Evaluating logistic regression models to estimate software project outcomes

ContextSoftware has been developed since the 1960s but the success rate of software development projects is still low. During the development of software, the probability of success is affected by various practices or aspects. To date, it is not clear which of these aspects are more important in influencing project outcome.ObjectiveIn this research, we identify aspects which could influence project success, build prediction models based on the aspects using data collected from multiple companies, and then test their performance on data from a single organization.MethodA survey-based empirical investigation was used to examine variables and factors that contribute to project outcome. Variables that were highly correlated to project success were selected and the set of variables was reduced to three factors by using principal components analysis. A logistic regression model was built for both the set of variables and the set of factors, using heterogeneous data collected from two different countries and a variety of organizations. We tested these models by using a homogeneous hold-out dataset from one organization. We used the receiver operating characteristic (ROC) analysis to compare the performance of the variable and factor-based models when applied to the homogeneous dataset.ResultsWe found that using raw variables or factors in the logistic regression models did not make any significant difference in predictive capability. The prediction accuracy of these models is more balanced when the cut-off is set to the ratio of success to failures in the datasets used to build the models. We found that the raw variable and factor-based models predict significantly better than random chance.ConclusionWe conclude that an organization wishing to estimate whether a project will succeed or fail may use a model created from heterogeneous data derived from multiple organizations.     

ASCENT: adaptive self-configuring sensor networks topologies

Advances in microsensor and radio technology enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. The low-per node cost allows these wireless networks of sensors and actuators to be densely distributed. The nodes in these dense networks coordinate to perform the distributed sensing and actuation tasks. Moreover, as described in this paper, the nodes can also coordinate to exploit the redundancy provided by high density so as to extend overall system lifetime. The large number of nodes deployed in this systems preclude manual configuration, and the environmental dynamics precludes design-time preconfiguration. Therefore, nodes have to self-configure to establish a topology that provides communication under stringent energy constraints. ASCENT builds on the notion that, as density increases, only a subset of the nodes is necessary to establish a routing forwarding backbone. In ASCENT, each node assesses its connectivity and adapts its participation in the multihop network topology based on the measured operating region. This paper motivates and describes the ASCENT algorithm and presents analysis, simulation, and experimental measurements. We show that the system achieves linear increase in energy savings as a function of the density and the convergence time required in case of node failures while still providing adequate connectivity.     

Prototyping: some new results

This research describes a survey of experienced software development practitioners in large organizations for their perceptions of the relative merits of the prototyping and waterfall approaches. Some results of earlier research are confirmed but a number of new insights are obtained. Prototyping is used by developers who are mainly concerned with early life cycle issues; improved communication with users, increased flexibility of the design produced and for early discovery of problems. Non-prototypers prefer to use a waterfall approach because they are more concerned with later life cycle issues—level of control provided, good communication with IS personnel, and the robustness and maintainability of the systems produced.     

Separation of cobalt and nickel from acidic sulfate solutions using mixtures of di(2‐ethylhexyl)phosphoric acid (DP‐8R) and hydroxyoxime (ACORGA M5640)

DP‐8R and ACORGA M5640 extractants diluted in Exxsol D100 were used to co‐extract cobalt and nickel from aqueous acidic sulfate media. The influences of equilibration time, temperature, equilibrium pH and reagent concentrations on the extraction of both metals have been studied. It was observed that both cobalt and nickel extraction are slightly sensitive to temperature but are pH dependent. Metal extraction equilibria are reached within about 5 min contact time. In addition, cobalt extraction depends on the extractant concentration in the organic phase. For a solution containing 0.5 g dm^?3 each of cobalt and nickel and an initial pH of 4.1, conditions were established for the co‐extraction of both metals and selective stripping (with H₂SO₄) of cobalt and nickel. Using the appropriate reagent concentrations the yield (extraction stage) for both metals exceeded 90%, and stripping of cobalt and nickel was almost quantitative. Copyright © 2004 Society of Chemical Industry     

Relationship between the colloidal and rheological properties of mineral suspensions

The electrokinetic and rheological behaviour of lateritic aqueous suspensions has been analyzed as a function of samples chemical composition, pH of suspensions, and nature and concentration of electrolyte added to the aqueous suspensions. First, it was determined that the isoelectric point (IEP) of suspensions in the presence of non‐adsorbing electrolytes is a function of the ratio serpentine/ goethite present in samples. The flow properties of the suspensions are strongly dependent on pH, reaching the highest values of apparent viscosity at values around the isoelectric point. Specific adsorption of silicate and magnesium species on particles surface was revealed by a shift in the IEP. In particular, silicate anions shifted the IEP value to acidic pH whilst magnesium cations shifted the value to basic pH. A similar trend was displayed in the rheological behaviour of suspensions where the highest viscosity values were shifted to the same direction.