Wyniki wyszukiwania - BazTech

1

Geochemistry of surface sediments from the northwestern Gulf of Mexico : implications for provenance and heavy metal contamination

Armstrong-Altrin John S., Botello Alfonso V., Villanueva Susana F., Soto Luis A.

Geological Quarterly

|

2019

|

Vol. 63, No. 3

522--538

EN

Thirty-five near-surface sediment samples were recovered from the continental shelf and upper slope regions of the north-western (NW) Gulf of Mexico. The geochemical data of the sediments recovered were examined to investigate the weathering intensity, provenance, palaeo-oxygenation condition, and level of heavy metal contamination. The sediments analysed showed a moderate to high intensity of chemical weathering. Major and trace element concentrations indicated a terrigenous origin, closely related to the weathering of rocks rich in aluminosilicates. The results of this study further revealed that major rivers, the Bravo and Soto La Marina, played an important role in delivering sediments to the study area. The concentration of transition trace elements such as Cr, Cu, Ni, and V revealed that the sediments were derived from intermediate rocks such as andesite. The V/Cr, Ni/Co, and Cu/Zn ratios in the sediments were <2, <5, and <1, respectively, suggesting a depositional process occurred under well-oxygenated conditions. Principle Component Analysis (PCA) did not show a significant difference in sediment texture between the continental shelf and slope areas. The enrichment factor (EF) and Geo-accumulation index (lgeo) values were <2 and <1, respectively, suggesting the absence of an anthropogenic input.

2

Underdetermined Blind Separation using modified subspace-based algorithm in the time-frequency domain

Li H., Shen Y-H., Cao M., Wang J-G.

Przegląd Elektrotechniczny

|

2011

|

R. 87, nr 7

280-283

EN

To solve the underdetermined blind separation (UBSS) problem, Aissa-El-Bey et al. have proposed the significant subspace-based algorithms in the time-frequency (TF) domain, where a fixed (maximum) value of K, i.e., the number of active sources overlapping at any TF point, is considered for simplicity. In this paper, based on the principle component analysis (PCA) technology, we propose a modified algorithm by estimating the number K for selected frequency bins where most energy is concentrated. Improved performances are obtained without increasing complexity.

PL

Do rozwiązania problem nieokreślonej ślepej separacji (UBSS) Aissa-El_Bey zaproponował algorytm czasowo-częstotliwościowy gdzie ustalono liczbę aktywnych źródeł pokrywających każdy punkt TF. W artykule zaproponowano zmodyfikowany algorytm bazujący na analizie składowej głównej PCA. Otrzymano poprawę parametrów bez powiększania skomplikowania metody.

3

PCA based modification of SIFT-like methods for object class recognition

Owczarek A.

Challenges of Modern Technology

|

2011

|

Vol. 2, no. 1

23--26

EN

This paper discusses a novel PCA based modification of standard SIFT and PCA-SIFT algorithms for the purpose of object class recognition. New descriptors intended to be simultaneously distinctive enough to describe the difference between features belonging to separate categories and general enough to capture the variations among features from the same class are proposed. The experimental results, gained for a test database, showing the reliability of introduced approach are presented.

4

Kernel Based Subspace Methods : Infrared vs Visible Face Recognition

Shahbe M. D., Hati S.

Machine Graphics and Vision

|

2009

|

Vol. 18, No. 1

47-66

EN

This paper investigates the use of kernel theory in two well-known, linear-based subspace representations: Principle Component Analysis (PCA) and Fisher's Linear Discriminant Analysis (FLD). The kernel-based method provides subspaces of high-dimensional feature spaces induced by some nonlinear mappings. The focus of this work is to evaluate the performances of Kernel Principle Component Analysis (KPCA) and Kernel Fisher's Linear Discriminant Analysis (KFLD) for infrared (IR) and visible face recognition. The performance of the kernel-based subspace methods is compared with that of the conventional linear algorithms: PCA and FLD. The main contribution of this paper is the evaluation of the sensitivities of both IR and visible face images to illumination conditions, facial expressions and facial occlusions caused by eyeglasses using the kernel-based subspace methods.