Ensemble missing data techniques for software effort prediction

Constructing an accurate effort prediction model is a challenge in software engineering. The development and validation of models that are used for prediction tasks require good quality data. Unfortunately, software engineering datasets tend to suffer from the incompleteness which could result to inaccurate decision making and project management and implementation. Recently, the use of machine learning algorithms has proven to be of great practical value in solving a variety of software engineering problems including software prediction, including the use of ensemble (combining) classifiers. Research indicates that ensemble individual classifiers lead to a significant improvement in classification performance by having them vote for the most popular class. This paper proposes a method for improving software effort prediction accuracy produced by a decision tree learning algorithm and by generating the ensemble using two imputation methods as elements. Benchmarking results on ten industrial datasets show that the proposed ensemble strategy has the potential to improve prediction accuracy compared to an individual imputation method, especially if multiple imputation is a component of the ensemble

An Empirical investigation into metrics for object-oriented software

Object-Oriented methods have increased in popularity over the last decade, and are now the norm for software development in many application areas. Many claims were made for the superiority of object-oriented methods over more traditional methods, and these claims have largely been accepted, or at least not questioned by the software community. Such was the motivation for this thesis. One way of capturing information about software is the use of software metrics. However, if we are to have faith in the information, we must be satisfied that these metrics do indeed tell us what we need to know. This is not easy when the software characteristics we are interested in are intangible and unable to be precisely defined. This thesis considers the attempts to measure software and to make predictions regarding maintainabilty and effort over the last three decades. It examines traditional software metrics and considers their failings in the light of the calls for better standards of validation in terms of measurement theory and empirical study. From this five lessons were derived. The relatively new area of metrics for object-oriented systems is examined to determine whether suggestions for improvement have been widely heeded. The thesis uses an industrial case study and an experiment to examine one feature of objectorientation, inheritance, and its effect on aspects of maintainability, namely number of defects and time to implement a change. The case study is also used to demonstrate that it is possible to obtain early, simple and useful local prediction systems for important attributes such as system size and defects, using readily available measures rather than attempting predefined and possibly time consuming metrics which may suffer from poor definition, invalidity or inability to predict or capture anything of real use. The thesis concludes that there is empirical evidence to suggest a hypothesis linking inheritance and increased incidence of defects and increased maintenance effort and that more empirical studies are needed in order to test the hypothesis. This suggests that we should treat claims regarding the benefits of object-orientation for maintenance with some caution. This thesis also concludes that with the ability to produce, with little effort, accurate local metrics, we have an acceptable substitute for the large predefined metrics suites with their attendant problems

Project Antares: A low cost modular launch vehicle for the future

The single stage to orbit launch vehicle Antares is based upon the revolutionary concept of modularity, enabling the Antares to efficiently launch communications satellites, as well as heavy payloads, into Earth's orbit and beyond. The basic unit of the modular system, a single Antares vehicle, is aimed at launching approximately 10,000 kg into low Earth orbit (LEO). When coupled with a Centaur upper stage it is capable of placing 3500 kg into geostationary orbit. The Antares incorporates a reusable engine, the Dual Mixture Ratio Engine (DMRE), as its propulsive device. This enables Antares to compete and excel in the satellite launch market by dramatically reducing launch costs. Antares' projected launch costs are $1340 per kg to LEO which offers a tremendous savings over launch vehicles available today. Inherent in the design is the capability to attach several of these vehicles together to provide heavy lift capability. Any number of these vehicles, up to seven, can be attached depending on the payload and mission requirements. With a seven vehicle configuration Antares's modular concept provides a heavy lift capability of approximately 70,000 kg to LEO. This expandability allows for a wider range of payload options such as large Earth satellites, Space Station Freedom support, and interplanetary spacecraft, and also offers a significant cost savings over a mixed fleet based on different launch vehicles

Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy

Background: Large-scale surveillance of mosquito populations is crucial to assess the intensity of vector-borne disease transmission and the impact of control interventions. However, there is a lack of accurate, cost-effective and high-throughput tools for mass-screening of vectors. Methods: A total of 750 Anopheles gambiae (Keele strain) mosquitoes were fed Plasmodium falciparum NF54 gametocytes through standard membrane feeding assay (SMFA) and afterwards maintained in insectary conditions to allow for oocyst (8 days) and sporozoite development (14 days). Thereupon, each mosquito was scanned using near infra-red spectroscopy (NIRS) and processed by quantitative polymerase chain reaction (qPCR) to determine the presence of infection and infection load. The spectra collected were randomly assigned to either a training dataset, used to develop calibrations for predicting oocyst- or sporozoite-infection through partial least square regressions (PLS); or to a test dataset, used for validating the calibration’s prediction accuracy. Results: NIRS detected oocyst- and sporozoite-stage P. falciparum infections with 88% and 95% accuracy, respectively. This study demonstrates proof-of-concept that NIRS is capable of rapidly identifying laboratory strains of human malaria infection in African mosquito vectors. Conclusions: Accurate, low-cost, reagent-free screening of mosquito populations enabled by NIRS could revolutionize surveillance and elimination strategies for the most important human malaria parasite in its primary African vector species. Further research is needed to evaluate how the method performs in the field following adjustments in the training datasets to include data from wild-caught infected and uninfected mosquitoes

Quantifying beliefs regarding telehealth: Development of the Whole Systems Demonstrator Service User Technology Acceptability Questionnaire

Introduction: Telehealth (TH) is a potential solution to the increased incidence of chronic illness in an ageing population.The extent to which older people and users with chronic conditions accept and adhere to using assistive technologies is a potential barrier to mainstreaming the service. This study reports the development and validation of the Whole Systems Demonstrator (WSD) Service User Technology Acceptability Questionnaire (SUTAQ). Methods: Questionnaires measuring the acceptability of TH, quality of life, well-being and psychological processes were completed by 478 users of TH. The 22 acceptability items were subject to principal components analysis (PCA) to determine sub-scales. Scale scores, relationships between scales and other patient reported outcome measures (PROMs), and group differences on scales were utilised to check the reliability and validity of the measure. Results: PCAs of SUTAQ items produced 6 TH acceptability scales: enhanced care, increased accessibility, privacy & discomfort, care personnel concerns, kit as substitution, and satisfaction. Scale scores indicated, individuals with long term conditions held beliefs. Significant correlations within these beliefs and between these scales and additional PROMs were coherent and the SUTAQ subscales were able to predict those more likely to refuse TH. Discussion: The SUTAQ is an instrument that can be used to measure user beliefs about the acceptability of TH, and has the ability to discriminate and predict individual differences in beliefs and behaviour. Measuring acceptability beliefs of TH users can provide valuable information to direct and target provision of services to increase uptake and maintain use of TH

The synthesis of recombinant membrane proteins in yeast for structural studies

Historically, recombinant membrane protein production has been a major challenge meaning that many fewer membrane protein structures have been published than those of soluble proteins. However, there has been a recent, almost exponential increase in the number of membrane protein structures being deposited in the Protein Data Bank. This suggests that empirical methods are now available that can ensure the required protein supply for these difficult targets. This review focuses on methods that are available for protein production in yeast, which is an important source of recombinant eukaryotic membrane proteins. We provide an overview of approaches to optimize the expression plasmid, host cell and culture conditions, as well as the extraction and purification of functional protein for crystallization trials in preparation for structural studies

Understanding the yeast host cell response to recombinant membrane protein production

Membrane proteins are drug targets for a wide range of diseases. Having access to appropriate samples for further research underpins the pharmaceutical industry's strategy for developing new drugs. This is typically achieved by synthesizing a protein of interest in host cells that can be cultured on a large scale, allowing the isolation of the pure protein in quantities much higher than those found in the protein's native source. Yeast is a popular host as it is a eukaryote with similar synthetic machinery to that of the native human source cells of many proteins of interest, while also being quick, easy and cheap to grow and process. Even in these cells, the production of human membrane proteins can be plagued by low functional yields; we wish to understand why. We have identified molecular mechanisms and culture parameters underpinning high yields and have consolidated our findings to engineer improved yeast host strains. By relieving the bottlenecks to recombinant membrane protein production in yeast, we aim to contribute to the drug discovery pipeline, while providing insight into translational processes

Pre-Training Muscle Characteristics of Subjects Who Are Obese Determine How Well Exercise Training Will Improve Their Insulin Responsiveness

Pre-training muscle characteristics of subjects who are obese determine how well exercise training will improve their insulin responsiveness. J Strength Cond Res 31(3): 798–808, 2017—Only half of prediabetic subjects who are obese who underwent exercise training without weight loss increased their insulin responsiveness. We hypothesized that those who improved their insulin responsiveness might have pretraining characteristics favoring a positive response to exercise training. Thirty nondiabetic subjects who were obese volunteered for 8 weeks of either strength training or endurance training. During training, subjects increased their caloric intake to prevent weight loss. Insulin responsiveness by euglycemic clamps and muscle fiber composition, and expression of muscle key biochemical pathways were quantified. Positive responders initially had 52% higher intermediate muscle fibers (fiber type IIa) with 27% lower slow-twitch fibers (type I) and 23% lower expression of muscle insulin receptors. Whether after weight training or stationary bike training, positive responders\u27 fiber type shifted away from type I and type IIa fibers to an increased proportion of type IIx fibers (fast twitch). Muscle insulin receptor expression and glucose transporter type 4 (GLUT4) expression increased in all trained subjects, but these moderate changes did not consistently translate to improvement in whole-body insulin responsiveness. Exercise training of previously sedentary subjects who are obese can result in muscle remodeling and increased expression of key elements of the insulin pathway, but in the absence of weight loss, insulin sensitivity improvement was modest and limited to about half of the participants. Our data suggest rather than responders being more fit, they may have been less fit, only catching up to the other half of subjects who are obese whose insulin responsiveness did not increase beyond their pretraining baseline

Effect of telecare on use of health and social care services: findings from the Whole Systems Demonstrator cluster randomised trial

Objective: to assess the impact of telecare on the use of social and health care. Part of the evaluation of the Whole Systems Demonstrator trial. Participants and setting: a total of 2,600 people with social care needs were recruited from 217 general practices in three areas in England. Design: a cluster randomised trial comparing telecare with usual care, general practice being the unit of randomisation. Participants were followed up for 12 months and analyses were conducted as intention-to-treat. Data sources: trial data were linked at the person level to administrative data sets on care funded at least in part by local authorities or the National Health Service. Main outcome measures: the proportion of people admitted to hospital within 12 months. Secondary endpoints included mortality, rates of secondary care use (seven different metrics), contacts with general practitioners and practice nurses, proportion of people admitted to permanent residential or nursing care, weeks in domiciliary social care and notional costs. Results: 46.8% of intervention participants were admitted to hospital, compared with 49.2% of controls. Unadjusted differences were not statistically significant (odds ratio: 0.90, 95% CI: 0.75–1.07, P = 0.211). They reached statistical significance after adjusting for baseline covariates, but this was not replicated when adjusting for the predictive risk score. Secondary metrics including impacts on social care use were not statistically significant. Conclusions: telecare as implemented in the Whole Systems Demonstrator trial did not lead to significant reductions in service use, at least in terms of results assessed over 12 months