The implementation of an Enterprise Geographical Information System to support Cadastre and Expropriation activities.

The processes of mobilization of land for infrastructures of public and private domain are developed according to proper legal frameworks and systematically confronted with the impoverished national situation as regards the cadastral identification and regularization, which leads to big inefficiencies, sometimes with very negative impact to the overall effectiveness. This project report describes Ferbritas Cadastre Information System (FBSIC) project and tools, which in conjunction with other applications, allow managing the entire life-cycle of Land Acquisition and Cadastre, including support to field activities with the integration of information collected in the field, the development of multi-criteria analysis information, monitoring all information in the exploration stage, and the automated generation of outputs. The benefits are evident at the level of operational efficiency, including tools that enable process integration and standardization of procedures, facilitate analysis and quality control and maximize performance in the acquisition, maintenance and management of registration information and expropriation (expropriation projects). Therefore, the implemented system achieves levels of robustness, comprehensiveness, openness, scalability and reliability suitable for a structural platform. The resultant solution, FBSIC, is a fit-for-purpose cadastre information system rooted in the field of railway infrastructures. FBSIC integrating nature of allows: to accomplish present needs and scale to meet future services; to collect, maintain, manage and share all information in one common platform, and transform it into knowledge; to relate with other platforms; to increase accuracy and productivity of business processes related with land property management.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

A simple method for integrating a complex model into an ensemble data assimilation system using MPI

This paper details a strategy for modifying the source code of a complex model so that the model may be used in a data assimilation context, {and gives the standards for implementing a data assimilation code to use such a model}. The strategy relies on keeping the model separate from any data assimilation code, and coupling the two through the use of Message Passing Interface (MPI) {functionality}. This strategy limits the changes necessary to the model and as such is rapid to program, at the expense of ultimate performance. The implementation technique is applied in different models with state dimension up to $2.7 \times 10^8$. The overheads added by using this implementation strategy in a coupled ocean-atmosphere climate model are shown to be an order of magnitude smaller than the addition of correlated stochastic random errors necessary for some nonlinear data assimilation techniques.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

Design and development of an agent-based information system for process improvement

To meet changing needs of customers and to survive in the increasingly globalised and competitive environment, it is necessary for companies to equip themselves with intelligent tools, thereby enabling managerial levels to use the tactical decision in a better way. However, the implementation of an intelligent system is always a challenge in Small- and Medium-sized Enterprises (SMEs). Therefore, a new and simple approach with 'process rethinking' ability is proposed to generate ongoing process improvements over time. In this paper, a roadmap of the development of an agent-based information system is described. A case example has also been provided to show how the system can assist non-specialists, for example, managers and engineers to make right decisions for a continual process improvement. Copyright © 2006 Inderscience Enterprises Ltd.

Configuring an open pipeline fulfilment system - a simulation study in an automotive context

Automotive producers are adopting multi-modal fulfillment models in which customers can be fulfilled by products from stock, by allocating as yet unmade products that are in the planning pipeline, or by building a product to order. This study explores how fulfillment is sensitive to several parameters of the system and how they interact with different methods for sequencing products into the production plan.

OpenDataHub: an open dataset management system

This thesis presents a cloud-based software platform for sharing publicly available scientific datasets. The proposed platform leverages the potential of NoSQL databases and asynchronous IO technologies, such as Node.JS, in order to achieve high performances and flexible solutions. This solution will serve two main groups of users. The dataset providers, which are the researchers responsible for sharing and maintaining datasets, and the dataset users, that are those who desire to access the public data. To the former are given tools to easily publish and maintain large volumes of data, whereas the later are given tools to enable the preview and creation of subsets of the original data through the introduction of filter and aggregation operations. The choice of NoSQL over more traditional RDDMS emerged from and extended benchmark between relational databases (MySQL) and NoSQL (MongoDB) that is also presented in this thesis. The obtained results come to confirm the theoretical guarantees that NoSQL databases are more suitable for the kind of data that our system users will be handling, i. e., non-homogeneous data structures that can grow really fast. It is envisioned that a platform like this can lead the way to a new era of scientific data sharing where researchers are able to easily share and access all kinds of datasets, and even in more advanced scenarios be presented with recommended datasets and already existing research results on top of those recommendations.

OpenDataHub: an open dataset management system

This thesis presents a cloud-based software platform for sharing publicly available scientific datasets. The proposed platform leverages the potential of NoSQL databases and asynchronous IO technologies, such as Node.JS, in order to achieve high performances and flexible solutions. This solution will serve two main groups of users. The dataset providers, which are the researchers responsible for sharing and maintaining datasets, and the dataset users, that are those who desire to access the public data. To the former are given tools to easily publish and maintain large volumes of data, whereas the later are given tools to enable the preview and creation of subsets of the original data through the introduction of filter and aggregation operations. The choice of NoSQL over more traditional RDDMS emerged from and extended benchmark between relational databases (MySQL) and NoSQL (MongoDB) that is also presented in this thesis. The obtained results come to confirm the theoretical guarantees that NoSQL databases are more suitable for the kind of data that our system users will be handling, i. e., non-homogeneous data structures that can grow really fast. It is envisioned that a platform like this can lead the way to a new era of scientific data sharing where researchers are able to easily share and access all kinds of datasets, and even in more advanced scenarios be presented with recommended datasets and already existing research results on top of those recommendations.

Designing a methodology for an office communication and information system:for executives in the Malaysian public sector : the Prime Minister's office

Modern managers are under tremendous pressure in attempting to fulfil a profoundly complex managerial task, that of handling information resources. Information management, an intricate process requiring a high measure of human cognition and discernment, involves matching a manager's lack of information processing capacity against his information needs, with voluminous information at his disposal. The nature of the task will undoubtedly become more complex in the case of a large organisation. Management of large-scale organisations is therefore an exceedingly challenging prospect for any manager to be faced with. A system that supports executive information needs will help reduce managerial and informational mismatches. In the context of the Malaysian public sector, the task of overall management lies with the Prime Minister and the Cabinet. The Prime Minister's Office is presently supporting the Prime Minister's information and managerial needs, although not without various shortcomings. The rigid formalised structure predominant of the Malaysian public sector, so opposed to dynamic treatment of problematic issues as faced by that sector, further escalates the managerial and organisational problem of coping with a state of complexity. The principal features of the research are twofold: the development of a methodology for diagnosing the problem organisation' and the design of an office system. The methodological development is done in the context of the Malaysian public sector, and aims at understanding the complexity of its communication and control situation. The outcome is a viable model of the public sector. `Design', on the other hand, is developing a syntax or language for office systems which provides an alternative to current views on office systems. The design is done with reference to, rather than for, the Prime Minister's Office. The desirable outcome will be an office model called Office Communication and Information System (OCIS).

Ammonia losses estimated by an open collector from urea applied to sugarcane straw

The quantification of ammonia (NH3) losses from sugarcane straw fertilized with urea can be performed with collectors that recover the NH3 in acid-treated absorbers. Thus, the use of an open NH3 collector with a polytetrafluoroethylene (PTFE)-wrapped absorber is an interesting option since its cost is low, handling easy and microclimatic conditions irrelevant. The aim of this study was to evaluate the efficiency of an open collector for quantifying NH3-N volatilized from urea applied over the sugarcane straw. The experiment was carried out in a sugarcane field located near Piracicaba, São Paulo, Brazil. The NH3-N losses were estimated using a semi-open static collector calibrated with 15N (reference method) and an open collector with an absorber wrapped in PTFE film. Urea was applied to the soil surface in treatments corresponding to rates of 50, 100, 150 and 200 kg ha-1 N. Applying urea-N fertilizer on sugarcane straw resulted in losses NH3-N up to 24 % of the applied rate. The amount of volatile NH3-N measured in the open and the semi-open static collector did not differ. The effectiveness of the collection system varied non-linearly, with an average value of 58.4 % for the range of 100 to 200 kg ha-1 of urea-N. The open collector showed significant potential for use; however, further research is needed to verify the suitability of the proposed method.

Healthcare Information System Selection Model for Medical Clinics

The issue of selecting an appropriate healthcare information system is a very essential one. If implemented healthcare information system doesn’t fit particular healthcare institution, for example there are unnecessary functions; healthcare institution wastes its resources and its efficiency decreases. The purpose of this research is to develop a healthcare information system selection model to assist the decision-making process of choosing healthcare information system. Appropriate healthcare information system helps healthcare institutions to become more effective and efficient and keep up with the times. The research is based on comparison analysis of 50 healthcare information systems and 6 interviews with experts from St-Petersburg healthcare institutions that already have experience in healthcare information system utilization. 13 characteristics of healthcare information systems: 5 key and 7 additional features are identified and considered in the selection model development. Variables are used in the selection model in order to narrow the decision algorithm and to avoid duplication of brunches. The questions in the healthcare information systems selection model are designed to be easy-to-understand for common a decision-maker in healthcare institution without permanent establishment.

Development of an open case-based decision-support system for diagnosis in oral pathology

Making diagnoses in oral pathology are often difficult and confusing in dental practice, especially for the lessexperienced dental student. One of the most promising areas in bioinformatics is computer-aided diagnosis, where a computer system is capable of imitating human reasoning ability and provides diagnoses with an accuracy approaching that of expert professionals. This type of system could be an alternative tool for assisting dental students to overcome the difficulties of the oral pathology learning process. This could allow students to define variables and information, important to improving the decision-making performance. However, no current open data management system has been integrated with an artificial intelligence system in a user-friendly environment. Such a system could also be used as an education tool to help students perform diagnoses. The aim of the present study was to develop and test an open case-based decisionsupport system.Methods: An open decision-support system based on Bayes' theorem connected to a relational database was developed using the C++ programming language. The software was tested in the computerisation of a surgical pathology service and in simulating the diagnosis of 43 known cases of oral bone disease. The simulation was performed after the system was initially filled with data from 401 cases of oral bone disease.Results: the system allowed the authors to construct and to manage a pathology database, and to simulate diagnoses using the variables from the database.Conclusion: Combining a relational database and an open decision-support system in the same user-friendly environment proved effective in simulating diagnoses based on information from an updated database.

AMMONIA LOSSES ESTIMATED BY AN OPEN COLLECTOR FROM UREA APPLIED TO SUGARCANE STRAW

The quantification of ammonia (NH3) losses from sugarcane straw fertilized with urea can be performed with collectors that recover the NH3 in acid-treated absorbers. Thus, the use of an open NH3 collector with a polytetrafluoroethylene (PTFE)-wrapped absorber is an interesting option since its cost is low, handling easy and microclimatic conditions irrelevant. The aim of this study was to evaluate the efficiency of an open collector for quantifying NH3-N volatilized from urea applied over the sugarcane straw. The experiment was carried out in a sugarcane field located near Piracicaba, Sao Paulo, Brazil. The NH3-N losses were estimated using a semi-open static collector calibrated with N-15 (reference method) and an open collector with an absorber wrapped in PTFE film. Urea was applied to the soil surface in treatments corresponding to rates of 50, 100, 150 and 200 kg ha(-1) N. Applying urea-N fertilizer on sugarcane straw resulted in losses NH3-N up to 24 % of the applied rate. The amount of volatile NH3-N measured in the open and the semi-open static collector did not differ. The effectiveness of the collection system varied non-linearly, with an average value of 58.4 % for the range of 100 to 200 kg ha(-1) of urea-N. The open collector showed significant potential for use; however, further research is needed to verify the suitability of the proposed method.