945 resultados para Information-Analytical System
Resumo:
The 'direct costs' attributable to 30 different endemic diseases of farm animals in Great Britain are estimated using a standardised method to construct a simple model for each disease that includes consideration of disease prevention and treatment costs. The models so far developed provide a basis for further analyses including cost-benefit analyses for the economic assessment of disease control options. The approach used reflects the inherent livestock disease information constraints, which limit the application of other economic analytical methods. It is a practical and transparent approach that is relatively easily communicated to veterinary scientists and policy makers. The next step is to develop the approach by incorporating wider economic considerations into the analyses in a way that will demonstrate to policy makers and others the importance of an economic perspective to livestock disease issues.
Resumo:
Successful results from training an adaptive controller to use optical information to balance an inverted pendulum are presented in comparison to the training requirements using traditional controller inputs. Results from research into the psychology of the sense of balance in humans are presented as the motivation for the investigation of this new type of controller. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training time for the adaptive controller and reduced performance (measured as the time the pendulum remains upright).
Resumo:
Information systems for business are frequently heavily reliant on software. Two important feedback-related effects of embedding software in a business process are identified. First, the system dynamics of the software maintenance process can become complex, particularly in the number and scope of the feedback loops. Secondly, responsiveness to feedback can have a big effect on the evolvability of the information system. Ways have been explored to provide an effective mechanism for improving the quality of feedback between stakeholders during software maintenance. Understanding can be improved by using representations of information systems that are both service-based and architectural in scope. The conflicting forces that encourage change or stability can be resolved using patterns and pattern languages. A morphology of information systems pattern languages has been described to facilitate the identification and reuse of patterns and pattern languages. The kind of planning process needed to achieve consensus on a system's evolution is also considered.
Resumo:
The Group on Earth Observations System of Systems, GEOSS, is a co-ordinated initiative by many nations to address the needs for earth-system information expressed by the 2002 World Summit on Sustainable Development. We discuss the role of earth-system modelling and data assimilation in transforming earth-system observations into the predictive and status-assessment products required by GEOSS, across many areas of socio-economic interest. First we review recent gains in the predictive skill of operational global earth-system models, on time-scales of days to several seasons. We then discuss recent work to develop from the global predictions a diverse set of end-user applications which can meet GEOSS requirements for information of socio-economic benefit; examples include forecasts of coastal storm surges, floods in large river basins, seasonal crop yield forecasts and seasonal lead-time alerts for malaria epidemics. We note ongoing efforts to extend operational earth-system modelling and assimilation capabilities to atmospheric composition, in support of improved services for air-quality forecasts and for treaty assessment. We next sketch likely GEOSS observational requirements in the coming decades. In concluding, we reflect on the cost of earth observations relative to the modest cost of transforming the observations into information of socio-economic value.
Resumo:
Demands for thermal comfort, better indoor air quality together with lower environmental impacts have had ascending trends in the last decade. In many circumstances, these demands could not be fully covered through the soft approach of bioclimatic design like optimisation of the building orientation and internal layout. This is mostly because of the dense urban environment and building internal energy loads. In such cases, heating, ventilation, air-conditioning and refrigeration (HVAC&R) systems make a key role to fulfill the requirements of indoor environment. Therefore, it is required to select the most proper HVAC&R system. In this study, a robust decision making approach for HVAC&R system selection is proposed. Technical performance, economic aspect and environmental impacts of 36 permutations of primary and secondary systems are taken into account to choose the most proper HVAC&R system for a case study office building. The building is a representative for the dominant form of office buildings in the UK. Dynamic performance evaluation of HVAC&R alternatives using TRNSYS package together with life cycle energy cost analysis provides a reliable basis for decision making. Six scenarios broadly cover the decision makers' attitudes on HVAC&R system selection which are analysed through Analytical Hierarchy Process (AHP). One of the significant outcomes reveals that, despite both the higher energy demand and more investment requirements associated with compound heating, cooling and power system (CCHP); this system is one of the top ranked alternatives due to the lower energy cost and C02 emissions. The sensitivity analysis reveals that in all six scenarios, the first five top ranked alternatives are not changed. Finally, the proposed approach and the results could be used by researchers and designers especially in the early stages of a design process in which all involved bodies face the lack of time, information and tools for evaluation of a variety of systems.
Resumo:
The mesospheric response to the 2002 Antarctic Stratospheric Sudden Warming (SSW) is analysed using the Canadian Middle Atmosphere Model Data Assimilation System (CMAM-DAS), where it represents a vertical propagation of information from the observations into the data-free mesosphere. The CMAM-DAS simulates a cooling in the lowest part of the mesosphere which is accomplished by resolved motions, but which is extended to the mid- to upper mesosphere by the response of the model's non-orographic gravity-wave drag parameterization to the change in zonal winds. The basic mechanism is that elucidated by Holton consisting of a net eastward wave-drag anomaly in the mesosphere during the SSW, although in this case there is a net upwelling in the polar mesosphere. Since the zonal-mean mesospheric response is shown to be predictable, this demonstrates that variations in the mesospheric state can be slaved to the lower atmosphere through gravity-wave drag.
Resumo:
Studies on learning management systems have largely been technical in nature with an emphasis on the evaluation of the human computer interaction (HCI) processes in using the LMS. This paper reports a study that evaluates the information interaction processes on an eLearning course used in teaching an applied Statistics course. The eLearning course is used as a synonym for information systems. The study explores issues of missing context in stored information in information systems. Using the semiotic framework as a guide, the researchers evaluated an existing eLearning course with the view to proposing a model for designing improved eLearning courses for future eLearning programmes. In this exploratory study, a survey questionnaire is used to collect data from 160 participants on an eLearning course in Statistics in Applied Climatology. The views of the participants are analysed with a focus on only the human information interaction issues. Using the semiotic framework as a guide, syntactic, semantic, pragmatic and social context gaps or problems were identified. The information interactions problems identified include ambiguous instructions, inadequate information, lack of sound, interface design problems among others. These problems affected the quality of new knowledge created by the participants. The researchers thus highlighted the challenges of missing information context when data is stored in an information system. The study concludes by proposing a human information interaction model for improving the information interaction quality issues in the design of eLearning course on learning management platforms and those other information systems.
Resumo:
With the increase in e-commerce and the digitisation of design data and information,the construction sector has become reliant upon IT infrastructure and systems. The design and production process is more complex, more interconnected, and reliant upon greater information mobility, with seamless exchange of data and information in real time. Construction small and medium-sized enterprises (CSMEs), in particular,the speciality contractors, can effectively utilise cost-effective collaboration-enabling technologies, such as cloud computing, to help in the effective transfer of information and data to improve productivity. The system dynamics (SD) approach offers a perspective and tools to enable a better understanding of the dynamics of complex systems. This research focuses upon system dynamics methodology as a modelling and analysis tool in order to understand and identify the key drivers in the absorption of cloud computing for CSMEs. The aim of this paper is to determine how the use of system dynamics (SD) can improve the management of information flow through collaborative technologies leading to improved productivity. The data supporting the use of system dynamics was obtained through a pilot study consisting of questionnaires and interviews from five CSMEs in the UK house-building sector.
Resumo:
We consider bipartitions of one-dimensional extended systems whose probability distribution functions describe stationary states of stochastic models. We define estimators of the information shared between the two subsystems. If the correlation length is finite, the estimators stay finite for large system sizes. If the correlation length diverges, so do the estimators. The definition of the estimators is inspired by information theory. We look at several models and compare the behaviors of the estimators in the finite-size scaling limit. Analytical and numerical methods as well as Monte Carlo simulations are used. We show how the finite-size scaling functions change for various phase transitions, including the case where one has conformal invariance.