949 resultados para Discriminant analysis


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Background/Objectives: We applied three dietary assessment methods and aimed at obtaining a set of physical, social and psychological variables that can discriminate those individuals who did not underreport (`never under-reporters`), those who underreported in one dietary assessment method (`occasional under-reporters`) and those who underreported in two or three dietary assessment methods (`frequent under-reporters`). Participants/Methods: Sixty-five women aged 18-57 years were recruited for this study. Total energy expenditure was determined by doubly labelled water, and energy intake was estimated by three 24-h diet recalls, 3-day food records and a food frequency questionnaire. A multiple discriminant analysis was used to identify which of those variables better discriminated the three groups: body mass index (BMI), income, education, social desirability, nutritional knowledge, dietary restraint, physical activity practice, body dissatisfaction and binge-eating symptoms. Results: Twenty-three participants were `never under-reporters`. Twenty-four participants were `occasional under-reporters` and 18 were `frequent under-reporters`. Four variables entered the discriminant model: income, BMI, social desirability and body dissatisfaction. According to potency indices, income contributed the most to the total discriminant power, followed in decreasing order by social desirability score, BMI and body dissatisfaction. Income, social desirability and BMI were the characteristics that mainly separated the `never under-reporters` from the under-reporters (occasional or frequent). Body dissatisfaction better discriminated the `occasional under-reporters` from the `frequent under-reporters`. Conclusions: `Frequent under-reporters` have a greater BMI, social desirability score, body dissatisfaction score and lower income. These four variables seemed to be able to discriminate individuals who are more prone to systematic under reporting. European Journal of Clinical Nutrition (2009) 63, 1192-1199; doi:10.1038/ejcn.2009.54; published online 15 July 2009

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A multivariate model using hierarchical clustering and discriminant analysis is used to identify clusters of community opportunity and community vulnerability across Australia's mega metropolitan regions, Variables used in the model measure aspects of structural economic change, occupational change, human capital, income, unemployment, family/household disadvantage, and housing stress. A nine-cluster solution is used to categorise communities across metropolitan space. Significant between-city variations in the incidence of these clusters of opportunity and vulnerability are apparent, suggesting the emergence of marked differentiation between Australia's mega metropolitan regions in their adjustments to changing economic and social conditions. JEL classification: C49, R11, R12.

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The vascular and bryophyte floras of subantarctic Heard Island were classified using cluster analysis into six vegetation communities: Open Cushion Carpet, Mossy Feldmark, Wet Mixed Herbfield, Coastal Biotic Vegetation, Saltspray Vegetation, and Closed Cushion Carpet. Multidimensional scaling indicated that the vegetation communities were not well delineated but were continua. Discriminant analysis and a classification tree identified altitude, wind, peat depth, bryophyte cover and extent of bare ground, and particle size as discriminating variables. The combination of small area, glaciation, and harsh climate has resulted in reduced vegetation variety in comparison to those subantarctic islands north of the Antarctic Polar Front Zone. Some of the functional groups and vegetation communities found on warmer subantarctic islands are not present on Heard Island, notably ferns and sedges and fernbrakes and extensive mires, respectively.

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The authors discern the community structure of the postindustrial city, with reference to Australia. They focus empirically on three major types of Australian urban center: urban regions. metropolitan areas that are not part of urban regions, and other major cities. These three account for almost three-quarters of the Australian population. The authors draw on a conceptualization formulated by Marcuse and van Kempen to guide the analysis, with a combination of cluster analysis and discriminant analysis being applied to aggregate (essentially census) data to identify the communities. Nine major Australian urban communities are identified-four are affluent. four are disadvantaged. and one is a working-class community. The communities found, however, differed greatly from those cited in the Marcuse and van Kempen schema.

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This study identifies and explores a new country of origin (COO) cue, “owned by….” The importance of three extrinsic cues “owned by …,” “made in …” and price was examined using conjoint analysis. Data were collected from a sample of 268 undergraduate students familiar with color televisions. Segments were formed using cluster analysis and analyzed using multiple discriminant analysis. “Owned by …” was found to be important and distinct from the “made in …” cue. Segments based on the two COO cues were identified using importance weights and individual utilities. When segments were formed using individual utilities the individual difference construct, economic nationalism, provided discriminatory power while consumer ethnocentrism did not, supporting the hypothesis that economic nationalism and consumer ethnocentrism differ. Practitioners can now use “owned by …” knowing that it forms an important and distinct marketing tool. Limitations and future research are discussed.

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The HCI community is actively seeking novel methodologies to gain insight into the user’s experience during interaction with both the application and the content. We propose an emotional recognition engine capable of automatically recognizing a set of human emotional states using psychophysiological measures of the autonomous nervous system, including galvanic skin response, respiration, and heart rate. A novel pattern recognition system, based on discriminant analysis and support vector machine classifiers is trained using movies’ scenes selected to induce emotions ranging from the positive to the negative valence dimension, including happiness, anger, disgust, sadness, and fear. In this paper we introduce an emotion recognition system and evaluate its accuracy by presenting the results of an experiment conducted with three physiologic sensors.

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The purpose of this paper is to analyze whether companies with a greater commitment to corporate social responsibility (SRI companies) perform differently on the stock market compared to companies that disregard SRI. Over recent years, this relationship has been taken up at both a theoretical and practical level, and has led to extensive scientific research of an empirical nature involving the examination of the relationships existing between the financial and social, environmental and corporate governance performance of a company and the relationship between SRI and investment decisions in the financial market. More specifically, this work provides empirical evidence for the Spanish market as to whether or not belonging to a group of companies the market classes as sustainable results in return premiums that set them apart from companies classed as conventional, and finds no differences in the stock market performance of companies considered to be SRI or conventional.

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We are concerned with providing more empirical evidence on forecast failure, developing forecast models, and examining the impact of events such as audit reports. A joint consideration of classic financial ratios and relevant external indicators leads us to build a basic prediction model focused in non-financial Galician SMEs. Explanatory variables are relevant financial indicators from the viewpoint of the financial logic and financial failure theory. The paper explores three mathematical models: discriminant analysis, Logit, and linear multivariate regression. We conclude that, even though they both offer high explanatory and predictive abilities, Logit and MDA models should be used and interpreted jointly.

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OBJECTIVE: To evaluate the discriminative and diagnostic values of neuropsychological tests for identifying schizophrenia patients. METHODS: A cross-sectional study with 36 male schizophrenia outpatients and 72 healthy matched volunteers was carried out. Participants underwent the following neuropsychological tests: Wisconsin Card Sorting test, Verbal Fluency, Stroop test, Mini Mental State Examination, and Spatial Recognition Span. Sensitivity and specificity estimated the diagnostic value of tests with cutoffs obtained using Receiver Operating Characteristic curves. The latent class model (diagnosis of schizophrenia) was used as gold standard. RESULTS: Although patients presented lower scores in most tests, the highest canonical function for the discriminant analysis was 0.57 (Verbal Fluency M). The best sensitivity and specificity were obtained in the Verbal Fluency M test (75 and 65, respectively). CONCLUSIONS: The neuropsychological tests showed moderate diagnostic value for the identification of schizophrenia patients. These findings suggested that the cognitive impairment measured by these tests might not be homogeneous among schizophrenia patients.

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Pine forests constitute some of the most important renewable resources supplying timber, paper and chemical industries, among other functions. Characterization of the volatiles emitted by different Pinus species has proven to be an important tool to decode the process of host tree selection by herbivore insects, some of which cause serious economic damage to pines. Variations in the relative composition of the bouquet of semiochemicals are responsible for the outcome of different biological processes, such as mate finding, egg-laying site recognition and host selection. The volatiles present in phloem samples of four pine species, P. halepensis, P. sylvestris, P. pinaster and P. pinea, were identified and characterized with the aim of finding possible host-plant attractants for native pests, such as the bark beetle Tomicus piniperda. The volatile compounds emitted by phloem samples of pines were extracted by headspace solid-phase micro extraction, using a 2 cm 50/30 mm divinylbenzene/carboxen/polydimethylsiloxane table flex solid-phase microextraction fiber and its contents analyzed by high-resolution gas chromatography, using flame ionization and a non polar and chiral column phases. The components of the volatile fraction emitted by the phloem samples were identified by mass spectrometry using time-of-flight and quadrupole mass analyzers. The estimated relative composition was used to perform a discriminant analysis among pine species, by means of cluster and principal component analysis. It can be concluded that it is possible to discriminate pine species based on the monoterpenes emissions of phloem samples.

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Na atualidade, está a emergir um novo paradigma de interação, designado por Natural User Interface (NUI) para reconhecimento de gestos produzidos com o corpo do utilizador. O dispositivo de interação Microsoft Kinect foi inicialmente concebido para controlo de videojogos, para a consola Xbox360. Este dispositivo demonstra ser uma aposta viável para explorar outras áreas, como a do apoio ao processo de ensino e de aprendizagem para crianças do ensino básico. O protótipo desenvolvido visa definir um modo de interação baseado no desenho de letras no ar, e realizar a interpretação dos símbolos desenhados, usando os reconhecedores de padrões Kernel Discriminant Analysis (KDA), Support Vector Machines (SVM) e $N. O desenvolvimento deste projeto baseou-se no estudo dos diferentes dispositivos NUI disponíveis no mercado, bibliotecas de desenvolvimento NUI para este tipo de dispositivos e algoritmos de reconhecimento de padrões. Com base nos dois elementos iniciais, foi possível obter uma visão mais concreta de qual o hardware e software disponíveis indicados à persecução do objetivo pretendido. O reconhecimento de padrões constitui um tema bastante extenso e complexo, de modo que foi necessária a seleção de um conjunto limitado deste tipo de algoritmos, realizando os respetivos testes por forma a determinar qual o que melhor se adequava ao objetivo pretendido. Aplicando as mesmas condições aos três algoritmos de reconhecimento de padrões permitiu avaliar as suas capacidades e determinar o $N como o que apresentou maior eficácia no reconhecimento. Por último, tentou-se averiguar a viabilidade do protótipo desenvolvido, tendo sido testado num universo de elementos de duas faixas etárias para determinar a capacidade de adaptação e aprendizagem destes dois grupos. Neste estudo, constatou-se um melhor desempenho inicial ao modo de interação do grupo de idade mais avançada. Contudo, o grupo mais jovem foi revelando uma evolutiva capacidade de adaptação a este modo de interação melhorando progressivamente os resultados.

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The most consumed squid species worldwide were characterized regarding their concentrations of minerals, fatty acids, cholesterol and vitamin E. Interspecific comparisons were assessed among species and geographical origin. The health benefits derived from squid consumption were assessed based on daily minerals intake and on nutritional lipid quality indexes. Squids contribute significantly to daily intake of several macro (Na, K, Mg and P) and micronutrients (Cu, Zn and Ni). Despite their low fat concentration, they are rich in long-chain omega-3 fatty acids, particularly docosahexaenoic (DHA) and eicosapentanoic (EPA) acids, with highly favorable ω-3/ω-6 ratios (from 5.7 to 17.7), reducing the significance of their high cholesterol concentration (140–549 mg/100 g ww). Assessment of potential health risks based on minerals intake, non-carcinogenic and carcinogenic risks indicated that Loligo gahi (from Atlantic Ocean), Loligo opalescens (from Pacific Ocean) and Loligo duvaucelii (from Indic Ocean) should be eaten with moderation due to the high concentrations of Cu and/or Cd. Canonical discriminant analysis identified the major fatty acids (C14:0, C18:0, C18:1, C18:3ω-3, C20:4ω-6 and C22:5ω-6), P, K, Cu and vitamin E as chemical discriminators for the selected species. These elements and compounds exhibited the potential to prove authenticity of the commercially relevant squid species.

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Espresso coffee beverages prepared from pure origin roasted ground coffees from the major world growing regions (Brazil, Ethiopia, Colombia, India, Mexico, Honduras, Guatemala, Papua New Guinea, Kenya, Cuba, Timor, Mussulo and China) were characterized and compared in terms of their mineral content. Regular consumption of one cup of espresso contributes to a daily mineral intake varying from 0.002% (sodium; Central America) to 8.73% (potassium; Asia). The mineral profiles of the espresso beverages revealed significant inter- and intra-continental differences. South American pure origin coffees are on average richer in the analyzed elements except for calcium, while samples from Central America have generally lower mineral amounts (except for manganese). Manganese displayed significant differences (p < 0.05) among the countries of each characterized continent. Intercontinental and inter-country discrimination between the major world coffee producers were achieved by applying canonical discriminant analysis. Manganese and calcium were found to be the best chemical descriptors for origin.

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Twenty-four hepatitis C virus patients coinfected with human T-lymphotropic virus type 1 were compared with six coinfected with HTLV-2 and 55 with HCV alone, regarding clinical, epidemiological, laboratory and histopathological data. Fischer's discriminant analysis was applied to define functions capable of differentiating between the study groups (HCV, HCV/HTLV-1 and HCV/HTLV-2). The discriminant accuracy was evaluated by cross-validation. Alcohol consumption, use of intravenous drugs or inhaled cocaine and sexual partnership with intravenous drug users were more frequent in the HCV/HTLV-2 group, whereas patients in the HCV group more often reported abdominal pain or a sexual partner with hepatitis. Coinfected patients presented higher platelet counts, but aminotransferase and gamma-glutamyl transpeptidase levels were higher among HCV-infected subjects. No significant difference between the groups was seen regarding liver histopathological findings. Through discriminant analysis, classification functions were defined, including sex, age group, intravenous drug use and sexual partner with hepatitis. Cross-validation revealed high discriminant accuracy for the HCV group.