Abstract Refactoring is a commonly accepted technique to improve the structure of object oriented software. The paper presents a multi-objective evolutionary approach for the Entity Refactoring Set Selection Problem (ERSSP) by treating the cost constraint as an objective and combining it with the effect objective. The refactoring selection problem is discussed here as a multi-objective optimization within the Search-Based Software Engineering... Refactoring is a commonly accepted technique to improve the structure of object oriented software. The paper presents a multi-objective evolutionary approach for the Entity Refactoring Set Selection Problem (ERSSP) by treating the cost constraint as an objective and combining it with the effect objective. The refactoring selection problem is discussed here as a multi-objective optimization within the Search-Based Software Engineering (SBSE) field. Different results of the proposed weighted objective genetic algorithm on a experimental didactic case study are presented and discussed. Read More Read Less

Abstract Gaussian mixture models (GMMs) remain the state of the art technique for modeling spectral envelope features for speech recognition systems. This paper presents a comparative analysis of the performance of three estimation algorithms Expectation Maximization (EM), Greedy EM Algorithm (GEM) and Figueiredo-Jain Algorithm (FJ) based Gaussian mixture models (GMMs) for text-independent speech biometrics verification. The simulation results are showed significant... Gaussian mixture models (GMMs) remain the state of the art technique for modeling spectral envelope features for speech recognition systems. This paper presents a comparative analysis of the performance of three estimation algorithms Expectation Maximization (EM), Greedy EM Algorithm (GEM) and Figueiredo-Jain Algorithm (FJ) based Gaussian mixture models (GMMs) for text-independent speech biometrics verification. The simulation results are showed significant performance achievements. The test performance of, EER=0.26 % for “EM”, EER=0.21 % for “GEM” and EER=0.16 % for “FJ”, show that the behavioral information scheme of speech biometrics is more robust and have a discriminating power, which can be explored for identity authentication. Read More Read Less

Abstract Graph representation in computers has always been a hot topic due to the number of applications that directly benefit from graphs. Multiple methods have emerged in computer science to represent graphs in numerical/logical formats; most of these methods rely heavily on pointers. However, most current business applications also rely heavily on relational databases as a primary source of storing information.... Graph representation in computers has always been a hot topic due to the number of applications that directly benefit from graphs. Multiple methods have emerged in computer science to represent graphs in numerical/logical formats; most of these methods rely heavily on pointers. However, most current business applications also rely heavily on relational databases as a primary source of storing information. Moreover, most databases are relational by nature, and this does not provide the best-fit scenario to represent graphs. In this work,we presenta solution to representing a graph in a relational database.We also provide a set of procedures to traverse this graph and determine the connection path between two given nodes. Read More Read Less

Abstract A two stage study on the applications of virtual operating systems ove the currently popular virtualised environment of VMware Workstation 6 was carried out. The current work addresses the findings generated during testing the performance of three different operating systems, Window XP, Ubuntu Linux, Macintosh operating system and applications running under VMware’s virtualized environment. The performance tests covered parameters such... A two stage study on the applications of virtual operating systems ove the currently popular virtualised environment of VMware Workstation 6 was carried out. The current work addresses the findings generated during testing the performance of three different operating systems, Window XP, Ubuntu Linux, Macintosh operating system and applications running under VMware’s virtualized environment. The performance tests covered parameters such as: boot-up and shut-down response times, central processing unit and random access memory usage. Similar resources had to be configured for each of the operating systems to receive meaningful results. The experiments revealed that VMware performance as a virtualised platform was satisfactory. The results concluded that the Macintosh operating system proved to be the worst in performance as compared to Windows XP and Ubuntu Linux. Ubuntu Linux performed impressively in the virtual environment with minor constraints which are listed in the paper. Windows XP was the best virtual operating system for use over VMware’s virtual environment from among the tested operating systems. This research provides a base for conducting further study in the area of virtualization such as depth of nesting of OSs in virtual environment, number of OSs that can be supported in VMware, security between various virtual OSs and between Virtual OSs and the external network environment. Read More Read Less

Abstract The need to process and analyze large data volumes, as well as to convey the information contained therein to decision makers naturally led to the development of OLAP systems. Similarly to SGBDs, OLAP systems must ensure optimum access to the storage environment. Thus, OLAP uses indexing algorithms for relational data and n-dimensional summarized data stored in cubes. This paper presents... The need to process and analyze large data volumes, as well as to convey the information contained therein to decision makers naturally led to the development of OLAP systems. Similarly to SGBDs, OLAP systems must ensure optimum access to the storage environment. Thus, OLAP uses indexing algorithms for relational data and n-dimensional summarized data stored in cubes. This paper presents a new n-dimensional cube indexing algorithm which provides better performance in comparison to the already implemented Tree-like index types. Read More Read Less