Multivariate statistical techniques are used to analyze complex data sets with many independent and dependent variables. The dataset may be analyzed for relationships among variables based on correlation, significance of group differences based on variance and covariance, prediction of group membership, and prediction of empirical or theoretical structure of the data. The choice among the available multivariate analysis techniques for each of these research questions is based on the nature of the variables, the number of independent and dependent variables and if the independent variables can be considered as covariates. This paper describes a software tool that can assist researchers in selecting the appropriate data analysis technique based on the research needs of the data. The data analyses techniques discussed in this paper are discriminant function analysis, multi-way frequency analysis and logistic regression. The structure underlying a dataset is based on multivariate approaches such as principal components analysis, factor analysis and structural equation modeling. The paper illustrates the software tool on the Fisher's Iris data set.
This paper describes an internet-based software tool developed for the West Virginia State Police Forensics Laboratory. The software enables law enforcement agents to submit crime information to the Forensic Laboratory via a secure Internet connection. Online electronic forms were created to mirror the existing paper based forms, making the transition easier. The process of submitting case information was standardized and streamlined, there by minimizing information inconsistency. The crime information once gathered is automatically stored in a database, and can be viewed and queried by any authorized law enforcement officers. The software tool will be deployed in all counties of WV.
This paper compares ship-dismantling processes in India and the U.S. The information for India was collected during an informal visit to the ship dismantling sites in Alang, India. The information for the U.S. was obtained from the MARAD report. For a 10,000-ton passenger ship, the Indian contractor makes a profit of about 24% compared to a loss of about 15% in the U.S. The loss in the US is primarily due to high labor costs, compliance to safety and health regulations and lack of market for used components and scrap metal.
This paper describes a database tool for Dismantling of Obsolete Vessels (DOVE). DOVE 1.0 consists of three databases: a) The Obsolete Vessels Database (OVD), b) The Metals and Alloys Database (MAD), and c) The Cutting Technology Database (CTD). The OVD provides information on ship name, type, year built, number, status, light displacement, length, beam, changes made, dead weight, number of propellers, propulsion type, and vessel location. The MAD provides information on several metals and alloys and the CTD has information on cutting technologies, decontamination technologies, and waste processing methodologies. DOVE 1.0 runs on an IBM compatible personal computer and was implemented in Visual Basic 6.0 using Microsoft Access as the database.
This paper presents an approach to extract manufacturing features and their corresponding attributes from a constructive solid geometry based commercial CAD software. Manufacturing features are limited to blind hole, through hole, blind pocket, through pocket, depression, notch, slot, and step. The attributes are limited to height, length, and width for a block feature, height and diameter for a hole feature.
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