Co-occurrence matrix

through information based on conceptual content, natural languages have limited the expression for such area of study. By Using Cholesky decomposition finds the lower triangular matrix that satisfies . For instance, with two random variables the decomposition is done as worked. Although, a determinant of the correlation matrix of the main variables does not have to be positive and in that case other transformation methods can be applied. NLP (natural language processing)is used for stemming, stop word

the topics are unobservable. In PLSI model the topics (aspects) are discovered, and hidden attribute classes are assigned to them. Suppose we have n documents in the text collection, m terms and k latent class variables. Let A be the term document matrix, A(di, ti) is the frequency of term tj in document dj, where i = 1, 2, …, n and j = 1, 2, …, m. One can normalize A in this way: ∑A(di, ti) = 1, where i=1 to m. In PLSI, each term ti in document di is originated from a latent semantic variable class

Abstract—Immune system failure can cause many human autoimmune diseases which make body produce antibodies in the blood which attack human antigens not foreign antigens and it can cause many serious and chronic illnesses. This phenomenon results in an auto-immune response which generate the auto-antibodies (ANAs) during this response. This auto-antibodies (ANAs) may be identified through the indirect immunofluorescence test (IIF). But unfortunately, today the IIF is still a subjective method as well

Challenges and Strategies of Matrix Organizations: Top-Level and Mid-Level Managers’ Perspectives Thomas Sy, College of Business Administration, California State University, Long Beach; Laura Sue D’Annunzio, A.T. Kearney Inc. U sing surveys, inter- views, and workshops with 294 toplevel and mid-level managers from seven major multinational corporations in six industries, we identified the top five contemporary challenges of the matrix organizational form: (1) misaligned goals

one another. LSA method is built on the assumption that words with similar meanings will occur in similar contexts and that related texts will be composed of similar words. This creates a co-occurrence matrix where each row represents a distinct term and each column a distinct document. The cells of the matrix are populated with frequency counts where each cell shows a count of the number of times the term of the corresponding row occurred in the document of the corresponding column. With large

color histogram, color correlogram, and dominant color descriptor (DCD) [1,3,4]. A simple color similarity between two images can be measured by comparing their color histograms. The color histogram, which is a common color descriptor, indicates the occurrence frequencies of colors in the image. The color correlogram describes the probability of finding color pairs at a fixed pixel distance and provides spatial information. Therefore color correlogram yields better retrieval accuracy in comparisonto

Traditionally, the study of microbial model systems in ecology has been limited, although the advent of molecular tools such as next generation sequencing has advanced the understanding of microbial community patterns and processes. This has resulted in a growing focus on studying fundamental ecological processes such as assembly and stability on microbial communities (Fierer, Ferrenberg, Flores, et al., 2012). Because of their simplicity, microbial model systems are in contrast with the complexity

75 and the computation speedup in done at 7.3. Well Markus et al another individual who have proposed that a GPU can be used to simulate or compute GLCM’s and can extract as minute as multiple microscopic images of biological cell. In the case of Co matrix they are saved as small packet to save storage so that unnecessary computation is avoided. It is specified in feature extraction that an optimized sequence to make the computation very simple. Computing or extraction feature was different between

extracting and inferring relations of expected contextual usage of words in passages of discourse. It is based on the application of a particular mathematical technique, called Singular Value Decomposition (SVD), to a word-by-document matrix [4]. The word-by-document matrix is formed from WBD inputs that consist of raw text parsed into words defined as unique character strings and separated into meaningful passages or samples such as sentences or paragraphs. This application provides a way of viewing

mitochondria, it is mediated by the mitochondrial processing peptidase as it undergoes a two-step proteolytic-process, resulting in a mature frataxin that resides in the mitochondrial matrix. The mature frataxin, which is a globular polypeptide, is involved in the iron-sulfur cluster assembly that occurs in the matrix. The frataxin reduces the activity of Iron-Sulfur Cluster (ISC)- containing enzymes, more specifically, aconitase, which leads to defective ATP