Fast Haar Transform Based Feature Extraction for Face Representation and Recognition

Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications and additions, which makes the projection process computationally expensive. To tackle this problem, this paper proposes two simple-but-effective fast subspace learning and image projection methods, fast Haar transform (FHT) based principal component analysis and FHT based spectral regression discriminant analysis. The advantages of these two methods result from employing both the FHT for subspace learning and the integral vector for feature extraction. Experimental results on three face databases demonstrated their effectiveness and efficiency.

Selection for variables in quantitative structure-activity/property relationship studies - Comparison between methods of orthogonal descriptors and leaps-and-bounds regression analysis

In this paper, the comparison of orthogonal descriptors and Leaps-and-Bounds regression analysis is performed. The results obtained by using orthogonal descriptors are better than that obtained by using Leaps-and-Bounds regression for the data set of nitrobenzenes used in this study. Leaps-and-Bounds regression can be used effectively for selection of variables in quantitative structure-activity/property relationship(QSAR/QSPR) studies. Consequently, orthogonalisation of descriptors is also a good method for variable selection for studies on QSAR/QSPR.

Prediction of molar absorptivities of color reagents during their color reactions with cerium using multiple regression analysis and neural network

A quantitative structure-property study has been made on the relationship between molar absorptivities (epsilon) of asymmetrical phosphone bisazo derivatives of chromotropic acid and their color reactions with cerium by multiple regression analysis and neural network. The new topological indices A(x1) - A(x3) suggested in our laboratory and molecular connectivity indices of 43 compounds have been calculated. The results obtained from the two methods are compared. The neural network model is superior to the regression analysis technique and gave a prediction which was sufficiently accurate to estimate the molar absorptivities of color reagents during their color reactions with cerium.

Quantitative structure-property relationships for colour reagents and their colour reactions with ytterbium using regression analysis and computational neural networks

In this paper, the new topological indices A(x1)-A(x3) suggested in our laboratory and molecular connectivity indices have been applied to multivariate analysis in structure-property studies. The topological indices of twenty asymmetrical phosphono bisazo derivatives of chromotropic acid have been calculated. The structure-property relationships between colour reagents and their colour reactions with ytterbium have been studied by A(x1)-A(x3) indices and molecular connectivity indices with satisfactory results. Multiple regression analysis and neural networks were employed simultaneously in this study.

QUANTITATIVE STRUCTURE-ACTIVITY-RELATIONSHIPS FOR TOXICITY OF PHENOLS USING REGRESSION-ANALYSIS AND COMPUTATIONAL NEURAL NETWORKS

Quantitative structure-toxicity models were developed that directly link the molecular structures of a et of 50 alkYlated and/or halogenated phenols with their polar narcosis toxicity, expressed as the negative logarithm of the IGC50 (50% growth inhibitor

Plot Erosion Model Using Gray Relational Analysis Method

The main factors affecting interrill erosion-including runoff discharge, rainfall intensity, mean flow velocity, and slope gradient-were analyzed by using a gray relational analysis. An equation for interrill erosion was derived by coupling this analysis with dimensional and regression analyses. The values of erosion rates predicted by this equation were in good agreement with experimental observations.

Spatial analysis for spring bloom and nutrient limitation in Xiangxi bay of three Gorges Reservoir

The spatial and temporal dynamics of physical variables, inorganic nutrients and phytoplankton chlorophyll a were investigated in Xiangxi Bay from 23 Feb. to 28 Apr. every six days, including one daily sampling site and one bidaily sampling site. The concentrations of nutrient variables showed ranges of 0.02-3.20 mg/L for dissolved silicate (Si); 0.06-2.40 mg/L for DIN (NH4N + NO2N + NO3N); 0.03-0.56 mg/L for PO4P and 0.22-193.37 mu g/L for chlorophyll a, respectively. The concentration of chlorophyll a and inorganic nutrients were interpolated using GIS techniques. The results indicated that the spring bloom was occurred twice in space during the whole monitoring period (The first one: 26 Feb.-23 Mar.; the second one: 23 Mar.-28 Apr.). The concentration of DIN was always high in the mouth of Xiangxi Bay, and PO4P was high in the upstream of Xiangxi Bay during the whole bloom period. Si seems no obvious difference in space in the beginning of the spring bloom, but showed high heterogeneity in space and time with the development of spring bloom. By comparing the interpolated maps of chlorophyll a and inorganic variables, obvious consumptions of Si and DIN were found when the bloom status was serious. However, no obvious depletion of PO4P was found. Spatial regression analysis could explained most variation of Chl-a except at the begin of the first and second bloom. The result indicated that Si was the factor limiting Chl-a in space before achieved the max area of hypertrophic in the first and second bloom period. When Si was obviously exhausted, DIN became the factor limiting the Chl-a in space. Daily and bidaily monitoring of Site A and B, representing for high DIN: PO4P ratio and low DIN:PO4P ratio, indicated that the concentration of Si was decreased with times at both site A and B, and the dramatically drop of DIN was found in the end monitoring at site B. Multiple stepwise regression analysis indicated that Si was the most important factor affect the development of spring bloom both at site A and B in time series.

Correlation analysis of the structures and stability constants of gadolinium(III) complexes

To simplify the abstraction of descriptors, for the correlation analysis of the stability constants of gadolinium(III) complexes and their ligand structures, aiming at gadolinium(III) complexes, we only considered the ligands and ignored the common parts of the structures, i.e., the metal ions. Quantum-chemical descriptors and topological indices were calculated to describe the structures of the ligands. Multiple regression analysis and neural networks were applied to construct the models between the ligands and the stability constants of gadolinium(III) complexes and satisfactory results were obtained.

Correlation analysis of the structures and pK(a) values of carboxylic acids

The quantum-chemical descriptors were used for QSPR study of the structures of carboxylic acids and their pK(a) values. The algorithm of "Leaps and Bounds" regression was performed for selection of the variables. The CoMFA method was carried out for 3D-QSPR. As the introduction of the charge of oxygen atom(Q(2)), the results obtained by CoMFA were improved greatly.

Correlation analysis of the structures and gas-liquid chromatographic retention indices of amines

Quantitative structure-retention relationship(QSRR) was studied for amines to gas-liquid chromatography on three stationary phases of different polarities with the topological indices A(m) (A(m1), A(m2), A(m3)) and gravitational index GI. The algorithm of "Leaps and Bounds" was performed for selection of the variables. And the multi-regression and the quasi-Newton neural networks were employed for the calculation with better results.

Quantitative structure-property relationship research to the analysis of photoionization sensitivity of organic compounds in gas chromatography

The A(m) index and molecular connectivity index were used for studying the photoionization sensitivity of some organic compounds in gas chromatography. The analysis of structure-property relationship between the photoionization sensitivity of the compounds and the A(m) indices or molecular connectivity indices has been carried out. The genetic algorighm was used to build the correlation model in this field. The results demonstrate that the property of compounds can be described by both A(m) indices and molecular connectivity indices, and the mathematical model obtained by the genetic algorithm was better than that by multivariate regression analysis.

Using otolith weight to predict the age of Pennahia macrocephalus in the mouth of the Beibu Gulf

The relation between otolith weight (OW) and the age of marine fish is studied. A total of 222 individuals of bighead white croaker, Pennahia macrocephalus were sampled seasonally in the mouth of the Beibu Gulf, the South China Sea, in 2007. Since there are no significant differences in sagittal OW between otolith in pairs (Pa parts per thousand yen0.05), the undamaged left sagittal otolith is used for age determination. The highest correlations among standard length, OW and fish ages are confirmed by linear, exponential and multinomial regression. Results show that sagittal OW overlaps only occasionally among age groups, and to individuals with similar standard length, the older and slower-growing fish has a heavier otolith because of the continued otolith material deposition. There are differences in sagittal OW among different age groups and significant positive linear relationship with age (P < 0.05). The age readings can be verified by plotting the sagittal OW versus the standard length for age groups, and the individuals with similar standard length but in different ages can be separated by sagittal OW frequency analysis. Mostly, the predicted ages using the regression between sagittal OW and ages are closed to the observed ages by counting annulus on scale. It indicates that the sagittal OW analysis is a useful technique for validating the accuracy of age determination by annuli counts, especially for individuals of similar size. Furthermore, the technique is applied for Pennahia macrocephalus with discussion in this paper.

Quantitative traits correlative analysis and growth comparison among different populations of bay scallop, Argopecten irradians

The shell traits and weight traits are measured in cultured populations of bay scallop, Argopecten irradians. The results of regression analysis show that the regression relationships for all the traits are significant (P < 0.01). The correlative coefficients between body weight, as well as tissue weight with shell length, shell height and shell width are significant (P < 0.05). But the correlative coefficients between the anterior and posterior auricle length with body weight as well as tissue weight are not significant (P > 0.05). The multiple regression equation is obtained to estimate live body weight and tissue weight. The above traits except anterior and posterior auricle length are used for the growth and production comparison among three cultured populations, Duncan's new multiple range procedure analysis shows that all the traits in the Lingshuiqiao (LSQ) population are much more significant than those of the other two populations (P < 0.01), and there is no significant difference between the Qipanmo (QPM) and Dalijia (DLJ) populations in all traits (P > 0.05). The results indicate that the LSQ population has a higher growth rate and is expected to be more productive than the other two populations.