A satisfação dos clientes internos e o comprometimento organizacional: um estudo à luz do modelo ASH nas indústrias alimentícias do RN

Currently the organizations are passing for continuous cycles of changes due to necessity of survival in the work market. The administration of the future points a way to the organizations of today and tomorrow, the search of the competitiveness from loyalty and motivation of its staff. Of this form, the model of the Auditoria do Sistema Humano (ASH), developed for Spanish researchers and that now it is being applied in Brazil, contemplates a series of dimensions about Human Resources management quality in the companies and the organizational effectiveness, such as the environment where the company is inserted, the strategies, the organizational drawing, the psychological and psychosocial processes, e the reached results. In this direction, the present research analyzed the factors of job satisfaction and organizational commitment, making, also, a relation of causality between the same ones. The quantitative-descriptive research had as population the employees of twenty three nourishing industries of the State of Rio Grande do Norte (Brazil), registered in the Federacy of the Industries of the state. The collection of the data occurred for the months of October of 2005 and March of 2006, by means of the application of questionnaire of model ASH. The sample was composed for 197 employees, however it was observed presence of five outliers, that they had been excluded from the analysis of the data. To extract the dimensions of the satisfaction and the commitment and identification the factorial analysis was used, with extraction method of principal components, rotation Varimax and normalization Kaiser. The gotten dimensions had been evaluated with the calculation of the coefficient Alpha of Cronbach. The factorial analysis of the pointers of the organizational commitment and identification had extracted ten factors. Of these, four had gotten significance of the analyses inside: affective commitment, values commitment, continuance commitment and necessity commitment. The result of the analysis of the pointers of job satisfaction indicated four factors: extrinsic, motivations, relation with the friends and auto-accomplishment. To deal with the data the relation between job satisfaction and organizational commitment it was used technique of multiple regression. The correlation between commitment and satisfaction was satisfactory, detaching the affective commitment with bigger index of correlation, followed of the affective one

Uso da técnica de análise de componentes principais na redefinição do parâmetro BLA

Dissertação (mestrado)—Universidade de Brasília, Instituto de Física, Programa de Pós-Graduação em Física, 2016.

MORPHOLOGICAL DIVERSITY OF MANGO GERMPLASM FROM THE UPPER ATHI RIVER REGION OF EASTERN KENYA: AN ANALYSIS BASED ON NON- FRUIT DESCRIPTORS

Phenotypic variation in plants can be evaluated by morphological characterization using visual attributes. Fruits have been the major descriptors for identification of different varieties of fruit crops. However, even in their absence, farmers, breeders and interested stakeholders require to distinguish between different mango varieties. This study aimed at determining diversity in mango germplasm from the Upper Athi River (UAR) and providing useful alternative descriptors for the identification of different mango varieties in the absence of fruits. A total of 20 International Plant Genetic Resources Institute (IPGRI) descriptors for mango were selected for use in the visual assessment of 98 mango accessions from 15 sites of the UAR region of eastern Kenya. Purposive sampling was used to identify farmers growing diverse varieties of mangoes. Evaluation of the descriptors was performed on-site and the data collected were then subjected to multivariate analysis including Principal Component Analysis (PCA) and Cluster analysis, one- way analysis of variance (ANOVA) and Chi square tests. Results classified the accessions into two major groups corresponding to indigenous and exotic varieties. The PCA showed the first six principal components accounting for 75.12% of the total variance. A strong and highly significant correlation was observed between the color of fully grown leaves, leaf blade width, leaf blade length and petiole length and also between the leaf attitude, color of young leaf, stem circumference, tree height, leaf margin, growth habit and fragrance. Useful descriptors for morphological evaluation were 14 out of the selected 20; however, ANOVA and Chi square test revealed that diversity in the accessions was majorly as a result of variations in color of young leaves, leaf attitude, leaf texture, growth habit, leaf blade length, leaf blade width and petiole length traits. These results reveal that mango germplasm in the UAR has significant diversity and that other morphological traits apart from fruits can be useful in morphological characterization of mango.

Parcellation of fMRI datasets with ICA and PLS: a data driven approach

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.

Agroclimatic classification: numerical- taxonomic procedures - a review.

The paper catalogues the procedures and steps involved in agroclimatic classification. These vary from conventional descriptive methods to modern computer-based numerical techniques. There are three mutually independent numerical classification techniques, namely Ordination, Cluster analysis, and Minimum spanning tree; and under each technique there are several forms of grouping techniques existing. The vhoice of numerical classification procedure differs with the type of data set. In the case of numerical continuous data sets with booth positive and negative values, the simple and least controversial procedures are unweighted pair group method (UPGMA) and weighted pair group method (WPGMA) under clustering techniques with similarity measure obtained either from Gower metric or standardized Euclidean metric. Where the number of attributes are large, these could be reduced to fewer new attributes defined by the principal components or coordinates by ordination technique. The first few components or coodinates explain the maximum variance in the data matrix. These revided attributes are less affected by noise in the data set. It is possible to check misclassifications using minimum spanning tree.

Forecasting errors, directional accuracy and profitability of currency trading: The case of EUR/USD exchange rate

We provide a comprehensive study of out-of-sample forecasts for the EUR/USD exchange rate based on multivariate macroeconomic models and forecast combinations. We use profit maximization measures based on directional accuracy and trading strategies in addition to standard loss minimization measures. When comparing predictive accuracy and profit measures, data snooping bias free tests are used. The results indicate that forecast combinations, in particular those based on principal components of forecasts, help to improve over benchmark trading strategies, although the excess return per unit of deviation is limited.

Adaptação do questionário de suporte parental (QSP-6) - versão reduzida para adolescentes

"A família tem grande poder de influência e de transformação na vida de crianças e adolescentes. Os estudos recentes referem que o suporte familiar parece influenciar o desenvolvimento de comportamentos agressivos. Afirmam ainda a existência de uma relação entre o comportamento de bullying e o suporte que os jovens recebem das suas famílias. Assim, partindo da hipótese de que na fase da adolescência dos filhos, o suporte social dos pais poderá estar na origem de diferentes tipos de comportamentos agressivos/vitimizantes, o objetivo deste estudo é o de explorar as propriedades psicométricas do Questionário de Suporte Parental (QSP-6) – versão reduzida para Adolescentes (Clouse, 2007). Deste modo, apresentamos os resultados obtidos a partir de uma amostra de 728 adolescentes e jovens (372 do sexo feminino e 356 do sexo masculino) com idades compreendidas entre os 12 e os 21 anos. A estrutura relacional dos 18 itens foi avaliada por uma Análise Fatorial Exploratória (AFE) sobre a matriz de correlações, com extração dos fatores pelo método das componentes principais, seguido de rotação varimax. Os estudos psicométricos do QSP-6 revelam, de forma global, bons índices de fiabilidade e validade do instrumento."

Geologia e geometalurgia dos minérios de fosfato na base do manto de intemperismo da mina do Barreiro, Araxá

Tese (doutorado)—Universidade de Brasília, Instituto de Geociências, Programa de Pós-Graduação em Geologia, 2015.

Efecto antiinflamatorio de extractos metanólicos de plantas de Azuay y Loja (Ecuador) a través del modelo de peces cebra

Los peces cebra son utilizados como modelo biológico para screening primario de extractos de plantas con potencial bioactividad, aprovechando sus similitudes: genética, fisiológica y respuesta farmacológica con los mamíferos. En el estudio se empleó este modelo para valorar la actividad antiinflamatoria de 36 extractos metanólicos de plantas medicinales utilizadas en las provincias de Azuay y Loja (Ecuador). Parte del material vegetal fue recolectado con el aporte de una hierbatera de etnia Saraguro. Los extractos fueron preparados por percolación y su toxicidad fue evaluada en peces cebra en concentraciones variables de 400 a 3,125 μg/ml, determinándose la máxima concentración tolerada para cada uno de ´estos. La actividad antiinflamatoria se evaluó a través del ensayo de migración leucocitaria inducida por lipopolisacárido de Sallmonella typhi. Los extractos de: Cestrum aff. peruvianum, Galinsoga parviflora, Galium sp., Oenothera tetraptera, Peperomia aff. galioides , Passiflora ampullaceae y Ambrosia arborescens, correspondientes al 18,92% de los analizados, mostraron un potencial antiinflamatorio comparable con indometacina y dexametasona; siendo el extracto metanólico de Cestrum aff. peruvianum el más relevante a 50 g/ml. El análisis fitoquímico básico de los extractos se realizó por cromatografía de capa fina, evidenciándose la presencia de saponinas y terpenoidoes como compuestos principales en la mayoría de los extractos.

Caracterização ambiental de bancos areno-lamosos nos campos petrolíferos de Macau e Serra (RN), como subsídio às medidas mitigadoras ao processo erosivo

On Rio Grande do Norte northern coast the process of sediment transport are intensely controlled by wind and sea (waves and currents) action, causing erosion and shoreline morphological instability. Due to the importance of such coastal zone it was realized the multi-spectral mapping and physical-chemical characterization of mudflats and mangroves aiming to support the mitigating actions related to the containment of the erosive process on the oil fields of Macau and Serra installed at the study area. The multi-spectral bands of 2000 and 2008 LANDSAT 5 TM images were submitted on the several digital processing steps and RGB color compositions integrating spectral bands and Principal Components. Such processing methodology was important to the mapping of different units on surface, together with field works. It was possible to make an analogy of the spectral characteristics of wetlands with vegetations areas (mangrove), showing the possibility to make a restoration of this area, contributing with the environmental monitoring of that ecosystem. The maps of several units were integrated in GIS environment at 1:60,000 scale, including the classification of features according to the presence or absence of vegetation cover. Thus, the strategy of methodology established that there are 10.13 km2 at least of sandy-muddy and of these approximately 0.89 km2 with the possibility to be used in a reforestation of typical flora of mangrove. The physical-chemical characterization showed areas with potential to introduce local species of mangrove and they had a pH above neutral with a mean of 8.4. The characteristic particle size is sand in the fine fractions, the high levels of carbonate, organic matter and major and trace element in general are concentrated where the sediment had the less particles size, showing the high correlation that those elements have with smaller particles of sediment. The application of that methodological strategy is relevant to the better understanding of features behavior and physical-chemical data of sediment samples collected on field allow the analysis of efficiency/capability of sandy-muddy to reforestation with local mangrove species for mitigation of the erosive action and coastal processes on the areas occupied by the oil industry

Metodologias estatísticas aplicadas a dados de análises químicas da água produzida em um campo maduro de petróleo

Produced water is characterized as one of the most common wastes generated during exploration and production of oil. This work aims to develop methodologies based on comparative statistical processes of hydrogeochemical analysis of production zones in order to minimize types of high-cost interventions to perform identification test fluids - TIF. For the study, 27 samples were collected from five different production zones were measured a total of 50 chemical species. After the chemical analysis was applied the statistical data, using the R Statistical Software, version 2.11.1. Statistical analysis was performed in three steps. In the first stage, the objective was to investigate the behavior of chemical species under study in each area of production through the descriptive graphical analysis. The second step was to identify a function that classify production zones from each sample, using discriminant analysis. In the training stage, the rate of correct classification function of discriminant analysis was 85.19%. The next stage of processing of the data used for Principal Component Analysis, by reducing the number of variables obtained from the linear combination of chemical species, try to improve the discriminant function obtained in the second stage and increase the discrimination power of the data, but the result was not satisfactory. In Profile Analysis curves were obtained for each production area, based on the characteristics of the chemical species present in each zone. With this study it was possible to develop a method using hydrochemistry and statistical analysis that can be used to distinguish the water produced in mature fields of oil, so that it is possible to identify the zone of production that is contributing to the excessive elevation of the water volume.

Comparison of Computer-Based and Optical Face Recognition Paradigms

The main objectives of this thesis are to validate an improved principal components analysis (IPCA) algorithm on images; designing and simulating a digital model for image compression, face recognition and image detection by using a principal components analysis (PCA) algorithm and the IPCA algorithm; designing and simulating an optical model for face recognition and object detection by using the joint transform correlator (JTC); establishing detection and recognition thresholds for each model; comparing between the performance of the PCA algorithm and the performance of the IPCA algorithm in compression, recognition and, detection; and comparing between the performance of the digital model and the performance of the optical model in recognition and detection. The MATLAB © software was used for simulating the models. PCA is a technique used for identifying patterns in data and representing the data in order to highlight any similarities or differences. The identification of patterns in data of high dimensions (more than three dimensions) is too difficult because the graphical representation of data is impossible. Therefore, PCA is a powerful method for analyzing data. IPCA is another statistical tool for identifying patterns in data. It uses information theory for improving PCA. The joint transform correlator (JTC) is an optical correlator used for synthesizing a frequency plane filter for coherent optical systems. The IPCA algorithm, in general, behaves better than the PCA algorithm in the most of the applications. It is better than the PCA algorithm in image compression because it obtains higher compression, more accurate reconstruction, and faster processing speed with acceptable errors; in addition, it is better than the PCA algorithm in real-time image detection due to the fact that it achieves the smallest error rate as well as remarkable speed. On the other hand, the PCA algorithm performs better than the IPCA algorithm in face recognition because it offers an acceptable error rate, easy calculation, and a reasonable speed. Finally, in detection and recognition, the performance of the digital model is better than the performance of the optical model.

The use of computer technology to compare and analyze community college dissertations

A purpose of this research study was to demonstrate the practical linguistic study and evaluation of dissertations by using two examples of the latest technology, the microcomputer and optical scanner. That involved developing efficient methods for data entry plus creating computer algorithms appropriate for personal, linguistic studies. The goal was to develop a prototype investigation which demonstrated practical solutions for maximizing the linguistic potential of the dissertation data base. The mode of text entry was from a Dest PC Scan 1000 Optical Scanner. The function of the optical scanner was to copy the complete stack of educational dissertations from the Florida Atlantic University Library into an I.B.M. XT microcomputer. The optical scanner demonstrated its practical value by copying 15,900 pages of dissertation text directly into the microcomputer. A total of 199 dissertations or 72% of the entire stack of education dissertations (277) were successfully copied into the microcomputer's word processor where each dissertation was analyzed for a variety of syntax frequencies. The results of the study demonstrated the practical use of the optical scanner for data entry, the microcomputer for data and statistical analysis, and the availability of the college library as a natural setting for text studies. A supplemental benefit was the establishment of a computerized dissertation corpus which could be used for future research and study. The final step was to build a linguistic model of the differences in dissertation writing styles by creating 7 factors from 55 dependent variables through principal components factor analysis. The 7 factors (textual components) were then named and described on a hypothetical construct defined as a continuum from a conversational, interactional style to a formal, academic writing style. The 7 factors were then grouped through discriminant analysis to create discriminant functions for each of the 7 independent variables. The results indicated that a conversational, interactional writing style was associated with more recent dissertations (1972-1987), an increase in author's age, females, and the department of Curriculum and Instruction. A formal, academic writing style was associated with older dissertations (1972-1987), younger authors, males, and the department of Administration and Supervision. It was concluded that there were no significant differences in writing style due to subject matter (community college studies) compared to other subject matter. It was also concluded that there were no significant differences in writing style due to the location of dissertation origin (Florida Atlantic University, University of Central Florida, Florida International University).

Elemental Analysis and Forensic Comparison of Soils by Laser-Induced Breakdown Spectroscopy (LIBS) and Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS)

The elemental analysis of soil is useful in forensic and environmental sciences. Methods were developed and optimized for two laser-based multi-element analysis techniques: laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and laser-induced breakdown spectroscopy (LIBS). This work represents the first use of a 266 nm laser for forensic soil analysis by LIBS. Sample preparation methods were developed and optimized for a variety of sample types, including pellets for large bulk soil specimens (470 mg) and sediment-laden filters (47 mg), and tape-mounting for small transfer evidence specimens (10 mg). Analytical performance for sediment filter pellets and tape-mounted soils was similar to that achieved with bulk pellets. An inter-laboratory comparison exercise was designed to evaluate the performance of the LA-ICP-MS and LIBS methods, as well as for micro X-ray fluorescence (μXRF), across multiple laboratories. Limits of detection (LODs) were 0.01-23 ppm for LA-ICP-MS, 0.25-574 ppm for LIBS, 16-4400 ppm for µXRF, and well below the levels normally seen in soils. Good intra-laboratory precision (≤ 6 % relative standard deviation (RSD) for LA-ICP-MS; ≤ 8 % for µXRF; ≤ 17 % for LIBS) and inter-laboratory precision (≤ 19 % for LA-ICP-MS; ≤ 25 % for µXRF) were achieved for most elements, which is encouraging for a first inter-laboratory exercise. While LIBS generally has higher LODs and RSDs than LA-ICP-MS, both were capable of generating good quality multi-element data sufficient for discrimination purposes. Multivariate methods using principal components analysis (PCA) and linear discriminant analysis (LDA) were developed for discriminations of soils from different sources. Specimens from different sites that were indistinguishable by color alone were discriminated by elemental analysis. Correct classification rates of 94.5 % or better were achieved in a simulated forensic discrimination of three similar sites for both LIBS and LA-ICP-MS. Results for tape-mounted specimens were nearly identical to those achieved with pellets. Methods were tested on soils from USA, Canada and Tanzania. Within-site heterogeneity was site-specific. Elemental differences were greatest for specimens separated by large distances, even within the same lithology. Elemental profiles can be used to discriminate soils from different locations and narrow down locations even when mineralogy is similar.

Professor gender, age, and “hotness” in influencing college students’ generation and interpretation of professor ratings

Undergraduate psychology students rated expectations of a bogus professor (randomly designated a man or woman and hot versus not hot) based on an online rating and sample comments as found on RateMyProfessors.com (RMP). Five professor qualities were derived using principal components analysis (PCA): dedication, attractiveness, enhancement, fairness, and clarity. Participants rated current psychology professors on the same qualities. Current professors were divided based on gender (man or woman), age (under 35 or 35 and older), and attractiveness (at or below the median or above the median). Using multivariate analysis of covariance (MANCOVA), students expected hot professors to be more attractive but lower in clarity. They rated current professors as lowest in clarity when a man and 35 or older. Current professors were rated significantly lower in dedication, enhancement, fairness, and clarity when rated at or below the median on attractiveness. Results, with previous research, suggest numerous factors, largely out of professors’ control, influencing how students interpret and create professor ratings. Caution is therefore warranted in using online ratings to select courses or make hiring and promotion decisions.