7,166 research outputs found
Towards a Common Language of Infrastructure Interdependency
Infrastructure systems can exist interdependently with one another either by design, necessity or evolution. There is
evidence that interdependencies can be the source of emergent benefits and hazards, and therefore there is value in
their identification and management. Achieving this requires collaboration and communication between infrastructure
stakeholders across all relevant sectors.
Recognising, developing and sharing multiple understandings of infrastructure interdependency and dependency will
facilitate a wide range of multi-disciplinary and cross-sectorial work and support productive stakeholder dialogues.
This paper therefore aims to initiate discussion around the nature of infrastructure interdependency and dependency
in order to establish the basis of a useful, coherent and complete conceptual taxonomy. It sets out an approach for
locating this taxonomy and language within a framework of commonplace stakeholder viewpoints.
The paper looks at the potential structural arrangements of infrastructure interdependencies before exploring the
qualitative ways in which the relationships can be characterised. This builds on the existing body of knowledge as
well as experience through case studies in developing an Interdependency Planning and Management Framework for
Infrastructure
Identification-method research for open-source software ecosystems
In recent years, open-source software (OSS) development has grown, with many developers around the world working on different OSS projects. A variety of open-source software ecosystems have emerged, for instance, GitHub, StackOverflow, and SourceForge. One of the most typical social-programming and code-hosting sites, GitHub, has amassed numerous open-source-software projects and developers in the same virtual collaboration platform. Since GitHub itself is a large open-source community, it hosts a collection of software projects that are developed together and coevolve. The great challenge here is how to identify the relationship between these projects, i.e., project relevance. Software-ecosystem identification is the basis of other studies in the ecosystem. Therefore, how to extract useful information in GitHub and identify software ecosystems is particularly important, and it is also a research area in symmetry. In this paper, a Topic-based Project Knowledge Metrics Framework (TPKMF) is proposed. By collecting the multisource dataset of an open-source ecosystem, project-relevance analysis of the open-source software is carried out on the basis of software-ecosystem identification. Then, we used our Spectral Clustering algorithm based on Core Project (CP-SC) to identify software-ecosystem projects and further identify software ecosystems. We verified that most software ecosystems usually contain a core software project, and most other projects are associated with it. Furthermore, we analyzed the characteristics of the ecosystem, and we also found that interactive information has greater impact on project relevance. Finally, we summarize the Topic-based Project Knowledge Metrics Framework
Early Quantitative Assessment of Non-Functional Requirements
Non-functional requirements (NFRs) of software systems are a well known source of uncertainty in effort estimation. Yet, quantitatively approaching NFR early in a project is hard. This paper makes a step towards reducing the impact of uncertainty due to NRF. It offers a solution that incorporates NFRs into the functional size quantification process. The merits of our solution are twofold: first, it lets us quantitatively assess the NFR modeling process early in the project, and second, it lets us generate test cases for NFR verification purposes. We chose the NFR framework as a vehicle to integrate NFRs into the requirements modeling process and to apply quantitative assessment procedures. Our solution proposal also rests on the functional size measurement method, COSMIC-FFP, adopted in 2003 as the ISO/IEC 19761 standard. We extend its use for NFR testing purposes, which is an essential step for improving NFR development and testing effort estimates, and consequently for managing the scope of NFRs. We discuss the advantages of our approach and the open questions related to its design as well
Exploiting a Goal-Decomposition Technique to Prioritize Non-functional Requirements
Business stakeholders need to have clear and realistic goals if they want to meet commitments in application development. As a consequence, at early stages they prioritize requirements. However, requirements do change. The effect of change forces the stakeholders to balance alternatives and reprioritize requirements accordingly. In this paper we discuss the problem of priorities to non-functional requirements subjected to change. We, then, propose an approach to help smooth the impact of such changes. Our approach favors the translation of nonoperational specifications into operational definitions that can be evaluated once the system is developed. It uses the goal-question-metric method as the major support to decompose non-operational specifications into operational ones. We claim that the effort invested in operationalizing NFRs helps dealing with changing requirements during system development. Based on\ud
this transformation and in our experience, we provide guidelines to prioritize volatile non-functional requirements
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Systems approach to assessing and improving local human research Institutional Review Board performance.
ObjectiveTo quantifying the interdependency within the regulatory environment governing human subject research, including Institutional Review Boards (IRBs), federally mandated Medicare coverage analysis and contract negotiations.MethodsOver 8000 IRB, coverage analysis and contract applications initiated between 2013 and 2016 were analyzed using traditional and machine learning analytics for a quality improvement effort to improve the time required to authorize the start of human research studies.ResultsStaffing ratios, study characteristics such as the number of arms, source of funding and number and type of ancillary reviews significantly influenced the timelines. Using key variables, a predictive algorithm identified outliers for a workflow distinct from the standard process. Improved communication between regulatory units, integration of common functions, and education outreach improved the regulatory approval process.ConclusionsUnderstanding and improving the interdependencies between IRB, coverage analysis and contract negotiation offices requires a systems approach and might benefit from predictive analytics
Non-functional requirements: size measurement and testing with COSMIC-FFP
The non-functional requirements (NFRs) of software systems are well known to add a degree of uncertainty to process of estimating the cost of any project. This paper contributes to the achievement of more precise project size measurement through incorporating NFRs into the functional size quantification process. We report on an initial solution proposed to deal with the problem of quantitatively assessing the NFR modeling process early in the project, and of generating test cases for NFR verification purposes. The NFR framework has been chosen for the integration of NFRs into the requirements modeling process and for their quantitative assessment. Our proposal is based on the functional size measurement method, COSMIC-FFP, adopted in 2003 as the ISO/IEC 19761 standard. Also in this paper, we extend the use of COSMIC-FFP for NFR testing purposes. This is an essential step for improving NFR development and testing effort estimates, and consequently for managing the scope of NFRs. We discuss the merits of the proposed approach and the open questions related to its design
Quantify resilience enhancement of UTS through exploiting connect community and internet of everything emerging technologies
This work aims at investigating and quantifying the Urban Transport System
(UTS) resilience enhancement enabled by the adoption of emerging technology
such as Internet of Everything (IoE) and the new trend of the Connected
Community (CC). A conceptual extension of Functional Resonance Analysis Method
(FRAM) and its formalization have been proposed and used to model UTS
complexity. The scope is to identify the system functions and their
interdependencies with a particular focus on those that have a relation and
impact on people and communities. Network analysis techniques have been applied
to the FRAM model to identify and estimate the most critical community-related
functions. The notion of Variability Rate (VR) has been defined as the amount
of output variability generated by an upstream function that can be
tolerated/absorbed by a downstream function, without significantly increasing
of its subsequent output variability. A fuzzy based quantification of the VR on
expert judgment has been developed when quantitative data are not available.
Our approach has been applied to a critical scenario (water bomb/flash
flooding) considering two cases: when UTS has CC and IoE implemented or not.
The results show a remarkable VR enhancement if CC and IoE are deploye
Statistical Mechanics and Information-Theoretic Perspectives on Complexity in the Earth System
Peer reviewedPublisher PD
A Topological Investigation of Phase Transitions of Cascading Failures in Power Grids
Cascading failures are one of the main reasons for blackouts in electric
power transmission grids. The economic cost of such failures is in the order of
tens of billion dollars annually. The loading level of power system is a key
aspect to determine the amount of the damage caused by cascading failures.
Existing studies show that the blackout size exhibits phase transitions as the
loading level increases. This paper investigates the impact of the topology of
a power grid on phase transitions in its robustness. Three spectral graph
metrics are considered: spectral radius, effective graph resistance and
algebraic connectivity. Experimental results from a model of cascading failures
in power grids on the IEEE power systems demonstrate the applicability of these
metrics to design/optimize a power grid topology for an enhanced phase
transition behavior of the system
Characterizing forest fragmentation : Distinguishing change in composition from configuration
This project was funded by the Government of Canada through the Mountain Pine Beetle Program, a three-year, $100 million program administered by Natural Resources Canada, Canadian Forest Service. Additional information on the Mountain Pine Beetle Program may be found at: http://mpb.cfs.nrcan.gc.ca.Forest fragmentation can generally be considered as two components: 1) compositional change representing forest loss, and 2) configurational change or change in the arrangement of forest land cover. Forest loss and configurational change occur simultaneously, resulting in difficulties isolating the impacts of each component. Measures of forest fragmentation typically consider forest loss and configurational change together. The ecological responses to forest loss and configurational change are different, thus motivating the creation of measures capable of isolating these separate components. In this research, we develop and demonstrate a measure, the proportion of landscape displacement from configuration (P), to quantify the relative contributions of forest loss and configurational change to forest fragmentation. Landscapes with statistically significant forest loss or configurational change are identified using neutral landscape simulations to generate underlying distributions for P. The new measure, P, is applied to a forest landscape where substantial forest loss has occurred from mountain pine beetle mitigation and salvage harvesting. The percent of forest cover and six LPIs (edge density, number of forest patches, area of largest forest patch, mean perimeter area ratio, corrected mean perimeter area ratio, and aggregation index) are used to quantify forest fragmentation and change. In our study area, significant forest loss occurs more frequently than significant configurational change. The P method we demonstrate is effective at identifying landscapes undergoing significant forest loss, significant configurational change, or experiencing a combination of both loss and configurational change.PostprintPeer reviewe
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