26434237
Method to Balance the Communication Among Multi-agents in Real Time Traffic Synchronization
A method to balance the communication among Multi-Agents in real time traffic synchronization is proposed in this research. The paper presents Air Traffic Flow Management (ATFM) problem and its synchronization property. For such a complex problem, combing grid computing with multi-agent coordination techniques to improve ATFM computational efficiency is the main objective of actual research. To demonstrate the developed model – ATFM in Grid Computing (ATFMGC), the grid architecture, the basic components and the relationship among them are described. At the same time, the function of agents (tactical planning agent etc.), their knowledge representation and inference processes are also discussed. As criteria to measure the effective to reduce quantity of the communication among agents and the delay of the flights, Standard of Balancing among Agents (SBA) is used in the analysis. The simulation shows the efficiency of the developed model and successful application in the case study.
12034739
An Algorithm for Determining the Controllers of Supervised Entities at the First and Second Levels: A Case Study with the Brazilian Central Bank
An algorithm was developed and implemented to find controllers from the stock shares for some financial institutions for the Brazilian Central Bank (BCB). The original problem is similar to a typical Sum of Subset problem that is suggested to be solved by a backtracking algorithm and the problem complexity is NP-complete. Usually BCB solves this problem manually which is time consuming and prone to errors. The heuristical approximation algorithm presented in this paper has polynomial complexity O(n3) and is based on subroutines for determining controllers at the first two levels. The paper describes the basic concepts and business rules currently employed in BCB, our algorithm and its major subroutines, it gives a brief complexity analysis and an example illustration at level 2. Our experimental results indicate the feasibility of an automation of the process of finding controllers. Though developed for BCB, our algorithm works equally well for other financial institutions.
37514455
An Algorithm for Determining the Controllers of Supervised Entities at the First Level: Brazilian Central Bank Case Study
To find controllers from the stock shares of a financial institution is an important task in the Brazilian Central Bank (BCB). The original problem is typically called Sum of Subset and suggested to be resolved by backtrack algorithm with NP-complete complexity. Currently BCB solves this problem manually which is time consuming and suffered from errors. In this study, an approximation algorithm with polynomial complexity O(n) for determining controllers was developed and implemented in BCB. This algorithm includes subroutines for determining controller at levels 1, 2, 3 and the main loops of combination. This paper describes the basic concepts and business rules currently employed in BCB, complexity analysis of the algorithm and its step by step applications at the first level. The implementation and experiment results indicate the feasibility of automation of controllers finding process. Though developed for BCB, it works equally well for all financial institutions which are controlled by stockholders in Brazil.
15110406
Grid Service Agents for Real Time Traffic Synchronization
Grid Service Agents for Real Time Traffic Synchronization is proposed in this research. The paper presents Air Traffic Flow Management (ATFM) problem and its synchronization property. For such a complex problem, using grid computing with multi-agent coordination and negotiation techniques to improve ATFM computational efficiency is the main objective of actual even further research. To demonstrate the developed model - Air Traffic Flow Management in Grid Computing (ATFMGC), the grid architecture, the basic components and relationships among them are described. At the same time, the function of agents, their knowledge representation and inference processes are also discussed. As an example, a tactical planning case study related with some Brazilian airports is illustrated.
17487983
A novel network allocation scheme in wireless mobile networks
A novel network allocation scheme of wireless mobile communications networks is investigated in this paper. We study the handoff rates of calls from one cell to another and obtain the blocking probabilities for new calls and handoff calls. Actual call connection time (ACCT) of a call is investigated, which is the total time a mobile user engaged in communications over a wireless network during a call connection and can be used to design appropriate charging schemes. Our numerical results show that how these measures depend on the new call arrival rate with specific reserved channels for handoff calls in each cell. These results are expected to be useful for the cost analysis for updating location and paging in wireless mobile network.
9528719
Integrating Heterogeneous E-learning Systems
E-learning is a novel education pattern that serves to solve the contradiction between the large amount of social demands and the lack of educational resources. With the popularization of e-learning, various teaching software, tools and e-learning platforms have unceasingly appeared. It is a burning question how to integrate various heterogeneous application systems for e-learning into an organic e-learning system. In this paper, an Integrated Framework for E-learning systems (IFE), which characterizes the reliability, the flexibility and the platform-independence, is proposed. It solves the problems faced while integrating the heterogeneous e-learning systems, such as the heterogeneity, the interoperation and the scalability. The practical application and the testing results on the performance indicate that the design of IFE is in reason and the e-learning system based on IFE can satisfy the concurrency requirements in practice.
17270817
Grid Computing in China
Abstract
Grid computing presents a new trend to distributed computation and Internet applications, which can construct a virtual single image of heterogeneous resources, provide uniform application interface and integrate widespread computational resources into super, ubiquitous and transparent aggregation. In the adoption of Grid computing, China, who is facing more resource heterogeneity and other specific demands, has put much effort on both research and practical utilization. In this paper, we introduce the major China Grid research projects and their perspective applications. First we give the overview of the four government-sponsored programs in Grid, namely the China National Grid, ChinaGrid, NSFC Grid, and ShanghaiGrid. Then we present six representative ongoing Grid systems in details, which are categorized into Grid middleware and Grid application. This paper provides the general picture of Grid computing in China, and shows the great efforts, devotion and confidence in China to use Grid technology to boost the society, economics and scientific research.

6293846
Cryptographic Key Generation from Biometric Data Using Lattice Mapping
Crypto-biometric systems are recently emerging as an effective process of key management to address the security weakness of conventional key release systems using pass-codes, tokens or pattern recognition based biometrics. This paper presents a lattice mapping based fuzzy commitment method for cryptographic key generation from biometric data. The proposed method not only outputs high entropy keys, but also conceals the original biometric data such that it is impossible to recover the biometric data even when the stored information in the system is open to an attacker. Simulated results have demonstrated that its authentication accuracy is comparable to the well-known k-nearest neighbour classification
450045
A Bootstrapping Approach to Named Entity Classification Using Successive Learners
This paper presents a new bootstrapping approach to named entity (NE) classification. This approach only requires a few common noun/pronoun seeds that correspond to the concept for the target NE type, e.g. he/she/man/woman for PERSON NE. The entire bootstrapping procedure is implemented as training two successive learners: (i) a decision list is used to learn the parsing-based high precision NE rules; (ii) a Hidden Markov Model is then trained to learn string sequence-based NE patterns. The second learner uses the training corpus automatically tagged by the first learner. The resulting NE system approaches supervised NE performance for some NE types. The system also demonstrates intuitive support for tagging user-defined NE types. The differences of this approach from the co-training-based NE bootstrapping are also discussed.