by measuring chemical oxygen demand (COD) values.
Signal Detection Methods and Discriminant Analysis Applied to Categorization of Newspaper and Government Documents: A Preliminary Study.

ERIC Educational Resources Information Center

Ng, Kwong Bor; Rieh, Soo Young; Kantor, Paul

2000-01-01

Discussion of natural language processing focuses on experiments using linear discriminant analysis to distinguish "Wall Street Journal" texts from "Federal Register" tests using information about the frequency of occurrence of word boundaries, sentence boundaries, and punctuation marks. Displays and interprets results in terms…
Time-order errors and standard-position effects in duration discrimination: An experimental study and an analysis by the sensation-weighting model.

PubMed

Hellström, Åke; Rammsayer, Thomas H

2015-10-01

Studies have shown that the discriminability of successive time intervals depends on the presentation order of the standard (St) and the comparison (Co) stimuli. Also, this order affects the point of subjective equality. The first effect is here called the standard-position effect (SPE); the latter is known as the time-order error. In the present study, we investigated how these two effects vary across interval types and standard durations, using Hellström's sensation-weighting model to describe the results and relate them to stimulus comparison mechanisms. In Experiment 1, four modes of interval presentation were used, factorially combining interval type (filled, empty) and sensory modality (auditory, visual). For each mode, two presentation orders (St-Co, Co-St) and two standard durations (100 ms, 1,000 ms) were used; half of the participants received correctness feedback, and half of them did not. The interstimulus interval was 900 ms. The SPEs were negative (i.e., a smaller difference limen for St-Co than for Co-St), except for the filled-auditory and empty-visual 100-ms standards, for which a positive effect was obtained. In Experiment 2, duration discrimination was investigated for filled auditory intervals with four standards between 100 and 1,000 ms, an interstimulus interval of 900 ms, and no feedback. Standard duration interacted with presentation order, here yielding SPEs that were negative for standards of 100 and 1,000 ms, but positive for 215 and 464 ms. Our findings indicate that the SPE can be positive as well as negative, depending on the interval type and standard duration, reflecting the relative weighting of the stimulus information, as is described by the sensation-weighting model.
Discriminant analysis of cardiovascular and respiratory variables for classification of road cyclists by specialty.

PubMed

Nikolić, Biljana; Martinović, Jelena; Matić, Milan; Stefanović, Đorđe

2018-05-29

Different variables determine the performance of cyclists, which brings up the question how these parameters may help in their classification by specialty. The aim of the study was to determine differences in cardiorespiratory parameters of male cyclists according to their specialty, flat rider (N=21), hill rider (N=35) and sprinter (N=20) and obtain the multivariate model for further cyclists classification by specialties, based on selected variables. Seventeen variables were measured at submaximal and maximum load on the cycle ergometer Cosmed E 400HK (Cosmed, Rome, Italy) (initial 100W with 25W increase, 90-100 rpm). Multivariate discriminant analysis was used to determine which variables group cyclists within their specialty, and to predict which variables can direct cyclists to a particular specialty. Among nine variables that statistically contribute to the discriminant power of the model, achieved power on the anaerobic threshold and the produced CO2 had the biggest impact. The obtained discriminatory model correctly classified 91.43% of flat riders, 85.71% of hill riders, while sprinters were classified completely correct (100%), i.e. 92.10% of examinees were correctly classified, which point out the strength of the discriminatory model. Respiratory indicators mostly contribute to the discriminant power of the model, which may significantly contribute to training practice and laboratory tests in future.
Seismic Discrimination

DTIC Science & Technology

1982-09-30

Frequency-wave-number analyses of data from Nevada Test Site (NTS) shots recorded at LASA were computed in the frequency range from 0.01 to 0.05 Hz (Ref...from events in the Soviet Union at a known test site . In order to put further factual basis behind the SP spectral discriminants we used, comparisons...explosion. A catalogue of presumed explosion# in the Soviet Union away from the regular test sites was assembled. A time-domain analysis of seismograms
[The professional responsibility of the factory physician].

PubMed

Tavani, M

1987-01-01

The author briefly reviews the present trends in jurisprudence concerning the professional liability of the physician in penal and civil law and, in the light of the much discussed decree issued by the Court of Cassation (Court of Appeal) (Decree No. 2799/86 - Labour Section), discusses the juridical position of the factory doctor, the juridical relationship between the doctor and the workforce, his contractual obligations, his rôle and his duties. The aspects that are more specifically appropriate to assessment of the professional liability of the factory doctor are described, commenting on the various criteria that may justify, in matters other than industrial accidents, recognition of the existence of an occupational disease.
Cooperative synchronized assemblies enhance orientation discrimination.

PubMed

Samonds, Jason M; Allison, John D; Brown, Heather A; Bonds, A B

2004-04-27

There is no clear link between the broad tuning of single neurons and the fine behavioral capabilities of orientation discrimination. We recorded from populations of cells in the cat visual cortex (area 17) to examine whether the joint activity of cells can support finer discrimination than found in individual responses. Analysis of joint firing yields a substantial advantage (i.e., cooperation) in fine-angle discrimination. This cooperation increases to more considerable levels as the population of an assembly is increased. The cooperation in a population of six cells provides encoding of orientation with an information advantage that is at least 2-fold in terms of requiring either fewer cells or less time than independent coding. This cooperation suggests that correlated or synchronized activity can increase information.
Energy-Discriminative Performance of a Spectral Micro-CT System

PubMed Central

He, Peng; Yu, Hengyong; Bennett, James; Ronaldson, Paul; Zainon, Rafidah; Butler, Anthony; Butler, Phil; Wei, Biao; Wang, Ge

2013-01-01

Experiments were performed to evaluate the energy-discriminative performance of a spectral (multi-energy) micro-CT system. The system, designed by MARS (Medipix All Resolution System) Bio-Imaging Ltd. (Christchurch, New Zealand), employs a photon-counting energy-discriminative detector technology developed by CERN (European Organization for Nuclear Research). We used the K-edge attenuation characteristic of some known materials to calibrate the detector’s photon energy discrimination. For tomographic analysis, we used the compressed sensing (CS) based ordered-subset simultaneous algebraic reconstruction techniques (OS-SART) to reconstruct sample images, which is effective to reduce noise and suppress artifacts. Unlike conventional CT, the principal component analysis (PCA) method can be applied to extract and quantify additional attenuation information from a spectral CT dataset. Our results show that the spectral CT has a good energy-discriminative performance and provides more attenuation information than the conventional CT. PMID:24004864
From gene to structure: The protein factory of the NBICS Centre of Kurchatov Institute

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

Boyko, K. M.; Lipkin, A. V.; Popov, V. O., E-mail: vpopov@inbi.ras.ru

2013-05-15

The Protein Factory was established at the Centre for Nano, Bio, Info, Cognitive, and Social Sciences and Technologies (NBICS Centre) of the National Research Centre 'Kurchatov Institute' in 2010. The Protein Factory, together with the Centre for Synchrotron Radiation and Nanotechnology, promote research on structural biology. This paper presents the technology platforms developed at the Protein Factory and the facilities available for researchers. The main projects currently being performed at the Protein Factory are briefly described.
A situational analysis of HIV/AIDS-related discrimination in Hanoi, Vietnam.

PubMed

Khoat, D V; Hong, L D; An, C Q; Ngu, D; Reidpath, D D

2005-07-01

The laws in Vietnam provide a framework within which one may judge the nature and type of health care-related discrimination to which people living with HIV (PLWHA) are subject. Despite the existence of stringent legislation protecting the rights of PLWHA, this study found that, in practice, PLWHA experienced significant structural discrimination in their daily lives. The discrimination experienced by PLWHA was exacerbated by the fact that, historically, HIV is associated with high-risk, marginalized groups such as drug users and sex workers. In the health care sector, discriminatory practices (for instance, refusal to treat), differential treatment and non-confidentiality were frequent. For the development of successful prevention and treatment strategies, a mutually desirable and equitable balance must be achieved between individual rights and needs and individual obligations to the broader society.
Quantization of liver tissue in dual kVp computed tomography using linear discriminant analysis

NASA Astrophysics Data System (ADS)

Tkaczyk, J. Eric; Langan, David; Wu, Xiaoye; Xu, Daniel; Benson, Thomas; Pack, Jed D.; Schmitz, Andrea; Hara, Amy; Palicek, William; Licato, Paul; Leverentz, Jaynne

2009-02-01

Linear discriminate analysis (LDA) is applied to dual kVp CT and used for tissue characterization. The potential to quantitatively model both malignant and benign, hypo-intense liver lesions is evaluated by analysis of portal-phase, intravenous CT scan data obtained on human patients. Masses with an a priori classification are mapped to a distribution of points in basis material space. The degree of localization of tissue types in the material basis space is related to both quantum noise and real compositional differences. The density maps are analyzed with LDA and studied with system simulations to differentiate these factors. The discriminant analysis is formulated so as to incorporate the known statistical properties of the data. Effective kVp separation and mAs relates to precision of tissue localization. Bias in the material position is related to the degree of X-ray scatter and partial-volume effect. Experimental data and simulations demonstrate that for single energy (HU) imaging or image-based decomposition pixel values of water-like tissues depend on proximity to other iodine-filled bodies. Beam-hardening errors cause a shift in image value on the scale of that difference sought between in cancerous and cystic lessons. In contrast, projection-based decomposition or its equivalent when implemented on a carefully calibrated system can provide accurate data. On such a system, LDA may provide novel quantitative capabilities for tissue characterization in dual energy CT.
[A survey on AIDS discrimination among medical college students].

PubMed

Liu, Jia-hong; Jiang, Hong-ying; Chen, Hong; Liao, Qing-hua; Fu, Jun; Lu, Fei-bao; Liu, Wei-xin; Li, Yue

2009-11-01

To understand the related knowledge, discrimination attitudes toward HIV/AIDS among medical college students, and to provide scientific evidence for further HIV/AIDS anti-discrimination intervention. By means of stratified cluster sampling to classes, 2844 undergraduate students were randomly selected from medical colleges. A self-designed and self-administered questionnaire survey was conducted, and SPSS 13.0 software was used for data analysis. 2501 valid questionnaires had been collected. The overall HIV/AIDS knowledge coverage rate of the respondents was 73.1% (1828/2501); The HIV/AIDS discrimination rates in different questions were varying, the discrimination rate of infected with AIDS by bad sex and sharing needles was 83.1% (2078/2501) and 77.7% (1943/2501) respectively, the discrimination rates in term of contacting with HIV patients and their daily necessities, sharing desks, personal social were all exceeding 40%. The medical students held serious discrimination attitudes to HIV infected persons and patients; it is necessary to strengthen anti-discrimination education about HIV/AIDS among medical students.
Demographic and clinical features related to perceived discrimination in schizophrenia.

PubMed

Fresán, Ana; Robles-García, Rebeca; Madrigal, Eduardo; Tovilla-Zarate, Carlos-Alfonso; Martínez-López, Nicolás; Arango de Montis, Iván

2018-04-01

Perceived discrimination contributes to the development of internalized stigma among those with schizophrenia. Evidence on demographic and clinical factors related to the perception of discrimination among this population is both contradictory and scarce in low- and middle-income countries. Accordingly, the main purpose of this study is to determine the demographic and clinical factors predicting the perception of discrimination among Mexican patients with schizophrenia. Two hundred and seventeen adults with paranoid schizophrenia completed an interview on their demographic status and clinical characteristics. Symptom severity was assessed using the Positive and Negative Syndrome Scale; and perceived discrimination using 13 items from the King's Internalized Stigma Scale. Bivariate linear associations were determined to identify the variables of interest to be included in a linear regression analysis. Years of education, age of illness onset and length of hospitalization were associated with discrimination. However, only age of illness onset and length of hospitalization emerged as predictors of perceived discrimination in the final regression analysis, with longer length of hospitalization being the independent variable with the greatest contribution. Fortunately, this is a modifiable factor regarding the perception of discrimination and self-stigma. Strategies for achieving this as part of community-based mental health care are also discussed. Copyright © 2017 Elsevier B.V. All rights reserved.
Factorial Structure of the French Version of the Rosenberg Self-Esteem Scale among the Elderly

ERIC Educational Resources Information Center

Gana, Kamel; Alaphilippe, Daniel; Bailly, Nathalie

2005-01-01

Ten different confirmatory factor analysis models, including ones with correlated traits correlated methods, correlated traits correlated uniqueness, and correlated traits uncorrelated methods, were proposed to examine the factorial structure of the French version of the Rosenberg Self-Esteem Scale (Rosenberg, 1965). In line with previous studies…
Exposing the dark sector with future Z factories

NASA Astrophysics Data System (ADS)

Liu, Jia; Wang, Lian-Tao; Wang, Xiao-Ping; Xue, Wei

2018-05-01

We investigate the prospects of searching dark sector models via exotic Z -boson decay at future e+e- colliders with Giga Z and Tera Z options. Four general categories of dark sector models, Higgs portal dark matter, vector-portal dark matter, inelastic dark matter, and axionlike particles, are considered. Focusing on channels motivated by the dark sector models, we carry out a model-independent study of the sensitivities of Z factories in probing exotic decays. The limits on branching ratios of the exotic Z decay are typically O (10-6- 10-8.5) for the Giga Z and O (10-7.5- 10-11) for the Tera Z , and they are compared with the projection for the high luminosity LHC. We demonstrate that future Z factories can provide its unique and leading sensitivity and highlight the complementarity with other experiments, including the indirect and direct dark matter search limits and the existing collider limits. Future Z factories will play a leading role in uncovering the hidden sector of the Universe in the future.

Design Learning of Teaching Factory in Mechanical Engineering

NASA Astrophysics Data System (ADS)

Putra, R. C.; Kusumah, I. H.; Komaro, M.; Rahayu, Y.; Asfiyanur, E. P.

2018-02-01

The industrial world that is the target of the process and learning outcomes of vocational high school (SMK) has its own character and nuance. Therefore, vocational education institutions in the learning process should be able to make the appropriate learning approach and in accordance with the industrial world. One approach to learning that is based on production and learning in the world of work is by industry-based learning or known as Teaching Factory, where in this model apply learning that involves direct students in goods or service activities are expected to have the quality so it is worth selling and accepted by consumers. The method used is descriptive approach. The purpose of this research is to get the design of the teaching factory based on the competency requirements of the graduates of the spouse industry, especially in the engineering department. The results of this study is expected to be one of the choice of model factory teaching in the field of machinery engineering in accordance with the products and competencies of the graduates that the industry needs.
Gloss discrimination and eye movements

NASA Astrophysics Data System (ADS)

Phillips, Jonathan B.; Ferwerda, James A.; Nunziata, Ann

2010-02-01

Human observers are able to make fine discriminations of surface gloss. What cues are they using to perform this task? In previous studies, we identified two reflection-related cues-the contrast of the reflected image (c, contrast gloss) and the sharpness of reflected image (d, distinctness-of-image gloss)--but these were for objects rendered in standard dynamic range (SDR) images with compressed highlights. In ongoing work, we are studying the effects of image dynamic range on perceived gloss, comparing high dynamic range (HDR) images with accurate reflections and SDR images with compressed reflections. In this paper, we first present the basic findings of this gloss discrimination study then present an analysis of eye movement recordings that show where observers were looking during the gloss discrimination task. The results indicate that: 1) image dynamic range has significant influence on perceived gloss, with surfaces presented in HDR images being seen as glossier and more discriminable than their SDR counterparts; 2) observers look at both light source highlights and environmental interreflections when judging gloss; and 3) both of these results are modulated by surface geometry and scene illumination.
Uncertainties in Eddy Covariance fluxes due to post-field data processing: a multi-site, full factorial analysis

NASA Astrophysics Data System (ADS)

Sabbatini, S.; Fratini, G.; Arriga, N.; Papale, D.

2012-04-01

Eddy Covariance (EC) is the only technologically available direct method to measure carbon and energy fluxes between ecosystems and atmosphere. However, uncertainties related to this method have not been exhaustively assessed yet, including those deriving from post-field data processing. The latter arise because there is no exact processing sequence established for any given situation, and the sequence itself is long and complex, with many processing steps and options available. However, the consistency and inter-comparability of flux estimates may be largely affected by the adoption of different processing sequences. The goal of our work is to quantify the uncertainty introduced in each processing step by the fact that different options are available, and to study how the overall uncertainty propagates throughout the processing sequence. We propose an easy-to-use methodology to assign a confidence level to the calculated fluxes of energy and mass, based on the adopted processing sequence, and on available information such as the EC system type (e.g. open vs. closed path), the climate and the ecosystem type. The proposed methodology synthesizes the results of a massive full-factorial experiment. We use one year of raw data from 15 European flux stations and process them so as to cover all possible combinations of the available options across a selection of the most relevant processing steps. The 15 sites have been selected to be representative of different ecosystems (forests, croplands and grasslands), climates (mediterranean, nordic, arid and humid) and instrumental setup (e.g. open vs. closed path). The software used for this analysis is EddyPro™ 3.0 (www.licor.com/eddypro). The critical processing steps, selected on the basis of the different options commonly used in the FLUXNET community, are: angle of attack correction; coordinate rotation; trend removal; time lag compensation; low- and high- frequency spectral correction; correction for air density
A comparison of two follow-up analyses after multiple analysis of variance, analysis of variance, and descriptive discriminant analysis: A case study of the program effects on education-abroad programs

Treesearch

Alvin H. Yu; Garry Chick

2010-01-01

This study compared the utility of two different post-hoc tests after detecting significant differences within factors on multiple dependent variables using multivariate analysis of variance (MANOVA). We compared the univariate F test (the ScheffÃ© method) to descriptive discriminant analysis (DDA) using an educational-tour survey of university study-...
Discrimination of three genetically close Aspergillus species by using high resolution melting analysis applied to indoor air as case study.

PubMed

Libert, Xavier; Packeu, Ann; Bureau, Fabrice; Roosens, Nancy H; De Keersmaecker, Sigrid C J

2017-04-04

Indoor air pollution caused by fungal contamination is suspected to have a public health impact. Monitoring of the composition of the indoor airborne fungal contaminants is therefore important. To avoid problems linked to culture-dependent protocols, molecular methods are increasingly being proposed as an alternative. Among these molecular methods, the polymerase chain reaction (PCR) and the real-time PCR are the most frequently used tools for indoor fungal detection. However, even if these tools have demonstrated their appropriate performance, some of them are not able to discriminate between species which are genetically close. A solution to this could be the use of a post-qPCR high resolution melting (HRM) analysis, which would allow the discrimination of these species based on the highly accurate determination of the difference in melting temperature of the obtained amplicon. In this study, we provide a proof-of-concept for this approach, using a dye adapted version of our previously developed qPCR SYBR®Green method to detect Aspergillus versicolor in indoor air, an important airborne fungus in terms of occurrence and cause of health problems. Despite the good performance observed for that qPCR method, no discrimination could previously be made between A. versicolor, Aspergillus creber and Aspergillus sydowii. In this study, we developed and evaluated an HRM assay for the discrimination between A. versicolor, Aspergillus creber and Aspergillus sydowii. Using HRM analysis, the discrimination of the 3 Aspergillus species could be made. No false positive, nor false negatives were observed during the performance assessment including 20 strains of Aspergillus. The limit of detection was determined for each species i.e., 0.5 pg of gDNA for A. creber and A. sydowii, and 0.1 pg of gDNA for A. versicolor. The HRM analysis was also successfully tested on environmental samples. We reported the development of HRM tools for the discrimination of A. versicolor, A. creber
Classification of electroencephalograph signals using time-frequency decomposition and linear discriminant analysis

NASA Astrophysics Data System (ADS)

Szuflitowska, B.; Orlowski, P.

2017-08-01

Automated detection system consists of two key steps: extraction of features from EEG signals and classification for detection of pathology activity. The EEG sequences were analyzed using Short-Time Fourier Transform and the classification was performed using Linear Discriminant Analysis. The accuracy of the technique was tested on three sets of EEG signals: epilepsy, healthy and Alzheimer's Disease. The classification error below 10% has been considered a success. The higher accuracy are obtained for new data of unknown classes than testing data. The methodology can be helpful in differentiation epilepsy seizure and disturbances in the EEG signal in Alzheimer's Disease.
Estimating the causes of traffic accidents using logistic regression and discriminant analysis.

PubMed

Karacasu, Murat; Ergül, Barış; Altin Yavuz, Arzu

2014-01-01

Factors that affect traffic accidents have been analysed in various ways. In this study, we use the methods of logistic regression and discriminant analysis to determine the damages due to injury and non-injury accidents in the Eskisehir Province. Data were obtained from the accident reports of the General Directorate of Security in Eskisehir; 2552 traffic accidents between January and December 2009 were investigated regarding whether they resulted in injury. According to the results, the effects of traffic accidents were reflected in the variables. These results provide a wealth of information that may aid future measures toward the prevention of undesired results.
Combining 1D and 2D linear discriminant analysis for palmprint recognition

NASA Astrophysics Data System (ADS)

Zhang, Jian; Ji, Hongbing; Wang, Lei; Lin, Lin

2011-11-01

In this paper, a novel feature extraction method for palmprint recognition termed as Two-dimensional Combined Discriminant Analysis (2DCDA) is proposed. By connecting the adjacent rows of a image sequentially, the obtained new covariance matrices contain the useful information among local geometry structures in the image, which is eliminated by 2DLDA. In this way, 2DCDA combines LDA and 2DLDA for a promising recognition accuracy, but the number of coefficients of its projection matrix is lower than that of other two-dimensional methods. Experimental results on the CASIA palmprint database demonstrate the effectiveness of the proposed method.
Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis.

PubMed

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-06-01

Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens.
Discrimination of irradiated MOX fuel from UOX fuel by multivariate statistical analysis of simulated activities of gamma-emitting isotopes

NASA Astrophysics Data System (ADS)

Åberg Lindell, M.; Andersson, P.; Grape, S.; Hellesen, C.; Håkansson, A.; Thulin, M.

2018-03-01

This paper investigates how concentrations of certain fission products and their related gamma-ray emissions can be used to discriminate between uranium oxide (UOX) and mixed oxide (MOX) type fuel. Discrimination of irradiated MOX fuel from irradiated UOX fuel is important in nuclear facilities and for transport of nuclear fuel, for purposes of both criticality safety and nuclear safeguards. Although facility operators keep records on the identity and properties of each fuel, tools for nuclear safeguards inspectors that enable independent verification of the fuel are critical in the recovery of continuity of knowledge, should it be lost. A discrimination methodology for classification of UOX and MOX fuel, based on passive gamma-ray spectroscopy data and multivariate analysis methods, is presented. Nuclear fuels and their gamma-ray emissions were simulated in the Monte Carlo code Serpent, and the resulting data was used as input to train seven different multivariate classification techniques. The trained classifiers were subsequently implemented and evaluated with respect to their capabilities to correctly predict the classes of unknown fuel items. The best results concerning successful discrimination of UOX and MOX-fuel were acquired when using non-linear classification techniques, such as the k nearest neighbors method and the Gaussian kernel support vector machine. For fuel with cooling times up to 20 years, when it is considered that gamma-rays from the isotope 134Cs can still be efficiently measured, success rates of 100% were obtained. A sensitivity analysis indicated that these methods were also robust.
Virtual Factory Framework for Supporting Production Planning and Control.

PubMed

Kibira, Deogratias; Shao, Guodong

2017-01-01

Developing optimal production plans for smart manufacturing systems is challenging because shop floor events change dynamically. A virtual factory incorporating engineering tools, simulation, and optimization generates and communicates performance data to guide wise decision making for different control levels. This paper describes such a platform specifically for production planning. We also discuss verification and validation of the constituent models. A case study of a machine shop is used to demonstrate data generation for production planning in a virtual factory.
Continuous glucose monitoring in subcutaneous tissue using factory-calibrated sensors: a pilot study.

PubMed

Hoss, Udo; Jeddi, Iman; Schulz, Mark; Budiman, Erwin; Bhogal, Claire; McGarraugh, Geoffrey

2010-08-01

Commercial continuous subcutaneous glucose monitors require in vivo calibration using capillary blood glucose tests. Feasibility of factory calibration, i.e., sensor batch characterization in vitro with no further need for in vivo calibration, requires a predictable and stable in vivo sensor sensitivity and limited inter- and intra-subject variation of the ratio of interstitial to blood glucose concentration. Twelve volunteers wore two FreeStyle Navigator (Abbott Diabetes Care, Alameda, CA) continuous glucose monitoring systems for 5 days in parallel for two consecutive sensor wears (four sensors per subject, 48 sensors total). Sensors from a prototype sensor lot with a low variability in glucose sensitivity were used for the study. Median sensor sensitivity values based on capillary blood glucose were calculated per sensor and compared for inter- and intra-subject variation. Mean absolute relative difference (MARD) calculation and error grid analysis were performed using a single calibration factor for all sensors to simulate factory calibration and compared to standard fingerstick calibration. Sensor sensitivity variation in vitro was 4.6%, which increased to 8.3% in vivo (P < 0.0001). Analysis of variance revealed no significant inter-subject differences in sensor sensitivity (P = 0.134). Applying a single universal calibration factor retrospectively to all sensors resulted in a MARD of 10.4% and 88.1% of values in Clarke Error Grid Zone A, compared to a MARD of 10.9% and 86% of values in Error Grid Zone A for fingerstick calibration. Factory calibration of sensors for continuous subcutaneous glucose monitoring is feasible with similar accuracy to standard fingerstick calibration. Additional data are required to confirm this result in subjects with diabetes.
Industrial Technology Modernization Program. Project 32. Factory Vision. Phase 2

DTIC Science & Technology

1988-04-01

instructions for the PWA’s, generating the numerical control (NC) program instructions for factory assembly equipment, controlling the process... generating the numerical control (NC) program instructions for factory assembly equipment, controlling the production process instructions and NC... Assembly Operations the "Create Production Process Program" will automatically generate a sequence of graphics pages (in paper mode), or graphics screens
A Factorial Analysis Study on Enzymatic Hydrolysis of Fiber Pressed Oil Palm Frond for Bioethanol Production

NASA Astrophysics Data System (ADS)

Hashim, F. S.; Yussof, H. W.; Zahari, M. A. K. M.; Illias, R. M.; Rahman, R. A.

2016-03-01

Different technologies have been developed to for the conversion of lignocellulosic biomass to suitable fermentation substrates for bioethanol production. The enzymatic conversion of cellulose seems to be the most promising technology as it is highly specific and does not produce substantial amounts of unwanted byproducts. The effects of agitation speed, enzyme loading, temperature, pH and reaction time on the conversion of glucose from fiber pressed oil palm frond (FPOPF) for bioethanol production were screened by statistical analysis using response surface methodology (RSM). A half fraction two-level factorial analysis with five factors was selected for the experimental design to determine the best enzymatic conditions that produce maximum amount of glucose. FPOPF was pre-treated with alkaline prior to enzymatic hydrolysis. The enzymatic hydrolysis was performed using a commercial enzyme Cellic CTec2. From this study, the highest yield of glucose concentration was 9.736 g/L at 72 hours reaction time at 35 °C, pH 5.6, and 1.5% (w/v) of enzyme loading. The model obtained was significant with p-value <0.0001. It is suggested that this model had a maximum point which is likely to be the optimum point and possible for the optimization process.
A Survey of the Medical Needs of a Group of Small Factories*

PubMed Central

Lee, W. R.

1962-01-01

The present interest in medical services for small factories is matched by the limited objective information which is available on the demand for and needs of such services. As a teaching project, a survey was made of factories with between 30 and 200 employees on an estate in the North West where there was no organized medical service. Unfortunately, time allowed only 22 factories to be visited. The findings, therefore, are regarded as indicative rather than conclusive, but this does not detract from their interest. Factories were visited by two or three postgraduate students who completed a questionnaire designed to standardize their findings. The questionnaire is included as an appendix to this paper. Regarding the demand for medical services, four of the 22 factories were subsidiaries of larger organizations and had part-time medical advice, 14 expressed no interest even if this would have involved no financial commitment, and the remaining four were interested for differing reasons. The needs of the factories in this context were found to be, first, advice and perhaps better supervision of non-mechanical hazards and, secondly, supervision of the first aid arrangements. From the ambulance journey records of the local authority there appeared to be no great demand for local casualty facilities. To meet these needs it is suggested that the functions of the appointed factory doctor might be modified to include wider supervision of non-mechanical hazards and supervision of first aid arrangements. It is also suggested that the National Health Service should form the basis for dealing with those cases requiring more than first aid. PMID:14463582
Factorial versus Typological Models: A Comparison of Methods for Personality Data

ERIC Educational Resources Information Center

von Davier, Matthias; Naemi, Bobby; Roberts, Richard D.

2012-01-01

This article describes an exploration of the distinction between typological and factorial latent variables in the domain of personality theory. Traditionally, many personality variables have been considered to be factorial in nature, even though there are examples of typological constructs dating back to Hippocrates. Recently, some…
Sexual behavior and perceived risk of HIV/AIDS among young migrant factory workers in Nepal.

PubMed

Puri, M; Cleland, J

2006-03-01

To analyze the sexual behavior, perceived risk of contracting STIs and HIV/AIDS, and protective behaviors of migrant workers aged 14-19 years in carpet and garment factories in the Kathmandu Valley, Nepal. A common assumption in Nepal is that young migrant workers experience an increase in vulnerability. Moving away from the social controls of family and community, they become exposed to a mixed-gender environment and therefore might initiate sex earlier or have more casual encounters than might otherwise be the case. The analysis is based on a representative sample survey of 1050 factory workers. Information was also obtained from 23 in-depth case histories. Both bivarite and multivariate techniques were applied to identify the factors associated with involvement in risky sexual behavior. Despite religious and cultural restrictions, one in five boys and one in eight unmarried girls reported experience of sexual intercourse. Early sexual experimentation, multiple partners, and low and irregular use of condoms are not uncommon. Instances of sexual exploitation by factory owners or managers were documented but were rare. Most nonregular sex partners were described as friends from the same factory or community. Despite high-risk behavior, relatively few young people considered themselves to be at risk of getting STIs or HIV/AIDS. Information on the possible consequences of unsafe sex is inadequate. Programs aimed at promotion of safer sex practices and life skill training that facilitates communication and utilization of sexual health services should target vulnerable migrant young people.
Tracing the contamination origin of coliform bacteria in two small food-processing factories.

PubMed

Tominaga, Tatsuya; Sekine, Masahiro; Oyaizu, Hiroshi

2008-09-01

The objective of this study was to trace contamination sources of coliform bacteria by comparing the types of coliforms between food samples and the processing environments in two small food-processing factories (factories A and B). Fermentation tests of five sugars enabled the successful classification of 16 representative type strains into eight distinct groups. The grouping procedure was then applied to comparison of the coliform flora between food products and various locations in their processing environments. The consistency between each food and the tested locations was evaluated using the Jaccard index. The air conditioner and refrigeration room floor in factory A showed an index of 1.00, while the shaping machine in factory B showed an index of 0.98, indicating that these locations could be contamination sources. The validity of our results was confirmed by randomly amplified polymorphic DNA, which showed 100% matched profiles between the air conditioner and the food in factory A, and highly matched profiles between the machine and the food in factory B. This method for comparing the coliform flora between food and environments has the potential to be a reliable tracing tool for various food industries.
Indoor air pollution evaluation with emphasize on HDI and biological assessment of HDA in the polyurethane factories.

PubMed

Mirmohammadi, Mirtaghi; Hakimi Ibrahim, M; Ahmad, Anees; Kadir, Mohd Omar Abdul; Mohammadyan, M; Mirashrafi, S B

2010-06-01

Today, many raw materials used in factories may have a dangerous effect on the physiological system of workers. One of them which is widely used in the polyurethane factories is diisocyanates. These compounds are widely used in surface coatings, polyurethane foams, adhesives, resins, elastomers, binders, and sealants. Exposure to diisocyanates causes irritation to the skin, mucous membranes, eyes, and respiratory tract. Hexamethylene diamine (HDA) is metabolite of hexamethylene diisocyanate (HDI). It is an excretory material by worker's urine who is exposed to HDI. Around 100 air samples were collected from five defined factories by midget impinger which contained dimethyl sulfoxide absorbent as a solvent and tryptamine as reagent. Samples were analyzed by high-performance liquid chromatography with EC\\UV detector using NIOSH 5522 method of sampling. Also, 50 urine samples collected from workers were also analyzed using William's biological analysis method. The concentration of HDI into all air samples were more than 88 microg/m(3), and they have shown high concentration of pollutant in the workplaces in comparison with NIOSH standard, and all of the workers' urine were contaminated by HDA. The correlation and regression test were used to obtain statistical model for HDI and HDA, which is useful for the prediction of diisocyanates pollution situation in the polyurethane factories.
n-Hexane polyneuropathy in a ball-manufacturing factory

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

Huang, C.C.; Shih, T.S.; Cheng, S.Y.

Five overt and two occult cases of n-hexane polyneuropathy occurred in a ball-manufacturing factory in Taiwan. The severity of polyneuropathy was directly related to the index of n-hexane exposure that occurred during the processes of cement coating and nylon fiber winding in a poorly ventilated room. The n-hexane concentrations over eight hours of personal sampling of the air of the cement coating and nylon fiber winding areas were 109 ppm and 86 ppm, respectively. After installation of a new factory ventilation system, these seven patients recovered completely, and there were no new cases in the two-year follow-up.

Metabolic modelling in the development of cell factories by synthetic biology

PubMed Central

Jouhten, Paula

2012-01-01

Cell factories are commonly microbial organisms utilized for bioconversion of renewable resources to bulk or high value chemicals. Introduction of novel production pathways in chassis strains is the core of the development of cell factories by synthetic biology. Synthetic biology aims to create novel biological functions and systems not found in nature by combining biology with engineering. The workflow of the development of novel cell factories with synthetic biology is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow. In this minireview, the role of metabolic modelling in synthetic biology will be discussed with a review of current status of compatible methods and models for the in silico design and quantitative evaluation of a cell factory. PMID:24688669
Correlations and fluctuations: Generalized factorial moments

NASA Astrophysics Data System (ADS)

Bialas, A.

2007-02-01

A systematic study of the relations between fluctuations of the extensive multiparticle variables and integrals of the inclusive multiparticle densities is presented. The generalized factorial moments are introduced and their physical meaning discussed. The effects of the additive conservation laws are analyzed.
A Novel Graph Constructor for Semisupervised Discriminant Analysis: Combined Low-Rank and k-Nearest Neighbor Graph

PubMed Central

Pan, Yongke; Niu, Wenjia

2017-01-01

Semisupervised Discriminant Analysis (SDA) is a semisupervised dimensionality reduction algorithm, which can easily resolve the out-of-sample problem. Relative works usually focus on the geometric relationships of data points, which are not obvious, to enhance the performance of SDA. Different from these relative works, the regularized graph construction is researched here, which is important in the graph-based semisupervised learning methods. In this paper, we propose a novel graph for Semisupervised Discriminant Analysis, which is called combined low-rank and k-nearest neighbor (LRKNN) graph. In our LRKNN graph, we map the data to the LR feature space and then the kNN is adopted to satisfy the algorithmic requirements of SDA. Since the low-rank representation can capture the global structure and the k-nearest neighbor algorithm can maximally preserve the local geometrical structure of the data, the LRKNN graph can significantly improve the performance of SDA. Extensive experiments on several real-world databases show that the proposed LRKNN graph is an efficient graph constructor, which can largely outperform other commonly used baselines. PMID:28316616
Discrimination and subjective well-being: protective influences of membership in a discriminated category.

PubMed

Hnilica, Karel

2011-03-01

Research reveals that discrimination has harmful effects on health and quality of life. Among the most frequent types of discrimination pertains gender and age discrimination. Research results show that discriminatory behaviours based on gender afflict predominantly women; age discrimination afflicts mainly older adults. At the same time, it has been found that members of these traditionally discriminated categories often use strategies that mitigate the effects of discrimination. Discrimination will have detrimental effects on subjective well-being. But its effects will be most harmful for persons who are not members of the traditionally discriminated categories. These hypotheses were tested on data from three waves of the European Social Survey that the Czech Republic also participated in. Data were analyzed in a series of multilevel random coefficients regression analyses with respondents nested within states and states nested within years of study. Both perceived gender discrimination and perceived age discrimination have negative effects on subjective well-being. However, gender discrimination had more harmful effects on the subjective well-being of men than women and age discrimination had the most harmful effects on the subjective well-being of people in their middle ages, not the elderly ones. Discrimination does not need to have most harmful effects on the quality of life of members of the categories that are discriminated against most often.
An examination of the factorial and convergent validity of four measures of conspiracist ideation, with recommendations for researchers.

PubMed

Swami, Viren; Barron, David; Weis, Laura; Voracek, Martin; Stieger, Stefan; Furnham, Adrian

2017-01-01

A number scales have been developed to measure conspiracist ideation, but little attention has been paid to the factorial validity of these scales. We reassessed the psychometric properties of four widely-used scales, namely the Belief in Conspiracy Theories Inventory (BCTI), the Conspiracy Mentality Questionnaire (CMQ), the Generic Conspiracist Beliefs Scale (GCBS), and the One-Item Conspiracy Measure (OICM). Eight-hundred-and-three U.S. adults completed all measures, along with measures of endorsement of 9/11 and anti-vaccination conspiracy theories. Through both exploratory and confirmatory factor analysis, we found that only the BCTI had acceptable factorial validity. We failed to confirm the factor structures of the CMQ and the GBCS, suggesting these measures had poor factorial validity. Indices of convergent validity were acceptable for the BCTI, but weaker for the other measures. Based on these findings, we provide suggestions for the future refinement in the measurement of conspiracist ideation.
Identification of Medicinal Mugua Origin by Near Infrared Spectroscopy Combined with Partial Least-squares Discriminant Analysis.

PubMed

Han, Bangxing; Peng, Huasheng; Yan, Hui

2016-01-01

Mugua is a common Chinese herbal medicine. There are three main medicinal origin places in China, Xuancheng City Anhui Province, Qijiang District Chongqing City, Yichang City, Hubei Province, and suitable for food origin places Linyi City Shandong Province. To construct a qualitative analytical method to identify the origin of medicinal Mugua by near infrared spectroscopy (NIRS). Partial least squares discriminant analysis (PLSDA) model was established after the Mugua derived from five different origins were preprocessed by the original spectrum. Moreover, the hierarchical cluster analysis was performed. The result showed that PLSDA model was established. According to the relationship of the origins-related important score and wavenumber, and K-mean cluster analysis, the Muguas derived from different origins were effectively identified. NIRS technology can quickly and accurately identify the origin of Mugua, provide a new method and technology for the identification of Chinese medicinal materials. After preprocessed by D1+autoscale, more peaks were increased in the preprocessed Mugua in the near infrared spectrumFive latent variable scores could reflect the information related to the origin place of MuguaOrigins of Mugua were well-distinguished according to K. mean value clustering analysis. Abbreviations used: TCM: Traditional Chinese Medicine, NIRS: Near infrared spectroscopy, SG: Savitzky-Golay smoothness, D1: First derivative, D2: Second derivative, SNV: Standard normal variable transformation, MSC: Multiplicative scatter correction, PLSDA: Partial least squares discriminant analysis, LV: Latent variable, VIP scores: Important score.
Actual curriculum development practices instrument: Testing for factorial validity

NASA Astrophysics Data System (ADS)

Foi, Liew Yon; Bakar, Kamariah Abu; Hamzah, Mohd Sahandri Gani; Alwi, Nor Hayati

2014-09-01

The Actual Curriculum Development Practices Instrument (ACDP-I) was developed and the factorial validity of the ACDP-I was tested (n = 107) using exploratory factor analysis procedures in the earlier work of [1]. Despite the ACDP-I appears to be content and construct valid instrument with very high internal reliability qualities for using in Malaysia, the accumulated evidences are still needed to provide a sound scientific basis for the proposed score interpretations. Therefore, the present study addresses this concern by utilising the confirmatory factor analysis to further confirm the theoretical structure of the variable Actual Curriculum Development Practices (ACDP) and enrich the psychometrical properties of ACDP-I. Results of this study have practical implication to both researchers and educators whose concerns focus on teachers' classroom practices and the instrument development and validation process.
Discrimination of Closely-Spaced Geosynchronous Satellites - Phase Curve Analysis & New Small Business Innovative Research (SBIR) Efforts

DTIC Science & Technology

2010-09-01

Discrimination of Closely-Spaced Geosynchronous Satellites – Phase Curve Analysis & New Small Business Innovative Research (SBIR) Efforts...such objects from one time epoch to another showcases the deficiencies in associating individual objects before and after the configuration change...1]) have emphasized examples of multiple satellites occupying the same geosynchronous slot, with individual satellites maneuvering about one another
Kernel PLS-SVC for Linear and Nonlinear Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Trejo, Leonard J.; Matthews, Bryan

2003-01-01

A new methodology for discrimination is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by support vector machines for classification. Close connection of orthonormalized PLS and Fisher's approach to linear discrimination or equivalently with canonical correlation analysis is described. This gives preference to use orthonormalized PLS over principal component analysis. Good behavior of the proposed method is demonstrated on 13 different benchmark data sets and on the real world problem of the classification finger movement periods versus non-movement periods based on electroencephalogram.
Workplace discrimination and health among Filipinos in the United States.

PubMed

de Castro, Arnold B; Gee, Gilbert C; Takeuchi, David T

2008-03-01

We examined the association between work discrimination and morbidity among Filipinos in the United States, independent of more-global measures of discrimination. Data were collected from the Filipino American Community Epidemiological Survey. Our analysis focused on 1652 participants who were employed at the time of data collection, and we used negative binomial regression to determine the association between work discrimination and health conditions. The report of workplace discrimination specific to being Filipino was associated with an increased number of health conditions. This association persisted even after we controlled for everyday discrimination, a general assessment of discrimination; job concerns, a general assessment of unpleasant work circumstances; having immigrated for employment reasons; job category; income; education; gender; and other sociodemographic factors. Racial discrimination in the workplace was positively associated with poor health among Filipino Americans after we controlled for reports of everyday discrimination and general concerns about one's job. This finding shows the importance of considering the work setting as a source of discrimination and its effect on morbidity among racial minorities.
Workplace Discrimination and Health Among Filipinos in the United States

PubMed Central

de Castro, Arnold B.; Gee, Gilbert C.; Takeuchi, David T.

2008-01-01

Objectives. We examined the association between work discrimination and morbidity among Filipinos in the United States, independent of more-global measures of discrimination. Methods. Data were collected from the Filipino American Community Epidemiological Survey. Our analysis focused on 1652 participants who were employed at the time of data collection, and we used negative binomial regression to determine the association between work discrimination and health conditions. Results. The report of workplace discrimination specific to being Filipino was associated with an increased number of health conditions. This association persisted even after we controlled for everyday discrimination, a general assessment of discrimination; job concerns, a general assessment of unpleasant work circumstances; having immigrated for employment reasons; job category; income; education; gender; and other sociodemographic factors. Conclusions. Racial discrimination in the workplace was positively associated with poor health among Filipino Americans after we controlled for reports of everyday discrimination and general concerns about one’s job. This finding shows the importance of considering the work setting as a source of discrimination and its effect on morbidity among racial minorities. PMID:18235069
Technology and Participation in Japanese Factories: The Consequences for Morale and Productivity.

ERIC Educational Resources Information Center

Hull, Frank; Azumi, Koya

1988-01-01

By fully using their human resources, Japanese factories mass produce goods of low cost and high quality. Participation in Japanese factories occurs in a more hierarchical framework than advocated in the Western model of worker democracy. (JOW)
Taxonomic discrimination of higher plants by pyrolysis mass spectrometry.

PubMed

Kim, S W; Ban, S H; Chung, H J; Choi, D W; Choi, P S; Yoo, O J; Liu, J R

2004-02-01

Pyrolysis mass spectrometry (PyMS) is a rapid, simple, high-resolution analytical method based on thermal degradation of complex material in a vacuum and has been widely applied to the discrimination of closely related microbial strains. Leaf samples of six species and one variety of higher plants (Rosa multiflora, R. multiflora var. platyphylla, Sedum kamtschaticum, S. takesimense, S. sarmentosum, Hepatica insularis, and H. asiatica) were subjected to PyMS for spectral fingerprinting. Principal component analysis of PyMS data was not able to discriminate these plants in discrete clusters. However, canonical variate analysis of PyMS data separated these plants from one another. A hierarchical dendrogram based on canonical variate analysis was in agreement with the known taxonomy of the plants at the variety level. These results indicate that PyMS is able to discriminate higher plants based on taxonomic classification at the family, genus, species, and variety level.
Impact of HIV/AIDS on labor productivity in Akaki fiber products factory, Ethiopia.

PubMed

Omer, Endashaw M; Mariam, Damen Haile

2008-04-01

HIV/AIDS has become a full-blown development crisis affecting all sectors of the economy in most developing countries. Its social and economic consequences are felt widely not only in health but in education, industry, agriculture as well as transport. The study attempted to estimate the changes in worker's output and attendance associated with advancing HIV infection, and direct costs incurred by a fiber products factory due to illness and death related to HIV/AIDS. The study is a retrospective cohort with accounting method of cost estimation. The study subjects were factory workers enrolled in a cohort study of HIV incidence and progression in Akaki, Ethiopia since February 1997. The mean incentive earnings were not significantly different between HIV positives and negatives at baseline (in 1997). However, in the following years (1998, 1999 and 2000) the incentive earnings of HIV positives were significantly lower than the incentive earnings of HIV negatives. Trend analysis showed that advancing HIV infection, as measured by drop in CD4 count and increasing viral load, is associated with reduction in productivity and increased sick leave days. The study has shown that there is a direct negative impact of HIV infection on the productivity of factory workers and recommends institution of ART centers and programs in work places to mitigate the socio economic impact of the pandemic.
High concentrations of heavy metals in PM from ceramic factories of Southern Spain

NASA Astrophysics Data System (ADS)

Sánchez de la Campa, Ana M.; de la Rosa, Jesús D.; González-Castanedo, Yolanda; Fernández-Camacho, Rocío; Alastuey, Andrés; Querol, Xavier; Pio, Casimiro

2010-06-01

In this study, physicochemical characterization of Atmospheric Particulate Matter (PM) was performed in an urban-industrial site background (Bailén, Southern Spain), highly influenced by the impact of emission plumes from ceramic factories. This area is considered one of the towns with the highest PM 10 levels and average SO 2 concentration in Spain. A three stages methodology was used: 1) real-time measurements of levels of PM 10 and gaseous pollutants, and sampling of PM; 2) chemical characterization using ICP-MS, ICP-OES, CI and TOT, and source apportionment analysis (receptor modelling) of PM; and 3) chemical characterization of emission plumes derived from representative factories. High ambient air concentrations were found for most major components and trace elements compared with other industrialized towns in Spain. V and Ni are considered fingerprints of PM derived from the emissions of brick factories in this area, and were shown to be of particular interest. This highlights the high V and Ni concentrations in PM 10 (122 ngV/m 3 and 23.4 ngNi/m 3), with Ni exceeding the 2013 annual target value for the European Directive 2004/107/EC (20 ng/m 3). The methodology of this work can be used by Government departments responsible for Environment and Epidemiology in planning control strategies for improving air quality.
Membership-degree preserving discriminant analysis with applications to face recognition.

PubMed

Yang, Zhangjing; Liu, Chuancai; Huang, Pu; Qian, Jianjun

2013-01-01

In pattern recognition, feature extraction techniques have been widely employed to reduce the dimensionality of high-dimensional data. In this paper, we propose a novel feature extraction algorithm called membership-degree preserving discriminant analysis (MPDA) based on the fisher criterion and fuzzy set theory for face recognition. In the proposed algorithm, the membership degree of each sample to particular classes is firstly calculated by the fuzzy k-nearest neighbor (FKNN) algorithm to characterize the similarity between each sample and class centers, and then the membership degree is incorporated into the definition of the between-class scatter and the within-class scatter. The feature extraction criterion via maximizing the ratio of the between-class scatter to the within-class scatter is applied. Experimental results on the ORL, Yale, and FERET face databases demonstrate the effectiveness of the proposed algorithm.
Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis

PubMed Central

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-01-01

Abstract. Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens. PMID:26057029
Religious Discrimination Discourse in the Mono-Cultural School: The Case of Poland

ERIC Educational Resources Information Center

Anczyk, Adam; Grzymala-Moszczynska, Joanna

2018-01-01

The article forms an analysis of the religious discrimination discourse in Polish public schools, with special attention paid to the culturally specific, Polish understanding of the notion of religious discrimination. The introductory part presents the concept of religious discrimination as present in anti-discriminatory policies. The following…
Burnout Factories: The Challenge of Retaining Great Teachers in Charter Schools

ERIC Educational Resources Information Center

Fusco, Mark

2017-01-01

In its well-intentioned effort to create alternatives to public school dropout factories, the charter school sector has created teacher burnout factories. But it does not have to be this way. Charter schools can continue to maintain high standards while creating a more sustainable work environment for teachers. This article examines the teacher…
Discriminative analysis of non-linear brain connectivity for leukoaraiosis with resting-state fMRI

NASA Astrophysics Data System (ADS)

Lai, Youzhi; Xu, Lele; Yao, Li; Wu, Xia

2015-03-01

Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.

Neural networks using broadband spectral discriminators reduces illumination required for broccoli identification in weedy fields

NASA Astrophysics Data System (ADS)

Hahn, Federico

1996-03-01

Statistical discriminative analysis and neural networks were used to prove that crop/weed/soil discrimination by optical reflectance was feasible. The wavelengths selected as inputs on those neural networks were ten nanometers width, reducing the total collected radiation for the sensor. Spectral data collected from several farms having different weed populations were introduced to discriminant analysis. The best discriminant wavelengths were used to build a wavelength histogram which selected the three best spectral broadbands for broccoli/weed/soil discrimination. The broadbands were analyzed using a new single broadband discriminator index named the discriminative integration index, DII, and the DII values obtained were used to train a neural network. This paper introduces the index concept, its results and its use for minimizing artificial lightning requirements with broadband spectral measurements for broccoli/weed/soil discrimination.
Component-based subspace linear discriminant analysis method for face recognition with one training sample

NASA Astrophysics Data System (ADS)

Huang, Jian; Yuen, Pong C.; Chen, Wen-Sheng; Lai, J. H.

2005-05-01

Many face recognition algorithms/systems have been developed in the last decade and excellent performances have also been reported when there is a sufficient number of representative training samples. In many real-life applications such as passport identification, only one well-controlled frontal sample image is available for training. Under this situation, the performance of existing algorithms will degrade dramatically or may not even be implemented. We propose a component-based linear discriminant analysis (LDA) method to solve the one training sample problem. The basic idea of the proposed method is to construct local facial feature component bunches by moving each local feature region in four directions. In this way, we not only generate more samples with lower dimension than the original image, but also consider the face detection localization error while training. After that, we propose a subspace LDA method, which is tailor-made for a small number of training samples, for the local feature projection to maximize the discrimination power. Theoretical analysis and experiment results show that our proposed subspace LDA is efficient and overcomes the limitations in existing LDA methods. Finally, we combine the contributions of each local component bunch with a weighted combination scheme to draw the recognition decision. A FERET database is used for evaluating the proposed method and results are encouraging.
Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

NASA Astrophysics Data System (ADS)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.
[The homogeneity of a population of yeasts from Camembert cheeses].

PubMed

Schmidt, J L; Daudin, J J

1983-01-01

Yeasts are found to a large extent in cheeses, more particularly in soft cheeses such as Camembert. The proximity between two species previously identified by standard methods was studied using a factorial discriminant analysis on 326 strains. Twenty-three fermentation and assimilation tests (discriminant variables) gave a fairly good discrimination between species. This treatment has allowed us to confirm the present tendencies noticed in yeast classification and has also enabled us to group some of the species.
An examination of the factorial and convergent validity of four measures of conspiracist ideation, with recommendations for researchers

PubMed Central

Swami, Viren; Barron, David; Weis, Laura; Voracek, Martin; Stieger, Stefan; Furnham, Adrian

2017-01-01

A number scales have been developed to measure conspiracist ideation, but little attention has been paid to the factorial validity of these scales. We reassessed the psychometric properties of four widely-used scales, namely the Belief in Conspiracy Theories Inventory (BCTI), the Conspiracy Mentality Questionnaire (CMQ), the Generic Conspiracist Beliefs Scale (GCBS), and the One-Item Conspiracy Measure (OICM). Eight-hundred-and-three U.S. adults completed all measures, along with measures of endorsement of 9/11 and anti-vaccination conspiracy theories. Through both exploratory and confirmatory factor analysis, we found that only the BCTI had acceptable factorial validity. We failed to confirm the factor structures of the CMQ and the GBCS, suggesting these measures had poor factorial validity. Indices of convergent validity were acceptable for the BCTI, but weaker for the other measures. Based on these findings, we provide suggestions for the future refinement in the measurement of conspiracist ideation. PMID:28231266
An Application of Fractional Factorial Designs to Study Drug Combinations

PubMed Central

Jaynes, Jessica; Ding, Xianting; Xu, Hongquan; Wong, Weng Kee; Ho, Chih-Ming

2013-01-01

Herpes simplex virus type 1 (HSV-1) is known to cause diseases of various severities. There is increasing interest to find drug combinations to treat HSV-1 by reducing drug resistance and cytotoxicity. Drug combinations offer potentially higher efficacy and lower individual drug dosage. In this paper, we report a new application of fractional factorial designs to investigate a biological system with HSV-1 and six antiviral drugs, namely, Interferon-alpha, Interferon-beta, Interferon-gamma, Ribavirin, Acyclovir, and TNF-alpha. We show how the sequential use of two- and three-level fractional factorial designs can screen for important drugs and drug interactions, as well as determine potential optimal drug dosages through the use of contour plots. Our initial experiment using a two-level fractional factorial design suggests that there is model inadequacy and drug dosages should be reduced. A follow-up experiment using a blocked three-level fractional factorial design indicates that TNF-alpha has little effect and HSV-1 infection can be suppressed effectively by using a right combination of the other five antiviral drugs. These observations have practical implications in the understanding of antiviral drug mechanism that can result in better design of antiviral drug therapy. PMID:22859316
Discrimination of gays and lesbians: a social justice perspective.

PubMed

Blackwell, Christopher W; Ricks, Janice L; Dzielgielewski, Sophia F

2004-01-01

The existence of discrimination against America's gay and lesbian citizens is widely supported in the research literature of many disciplines. This article provides a specific analysis of this discrimination and demonstrates the stark contrast between the discrimination of gays and lesbians in American society and the social justice concepts of equality and fairness. The works of Rawls, and later the works of Nussbaum, provide the theoretical framework highlighting the factors related to this discrimination and inequality. In the concluding section, specific implications for future policy development are presented that are designed to ensure that gays and lesbians are not further discriminated against. Areas examined include civil unions, gay marriages, adoptions, hate crime legislation and cessation of the U.S. military's "Don't Ask, Don't Tell, Don't Pursue" policy, advocating for inclusion of open gays and lesbians in military positions and commandership.
The Sociology of Discrimination: Racial Discrimination in Employment, Housing, Credit, and Consumer Markets

PubMed Central

Pager, Devah; Shepherd, Hana

2010-01-01

Persistent racial inequality in employment, housing, and a wide range of other social domains has renewed interest in the possible role of discrimination. And yet, unlike in the pre–civil rights era, when racial prejudice and discrimination were overt and widespread, today discrimination is less readily identifiable, posing problems for social scientific conceptualization and measurement. This article reviews the relevant literature on discrimination, with an emphasis on racial discrimination in employment, housing, credit markets, and consumer interactions. We begin by defining discrimination and discussing relevant methods of measurement. We then provide an overview of major findings from studies of discrimination in each of the four domains; and, finally, we turn to a discussion of the individual, organizational, and structural mechanisms that may underlie contemporary forms of discrimination. This discussion seeks to orient readers to some of the key debates in the study of discrimination and to provide a roadmap for those interested in building upon this long and important line of research. PMID:20689680
Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA).

PubMed

Kassouf, Amine; Maalouly, Jacqueline; Rutledge, Douglas N; Chebib, Hanna; Ducruet, Violette

2014-11-01

Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of the proposed approach was also tested using two spectrometers with considerable differences in their sensitivities. Discrimination rates were not affected proving that the developed approach could be extrapolated to different spectrometers. MIR combined with ICA is a promising tool for plastic waste separation that can help improve performance in this field; however further technological improvements and developments are required before it can be applied
Bias of phencyclidine discrimination by the schedule of reinforcement.

PubMed Central

McMillan, D E; Wenger, G R

1984-01-01

Pigeons, trained to discriminate phencyclidine from saline under a procedure requiring the bird to track the location of a color, received cumulative doses of phencyclidine, pentobarbital, or d-amphetamine with a variety of schedules of reinforcement in effect (across phases). When the same second-order schedules were used to reinforce responding after either saline or phencyclidine administration, stimulus control by phencyclidine did not depend on the schedule parameter. When different second-order schedules were used that biased responding toward the phencyclidine-correlated key color, pigeons responded on the phencyclidine-correlated key at lower doses of phencyclidine and pentobarbital than when the second-order schedule biased responding toward the saline key color. A similar but less marked effect was obtained with d-amphetamine. Attempts to produce bias by changing reinforcement magnitude (duration of food availability) were less successful. A signal-detection analysis of dose-effect curves for phencyclidine under two of the second-order schedules employed suggested that at low doses of phencyclidine, response bias is a major determinant of responding. As doses were increased, position preferences occurred and response bias decreased; at higher doses both response bias and position preference decreased and discriminability increased. With low doses of pentobarbital, responding again was biased but increasing doses produced position preference with only small increases in discriminability. At low doses of d-amphetamine responding also was biased, but bias did not decrease consistently with dose nor did discriminability increase. These experiments suggest that the schedule of reinforcement can be used to bias responding toward or away from making the drug-correlated response in drug discrimination experiments, and that signal-detection analysis and analysis of responding at a position can be used to separate the discriminability of the drug state from other
Trace element analysis of rough diamond by LA-ICP-MS: a case of source discrimination?

PubMed

Dalpé, Claude; Hudon, Pierre; Ballantyne, David J; Williams, Darrell; Marcotte, Denis

2010-11-01

Current profiling of rough diamond source is performed using different physical and/or morphological techniques that require strong knowledge and experience in the field. More recently, chemical impurities have been used to discriminate diamond source and with the advance of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) empirical profiling of rough diamonds is possible to some extent. In this study, we present a LA-ICP-MS methodology that we developed for analyzing ultra-trace element impurities in rough diamond for origin determination ("profiling"). Diamonds from two sources were analyzed by LA-ICP-MS and were statistically classified by accepted methods. For the two diamond populations analyzed in this study, binomial logistic regression produced a better overall correct classification than linear discriminant analysis. The results suggest that an anticipated matrix match reference material would improve the robustness of our methodology for forensic applications. © 2010 American Academy of Forensic Sciences.
Fast discrimination of hydroxypropyl methyl cellulose using portable Raman spectrometer and multivariate methods

NASA Astrophysics Data System (ADS)

Song, Biao; Lu, Dan; Peng, Ming; Li, Xia; Zou, Ye; Huang, Meizhen; Lu, Feng

2017-02-01

Raman spectroscopy is developed as a fast and non-destructive method for the discrimination and classification of hydroxypropyl methyl cellulose (HPMC) samples. 44 E series and 41 K series of HPMC samples are measured by a self-developed portable Raman spectrometer (Hx-Raman) which is excited by a 785 nm diode laser and the spectrum range is 200-2700 cm-1 with a resolution (FWHM) of 6 cm-1. Multivariate analysis is applied for discrimination of E series from K series. By methods of principal components analysis (PCA) and Fisher discriminant analysis (FDA), a discrimination result with sensitivity of 90.91% and specificity of 95.12% is achieved. The corresponding receiver operating characteristic (ROC) is 0.99, indicting the accuracy of the predictive model. This result demonstrates the prospect of portable Raman spectrometer for rapid, non-destructive classification and discrimination of E series and K series samples of HPMC.
Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis.

PubMed

Lee, Byeong-Ju; Kim, Hye-Youn; Lim, Sa Rang; Huang, Linfang; Choi, Hyung-Kyoon

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values.
Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis

PubMed Central

Lim, Sa Rang; Huang, Linfang

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values. PMID:29049369
A two-stage linear discriminant analysis via QR-decomposition.

PubMed

Ye, Jieping; Li, Qi

2005-06-01

Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional data, such as image and text classification. An intrinsic limitation of classical LDA is the so-called singularity problems; that is, it fails when all scatter matrices are singular. Many LDA extensions were proposed in the past to overcome the singularity problems. Among these extensions, PCA+LDA, a two-stage method, received relatively more attention. In PCA+LDA, the LDA stage is preceded by an intermediate dimension reduction stage using Principal Component Analysis (PCA). Most previous LDA extensions are computationally expensive, and not scalable, due to the use of Singular Value Decomposition or Generalized Singular Value Decomposition. In this paper, we propose a two-stage LDA method, namely LDA/QR, which aims to overcome the singularity problems of classical LDA, while achieving efficiency and scalability simultaneously. The key difference between LDA/QR and PCA+LDA lies in the first stage, where LDA/QR applies QR decomposition to a small matrix involving the class centroids, while PCA+LDA applies PCA to the total scatter matrix involving all training data points. We further justify the proposed algorithm by showing the relationship among LDA/QR and previous LDA methods. Extensive experiments on face images and text documents are presented to show the effectiveness of the proposed algorithm.
The factorial structure of job-related affective well-being: Polish adaptation of the Warr's measure.

PubMed

Mielniczuk, Emilia; Łaguna, Mariola

2018-02-16

The first aim of the study reported in this article was to test the factorial structure of job-related affect in a Polish sample. The second aim was to develop the Polish adaptation of the Warr's job-related affective well-being measure published in 1990, which is designed to assess 4 types of affect at work: anxiety, comfort, depression, enthusiasm. A longitudinal study design with 2 measurement times was used for verifying the psychometric properties of the Polish version of the measure. The final sample consisted of 254 Polish employees from different professions. Participants were asked to fill in a set of questionnaires consisting of measures capturing job-related affective well-being, mood, and turnover intention. The first step of analysis was to test the theoretically-based structure of the job-related affective well-being measure in a Polish sample. The confirmatory factor analysis revealed that a 4-factor model best describes the structure of the measure in comparison to 5 alternative models. Next, reliability of this measure was assessed. All scales achieved good internal consistency and acceptable test-retest reliability after 2 weeks. Finally, the convergent and discriminant validity as well as the criterion and predictive validity of all job-related affective well-being scales was confirmed, based on correlations between job-related affect and mood as well as turnover intention. The results suggest that the Polish adaptation of Warr's job-related affective well-being measure can be used by scientists as well as by practitioners who aim at assessing 4 types of affective well-being at a work context. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.
Systems biology of yeast: enabling technology for development of cell factories for production of advanced biofuels.

PubMed

de Jong, Bouke; Siewers, Verena; Nielsen, Jens

2012-08-01

Transportation fuels will gradually shift from oil based fuels towards alternative fuel resources like biofuels. Current bioethanol and biodiesel can, however, not cover the increasing demand for biofuels and there is therefore a need for advanced biofuels with superior fuel properties. Novel cell factories will provide a production platform for advanced biofuels. However, deep cellular understanding is required for improvement of current biofuel cell factories. Fast screening and analysis (-omics) methods and metabolome-wide mathematical models are promising techniques. An integrated systems approach of these techniques drives diversity and quantity of several new biofuel compounds. This review will cover the recent technological developments that support improvement of the advanced biofuels 1-butanol, biodiesels and jetfuels. Copyright © 2011 Elsevier Ltd. All rights reserved.
Are psychological measures and actuarial data equally effective in discriminating among the prison population? Analysis by crimes

PubMed Central

Burneo-Garcés, Carlos; Marín-Morales, Agar; Pérez-García, Miguel

2018-01-01

The ability of a wide range of psychological and actuarial measures to characterize crimes in the prison population has not yet been compared in a single study. Our main objective was to determine if the discriminant capacity of psychological measures (PM) and actuarial data (AD) varies according to the crime. An Ecuadorian sample of 576 men convicted of Robbery, Murder, Rape and Drug Possession crimes was evaluated through an ad hoc questionnaire, prison files and the Spanish adaptation of the Personality Assessment Inventory. Discriminant analysis was used to establish, for each crime, the discriminant capacity and the classification accuracy of a model composed of AD (socio-demographic and judicial measures) and a second model incorporating PM. The AD showed a superior discriminant capacity, whilst the contribution of both types of measures varied according to the crime. The PM generated some increase in the correct classification percentages for Murder, Rape and Drug Possession, but their contribution was zero for the crime of Robbery. Specific profiles of each crime were obtained from the strongest significant correlations between the value of each explanatory variable and the probability of belonging to the crime. The AD model is more robust when these four crimes are characterized. The contribution of AD and PM depends on the crime, and the inclusion of PM in actuarial models moderately optimizes the classification accuracy of Murder, Rape, and Drug Possession crimes. PMID:29874264
Health state after treatment: a reason for discrimination?

PubMed

Abellan-Perpiñan, J M; Pinto-Prades, J L

1999-12-01

In this paper the issue of discrimination between patients based on the health improvement that each can achieve is addressed. Previous research in this area by Nord has shown that, in this context, society's preferences may be quite opposite to the principle of health maximization present in cost utility analysis. Using a different experimental design from that used by Nord, some results are achieved which suggest that social preferences may be somewhere in between two opposite extremes, which are that discrimination based on the degree of health improvement is never acceptable and that discrimination based on the degree of health improvement is always acceptable. Copyright 1999 John Wiley & Sons, Ltd.
Autocrine and/or paracrine insulin-like growth factor-I activity in skeletal muscle

NASA Technical Reports Server (NTRS)

Adams, Gregory R.

2002-01-01

Similar to bone, skeletal muscle responds and adapts to changes in loading state via mechanisms that appear to be intrinsic to the muscle. One of the mechanisms modulating skeletal muscle adaptation it thought to involve the autocrine and/or paracrine production of insulinlike growth factor-I. This brief review outlines components of the insulinlike growth factor-I system as it relates to skeletal muscle and provides the rationale for the theory that insulinlike growth factor-I is involved with muscle adaptation.

Racial discrimination, gender discrimination, and substance abuse among Latina/os nationwide.

PubMed

Otiniano Verissimo, Angie Denisse; Gee, Gilbert C; Ford, Chandra L; Iguchi, Martin Y

2014-01-01

This study investigates the relationship between discrimination and substance abuse among Latina/os, and further examines whether this relationship differs by gender and type of discrimination. Analyses focus on the Latina/o respondents (n = 1,039 men; n = 1,273 women) from the National Latino and Asian American Study carried out from 2002-2003. Outcomes were alcohol abuse and drug abuse measured using DSM-IV definitions and criteria. Additional covariates included immigrant characteristics and demographics. Analyses were completed using gender-stratified multinomial logistic regression. Men reported more discrimination (39.6% vs. 30.3%) and had higher prevalence of alcohol abuse (16.5% vs. 4.5%) and drug abuse (9.5% vs. 2.3%) than women. Discrimination was significantly associated with increased risk of alcohol abuse for women and increased risk of drug abuse for men. Men and women also varied in the types of discrimination (e.g., racial vs. gender) reported, and in the associations between these types of discrimination and substance abuse. These data indicate that discrimination is associated with different substance abuse outcomes between genders. Future research should consider the mechanisms that explain these differences.
DISCRIMINATION OF EMOTIONAL STATES AMONGST THE TAMILS

PubMed Central

Somasundaram, O.

1992-01-01

Leff has concluded from his analysis of the JPSS Study that the emotions of anxiety, depression and irritability are poorly discriminated amongst the population using non-Indo-European languages. The present author after analyzing similar data from the ICMR Multicentred Collaborative Study of Factors Associated with the Course and outcome of Schizophrenia that the Tamil population using Tamil, a non-Indo-European language is able to discriminate these emotions as well as the brethren speaking Hindi of lndo-European origin. PMID:21776093
Metals distribution in soils around the cement factory in southern Jordan.

PubMed

Al-Khashman, Omar A; Shawabkeh, Reyad A

2006-04-01

Thirty one soil samples were collected from south Jordan around the cement factory in Qadissiya area. The samples were obtained at two depths, 0-10 cm and 10-20 cm and were analyzed by atomic absorption spectrophotometery for Pb, Zn, Cd, Fe, Cu and Cr. Physicochemical factors believed to affect their mobility of metals in soil of the study area were examined such as; pH, TOM, CaCO3, CEC and conductivity. The relatively high concentrations of lead, zinc and cadmium in the soil samples of the investigated area were related to anthropogenic sources such as cement industry, agriculture activities and traffic emissions. It was found that the lead, zinc and cadmium have the highest level in area close to the cement factory, while the concentration of chromium was low. This study indicate that all of the metals are concentrated on the surface soil, and decreased in the lower part of the soil, this due to reflects their mobility and physical properties of soil and its alkaline pH values. The use of factor analysis showed that anthropogenic activities seem to be the responsible source of pollution for metals in urban soils.
Differentiating sex and species of Western Grebes (Aechmophorus occidentalis) and Clark's Grebes (Aechmophorus clarkii) and their eggs using external morphometrics and discriminant function analysis

USGS Publications Warehouse

Hartman, C. Alex; Ackerman, Joshua T.; Eagles-Smith, Collin A.; Herzog, Mark

2016-01-01

In birds where males and females are similar in size and plumage, sex determination by alternative means is necessary. Discriminant function analysis based on external morphometrics was used to distinguish males from females in two closely related species: Western Grebe (Aechmophorus occidentalis) and Clark's Grebe (A. clarkii). Additionally, discriminant function analysis was used to evaluate morphometric divergence between Western and Clark's grebe adults and eggs. Aechmophorus grebe adults (n = 576) and eggs (n = 130) were sampled across 29 lakes and reservoirs throughout California, USA, and adult sex was determined using molecular analysis. Both Western and Clark's grebes exhibited considerable sexual size dimorphism. Males averaged 6–26% larger than females among seven morphological measurements, with the greatest sexual size dimorphism occurring for bill morphometrics. Discriminant functions based on bill length, bill depth, and short tarsus length correctly assigned sex to 98% of Western Grebes, and a function based on bill length and bill depth correctly assigned sex to 99% of Clark's Grebes. Further, a simplified discriminant function based only on bill depth correctly assigned sex to 96% of Western Grebes and 98% of Clark's Grebes. In contrast, external morphometrics were not suitable for differentiating between Western and Clark's grebe adults or their eggs, with correct classification rates of discriminant functions of only 60%, 63%, and 61% for adult males, adult females, and eggs, respectively. Our results indicate little divergence in external morphology between species of Aechmophorus grebes, and instead separation is much greater between males and females.
Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA)

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

Kassouf, Amine, E-mail: amine.kassouf@agroparistech.fr; INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy; AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris

2014-11-15

Highlights: • An innovative technique, MIR-ICA, was applied to plastic packaging separation. • This study was carried out on PE, PP, PS, PET and PLA plastic packaging materials. • ICA was applied to discriminate plastics and 100% separation rates were obtained. • Analyses performed on two spectrometers proved the reproducibility of the method. • MIR-ICA is a simple and fast technique allowing plastic identification/classification. - Abstract: Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energymore » recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The
Hardwood log grades and lumber grade yields for factory lumber logs

Treesearch

Leland F. Hanks; Glenn L. Gammon; Robert L. Brisbin; Everette D. Rast

1980-01-01

The USDA Forest Service Standard Grades for Hardwood Factory Lumber Logs are described, and lumber grade yields for 16 species and 2 species groups are presented by log grade and log diameter. The grades enable foresters, log buyers, and log sellers to select and grade those log suitable for conversion into standard factory grade lumber. By using the apropriate lumber...
Molecular pathways: transcription factories and chromosomal translocations.

PubMed

Osborne, Cameron S

2014-01-15

The mammalian nucleus is a highly complex structure that carries out a diverse range of functions such as DNA replication, cell division, RNA processing, and nuclear export/import. Many of these activities occur at discrete subcompartments that intersect with specific regions of the genome. Over the past few decades, evidence has accumulated to suggest that RNA transcription also occurs in specialized sites, called transcription factories, that may influence how the genome is organized. There may be certain efficiency benefits to cluster transcriptional activity in this way. However, the clustering of genes at transcription factories may have consequences for genome stability, and increase the susceptibility to recurrent chromosomal translocations that lead to cancer. The relationships between genome organization, transcription, and chromosomal translocation formation will have important implications in understanding the causes of therapy-related cancers. ©2013 AACR.
DISCRIMINATION OF GRANITOIDS AND MINERALIZED GRANITOIDS IN THE MIDYAN REGION, NORTHWESTERN ARABIAN SHIELD, SAUDI ARABIA, BY LANDSAT MSS DATA-ANALYSIS.

USGS Publications Warehouse

Davis, Philip A.; Grolier, Maurice J.

1984-01-01

Landsat multispectral scanner (MSS) band and band-ratio databases of two scenes covering the Midyan region of northwestern Saudi Arabia were examined quantitatively and qualitatively to determine which databases best discriminate the geologic units of this semi-arid and arid region. Unsupervised, linear-discriminant cluster-analysis was performed on these two band-ratio combinations and on the MSS bands for both scenes. The results for granitoid-rock discrimination indicated that the classification images using the MSS bands are superior to the band-ratio classification images for two reasons, discussed in the paper. Yet, the effects of topography and material type (including desert varnish) on the MSS-band data produced ambiguities in the MSS-band classification results. However, these ambiguities were clarified by using a simulated natural-color image in conjunction with the MSS-band classification image.
Factorial Composition of Counsellor Effectiveness Scale

ERIC Educational Resources Information Center

Oluseyi, Adeyemo Emily; Oreoluwa, Shaba Veronica

2014-01-01

The study developed a set of items that could measure counsellor effectiveness. It reduced the initial set of variables related to counsellor effectiveness to such number of variables that are generally perceived as indicative of counsellor effectiveness and determined the factorial composition of the scale. in order to identify the major factors…
Ultrasonic analysis to discriminate bread dough of different types of flour

NASA Astrophysics Data System (ADS)

García-Álvarez, J.; Rosell, C. M.; García-Hernández, M. J.; Chávez, J. A.; Turó, A.; Salazar, J.

2012-12-01

Many varieties of bread are prepared using flour coming from wheat. However, there are other types of flours milled from rice, legumes and some fruits and vegetables that are also suitable for baking purposes, used alone or in combination with wheat flour. The type of flour employed strongly influences the dough consistency, which is a relevant property for determining the dough potential for breadmaking purposes. Traditional methods for dough testing are relatively expensive, time-consuming, off-line and often require skilled operators. In this work, ultrasonic analysis are performed in order to obtain acoustic properties of bread dough samples prepared using two different types of flour, wheat flour and rice flour. The dough acoustic properties can be related to its viscoelastic characteristics, which in turn determine the dough feasibility for baking. The main advantages of the ultrasonic dough testing can be, among others, its low cost, fast, hygienic and on-line performance. The obtained results point out the potential of the ultrasonic analysis to discriminate doughs of different types of flour.
Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

PubMed

Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan

2013-01-01

Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.). Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13-30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset. Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues
Suppression of the µ Rhythm during Speech and Non-Speech Discrimination Revealed by Independent Component Analysis: Implications for Sensorimotor Integration in Speech Processing

PubMed Central

Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan

2013-01-01

Background Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.) Methods Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80–100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. Results ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13–30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset. Conclusions Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then
A survey of airborne and skin exposures to chemicals in footwear and equipment factories in Thailand.

PubMed

Todd, Lori A; Mottus, Kathleen; Mihlan, Gary J

2008-03-01

This research reports on a pilot industrial hygiene study that was performed at four footwear factories and two equipment factories in Thailand. Workers in these factories were exposed through inhalation and dermal contact to a large number of organic vapors from solvents and cements that were hand applied. In addition, these workers were exposed to highly toxic isocyanates primarily through the dermal route. A total of 286 personal air samples were obtained at the four footwear factories using organic vapor monitors; individual job tasks were monitored using a real-time MIRAN Spectrometer. A total of 64 surface, tool, or hand samples were monitored for isocyanates using surface contamination detectors. Real-time measurements were also obtained for organic vapors in two equipment factories. From 8% to 21% of the workers sampled in each footwear factory were overexposed to mixtures of chemicals from solvents and cements. Up to 100% of the workers performing specific job tasks were overexposed to mixtures of chemicals. From 39% to 69% of the surface samples were positive for unreacted isocyanates. Many of the real-time measurements obtained in the equipment factories exceeded occupational exposure limits. Personal protective equipment and engineering controls were inadequate in all of the factories.
Linking structural biology with genome research: Beamlines for the Berlin ``Protein Structure Factory'' initiative

NASA Astrophysics Data System (ADS)

Illing, Gerd; Saenger, Wolfram; Heinemann, Udo

2000-06-01

The Protein Structure Factory will be established to characterize proteins encoded by human genes or cDNAs, which will be selected by criteria of potential structural novelty or medical or biotechnological usefulness. It represents an integrative approach to structure analysis combining bioinformatics techniques, automated gene expression and purification of gene products, generation of a biophysical fingerprint of the proteins and the determination of their three-dimensional structures either by NMR spectroscopy or by X-ray diffraction. The use of synchrotron radiation will be crucial to the Protein Structure Factory: high brilliance and tunable wavelengths are prerequisites for fast data collection, the use of small crystals and multiwavelength anomalous diffraction (MAD) phasing. With the opening of BESSY II, direct access to a third-generation XUV storage ring source with excellent conditions is available nearby. An insertion device with two MAD beamlines and one constant energy station will be set up until 2001.
76 FR 77175 - New York Fun Factory Fireworks Display, Western Long Island Sound; Mamaroneck, NY

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-12

...-AA00 New York Fun Factory Fireworks Display, Western Long Island Sound; Mamaroneck, NY AGENCY: Coast... in support of the New York Fun Factory Fireworks display. This action is necessary to provide for the... the Coast Guard to define regulatory safety zones. On May 10, 2012 New York Fun Factory Events is...
Genetic privacy and non-discrimination.

PubMed

Romeo Casabona, Carlos María

2011-01-01

The UN Inter-Agency Committee on Bioethics met for its tenth meeting at the UNESCO headquarters in Paris on 4-5th March 2011. Member organisations such as the WHO and UNESCO were in attendance alongside associate members such as the Council for Europe, the European Commission, the Organisation for Economic Co-operation and Development and the World Trade Organisation. Discussion centred on the theme "genetic privacy and nondiscrimination". The United Nations Economic and Social Council (ECOSOC) had previously considered, from a legal and ethical perspective, the implications of increasingly sophisticated technologies for genetic privacy and non-discrimination in fields such as medicine, employment and insurance. Thus, the ECOSOC requested that UNESCO report on relevant developments in the field of genetic privacy and non-discrimination. In parallel with a consultation process with member states, UNESCO launched a consultation with the UN Interagency Committee on Bioethics. This article analyses the report presented by the author concerning the analysis of the current contentions in the field and illustrates attempts at responding on a normative level to a perceived threat to genetic privacy and non-discrimination.
Evaluation of a highly discriminating multiplex multi-locus variable-number of tandem-repeats (MLVA) analysis for Vibrio cholerae.

PubMed

Olsen, Jaran S; Aarskaug, Tone; Skogan, Gunnar; Fykse, Else Marie; Ellingsen, Anette Bauer; Blatny, Janet M

2009-09-01

Vibrio cholerae is the etiological agent of cholera and may be used in bioterror actions due to the easiness of its dissemination, and the public fear for acquiring the cholera disease. A simple and highly discriminating method for connecting clinical and environmental isolates of V. cholerae is needed in microbial forensics. Twelve different loci containing variable numbers of tandem-repeats (VNTRs) were evaluated in which six loci were polymorphic. Two multiplex reactions containing PCR primers targeting these six VNTRs resulted in successful DNA amplification of 142 various environmental and clinical V. cholerae isolates. The genetic distribution inside the V. cholerae strain collection was used to evaluate the discriminating power (Simpsons Diversity Index=0.99) of this new MLVA analysis, showing that the assay have a potential to differentiate between various strains, but also to identify those isolates which are collected from a common V. cholerae outbreak. This work has established a rapid and highly discriminating MLVA assay useful for track back analyses and/or forensic studies of V. cholerae infections.
Discriminant Analysis as a Tool for Admission Selection to Special Academic Programs. AIR 1986 Annual Forum Paper.

ERIC Educational Resources Information Center

Kissel, Mary Ann

The use of stepwise discriminant analysis as a means to select entering students who would benefit from a special program for the disadvantaged was studied. In fall 1984, 278 full-time black students were admitted as first-time students to a large urban university. Of the total, 200 entered a special program for the disadvantaged and 78 entered…
Environmental factors affecting antipyrine metabolism in London factory and office workers.

PubMed Central

Fraser, H S; Mucklow, J C; Bulpitt, C J; Kahn, C; Mould, G; Dollery, C T

1979-01-01

1 Measurements of antipyrine clearance in saliva have been made in 128 London factory and office workers. 2 Mean antipyrine clearance in 56 Asian immigrants was 40% slower than in 72 White subjects. 3 Although dietary differences existed between the two groups, analysis of their effect independently of race was impossible since all but one of the vegetarians were Asian and the non-vegetarians were nearly all White. 4 In the White subjects, use of the oral contraceptive reduced clearance by 38% in women, while cigarette smoking increase clearance by 38% in men. PMID:427001
Japanese International Female Students' Experience of Discrimination, Prejudice, and Stereotypes

ERIC Educational Resources Information Center

Bonazzo, Claude; Wong, Y. Joel

2007-01-01

This qualitative study examined four Japanese international female college students' experience of discrimination, prejudice, and stereotypes in a predominately white university. Four themes emerged from the analysis of data: (1) overt forms of prejudice and discrimination; (2) stereotypes common to Asians; (3) stereotypes unique to the Japanese;…

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