Comparative Analysis of Classical and Modified Moses Test

Moses test is a nonparametric method to test the equality of two dispersion parameters. The Moses test does not assume equality of location parameters, and this fact gives the test wider applicability. However, this test is inefficient since different people applying the test will obtain different values because of a random process. One sub-division may lead to significant results where another does not. To overcome the problem of uniqueness of the result, this study proposed to modify the random selection of the observation for the subsamples based on the ranking procedure to lead for a unique result for each solution. The original and modified Moses test were tested on the same data set. The finding shows that the result for both tests is similar in terms of decision and conclusion. The analysis revealed that the modified Moses test based on ranking approach has a smaller sum of squared values compared to the original Moses test. Thus, the variability of data for each subsample is decreased as well. Ranking approach can be used as an alternative to replacing the random procedure of selecting observations for subsample to overcome the problem of uniqueness in the test statistic.

Methodology for Calculating the European Innovation Scoreboard—Proposition for Modification

The primary purpose of this article is to identify determinants affecting the Summary Innovation Index and, consequently, the positions of countries on the European Innovation Scoreboard (EIS). Then, based on the identified determinants, these countries are ranked using the linear ordering method. This article presents the concept of innovation as an unwavering subject of interest for researchers from around the world. Issues relating to measuring innovation, which is necessary for the efficient management of an organization, as well as to the study of innovation in individual countries, are discussed. Special attention is drawn to the methodological aspects of constructing the European Innovation Scoreboard (EIS). The identification of determinants affecting the level of the Summary Innovation Index is performed through stepwise regression. This makes it possible to reduce the number of factors utilized in the EIS ranking procedure from 27 to 22. This was the inspiration to apply an innovative approach and use the linear ordering method, in order to show that it is possible to obtain a ranking that is very similar to the EIS ranking with a reduced number of indicators. These results may be significant, both for units developing this type of ranking and for users, such as decision-makers, using the results to make strategic decisions. In our opinion, this innovative approach—that is, using the linear ordering method and a reduced number of indicators—makes it possible to create a more transparent EIS ranking. This article is of theoretical, methodological, and empirical interest.

Vintage Ratings: Applications of a Ranking Procedure to Facilitate a Better Understanding of Climate’s Role in Wine Quality

Four factors that influence wine quality include the grape variety, the environment it is grown in, and the viticultural and the winemaking practices used to grow the fruit and craft the wines. However, being able to separate these factors and define their exact role in wine quality is frustratingly problematic.

Preference Ranking Procedure: Method Validation with Dogs

The growth of the number of pet products and the pet food industry is continuous. This is partially driven by palatability and perceptions of preference. A preference ranking procedure for dogs has been proposed in order to suggest a more efficient method to study the palatability of food products for dogs. This method was developed based on the assumption that (1) dogs would be more motivated to solve a puzzle for foods that they preferred and (2) the order in which the dogs obtained the treats from the puzzles would indicate the ranking of their preferences. This current study included a validation test that was conducted with 12 dogs to determine if the proposed method was reliable. The validation followed the same procedure as the preliminary test for most parts and dedicated a separate phase each for training, fats, proteins, starches, and complex diets. The results from phases 2 to 4 showed a similar pattern with the preliminary test: Fish oil was preferred over lard, liver over beef, and corn over chickpea. The results from phase 5 showed that the ranking of the combination of the ingredients reflected the preference of the dogs for individual ingredients. As a result, this method was concluded to be reliable.

Self-instruction in ranking of railway enterprise for energy efficiency

Adaptive methods of energy efficiency control are looked upon under ambiguity conditions, based on self-instruction and human factor. The objective of dichotomous ranking of energy efficiency stochastic potential was set and solved in case when its probabilistic characteristics are known. In a reverse situation, it is suggested to use self-instruction for determination of the most suitable parameter of ranking procedure. A case of asymmetrical awareness of a decision-making person about ranking and a personnel responsible for energy efficiency was studied. Herewith, the forward-looking personnel chooses its indicators in such a way that the individual objective function which depends on ranking results , can be maximized. Such activity of the personnel may bring to under-estimation of the energy efficiency indicator as compared to the potential. As a consequence, application of self-instruction may pervert ranking parameter assessment. In order to solve this problem there were suggested self-instruction mechanisms in ranking which simulate personnel management under conditions of ambiguity. The results of these mechanisms functioning are estimates of ranking parameters, norms and ranks, determining personnel stimuli. There were found out appropriate conditions of mechanism synthesis of self-instruction in ranking, when a decision-making person identifies the most suitable parameter of the ranking procedure. These conditions are illustrated with the example of energy efficiency ranking self-instruction of the railway enterprise in the process of realization of «RZD» holding energy efficiency improvement program.

Sentimental Analysis and LSI Similarity Measure for Efficient Page Ranking

Supplementary factor to the general pagerank calculation which is utilized by Google chrome to rank sites in their web index results is tended to in this paper. These extra factors incorporate couple of ideas which expressly results to build the precision of evaluating the PageRank value. By making a decision about the likeness between the web page content with the text extracted from different site pagesresulted in topmost search using few keywords of the considered page for which the rank is to be determined by utilizing a comparability measure. It results with a worth or rate which speaks to the significance or similarity factor. Further, in a similar strategy if sentimental analysis is applied the search results of the keywords could be analysed with keywords of the page considered, it results with a Sentimental Analysed factor.In this way, one can improve and execute the Page ranking procedure which results with a superior accuracy.Hadoop Distributed File System is used to compute the page rank of input nodes. Python is chosen for parallel page rank algorithm that is executed on Hadoop

Pugh Controlled Convergence and Social Choice Theory

The Pugh Method of Controlled Convergence is evaluated based on social choice theory, both from an axiomatic basis, and by examining all possible cases of attribute ranks for a range of numbers of alternatives and numbers of attributes. The evaluation shows that, for a typical Pugh application, concept selection varies with the arbitrary choice of datum or is simply incorrect in about one-third of the cases. While there are merits to the iteration steps and creation of new alternatives within the Pugh method, a simpler and more expressive concept ranking procedure can give far superior results.