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A Three–Level Aggregation Model for Evaluating Software Usability by Fuzzy Logic

Abstract

Rapid deployment of IT brings about new issues with software usability measurement. Usability is based on users’ experience and is strongly subjective, having a qualitative character. The users’ comfort is usually collected by surveys in their daily work. The present article stems from an experimental study related to the evaluation of the usability of tools by a rule-based system. The work suggests a robust computational model that will be able to avoid the main problems arising from the experimental study (a large and less-legible rule base) and to deal with the vagueness of IT user experience, different levels of skills and various numbers of filled questionnaires in different departments. The computational model is based on three hierarchical levels of aggregation supported by fuzzy logic. Choices for the most suitable aggregation functions in each level are advocated and illustrated with examples. The number of questions and granularity of answers in this approach can be adjusted to each user group, which could reduce the response burden and errors. Finally, the paper briefly describes further possibilities of the suggested approach.

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Robust Parameter Design Using the Weighted Metric Method—The Case of ‘the Smaller the Better’

(8): 826-836. Fathi, Y., (1991). A nonlinear programming approach to the parameter design problem, European Journal of Operational Research 53(3): 371-381. Hwang, C.L. and Masud, A.S. Md., (1979). Multiple Objective Decision Making Methods and Applications , Springer, Berlin. Jeong, I. and Kim, K., (2005). D-STEM: A modified step method with desirability function concept, Computers and Operations Research 32(12): 3175-3190. Khattree, P., (1996). Robust parameter

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Ultra regular covering space and its automorphism group

-91. Han, S. E. (2005d). On the simplicial complex stemmed from a digital graph, Honam Mathematical Journal   27 (1): 115-129. Han, S. E. (2006a). Connected sum of digital closed surfaces, Information Sciences   176 (3): 332-348. Han, S. E. (2006b). Discrete Homotopy of a Closed k-Surface , Lecture Notes in Computer Science, Vol. 4040, Springer-Verlag, Berlin, pp. 214-225. Han, S. E. (2006c). Erratum to "Non-product property of the digital fundamental group", Information Sciences   176 (1

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Machine learning techniques combined with dose profiles indicate radiation response biomarkers

, The Journal of Nuclear Medicine 38 (2): 280. Schmid, P.R., Palmer, N.P., Kohane, I.S. and Berger, B. (2012). Making sense out of massive data by going beyond differential expression, Proceedings of the National Academy of Sciences 109 (15): 5594–5599. Shao, L., Luo, Y. and Zhou, D. (2014). Hematopoietic stem cell injury induced by ionizing radiation, Antioxidants & Redox Signaling 20 (9): 1447–1462. Terpstra, T.J. (1952). The asymptotic normality and consistency of Kendall’s test against trend, when ties are present in one ranking

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The mineralization effect of wheat straw on soil properties described by MFPC analysis and other methods

Abstract

Recycling of crop residues is essential to sustain soil fertility and crop production. Despite the positive effect of straw incorporation, the slow decomposition of that organic substance is a serious issue. The aim of the study was to assess the influence of winter wheat straws with different degrees of stem solidness on the rate of decomposition and soil properties. An incubation experiment lasting 425 days was carried out in controlled conditions. To perform analyses, soil samples were collected after 7, 14, 21, 28, 35, 49, 63, 77, 91, 119, 147, 175, 203, 231, 259, 313, 341, 369, 397 and 425 days of incubation. The addition of two types of winter wheat straw with different degree of stem solidness into the sandy soil differentiated the experimental treatments. The results demonstrate that straw mineralization was a relatively slow process and did not depend on the degree of filling of the stem by pith. Multivariate functional principal component analysis (MFPC) gave proof of significant variation between the control soil and the soil incubated with the straws. The first functional principal component describes 48.53% and the second 18.55%, of the variability of soil properties. Organic carbon, mineral nitrogen and sum of bases impact on the first functional principal component, whereas, magnesium, sum of bases and total nitrogen impact on the second functional principal component.

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On an optimal control strategy in a kinetic social dynamics model

. 1407-1429, 2015. 22. A. Barrea and M. E. Hernández, Optimal control of a delayed breast cancer stem cells nonlinear model, Optimal Control Applications and Methods, vol. 37, no. 2, pp. 248-258, 2016. 23. M. Gerdts, Optimal control of ODEs and DAEs. Walter de Gruyter, 2012. 24. S. Lenhart and J. T. Workman, Optimal control applied to biological models. Crc Press, 2007. 25. UNU-IHDP., Inclusive wealth report 2012: measuring progress toward sustainability. Cambridge University Press, 2012

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Modelling Morphographemic Alternations in Derivation of Czech

Bibliography Aronoff, M. Word Formation in Generative Grammar . The MIT Press, Cambridge, 1976. Aronoff, M. Morphology by itself: stems and inflectional classes . The MIT Press, Cambridge, 1994. Baayen, R., R. Piepenbrock, and L. Gulikers. CELEX2 lexical database. LDC96L14. Philadelphia: Linguistic Data Consortium, 1995. Baerman, M. The Oxford Handbook of Inflection . Oxford University Press, Oxford, 2015. Baranes, M. and B. Sagot. A Language-independent Approach to Extracting Derivational Relations from an Inflectional Lexicon

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Computing Bayes factors to measure evidence from experiments: An extension of the BIC approximation

Summary

Bayesian inference affords scientists powerful tools for testing hypotheses. One of these tools is the Bayes factor, which indexes the extent to which support for one hypothesis over another is updated after seeing the data. Part of the hesitance to adopt this approach may stem from an unfamiliarity with the computational tools necessary for computing Bayes factors. Previous work has shown that closed-form approximations of Bayes factors are relatively easy to obtain for between-groups methods, such as an analysis of variance or t-test. In this paper, I extend this approximation to develop a formula for the Bayes factor that directly uses information that is typically reported for ANOVAs (e.g., the F ratio and degrees of freedom). After giving two examples of its use, I report the results of simulations which show that even with minimal input, this approximate Bayes factor produces similar results to existing software solutions.

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Acquisition du tchèque par les francophones: Analyse automatique des erreurs de déclinaison

Acquisition du tchèque par les francophones: Analyse automatique des erreurs de déclinaison

This paper is a summary of our PhD thesis (Šmilauer, 2008) that presents the concept and the implementation of a platform of computer-assisted language learning, featuring on-line fill-in-the-blank exercises with feedback on errors in Czech declension (www.cetlef.fr). Morphological annotation of required forms enables a didactic presentation of the morphological system on the learning platform, as well as the implementation of a procedure of automatic error diagnosis that is carried out by the comparison of an erroneous production with hypothetical forms generated from the stem of the required form. The device can be used as a source of data for a research into second langauge acquisition.

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On determination of ETL – a distributional approach

References Eubank R. (1988): Spline Smoothing and Nonparametric Regression. Marcel Dekker, New York. Afzal M., Yasin M., Sherawat S.M. (2002): Evaluation and Demonstration of Economic Threshold Level (ETL) for Chemical Control of Rice Stem Borers Scirpophagaincertulus Wlk . And S.innotata Wl. International Journal of Agriculture and Biology 3: 323-325. Simonoff J. (1995): Smoothing Methods of Statistics. Springer. New York. Thisted R.A. (1988): Elements of Statistical Computing

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