Component Analysis

Twenty nine germplasm lines of Chenopodium quinoa and two of Chenopodium berlandieri subsp. nuttalliae were evaluated for 12 morphological and 7 quality traits for two test seasons. The 19 traits were analyzed for cluster and principal component analysis. The first four PCs contributed 78.70 % of the variability among the germplasm lines. The first PC accounted for 39.5% of the variation and had inflorescence/plant, plant height and stem diameter as the traits with largest coefficients, all with positive sign. The characters with greatest positive weight on PC2 were days to maturity (0.309), inflorescence length (0.260) and branches/plant. All the germplasm lines were grouped into six clusters based on average linkage method. Cluster III had high values for seed yield and most of the quality traits but showed a small seed size. The dendrogram separated the two lines of C. berlandieri subsp. nuttalliae from the quinoa lines.

... Con-sidering that the Superior Province was constructed largely from the addition of mantle-derived material between 3100 and 2600 Ma (Card 1990) and that the Grenville Province comprises tectonically stacked slices of reworked Archean and Proterozoic rock assemblages ...

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.

Data compression is the most important step in many signal processing and pattern recogni- tion applications. We come across very high dimensional data in such applications. Before processing of large-dimensional datasets, we need to reduce the dimensions to have lesser storage space and reduced computational complexities while retaining the maximum information. Principal Component Analysis (PCA) is one such technique that

A new windows based graphical tool to facilitate the teaching and learning the symmetrical components analysis is described In this paper. This software provides a user-friendly environment to aid the studies of symmetrical components. The software calculates and displays graphically the ABC sequence and the corresponding phasors of symmetrical components. Taking the advantages of the graphical user interface (GUI), it provides the student with interactive visual communication to analyze and better understand the relationship between the ABC sequence and symmetrical components. Students can manipulate the graphical displays either using keyboard input or mouse operation. Besides, students can use this tool to analyze the unsymmetrical short circuit fault currents. It is hoped that this tool makes the learning process more interactive, interesting and user friendly.

The key applications of sparse signal processing are sampling, coding, spectral estimation, array processing, component analysis, and multipath channel estimation. In terms of reconstruction algorithms, linkages are made with random sampling, compressed sensing and rate of innovation. The redundancy introduced by channel coding in finite/real Galois fields is then related to sampling with similar reconstruction algorithms. The methods of Prony, Pisarenko, and MUSIC are next discussed for sparse frequency domain representations. Specifically, the relations of the approach of Prony to an annihilating filter and Error Locator Polynomials in coding are emphasized; the Pisarenko and MUSIC methods are further improvements of the Prony method. Such spectral estimation methods is then related to multi-source location and DOA estimation in array processing. The notions of sparse array beamforming and sparse sensor networks are also introduced. Sparsity in unobservable source signals is also shown to facilitate source separation in SCA; the algorithms developed in this area are also widely used in compressed sensing. Finally, the multipath channel estimation problem is shown to have a sparse formulation; algorithms similar to sampling and coding are used to estimate OFDM channels.

The modified Scleroderma Health Assessment Questionnaire (SSc HAQ) is a functional score to assess systemic sclerosis (SSc) comprising the HAQ disease index (HAQ-DI) plus five specific visual analogue scales (VAS). Since it was validated in English-speaking patients only, its general use in any other language necessitates prior cross-cultural adaptation and validation. We designed this study to assess its value in French-speaking patients and to validate the French version according to international recommendations. We elaborated a French version using the “forward-backward” method. We then validated its psychometric properties with 100 consecutive SSc French-speaking patients who had undergone simultaneous clinical and paraclinical examination. In addition, we calculated the SSc HAQ score, a new outcome measure, which is obtained by pooling the eight domains from the HAQ-DI with the five organ VAS. Our study confirmed the psychometric properties of the SSc HAQ in non-English-speaking patients with (a) structural validity: the major component analysis, performed on the HAQ-DI and the five VAS, yielding a two-factor structure; (b) convergent validity: with high correlation coefficients between the SSc HAQ score and the physical component score of the SF-36 (r=−0.74, p<0.0001); (c) discriminant validity: the SSc HAQ score was better in patients with limited than with diffuse SSc (0.5±0.5 vs 1.1±0.7, respectively, p<0.0001) in relation to the number of clinical involvements; (d) reproducibility was high using the test-retest procedure (r=0.98). This study showed the value of the SSc HAQ, which is a simple, discriminant, reproducible self-administered questionnaire to evaluate French-speaking SSc patients. In addition, we suggest the use of a new outcome measure, the SSc HAQ score, to assess this systemic disease more accurately.

This work consisted of two complementary sets of experiments in which breads differing in their recipe and/or process were characterised according to their odorant perception, volatile compound composition and physical properties. The results revealed that commercial partially baked and/or partially baked frozen breads were characterised by a different odour compared to commercial conventional, fully baked frozen and frozen dough breads,