2,164 research outputs found
Reporting experiments to satisfy professionals information needs
Although the aim of empirical software engineering is to provide evidence for selecting the appropriate technology, it appears that there is a lack of recognition of this work in industry. Results from empirical research only rarely seem to find their way to company decision makers. If information relevant for software managers is provided in reports on experiments, such reports can be considered as a source of information for them when they are faced with making decisions about the selection of software engineering technologies. To bridge this communication gap between researchers and professionals, we propose characterizing the information needs of software managers in order to show empirical software engineering researchers which information is relevant for decision-making and thus enable them to make this information available. We empirically investigated decision makers? information needs to identify which information they need to judge the appropriateness and impact of a software technology. We empirically developed a model that characterizes these needs. To ensure that researchers provide relevant information when reporting results from experiments, we extended existing reporting guidelines accordingly.We performed an experiment to evaluate our model with regard to its effectiveness. Software managers who read an experiment report according to the proposed model judged the technology?s appropriateness significantly better than those reading a report about the same experiment that did not explicitly address their information needs. Our research shows that information regarding a technology, the context in which it is supposed to work, and most importantly, the impact of this technology on development costs and schedule as well as on product quality is crucial for decision makers
State-of-the-art in integrated vehicle health management
Integrated vehicle health management (IVHM) is a collection of data relevant to the present and future performance of a vehicle system and its transformation into information can be used to support operational decisions. This design and operation concept embraces an integration of sensors, communication technologies, and artificial intelligence to provide vehicle-wide abilities to diagnose problems and recommend solutions. This article aims to report the state-of-the-art of IVHM research by presenting a systematic review of the literature. The literature from different sources is collated and analysed, and the major emerging themes are presented. On this basis, the article describes the IVHM concept and its evolution, discusses configurations and existing applications along with main drivers, potential benefits and barriers to adoption, summarizes design guidelines and available methods, and identifies future research challenges
Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems
As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability
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A knowledge sharing framework to support rapid prototyping in collaborative automotive supply chain
In today’s global economy, competition is increasingly driven by a high rate of product renewal. In this context, with market demands for the development of high quality products at lower costs, highly customisable and with short life cycles, new technologies have been adopted by the automotive manufacturers in the move away from a local economy towards the global economy. The continuous evolution of this technology often requires the updating and integration of existing systems within new environments, in order to avoid technological obsolescence. To allow companies to compete in the global market, they (the companies) can no longer be seen acting as standalone entities and are having to reconsider their organisational and operational structure. This thesis presents a Knowledge Sharing Framework Design Roadmap to support rapid prototyping in the automotive and collaborative supply chain. IranKhodro Diesel (IKD) is the automotive company and CarGlass Company (Iran) is the supplier and sponsor of this research study. These two companies will be used to develop and test the Knowledge Sharing Framework Design Roadmap (KSFDR) methodology.
An industrially based case study was conducted in IKD and CarGlass to identify key elements in the Knowledge Sharing Framework and provide the focus for this study. The study itself drew on empirical sources of data, including interviews with IKD personnel via an internal company survey. The absence of mechanisms to make information accessible in a multilingual environment and its dissemination to geographically dispersed NPD project team members was identified along with the lack of explicit information about the knowledge used and generated to support first stage rapid prototyping in the product development process with respect to reduction of costs and lead times.
The Knowledge Sharing Framework Design Roadmap was tested between IKD and CarGlass. The business objectives in both IKD and CarGlass are the main drivers of knowledge system development. The main novel point from this research study is that this particular framework can be used to capture and disseminate information and knowledge. This was supported by positive feedback from a series of interviews with NPD practitioners. The Knowledge Sharing Framework Design Roadmap (KSFDR) methodology, however, can also be applied in other manufacturing and business environments. Further testing of the framework is strongly advised to minimise any minor flaws, which remain
On driver behavior recognition for increased safety:A roadmap
Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced
Corrosion challenges towards a sustainable society
A global transition towards more sustainable, affordable and reliable energy systems is being stimulated by the Paris Agreement and the United Nation's 2030 Agenda for Sustainable Development. This poses a challenge for the corrosion industry, as building climate-resilient energy systems and infrastructures brings with it a long-term direction, so as a result the long-term behaviour of structural materials (mainly metals and alloys) becomes a major prospect. With this in mind "Corrosion Challenges Towards a Sustainable Society" presents a series of cases showing the importance of corrosion protection of metals and alloys in the development of energy production to further understand the science of corrosion, and bring the need for research and the consequences of corrosion into public and political focus. This includes emphasis on the limitation of greenhouse gas emissions, on the lifetime of infrastructures, implants, cultural heritage artefacts, and a variety of other topics
Benefit of Digital Transformation for Telecommunication Organaization
This paper intends to outline the benefits that are realized by telecommunications industry when they transform digitally. The paper will also review some of the existing literature about the impacts that has already been realized by various telecommunications companies upon transforming digitally. Recommendations about how telecommunication organizations can better realize the benefits of digital transformation have also been covered. Keywords: digital transformation, telecommunication industry
Innovation, pricing and regulatory policies in the German pharmaceutical market
The legislator uses regulative instruments to induce a specific behavior in the drug market of the German Statutory Health Insurance. Empirical and theoretical models were used to evaluate them. Reference pricing, co-payments, lead compounds, and rebate contracts have an effect on prescription behavior. The latter however might lead to monopolies while the early benefit evaluation does not encourage investments into leap innovations. Overall, the instruments only partially fulfill their goal
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