56 resultados para software management infrastructure


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The UK’s transport infrastructure is one of the most heavily used in the world. The performance of these networks is critically dependent on the performance of cutting and embankment slopes which make up £20B of the £60B asset value of major highway infrastructure alone. The rail network in particular is also one of the oldest in the world: many of these slopes are suffering high incidents of instability (increasing with time). This paper describes the development of a fundamental understanding of earthwork material and system behaviour, through the systematic integration of research across a range of spatial and temporal scales. Spatially these range from microscopic studies of soil fabric, through elemental materials behaviour to whole slope modelling and monitoring and scaling up to transport networks. Temporally, historical and current weather event sequences are being used to understand and model soil deterioration processes, and climate change scenarios to examine their potential effects on slope performance in futures up to and including the 2080s. The outputs of this research are being mapped onto the different spatial and temporal scales of infrastructure slope asset management to inform the design of new slopes through to changing the way in which investment is made into aging assets. The aim ultimately is to help create a more reliable, cost effective, safer and more resilient transport system.

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Both Northern Ireland and Republic of Ireland governments recognise the current infrastructural deficits in their respective jurisdictions which, if not addressed, will undermine the future economic prosperity of both regions. This paper considers the adoption of a collaborative approach on the island to addressing the deficit, using public private partnerships (PPP) as the delivery vehicle. It presents a critical perspective of the challenges and opportunities posed by adopting such a cross-border approach. Whilst PPPs have the potential to bring about North-South co-operation, bridge gaps in infrastructure capacity and facilitate the advancement of sectoral knowledge, their adoption on a cross border basis will require significant reorganisation and change at administrative and sectoral levels. This review concludes that governments and construction sector representatives in Northern Ireland and the Republic of Ireland have still some work to do in order to enhance the capability and readiness of public and private partners to evolve an all-island PPP infrastructure development approach.

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Software product development is recognised as difficult due to the intangible nature of the product, requirements elicitation, effective progress measurement, and so forth. In this paper, we describe some of the challenges of software product development and how the challenges are being met by lean management principles and techniques. Specifically, we examine lean principles and techniques that were devised by Toyota and other manufacturers over the last 50 years. Applying lean principles to software development projects has been advocated for over ten years and it will be shown that the extensive lean literature is a valuable source of ideas for software development. A case study with a software development organisation, Timberline Inc., will demonstrate that lean principles and techniques can be successfully applied to software product development.

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This study describes a study of 14 software companies, on how they initiate and pre-plan software projects. The aim was to obtain an indication of the range of planning activities carried out. The study, using a convenience sample, was carried out using structured interviews, with questions about early software project planning activities. The study offers evidence that an iterative and incremental development process presents extra difficulties in the case of fixed-contract projects. The authors also found evidence that feasibility studies were common, but generally informal in nature. Documentation of the planning process, especially for project scoping, was variable. For incremental and iterative development projects, an upfront decision on software architecture was shown to be preferred over allowing the architecture to just ‘emerge’. There is also evidence that risk management is recognised but often performed incompletely. Finally appropriate future research arising from the study is described.

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Purpose: The purpose of this paper is to examine the extent and nature of greening the supply chain (SC) in the UK manufacturing sector; and the factors that influence the breadth and depth of this activity.

Design/methodology/approach: Based on the findings from a sample of manufacturing organisations drawn from the membership of The Chartered Institute for Purchasing and Supply. Data are collected using a questionnaire, piloted and pre-tested before distribution with responses from 60 manufacturing companies.

Findings: On average manufacturers perceive the greatest pressure to improve environmental performance through legislation and internal drivers (IDs). The least influential pressures are related to societal drivers and SC pressures from individual customers. Green supply chain management (GSCM) practices amongst this “average” group of UK manufacturing organisations are focusing on internal, higher risk, descriptive activities, rather than proactive, external engagement processes. Environmental attitude (EA) is a key predictor of GSCM activity and those organisations that have a progressive attitude are also operationally very active. EA shows some relationship to legislative drivers but other factors are also influential. Operational activity may also be moderated by organisational contingencies such as risk, size, and nationality.

Research limitations/implications: The main limitation to this paper is the relatively small manufacturing sample.

Practical implications: This paper presents a series of constructs that identify GSCM operational activities companies to benchmark themselves against. It suggests which factors are driving these operational changes and how industry contingencies may be influential.

Originality/value: This paper explores what is driving environmental behaviour amongst an “average” sample of manufacturers, what specific management practices take place and the relationships between them.

Keywords: Manufacturing industries, Environmental management, Supply chain management, Sustainable development, United Kingdom
Paper type: Research paper

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To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioral data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals’ environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.

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For any proposed software project, when the software requirements specification has been established, requirements changes may result in not only a modification of the requirements specification but also a series of modifications of all existing artifacts during the development. Then it is necessary to provide effective and flexible requirements changes management. In this paper, we present an approach to managing requirements changes based on Booth’s negotiation-style framework for belief revision. Informally, we consider the current requirements specification as a belief set about the system-to-be. The request of requirements change is viewed as new information about the same system-to-be. Then the process of executing the requirements change is a process of revising beliefs about the system-to-be. We design a family of belief negotiation models appropriate for different processes of requirements revision, including the setting of the request of requirements change being fully accepted, the setting of the current requirements specification being fully preserved, and that of the current specification and the request of requirements change reaching a compromise. In particular, the prioritization of requirements plays an important role in reaching an agreement in each belief negotiation model designed in this paper.

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A queue manager (QM) is a core traffic management (TM) function used to provide per-flow queuing in access andmetro networks; however current designs have limited scalability. An on-demand QM (OD-QM) which is part of a new modular field-programmable gate-array (FPGA)-based TM is presented that dynamically maps active flows to the available physical resources; its scalability is derived from exploiting the observation that there are only a few hundred active flows in a high speed network. Simulations with real traffic show that it is a scalable, cost-effective approach that enhances per-flow queuing performance, thereby allowing per-flow QM without the need for extra external memory at speeds up to 10 Gbps. It utilizes 2.3%–16.3% of a Xilinx XC5VSX50t FPGA and works at 111 MHz.

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As a class of defects in software requirements specification, inconsistency has been widely studied in both requirements engineering and software engineering. It has been increasingly recognized that maintaining consistency alone often results in some other types of non-canonical requirements, including incompleteness of a requirements specification, vague requirements statements, and redundant requirements statements. It is therefore desirable for inconsistency handling to take into account the related non-canonical requirements in requirements engineering. To address this issue, we propose an intuitive generalization of logical techniques for handling inconsistency to those that are suitable for managing non-canonical requirements, which deals with incompleteness and redundancy, in addition to inconsistency. We first argue that measuring non-canonical requirements plays a crucial role in handling them effectively. We then present a measure-driven logic framework for managing non-canonical requirements. The framework consists of five main parts, identifying non-canonical requirements, measuring them, generating candidate proposals for handling them, choosing commonly acceptable proposals, and revising them according to the chosen proposals. This generalization can be considered as an attempt to handle non-canonical requirements along with logic-based inconsistency handling in requirements engineering.