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Parametry procesowe krystalizacji fluidalnej

100%

Wójcik J.

Chemik

2005

tom Vol. 58, nr 6

310-312

Przedstawiono parametry procesowe stosowane dla oceny procesu krystalizacji fluidalnej, takie jak czas przebywania, wydajność właściwa objętościowa i powierzchniowa oraz współczynnik intensywności rozdziału. Omówiono ich znaczenie i sens fizykalny. Na podstawie posiadanych danych doświadczalnych, obliczono ich wartości. Przeprowadzono próbę uogólnienia wyników.

Basic process' factors for fluidized-bed crystallization as residence time, specific productivity, specific area productivity and separation intensity factor are introduced in this work. Their physical sense and significance are discussed. Their values are calculated from experimental data. Generalization try of the results is performed.

Factors of software quality - analysis of extended ISBSG dataset

63%

Radliński Ł.

Foundations of Computing and Decision Sciences

2011

tom Vol. 36, No. 3-4

293-313

In this paper, we analyze the extended ISBSG dataset, which contains data on a wide range of software projects developed in various companies worldwide. The main aim of this paper is to identify important factors that influence software quality and to investigate the nature of these relationships. This analysis involves using various statistical techniques, both analytical and graphical. We provide a rating for each variable to express the strength of its relationship with software quality. Unlike earlier analyses, we focus on the business perspective and its relationships on software quality. Obtained results may be used do support decision making in software projects, specifically by demonstrating the impact of selected software development practices.

On generating Bayesian nets from small local qualitative data for software development effort and quality prediction

63%

Radliński Ł.

Metody Informatyki Stosowanej

2011

tom nr 2

121-136

The aim of this paper is to investigate if it is possible to build accurate Bayesian net models for software development effort and quality prediction under two assumptions for model generation: (1) no expert knowledge is incorporated, (2) only small local qualitative data is used. Models generated in this study provide predictions with medium level of accuracy, yet still keeping the literature average. Thus, they can be used to make only rough estimations at the early software development stage. However, they can be a useful base for detailed models incorporating expert knowledge and tailored for individual needs.