SUMMARY The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates filtering and identification of metabolite peaks, paying particular attention to common s...

The application of the method for assessing the level of safety at work starts with a document that contains the cover page, the description of the company (name, location, core business, organizational chart etc.), description of the work system, a detailed list of its components, and a brief description of the assessment method. It continues with a Microsoft Excel document, which represents t...

Data clustering refers to the method of grouping data into different groups depending on their characteristics. This grouping brings an order in the data and hence further processing on this data is made easier. This paper explains the clustering process using the simplest of clustering algorithms the K-Means. The novelty of the paper comes from the fact that it shows a way to perform clusterin...

We propose a new MCDM method based on fuzzy pair-wise comparisons and a feedback between the criteria. The evaluation of the weights of criteria, the variants as well as the feedback between the criteria is based on the data given in pair-wise comparison matrices. Extended arithmetic operations with fuzzy numbers are used as well as ordering fuzzy relations to compare fuzzy outcomes. An illustr...

Through quantitative evaluation of the data and information compiled in the literature review and survey, an explicitly defined list of alternatives and decision criteria to evaluate rehabilitation alternatives was developed for culverts 122 centimeter (48 inch) in diameter or smaller. Relative weights of each criterion were assigned in comparison to the defined alternatives, thereby allowing a...

Data clustering refers to the method of grouping data into different groups depending on their characteristics. This grouping brings an order in the data and hence further processing on this data is made easier. This paper explains the clustering process using the simplest of clustering algorithms the K-Means. The novelty of the paper comes from the fact that it shows a way to perform clusterin...

Monte Carlo (MC) simulation includes a wide range of stochastic techniques used to quantitatively evaluate the behavior of complex systems or processes. Microsoft Excel spreadsheets with Visual Basic for Applications (VBA) software is, arguably, the most commonly employed general purpose tool for MC simulation. Despite the popularity of the Excel in many industries and educational institutions,...

Background: Nonlinear relationships are common in the environmental discipline. Spreadsheet packages such as Microsoft Excel come with an add-on for nonlinear regression, but parameter uncertainty estimates are not yet available. The purpose of this paper is to use Monte Carlo and bootstrap methods to estimate nonlinear parameter uncertainties with a Microsoft Excel spreadsheet. As an example, ...

This paper describes WCourEva, a new Web-based course evaluation system being developed at the University of Nagasaki. WCourEva is intended to assist administrative staff in defining a default questionnaire for each academic unit as well as additional customized questionnaires for individual instructors. The advantages include easy development and maintenance of the default and additional quest...

This paper presents the laboratory restructuring and development for the course of Electric Machinery, also known as Electric Machines or Energy Conversion, for an integrative teaching approach. It illustrates the laboratory restructuring by using modern computer software and hardware information technology (IT) tools, by introducing DSP and digital control technology, and by restructuring a tr...