The purpose of this article is to weigh up the foremost imperative features of Chronic Kidney Disease (CKD). This study is based mostly on three cluster techniques like; K means, Fuzzy c-means and hierarchical clustering. The authors used evolutionary techniques like genetic algorithms (GA) to...

The genetic diagnosis of neuromuscular disorder is an active area of research. Microarrays are used to detect the changes in genes for the accurate diagnosis. Unfortunately, the number of genes in gene expression data is very large as compared to number of samples. The number of genes needs to...

Intricate user-behaviors can be understood by discovering user interests from their reviews. Topic modeling techniques have been extensively explored to discover latent user interests from user reviews. However, a topic extracted by topic modelling techniques can be a mixture of several quite...

Part I of this two-part paper has presented flow-based market coupling (FBMC), the implicit congestion management method used to couple the CentralWestern European (CWE) electricity markets. It has also introduced a large-scale model framework for FBMC assessments, focusing on modeling the...

Market delineation is a fundamental tool in modern antitrust analysis. However, the definition of relevant markets can be very difficult in practice. This preliminary draft applies a new methodology combining a simple price correlation test with hierarchical clustering -a method known from...

This paper presents a nonspatial operationalization of the Krumhansl (1978, 1982) distancedensity model of similarity. This model assumes that the similarity between two objects i and j is a function of both the interpoint distance between i and j and the density of other stimulus points in the...

The psychometric and classification literatures have illustrated the fact that a wide class of discrete or network models (e.g., hierarchical or ultrametric trees) for the analysis of ordinal proximity data are plagued by potential degenerate solutions if estimated using traditional nonmetric...

This study assesses the impact of socioeconomic and cultural factors that are likely to have effects on the development of artificial intelligence at the national level. This technology is evaluated both globally and in terms of its components: qualified users, technical capabilities,...

The objective of the study was to predict the future performance of banks based on the contextual information provided in annual reports. The European Central Bank has observed that performance prediction models in earlier studies mainly rely on quantitative financial data, which are...

This study uses text and data mining to investigate the relationship between the text patterns of annual reports published by US listed companies and sales performance. Taking previous research a step further, although annual reports show only past and present financial information, analyzing...