Research Proposal on Distinct Study and Significant of Search Techniques in Web Mining

The goal of this research is to provide a more current evaluation and update of web mining research and how machine learning techniques can be applied to web mining techniques available. Currenttrends in each of the three different types of web mining are reviewed in the categories of web content mining, web usage mining, and web structure mining.Unlike previous investigators, we divide web mining processes into the following five subtasks such as resource finding and retrieving, information selection and preprocessing, patterns analysis and recognition, validation and interpretation, and visualization.Major limitations of web mining research are lack of suitable test collections that can be reused by researchers and difficulty to collect web usage data across different web sites. Most web mining applications have been reviewed in this research. Although the activities are still in their early stages and should continue to develop as the Web evolves. This research shows that frequent pattern growth algorithm produces more efficient and accurate results to compare with K-Apriori algorithm. The proposed methods were successfully tested and results were observed and compared with existing methods on the web log files using machine learning techniques

Truss morphometry in the Asian seabass - Lates calcarifer

Truss network analysis was carried out using data of the Asian seabass Lates calcarifer sampled from five different locations along the Indian'coast, in an effort to examine the stock differences based on juveniles1 pre-adults. Principal Components Analysis was carried out on the multivariate morphometric data. Shearing was done in order to obtain a size-free shape component. It was observed that the first factor loadings were positive and nearly of the same magnitude indicating that PC I is a measure of size. A few truss measurements contributed to the shape differences among the stocks. As far as the shape differences are concerned, the Kakdwip stock was different from the rest of the stocks. A similar trend was discernible in the Chennai stock. However, there were no shape differences among the Chilka, Kakinada and Goa stock

Barcoding of Asian seabass across its geographic range provides evidence for its bifurcation into two distinct species

Asian seabass or barramundi (Lates calcarifer) is an important food fish with commercial value and a wide geographic distribution. Though some reports based on molecular and/or morphological data exist, a comprehensive effort to establish species identity across its range is lacking. In order to address this issue and especially to ascertain whether the wide-spread distribution has resulted in bifurcation of the species, we collected Asian seabass samples from various locations representing the Western and Eastern Coastline of India, Andaman and Nicobar Islands, Bangladesh and Australia. Samples from Malaysia, Indonesia, Thailand and Singapore were collected as part of a previous study. DNA sequence variations, including cytochrome c oxidase subunit 1 (COI), 16S rDNA and the highly variable D-loop (or control region), were examined to establish species delineation. Data from all the sequences analyzed concordantly point to the existence of at least two distinct species—one representing the Indian subcontinent plus Myanmar, and a second, representing Southeast Asia (Singapore, Malaysia, Thailand and Indonesia) plus Northern Australia. These data are useful for conservation ecology, aquaculture management, for establishing the extent of genetic diversity in the Asian seabass and implementing selective breeding programs for members of this species complex

Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics

Recursive Cluster Elimination Based Support Vector Machine for Disease State Prediction Using Resting State Functional and Effective Brain Connectivity

Brain state classification has been accomplished using features such as voxel intensities, derived from functional magnetic resonance imaging (fMRI) data, as inputs to efficient classifiers such as support vector machines (SVM) and is based on the spatial localization model of brain function. With the advent of the connectionist model of brain function, features from brain networks may provide increased discriminatory power for brain state classification.In this study, we introduce a novel framework where in both functional connectivity (FC) based on instantaneous temporal correlation and effective connectivity (EC) based on causal influence in brain networks are used as features in an SVM classifier. In order to derive those features, we adopt a novel approach recently introduced by us called correlation-purged Granger causality (CPGC) in order to obtain both FC and EC from fMRI data simultaneously without the instantaneous correlation contaminating Granger causality. In addition, statistical learning is accelerated and performance accuracy is enhanced by combining recursive cluster elimination (RCE) algorithm with the SVM classifier. We demonstrate the efficacy of the CPGC-based RCE-SVM approach using a specific instance of brain state classification exemplified by disease state prediction. Accordingly, we show that this approach is capable of predicting with 90.3% accuracy whether any given human subject was prenatally exposed to cocaine or not, even when no significant behavioral differences were found between exposed and healthy subjects.The framework adopted in this work is quite general in nature with prenatal cocaine exposure being only an illustrative example of the power of this approach. In any brain state classification approach using neuroimaging data, including the directional connectivity information may prove to be a performance enhancer. When brain state classification is used for disease state prediction, our approach may aid the clinicians in performing more accurate diagnosis of diseases in situations where in non-neuroimaging biomarkers may be unable to perform differential diagnosis with certainty

Root Canal Anatomy of Maxillary and Mandibular Teeth

It is a common knowledge that a comprehensive understanding of the complexity of the internal anatomy of teeth is imperative to ensure successful root canal treatment. The significance of canal anatomy has been emphasized by studies demonstrating that variations in canal geometry before cleaning, shaping, and obturation procedures had a greater effect on the outcome than the techniques themselves. In recent years, significant technological advances for imaging teeth, such as CBCT and micro-CT, respectively, have been introduced. Their noninvasive nature allows to perform in vivo anatomical studies using large populations to address the influence of several variables such as ethnicity, aging, gender, and others, on the root canal anatomy, as well as to evaluate, quantitatively and/or qualitatively, specific and fine anatomical features of a tooth group. The purpose of this chapter is to summarize the morphological aspects of the root canal anatomy published in the literature of all groups of teeth and illustrate with three-dimensional images acquired from micro-CT technology.info:eu-repo/semantics/publishedVersio