Trends in bulk electron-structural features of early transition-metal carbides

A detailed and systematic density-functional theory (DFT) study of a series of early transition-metal carbides (TMC's) in the NaCl structure is presented. The focus is on the trends in the electronic structure and nature of bonding, which are essential for the understanding of the reactivity of TMC's. The employed approach is based on a thorough complementary analysis of the electron density differences, the density of states (DOS), the band structure, and the real-space wave functions to gain insight into the bonding of this class of materials and get a more detailed picture of it than previously achieved, as the trend study allows for a systematic identification of the bond character along the different bands. Our approach confirms the presence of both the well-known TM--C and TM--TM bonds and, more importantly, it shows the existence and significance of direct C--C bonds in all investigated TMC's, which are frequently neglected but have been recently identified in some cases [Solid State Commun. 121, 411 (2002); Phys. Rev. B 75, 235438 (2007)]. New information on the spatial extent of the bonds, their \textit{k}-space location within the band structure, and their importance for the bulk cohesion is provided. Trends in covalency and ionicity are presented. The resulting electron-structural trends are analyzed and discussed within a two-level model

Evaluation of Statistical Features for Medical Image Retrieval

In this paper we present a complete system allowing the classification of medical images in order to detect possible diseases present in them. The proposed method is developed in two distinct stages: calculation of descriptors and their classification. In the first stage we compute a vector of thirty-three statistical features: seven are related to statistics of the first level order, fifteen to that of second level where thirteen are calculated by means of co-occurrence matrices and two with absolute gradient; the last thirteen finally are calculated using run-length matrices. In the second phase, using the descriptors already calculated, there is the actual image classification. Naive Bayes, RBF, Support VectorMa- chine, K-Nearest Neighbor, Random Forest and Random Tree classifiers are used. The results obtained from the proposed system show that the analysis carried out both on textured and on medical images lead to have a high accuracy

Statistical Features for Image Retrieval: A Quantitative Comparison

In this paper we present a comparison between various statistical descriptors and analyze their goodness in classifying textural images. The chosen statistical descriptors have been proposed by Tamura, Battiato and Haralick. In this work we also test a combination of the three descriptors for texture analysis. The databases used in our study are the well-known Brodatz’s album and DDSM(Heath et al., 1998). The computed features are classified using the Naive Bayes, the RBF, the KNN, the Random Forest and Random Tree models. The results obtained from this study show that we can achieve a high classification accuracy if the descriptors are used all together

Atomic and molecular adsorption on transition-metal carbide (111) surfaces from density-functional theory: A trend study of surface electronic factors

This study explores atomic and molecular adsorption on a number of early transition-metal carbides (TMC's) by means of density-functional theory calculations. Trend studies are conducted with respect to both period and group in the periodic table, choosing the substrates ScC, TiC, VC, ZrC, NbC, delta-MoC, TaC, and WC and the adsorbates H, B, C, N, O, F, NH, NH2, and NH3. Trends in adsorption strength are explained in terms of surface electronic factors, by correlating the calculated adsorption energy values with the calculated surface electronic structures. The results are rationalized with use of a concerted-coupling model (CCM), which has previously been applied succesfully to the description of adsorption on TiC(111) and TiN(111) surfaces [Solid State Commun. 141, 48 (2007)]. First, the clean TMC(111) surfaces are characterized by calculating surface energies, surface relaxations, Bader charges, and surface-localized densities of states (DOS's). Detailed comparisons between surface and bulk DOS's reveal the existence of transition-metal localized SR's (TMSR's) in the pseudogap and of several C-localized SR's (CSR's) in the upper valence band on all considered TMC(111) surfaces. Then, atomic and molecular adsorption energies, geometries, and charge transfers are presented. An analysis of the adsorbate-induced changes in surface DOS's reveals a presence of both adsorbate--TMSR and adsorbate--CSR's interactions, of varying strengths depending on the surface and the adsorbate. These variations are correlated to the variations in adsorption energies. The results are used to generalize the content and applications of the previously proposed CCM to this larger class of substrates and adsorbates. Implications for other classes of materials, for catalysis, and for other surface processes are discussed

Shape matching by curve modelling and alignment

Automatic information retrieval in the eld of shape recognition has been widely covered by many research elds. Various techniques have been developed using different approaches such as intensity-based, modelbased and shape-based methods. Whichever is the way to represent the objects in images, a recognition method should be robust in the presence of scale change, translation and rotation. In this paper we present a new recognition method based on a curve alignment technique, for planar image contours. The method consists of various phases including extracting outlines of images, detecting signicant points and aligning curves. The dominant points can be manually or automatically detected. The matching phase uses the idea of calculating the overlapping indices between shapes as similarity measures. To evaluate the effectiveness of the algorithm, two databases of 216 and 99 images have been used. A performance analysis and comparison is provided by precision-recall curves

Nature of Versatile Chemisorption on TiC(111) and TiN(111) Surfaces

Density-functional calculations on the polar TiX(111) (X = C, N) surfaces show (i) for clean surfaces, strong Ti3d-derived surface resonances (SR's) at the Fermi level and X2p-derived SR's deep in the upper valence band and (ii) for adatoms in periods 1-3, pyramidic trends in atomic adsorption energies, peaking at oxygen (9 eV). A concerted-coupling model, where adatom states couple to both kinds of SR's in a concerted way, describes the adsorption. The chemisorption versatility and the general nature of the model indicate ramifications and predictive abilities in, e.g., growth and catalysis.Comment: 5 pages, 4 figures, submitted to Physical Review Letters (2006