Current Issue : October - December Volume : 2014 Issue Number : 4 Articles : 5 Articles
Under a broad comprehension of Software Engineering, it is preferred the term software life cycle\ninstead of just software production. The reason is that cycle starts at software conception and\nstops when the software is relegated. Given contemporary companies� market strategies of focusing\non their competitive advantages, most of them have externalized their software production to\noutsourced services. Therefore, the call for software tenders has become a common step in the\nsoftware life cycle. In this paper, we present a tool which aids non-experts to specify call for software\ntenders. The motivation was Chile situation of most of rural and semi-urban city halls which\ndo not have engineering teams to build call for software tenders. We describe the problem in\nterms of lack of competitiveness and empty biddings generated by low quality calls for tenders. As\na second step, we show the technical considerations to develop the proposed tool and its features.\nWe include an initial tool perception from a first group of users....
In this study, we propose a data preprocessing algorithm called D-IMPACT inspired by the IMPACT\nclustering algorithm. D-IMPACT iteratively moves data points based on attraction and density to\ndetect and remove noise and outliers, and separate clusters. Our experimental results on two-dimensional\ndatasets and practical datasets show that this algorithm can produce new datasets such\nthat the performance of the clustering algorithm is improved....
Since the Mid 1980�s, an increasing number of project management software packages (PMSP) has\nappeared in the market to support project management organizations. Despite the wide spread of\nPMSP, projects based organizations are left unguided as to how they should select the most appropriate\nsoftware tool for their intended business use. The aim of this research was to apply a\nscoring model developed using ISO/IEC 14,000 software evaluation criteria to evaluate the effectiveness\nof two software packages in terms of functionality and price, and produce a summary of\nthe evaluation records. To achieve research objective, a questionnaire survey method was used to\ninvestigate the two different project management software packages. One questionnaire was circulated\namong software users in various locations and another was targeting the software vendors.\nThe findings of this study revealed differences between the two packages under investigation\nand highlighted the strength and weakness of each package. The author was able to assess the\nefficiency of each software package and provided a score for each attribute which helps the user to\nunderstand how the software package performs. This investigation revealed that the software user\nis not concerned with the most sophisticated package, or the package that has more advanced\ntools and features. What is more important for the user is their need to produce simple time\ncharts, simple resource and cost analysis and basic reports....
The larger the size of the data, structured or unstructured, the harder to understand and make use\nof it. One of the fundamentals to machine learning is feature selection. Feature selection, by reducing\nthe number of irrelevant/redundant features, dramatically reduces the run time of a\nlearning algorithm and leads to a more general concept. In this paper, realization of feature selection\nthrough a neural network based algorithm, with the aid of a topology optimizer genetic algorithm,\nis investigated. We have utilized NeuroEvolution of Augmenting Topologies (NEAT) to select\na subset of features with the most relevant connection to the target concept. Discovery and\nimprovement of solutions are two main goals of machine learning, however, the accuracy of these\nvaries depends on dimensions of problem space. Although feature selection methods can help to\nimprove this accuracy, complexity of problem can also affect their performance. Artificialneural\nnetworks are proven effective in feature elimination, but as a consequence of fixed topology of\nmost neural networks, it loses accuracy when the number of local minimas is considerable in the\nproblem. To minimize this drawback, topology of neural network should be flexible and it should\nbe able to avoid local minimas especially when a feature is removed. In this work, the power of\nfeature selection through NEAT method is demonstrated. When compared to the evolution of\nnetworks with fixed structure, NEAT discovers significantly more sophisticated strategies. The\nresults show NEAT can provide better accuracy compared to conventional Multi-Layer Perceptron\nand leads to improved feature selection....
Nowadays software is taking a very important role in almost all aspects of our daily lives which\ngave great importance to the study field of Software Engineering. However, most of the current\nSoftware Engineering graduates in Jordan lack the required knowledge and skills to join software\nindustry because of many reasons. This research investigates these reasons by firstly analyzing\nmore than 1000 software job listings in Jordanian and Gulf area e-recruitment services in order to\ndiscover the skills and knowledge areas that are mostly required by software industry in Jordan\nand the Gulf area, and secondly comparing these knowledge areas and skills with those provided\nby the Software Engineering curricula at the Jordanian Universities. The awareness of the Software\nEngineering students and academic staff of the concluded mostly required knowledge areas\nand skills is measured using two questionnaires. Recommendations to decrease the gap between\nSoftware Engineering academia and industry had also been taken from a sample of software companies�\nmanager using a third questionnaire. The results of this research revealed that many important\nskills such as Web applications development are very poorly covered by Software engineering\ncurricula and that many Software engineering students and academic staffs are not aware\nabout many of the mostly needed skills to join industry....
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