Abstract

Abstract
Context: Keyword research is a widely used resource for retrieving information through search engines available on the Internet. However, most of the information available in the world fails to be obtained by conventional search processes due to its storage in databases, most of them relational. Studies that offer effective solutions when these data sources include relational databases have not been found in the literature. Objective: To present a solution for retrieving information stored in heterogeneous data sources using the OAI-PMH protocol as a mechanism that promotes interoperability. Method: Implementing a system that runs keyword queries in heterogeneous data sources through the collection of metadata exposed to OAI-PMH in data providers. Also, this study proposes a web service that uses public methods to allow relational database information to be returned without the need for additional efforts. Results: The simulations produced a return of information from metadata of digital objects and relational databases, obtained by data providers. Running query examples was successful in retrieving information in all data sources surveyed. Conclusion: This study proposes a solution for retrieving information stored in heterogeneous data sources. The proposed solution proved feasible by allowing keyword research in digital libraries and relational databases using OAI-PMH.

Abstract

Abstract
Consider the problem of partitioned scheduling of an implicit-deadline sporadic task set on heterogeneous multiprocessors to meet all deadlines. Each processor is either of type-1 or type-2. We present a new algorithm, FF-3C, for this problem. FF-3C offers low time-complexity and provably good performance. Specifically, FF-3C offers (i) a time-complexity of O(na <...max(m,logn)+ma <...logm), where n is the number of tasks and m is the number of processors and (ii) the guarantee that if a task set can be scheduled by an optimal partitioned-scheduling algorithm to meet all deadlines then FF-3C meets all deadlines as well if given processors at most times as fast (referred to as speed competitive ratio) and tasks are scheduled using EDF; where alpha is a property of the task set. The parameter alpha is in the range (0,0.5] and for each task, it holds that its utilization is no greater than alpha or greater than 1-alpha on each processor type. Thus, the speed competitive ratio of FF-3C can never exceed 2. We also present several extensions to FF-3C; these offer the same performance guarantee and time-complexity but with improved average-case performance. Via simulations, we compare the performance of our new algorithms and two state-of-the-art algorithms (and variations of the latter). We evaluate algorithms based on (i) running time and (ii) the necessary multiplication factor, i.e., the amount of extra speed of processors that the algorithm needs, for a given task set, so as to succeed, compared to an optimal task assignment algorithm. Overall, we observed that our new algorithms perform significantly better than the state-of-the-art. We also observed that our algorithms perform much better in practice, i.e., the necessary multiplication factor of the algorithms is much smaller than their speed competitive ratio. Finally, we also present a clustered version of the new algorithm.

Abstract

Abstract
The municipal planning and management tasks are generally performed based on text documents or through digital maps provided by geographic information systems (GIS). However, most municipal GIS follow different data models, leading to interoperability problems when there is a need to combine data from different sources. Furthermore, most of the time these tasks are performed in a collaborative way between the municipal technicians, emerging some difficulties in decision making due to the three-dimensional nature of urban space. Thus, this paper describes a methodology which can integrate multiple sources of real data from diverse municipal GIS, in a unified data model based on the CityGML specification. This model is mapped onto an urban ontology oriented for procedural modeling, which, in turn, produces the threedimensional models of the urban environments. The system developed operates in a client-server approach, where the server is responsible for mapping the urban information to the unified data model and the client represents the procedural modeling technology that generates the urban environment in three-dimensional format, allowing users to interact and amplify the existing urban information.