Development and Utility of Quality Metrics for Ambulatory Pediatric Cardiology in Kawasaki Disease.

The Adult Congenital and Pediatric Cardiology (ACPC) Section of the American College of Cardiology sought to develop quality indicators/metrics for ambulatory pediatric cardiology practice. The objective of this study was to report the creation of metrics for patients with Kawasaki disease. Over a period of 5 months, 12 pediatric cardiologists developed 24 quality metrics based on the most relevant statements, guidelines, and research studies pertaining to Kawasaki disease. Of the 24 metrics, the 8 metrics deemed the most important, feasible, and valid were sent on to the ACPC for consideration. Seven of the 8 metrics were approved using the RAND method by an expert panel. All 7 metrics approved by the ACPC council were accepted by ACPC membership after an "open comments" process. They have been disseminated to the pediatric cardiology community for implementation by the ACPC Quality Network

Evaluating the economic return to public wind energy research and development in the United States

The U.S. government has invested in wind energy research since 1976. Building on a literature that has sought to develop and apply methods for retrospective benefit-to-cost evaluation for federal research programs, this study provides a quantitative analysis of the economic social return on these historical wind energy research investments. Importantly, the study applies multiple innovative methods and varies important input parameters to test the sensitivity of the results. The analysis considers public wind research expenditures and U.S. wind power deployment over the period 1976–2017, while also accounting for the full useful lifetime of wind projects built over this period. Assessed benefits include energy cost savings and health benefits due to reductions in air pollution. Overall, this analysis demonstrates sizable, positive economic returns on past wind energy research. Under the core analysis and with a 3% real discount rate, the net benefits from historical federal wind energy research investments are found to equal $31.4 billion, leading to an 18 to 1 benefit-to-cost ratio and an internal rate of return of 15.4%. Avoided carbon dioxide emissions are not valued in monetary terms, but are estimated at 1510 million metric tons. Alternative methods and input assumptions yield benefit-to-cost ratios that fall within a relatively narrow range from 7-to-1 to 21-to-1, reinforcing in broad terms the general finding of a sizable positive return on investment. Unsurprisingly, results are sensitive to the chosen discount rate, with higher discount rates leading to lower benefit-to-cost ratios, and lower discount rates yielding higher benefit-to-cost ratios

Predicting and Evaluating Software Model Growth in the Automotive Industry

The size of a software artifact influences the software quality and impacts the development process. In industry, when software size exceeds certain thresholds, memory errors accumulate and development tools might not be able to cope anymore, resulting in a lengthy program start up times, failing builds, or memory problems at unpredictable times. Thus, foreseeing critical growth in software modules meets a high demand in industrial practice. Predicting the time when the size grows to the level where maintenance is needed prevents unexpected efforts and helps to spot problematic artifacts before they become critical. Although the amount of prediction approaches in literature is vast, it is unclear how well they fit with prerequisites and expectations from practice. In this paper, we perform an industrial case study at an automotive manufacturer to explore applicability and usability of prediction approaches in practice. In a first step, we collect the most relevant prediction approaches from literature, including both, approaches using statistics and machine learning. Furthermore, we elicit expectations towards predictions from practitioners using a survey and stakeholder workshops. At the same time, we measure software size of 48 software artifacts by mining four years of revision history, resulting in 4,547 data points. In the last step, we assess the applicability of state-of-the-art prediction approaches using the collected data by systematically analyzing how well they fulfill the practitioners' expectations. Our main contribution is a comparison of commonly used prediction approaches in a real world industrial setting while considering stakeholder expectations. We show that the approaches provide significantly different results regarding prediction accuracy and that the statistical approaches fit our data best

The Effect of Security Education and Expertise on Security Assessments: the Case of Software Vulnerabilities

In spite of the growing importance of software security and the industry demand for more cyber security expertise in the workforce, the effect of security education and experience on the ability to assess complex software security problems has only been recently investigated. As proxy for the full range of software security skills, we considered the problem of assessing the severity of software vulnerabilities by means of a structured analysis methodology widely used in industry (i.e. the Common Vulnerability Scoring System (\CVSS) v3), and designed a study to compare how accurately individuals with background in information technology but different professional experience and education in cyber security are able to assess the severity of software vulnerabilities. Our results provide some structural insights into the complex relationship between education or experience of assessors and the quality of their assessments. In particular we find that individual characteristics matter more than professional experience or formal education; apparently it is the \emph{combination} of skills that one owns (including the actual knowledge of the system under study), rather than the specialization or the years of experience, to influence more the assessment quality. Similarly, we find that the overall advantage given by professional expertise significantly depends on the composition of the individual security skills as well as on the available information.Comment: Presented at the Workshop on the Economics of Information Security (WEIS 2018), Innsbruck, Austria, June 201

RTP control protocol (RTCP) extended report (XR) block for independent reporting of burst/fgp discard metrics

This document defines an RTP Control Protocol (RTCP) Extended Report (XR) block that allows the reporting of burst/gap discard metrics independently of the burst/gap loss metrics for use in a range of RTP applications

A Model-Driven Architecture Approach to the Efficient Identification of Services on Service-oriented Enterprise Architecture

Service-Oriented Enterprise Architecture requires the efficient development of loosely-coupled and interoperable sets of services. Existing design approaches do not always take full advantage of the value and importance of the engineering invested in existing legacy systems. This paper proposes an approach to define the key services from such legacy systems effectively. The approach focuses on identifying these services based on a Model-Driven Architecture approach supported by guidelines over a wide range of possible service types

Introducing Energy Efficiency into SQALE

Energy Efficiency is becoming a key factor in software development, given the sharp growth of IT systems and their impact on worldwide energy consumption. We do believe that a quality process infrastructure should be able to consider the Energy Efficiency of a system since its early development: for this reason we propose to introduce Energy Efficiency into the existing quality models. We selected the SQALE model and we tailored it inserting Energy Efficiency as a sub-characteristic of efficiency. We also propose a set of six source code specific requirements for the Java language starting from guidelines currently suggested in the literature. We experienced two major challenges: the identification of measurable, automatically detectable requirements, and the lack of empirical validation on the guidelines currently present in the literature and in the industrial state of the practice as well. We describe an experiment plan to validate the six requirements and evaluate the impact of their violation on Energy Efficiency, which has been partially proved by preliminary results on C code. Having Energy Efficiency in a quality model and well verified code requirements to measure it, will enable a quality process that precisely assesses and monitors the impact of software on energy consumptio