Empirical Investigation on Agile Methods Usage: Issues Identified from Early Adopters in Malaysia

Agile Methods are a set of software practices that can help to produce products faster and at the same time deliver what customers want. Despite the benefits that Agile methods can deliver, however, we found few studies from the Southeast Asia region, particularly Malaysia. As a result, less empirical evidence can be obtained in the country making its implementation harder. To use a new method, experience from other practitioners is critical, which describes what is important, what is possible and what is not possible concerning Agile. We conducted a qualitative study to understand the issues faced by early adopters in Malaysia where Agile methods are still relatively new. The initial study involves 13 participants including project managers, CEOs, founders and software developers from seven organisations. Our study has shown that social and human aspects are important when using Agile methods. While technical aspects have always been considered to exist in software development, we found these factors to be less important when using Agile methods. The results obtained can serve as guidelines to practitioners in the country and the neighbouring regions

A feature selection method for classification within functional genomics experiments based on the proportional overlapping score

Background: Microarray technology, as well as other functional genomics experiments, allow simultaneous measurements of thousands of genes within each sample. Both the prediction accuracy and interpretability of a classifier could be enhanced by performing the classification based only on selected discriminative genes. We propose a statistical method for selecting genes based on overlapping analysis of expression data across classes. This method results in a novel measure, called proportional overlapping score (POS), of a feature's relevance to a classification task.Results: We apply POS, along-with four widely used gene selection methods, to several benchmark gene expression datasets. The experimental results of classification error rates computed using the Random Forest, k Nearest Neighbor and Support Vector Machine classifiers show that POS achieves a better performance.Conclusions: A novel gene selection method, POS, is proposed. POS analyzes the expressions overlap across classes taking into account the proportions of overlapping samples. It robustly defines a mask for each gene that allows it to minimize the effect of expression outliers. The constructed masks along-with a novel gene score are exploited to produce the selected subset of genes

Re-Arrest Among Juvenile Justice-Involved Youth: An Examination Of The Static And Dynamic Risk Factors

The purpose of this study is to investigate the static and dynamic risk factors for re-arrest among detained youth by examining gender, race/ethnicity, age, special education and mental health variables (i.e., anger/irritability, depression/anxiety, somatic complaints, suicide ideation, thought disturbances, and traumatic experiences). The demographic profiles of detained youth with one admit were also compared with those with multiple admits to the juvenile detention center. With regards to static risk factors, older, white, and special education were significantly at risk of re-arrest. Concerning dynamic risk factors, only anger/irritability predicted re-arrest. Practice implications are also discussed

Optymalizacja zagadnienia produkcyjnego z wykorzystaniem programowania matematycznego

In production activity, starting manufacturing of a new product involves taking a particular risk. Therefore, the need arises for investigating the rational basis for starting such projects. This process should begin from the verification of the opportunities of reaching the expected effects of the new production. One of the methods of solving the complex problems is mathematical programming, whose utility was demonstrated with an example of a manufacturing enterprise.W działalności produkcyjnej rozpoczęcie produkcji nowego wyboru wiąże się z podjęciem pewnego ryzyka, stąd też istnieje potrzeba uprzedniego zbadania racjonalnych podstaw przystąpienia do takiego przedsięwzięcia. Proces ten powinien rozpocząć się od zbadania możliwości osiągnięcia spodziewanych efektów nowej produkcji. Jednym ze sposobów rozwiązywania złożonych problemów jest programowanie matematyczne, którego użyteczność przedstawiono na przykładzie przedsiębiorstwa produkcyjnego