Influence of Parameters on Usability Attributes in Software Projects

To attain certain level of usability, a variety of criteria may be used related to a software project. These criteria are involved with intent of driving various factors associated with software development. These criteria are termed as project parameters. It has been observed that these parameters may influence different attributes associated with software projects thereby indulge with the same instinct for usability attributes also. However, the involvement of these parameters may be mounded in such a way that may lead to characterize the projects more specifically in usability perspective. For the same reason, it is needed to provide measures for characterizing projects. Therefore, an empirical method is proposed for estimation of influence of project parameters on associated usability attributes in a software project in this paper. It will provide quantitative measures related to software projects which in turn will be useful for ranking usability attributes. Usability measurement may also be performed subsequently

Generalized Agile Estimation Method

Agile cost estimation process always possesses research prospects due to lack of algorithmic approaches for estimating cost, size and duration. Existing algorithmic approach i.e. Constructive Agile Estimation Algorithm (CAEA) is an iterative estimation method that incorporates various vital factors affecting the estimates of the project. This method has lots of advantages but at the same time has some limitations also. These limitations may due to some factors such as number of vital factors and uncertainty involved in agile projects etc. However, a generalized agile estimation may generate realistic estimates and eliminates the need of experts. In this paper, we have proposed iterative Generalized Estimation Method (GEM) and presented algorithm based on it for agile with case studies. GEM  based algorithm various project domain classes and vital factors with prioritization level. Further, it incorporates uncertainty factor to quantify the risk of project for estimating cost, size and duration. It also provides flexibility to project managers for deciding on number of vital factors, uncertainty level and project domains thereby maintaining the agility

Generalized Software Security Framework

Security of information has become a major concern in today's digitized world. As a result, effective techniques to secure information are required. The most effective way is to incorporate security in the development process itself thereby resulting into secured product. In this paper, we propose a framework that enables security to be included in the software development process. The framework consists of three layers namely; control layer, aspect layer and development layer. The control layer illustrates the managerial control of the entire software development process with the help of governance whereas aspect layer recognizes the security mechanisms that can be incorporated during the software development to identify the various security features. The development layer helps to integrate the various security aspects as well as the controls identified in the above layers during the development process. The layers are further verified by a survey amongst the IT professionals. The professionals concluded that the developed framework is easy to use due to its layered architecture and, can be customized for various types of softwares

Impact of a United Kingdom-wide campaign to tackle antimicrobial resistance on self-reported knowledge and behaviour change

BackgroundAs part of the 2014 European Antibiotic Awareness Day plans, a new campaign called Antibiotic Guardian (AG) was launched in the United Kingdom, including an online pledge system to increase commitment from healthcare professionals and members of the public to reduce antimicrobial resistance (AMR). The aim of this evaluation was to determine the impact of the campaign on self-reported knowledge and behaviour around AMR.MethodsAn online survey was sent to 9016 Antibiotic Guardians (AGs) to assess changes in self-reported knowledge and behaviour (outcomes) following the campaign. Logistic regression models, adjusted for variables including age, sex and pledge group (pledging as member of public or as healthcare professional), were used to estimate associations between outcomes and AG characteristics.Results2478 AGs responded to the survey (27.5% response rate) of whom 1696 (68.4%)pledged as healthcare professionals and 782 (31.6%) as members of public (similar proportions to the total number of AGs). 96.3% of all AGs who responded had prior knowledge of AMR. 73.5% of participants were female and participants were most commonly between 45-54 years old. Two thirds (63.4%) of participants reported always acting according to their pledge. Members of the public were more likely to act in line with their pledge than professionals (Odds Ratio (OR) =3.60, 95% Confidence Interval (CI): 2.88-4.51). Approximately half of participants (44.5%) (both healthcare professionals and members of public) reported that they acquired more knowledge about AMR postcampaign.People that were confused about AMR prior to the campaign acquired moreknowledge after the campaign (OR=3.10, 95% CI: 1.36-7.09). More participantsreported a sense of personal responsibility towards tackling AMR post-campaign, increasing from 58.3% of participants pre-campaign to 70.5% post-campaign.ConclusionThis study demonstrated that the campaign increased commitment to tackling AMR in both healthcare professional and member of the public, increased self-reported knowledge and changed self-reported behaviour particularly among people with prior AMR awareness. Online pledge schemes can be an effective and inexpensive way to engage people with the problem of AMR especially among those with prior awareness of the topic

COLUMN-STORE: DECISION TREE CLASSIFICATION OF UNSEEN ATTRIBUTE SET

ABSTRACT A decision tree can be used for clustering of frequently used attributes to improve tuple reconstruction time in column-stores databases. Due to ad-hoc nature of queries, strongly correlative attributes are grouped together using a decision tree to share a common minimum support probability distribution. At the same time in order to predict the cluster for unseen attribute set, the decision tree may work as a classifier. In this paper we propose classification and clustering of unseen attribute set using decision tree to improve tuple reconstruction time

Using observational data to emulate a randomized trial of dynamic treatment switching strategies

BACKGROUND: When a clinical treatment fails or shows suboptimal results, the question of when to switch to another treatment arises. Treatment switching strategies are often dynamic because the time of switching depends on the evolution of an individual's time-varying covariates. Dynamic strategies can be directly compared in randomized trials. For example, HIV-infected individuals receiving antiretroviral therapy could be randomized to switching therapy within 90 days of HIV-1 RNA crossing above a threshold of either 400 copies/ml (tight-control strategy) or 1000 copies/ml (loose-control strategy).METHODS: We review an approach to emulate a randomized trial of dynamic switching strategies using observational data from the Antiretroviral Therapy Cohort Collaboration, the Centers for AIDS Research Network of Integrated Clinical Systems and the HIV-CAUSAL Collaboration. We estimated the comparative effect of tight-control vs. loose-control strategies on death and AIDS or death via inverse-probability weighting.RESULTS: Of 43 803 individuals who initiated an eligible antiretroviral therapy regimen in 2002 or later, 2001 met the baseline inclusion criteria for the mortality analysis and 1641 for the AIDS or death analysis. There were 21 deaths and 33 AIDS or death events in the tight-control group, and 28 deaths and 41 AIDS or death events in the loose-control group. Compared with tight control, the adjusted hazard ratios (95% confidence interval) for loose control were 1.10 (0.73, 1.66) for death, and 1.04 (0.86, 1.27) for AIDS or death.CONCLUSIONS: Although our effective sample sizes were small and our estimates imprecise, the described methodological approach can serve as an example for future analyses