807 resultados para Accounting Information Systems


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The continuous growth of peer-to-peer networks has made them responsible for a considerable portion of the current Internet traffic. For this reason, improvements in P2P network resources usage are of central importance. One effective approach for addressing this issue is the deployment of locality algorithms, which allow the system to optimize the peers` selection policy for different network situations and, thus, maximize performance. To date, several locality algorithms have been proposed for use in P2P networks. However, they usually adopt heterogeneous criteria for measuring the proximity between peers, which hinders a coherent comparison between the different solutions. In this paper, we develop a thoroughly review of popular locality algorithms, based on three main characteristics: the adopted network architecture, distance metric, and resulting peer selection algorithm. As result of this study, we propose a novel and generic taxonomy for locality algorithms in peer-to-peer networks, aiming to enable a better and more coherent evaluation of any individual locality algorithm.

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The present paper proposes a flexible consensus scheme for group decision making, which allows one to obtain a consistent collective opinion, from information provided by each expert in terms of multigranular fuzzy estimates. It is based on a linguistic hierarchical model with multigranular sets of linguistic terms, and the choice of the most suitable set is a prerogative of each expert. From the human viewpoint, using such model is advantageous, since it permits each expert to utilize linguistic terms that reflect more adequately the level of uncertainty intrinsic to his evaluation. From the operational viewpoint, the advantage of using such model lies in the fact that it allows one to express the linguistic information in a unique domain, without losses of information, during the discussion process. The proposed consensus scheme supposes that the moderator can interfere in the discussion process in different ways. The intervention can be a request to any expert to update his opinion or can be the adjustment of the weight of each expert`s opinion. An optimal adjustment can be achieved through the execution of an optimization procedure that searches for the weights that maximize a corresponding soft consensus index. In order to demonstrate the usefulness of the presented consensus scheme, a technique for multicriteria analysis, based on fuzzy preference relation modeling, is utilized for solving a hypothetical enterprise strategy planning problem, generated with the use of the Balanced Scorecard methodology. (C) 2009 Elsevier Inc. All rights reserved.

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The Learning Object (OA) is any digital resource that can be reused to support learning with specific functions and objectives. The OA specifications are commonly offered in SCORM model without considering activities in groups. This deficiency was overcome by the solution presented in this paper. This work specified OA for e-learning activities in groups based on SCORM model. This solution allows the creation of dynamic objects which include content and software resources for the collaborative learning processes. That results in a generalization of the OA definition, and in a contribution with e-learning specifications.

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One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

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Video adaptation is an extensively explored content providing technique aimed at appropriately suiting several usage scenarios featured by different network requirements and constraints, user`s terminal and preferences. However, its usage in high-demand video distribution systems, such as CNDs, has been badly approached, ignoring several aspects of optimization of network use. To address such deficiencies, this paper presents an approach for implementing the adaptation service by exploring the concept of overlay services networks. As a result of demonstrate the benefits of this proposal, it is made a comparison of this proposed adaptation service with other strategies of video adaptation.

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This paper presents an Adaptive Maximum Entropy (AME) approach for modeling biological species. The Maximum Entropy algorithm (MaxEnt) is one of the most used methods in modeling biological species geographical distribution. The approach presented here is an alternative to the classical algorithm. Instead of using the same set features in the training, the AME approach tries to insert or to remove a single feature at each iteration. The aim is to reach the convergence faster without affect the performance of the generated models. The preliminary experiments were well performed. They showed an increasing on performance both in accuracy and in execution time. Comparisons with other algorithms are beyond the scope of this paper. Some important researches are proposed as future works.

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This paper contains a new proposal for the definition of the fundamental operation of query under the Adaptive Formalism, one capable of locating functional nuclei from descriptions of their semantics. To demonstrate the method`s applicability, an implementation of the query procedure constrained to a specific class of devices is shown, and its asymptotic computational complexity is discussed.

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This paper presents a free software tool that supports the next-generation Mobile Communications, through the automatic generation of models of components and electronic devices based on neural networks. This tool enables the creation, training, validation and simulation of the model directly from measurements made on devices of interest, using an interface totally oriented to non-experts in neural models. The resulting model can be exported automatically to a traditional circuit simulator to test different scenarios.

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This paper proposes a simple high-level programming language, endowed with resources that help encoding self-modifying programs. With this purpose, a conventional imperative language syntax (not explicitly stated in this paper) is incremented with special commands and statements forming an adaptive layer specially designed with focus on the dynamical changes to be applied to the code at run-time. The resulting language allows programmers to easily specify dynamic changes to their own program`s code. Such a language succeeds to allow programmers to effortless describe the dynamic logic of their adaptive applications. In this paper, we describe the most important aspects of the design and implementation of such a language. A small example is finally presented for illustration purposes.

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In this paper, a comparative analysis of the long-term electric power forecasting methodologies used in some South American countries, is presented. The purpose of this study is to compare and observe if such methodologies have some similarities, and also examine the behavior of the results when they are applied to the Brazilian electric market. The abovementioned power forecasts were performed regarding the main four consumption classes (residential, industrial, commercial and rural) which are responsible for approximately 90% of the national consumption. The tool used in this analysis was the SAS (c) program. The outcome of this study allowed identifying various methodological similarities, mainly those related to the econometric variables used by these methods. This fact strongly conditioned the comparative results obtained.

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The single phase induction motors needs two stator windings to produce rotating magnetic field : one main winding and the other auxiliary winding. The aim of the auxiliary winding is to create the rotating electromagnetic field when the machine is started-up and is afterwards turned off, generally through the centrifugal switch coupled together with the shaft of the machine rotor. The main purpose of this document is to evaluate the influence that the two windings have on the external characteristics of the single phase induction motor. For this purpose, two different kinds of windings were carried out and simulated, with the proposal to obtain some benefits. The main winding and the auxiliary winding were prepared and mounted on a prototype. The simulation was done via software based FEM, to make the extraction and results analysis possible. This results are shown at the end this document.

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This paper compares the behaviour of two different control structures of automatic voltage regulators of synchronous machines equipped with static excitation systems. These systems have a fully controlled thyristor bridge that supplies DC current to the rotor winding. The rectifier bridge is fed by the stator terminals through a step-down transformer. The first control structure, named ""Direct Control"", has a single proportional-integral (PI) regulator that compares stator voltage setpoint with measured voltage and acts directly on the thyristor bridge`s firing angle. This control structure is usually employed in commercial excitation systems for hydrogenerators. The second structure, named ""Cascade Control"", was inspired on control loops of commercial DC motor drives. Such drives employ two PIs in a cascade arrangement, the external PI deals with the motor speed while the internal one regulates the armature current. In the adaptation proposed, the external PI compares setpoint with the actual stator voltage and produces the setpoint to the internal PI-loop which controls the field current.

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The following papers constitute a selection among the best papers presented at the Ninth IEEE/IAS International Conference on Industry Applications (INDUSCON) held in Sao Paulo from 8(th) to 10(th) of November, 2010. This event gathered a significant number of people from academia and industry interested in applications of Electrical and Electronic engineering to industry.

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The TCP/IP architecture was consolidated as a standard to the distributed systems. However, there are several researches and discussions about alternatives to the evolution of this architecture and, in this study area, this work presents the Title Model to contribute with the application needs support by the cross layer ontology use and the horizontal addressing, in a next generation Internet. For a practical viewpoint, is showed the network cost reduction for the distributed programming example, in networks with layer 2 connectivity. To prove the title model enhancement, it is presented the network analysis performed for the message passing interface, sending a vector of integers and returning its sum. By this analysis, it is confirmed that the current proposal allows, in this environment, a reduction of 15,23% over the total network traffic, in bytes.

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This work introduces the problem of the best choice among M combinations of the shortest paths for dynamic provisioning of lightpaths in all-optical networks. To solve this problem in an optimized way (shortest path and load balance), a new fixed routing algorithm, named Best among the Shortest Routes (BSR), is proposed. The BSR`s performance is compared in terms of blocking probability and network utilization with Dijkstra`s shortest path algorithm and others algorithms proposed in the literature. The evaluated scenarios include several representative topologies for all-optical networking and different wavelength conversion architectures. For all studied scenarios, BSR achieved superior performance. (C) 2010 Elsevier B.V. All rights reserved.