Bit-Width Analysis for General Applications

It has been widely known that a significant part of the bits are useless or even unused during the program execution. Bit-width analysis targets at finding the minimum bits needed for each variable in the program, which ensures the execution correctness and resources saving. In this paper, we proposed a static analysis method for bit-widths in general applications, which approximates conservatively at compile time and is independent of runtime conditions. While most related work focus on integer applications, our method is also tailored and applicable to floating point variables, which could be extended to transform floating point number into fixed point numbers together with precision analysis. We used more precise representations for data value ranges of both scalar and array variables. Element level analysis is carried out for arrays. We also suggested an alternative for the standard fixed-point iterations in bi-directional range analysis. These techniques are implemented on the Trimaran compiler structure and tested on a set of benchmarks to show the results.

An analysis of the management of a public sector project: a systems-based case study

The management of a public sector project is analysed using a model developed from systems theory. Linear responsibility analysis is used to identify the primary and key decision structure of the project and to generate quantitative data regarding differentiation and integration of the operating system, the managing system and the client/project team. The environmental context of the project is identified. Conclusions are drawn regarding the project organization structure's ability to cope with the prevailing environmental conditions. It is found that the complexity of the managing system imposed on the project was unable to achieve this and created serious deficiencies in the outcome of the project.

Organizational analysis of building projects

The principles of organization theory are applied to the organization of construction projects. This is done by proposing a framework for modelling the whole process of building procurement. This consists of a framework for describing the environments within which construction projects take place. This is followed by the development of a series of hypotheses about the organizational structure of construction projects. Four case studies are undertaken, and the extent to which their organizational structure matches the model is compared to the level of success achieved by each project. To this end there is a systematic method for evaluating the success of building project organizations, because any conclusions about the adequacy of a particular organization must be related to the degree of success achieved by that organization. In order to test these hypotheses, a mapping technique is developed. The technique offered is a development of a technique known as Linear Responsibility Analysis, and is called "3R analysis" as it deals with roles, responsibilities and relationships. The analysis of the case studies shows that they tended to suffer due to inappropriate organizational structure. One of the prevailing problems of public sector organization is that organizational structures are inadequately defined, and too cumbersome to respond to environmental demands on the project. The projects tended to be organized as rigid hierarchies, particularly at decision points, when what was required was a more flexible, dynamic and responsive organization. The study concludes with a series of recommendations; including suggestions for increasing the responsiveness of construction project organizations, and reducing the lead-in times for the inception periods.

On the role of the ocean in projected atmospheric stability changes in the Atlantic polar low region

The occurrence of destructive mesoscale ‘polar low’ cyclones in the subpolar North Atlantic is projected to decline under anthropogenic change, due to an increase in atmospheric static stability. This letter reports on the role of changes in ocean circulation in shaping the atmospheric stability. In particular, the Atlantic Meridional Overturning Circulation (AMOC) is projected to weaken in response to anthropogenic forcing, leading to a local minimum in warming in this region. The reduced warming is restricted to the lower troposphere, hence contributing to the increase in static stability. Linear correlation analysis of the CMIP3 climate model ensemble suggests that around half of the model uncertainty in the projected stability response arises from the varied response of the AMOC between models.

ENHANCING MULTISCALE FRACTAL DESCRIPTORS USING FUNCTIONAL DATA ANALYSIS

This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.

Análise dinâmica de vigas assimétricas em curva com parede fina e aberta submetidas a ação de carga móveis

Fundamentalmente, o presente trabalho faz uma análise elástica linear de pontes ou vigas curvas assimétricas de seção transversal aberta e de parede fina, com propriedades físicas, geométricas e raio de curvatura constantes ao longo do eixo baricêntrico. Para tanto, utilizaram-se as equações diferenciais de VLASOV considerando o acoplamento entre as deformações nas direções vertical, transversal, axial de torcão nal. Na solução do sistema de quatro equações com derivadas parciais foi utilizado um apropriado método numérico de integração (Diferenças Finitas Centrais). A análise divide-se, basicamente, em dois tipos: análise DINÂMICA e ESTATICA. Ambas são utilizadas também na determinação do coeficiente de impacto (C.M.D.). A primeira refere-se tanto na determinação das características dinâmicas básicas (frequências naturais e respectivos modos de vibração), como também na determinação da resposta dinâmica da viga, em tensões e deformações, para cargas móveis arbitrárias. Vigas com qualquer combinação das condições de contorno, incluindo bordos rotulados e engastados nas três direções de flexão e na torção, são consideradas. 0s resultados da análise teórica, obtidos pela aplicação de programas computacionais implementados em microcomputador (análise estática) e no computador B-6700 (análise dinâmica), são comparados tanto com os da bibliografia técnica como também com resultados experimentais, apresentando boa correlação.

Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.

Comparação entre análises para permanência no rebanho de vacas Nelore utilizando modelo linear e modelo de limiar

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Thermodynamic properties applied to the sorption isotherms of kiwifruit

The net isosteric heat and entropy of water sorption were calculated for kiwifruit, based on sorption isotherms obtained by the static gravimetric method at different temperatures (20 to 70 degreesC). The Guggenheim-Anderson-deBoer equation was fitted to the experimental data, using direct non-linear regression analysis; the agreement between experimental and calculated values was satisfactory. The net isosteric heat of sorption was estimated from equilibrium sorption data, using the Clausius-Clapeyron equation. Isosteric heats of sorption were found to increase with increasing temperature and could be well adjusted by an exponential relationship. The enthalpy-entropy compensation theory was applied to sorption isotherms and plots of DeltaH versus DeltaS provided the isokinetic temperature, T-B = 450.9 +/- 7.7 K, indicating an enthalpy-controlled desorption process over the whole range of moisture content considered.

Determinantes da evolução do peso e altura em crianças de 3 meses a 6 anos assistidas em creche: Análise por modelo linear não hierarquizado em ensaio quase-experimental

Objective. To assess factors determining growth in a group of children between 3 months and 6 years old enrolled in a public municipal (i.e., government-supported, not private) day-care center, in comparison to a group of children with similar characteristics but who were not enrolled in the center. Methods. A quasi-experimental study was designed to observe 444 children aged 3 to 72 months from a low-income neighborhood in the city of Sorocaba, in the state of São Paulo, Brazil. Two groups were studied: 164 children enrolled in a local municipal day-care center (intervention group) and 280 not receiving care at the center (nonintervention, comparison group) but instead being cared for at home. Both groups were seen four times over a period of 16 months. At each observation session, the children's weight and height were measured. Information was also collected on the mother's sociodemographic characteristics and the illnesses she had suffered as well as the child's weight and other health characteristics at birth, the child's illnesses in the 15 days before each observation, and any hospitalizations. Results. The children in both groups were from low-income families, with 65% of the families having an average monthly income below US$ 100; 80% of the mothers had received 8 years of schooling or less. Multivariate linear regression analysis showed that at the first observation (just before enrollment in the day-care center), birth weight was the only factor that explained the nutritional differences between the two groups. Subsequent analyses showed that being in day care was the factor that best explained the differences between the groups, especially in terms of the adequacy of weight for age, after controlling for birthweight, sex, age at the beginning of the study, and illnesses in the 15 days before an observation session. The nutritional impact of the intervention was significant as early as 3 months after being enrolled in day care. Conclusions. The nutritional benefits of the care provided at the center outweighed the negative effects sometimes seen in such centers, such as the greater morbidity that children in day-care centers often experience in comparison to children receiving care at home.

Estudo dos critérios de falhas em compósitos PPS/fibras de carbono utilizando elementos finitos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Context-sensitive analysis of x86 obfuscated executables

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs

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.

Quantitative Chemical Profile and Multivariate Statistical Analysis of Alembic Distilled Sugarcane Spirit Fractions

Concentrations of 39 organic compounds were determined in three fractions (head, heart and tail) obtained from the pot still distillation of fermented sugarcane juice. The results were evaluated using analysis of variance (ANOVA), Tukey's test, principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). According to PCA and HCA, the experimental data lead to the formation of three clusters. The head fractions give rise to a more defined group. The heart and tail fractions showed some overlap consistent with its acid composition. The predictive ability of calibration and validation of the model generated by LDA for the three fractions classification were 90.5 and 100%, respectively. This model recognized as the heart twelve of the thirteen commercial cachacas (92.3%) with good sensory characteristics, thus showing potential for guiding the process of cuts.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.