7987221
Using VRML and JAVA to Build Virtual Game-Based Learning Environment for Addition and Subtraction Operation
How to make elementary mathematics education vivid and interesting? In this paper, we describe how to use VRML and JAVA to build a virtual game-based learning environment (VGBLE), in which children can learn addition and subtraction operation through games and hence children’s interesting in learning and effects will be improved.
30192317
Modeling and Simulation of Continuous Time-Invariant Systems in Simulation Based Learning Environments
Simulation based learning environments are widely used in elementary and secondary science education. However, a large number of these learning environments are domain-dependent so that they are only useful in some special domains. In this paper, we put forward a new method of simulating continuous time-invariant systems by using frame based knowledge representation and interpretive structural modeling. This method is helpful to realize the separation of knowledge representation and simulation program, and promotes the reusability of a simulation based learning environment.
12282317
A note on “a mapping algorithm for computer-assisted exploration in the design of embedded systems”
The scaling of autoclave and leaching-equipment surfaces during the high pressure leaching of nickeliferous oxide and silicate ores is controlled during leaching to favor the formation of scale containing substantial amounts of magnesium sulfate that is more easily removed by chemical dissolution using water or dilute sulfuric acid at temperatures ranging from about 50 DEG C. to 250 DEG C. than scale containing substantial amounts of alunite.
15396672
Maintaining System State Information in a Multiagent Environment for Effective Learning
One fundamental issue in multiagent reinforcement learning is how to deal with the limited local knowledge of an agent in order to achieve effective learning. In this paper, we argue that this issue can be more effectively solved if agents are equipped with a consistent global view. We achieve this by requiring agents to follow an interacting protocol. The properties of the protocol are derived and theoretically analyzed. A distributed protocol that satisfies these properties is presented. The experimental evaluations are conducted for a well-known test-case (i.e., pursuit game) in the context of two learning algorithms. The results show that the protocol is effective and the reinforcement learning algorithms using it perform much better. key words: multiagent system, system state, distributed protocol, token ring
26669443
Bottom-up discovery of frequent rooted unordered subtrees
In the past decade, XML has emerged as the standard language for information exchanging over the Internet. Due to its tree-structure paradigm, XML is superior for its capability of storing, querying, and manipulating complex data. Therefore, discovering frequent tree patterns over tree-structured data has become an interesting topic for XML data management. In this paper, we propose a tree mining algorithm, named BUXMiner, for finding a special class of frequent trees, called rooted unordered trees, from a tree-structured database. BUXMiner employs an efficient bottom-up approach to enumerate all candidate trees over a compact global tree guide and computes the frequent trees based on the tree guide. In addition to BUXMiner, we also propose a mining approach called BUMXMiner to discover the maximal frequent rooted unordered trees. We compare BUXMiner with previous tree-structure mining algorithms, namely XQPMinerTID and FastXMiner, which were also proposed to discover rooted unordered trees. The experimental results show that our algorithm outperforms XQPMinerTID and FastXMiner in terms of efficiency. The performance results from real-world applications also indicate the usefulness of our proposed tree mining algorithms in a variety of web applications, such as analysis of web page access patterns and mining frequent XML query patterns for caching.
2597224
A workflow-based distributed multidisciplinary design optimization framework
In this paper, we propose a generic framework for multidisciplinary design optimization application, which incorporates several existing technologies such as workflow, agent, adapter, Web and XML workflow is used to allow the designer to construct complex branching and iterative MDO problem formulations and automate the design process execution. Agent is employed to manage and coordinate the operations on system resources, and more significantly perform the dynamic load balancing among a cluster of computers. Adapter is integrated to encapsulate commercial or noncommercial engineering tools to provide the designer with uniform interfaces. Web enables the geographically distributed experts to solve a multi-disciplinary problem cooperatively. XML is used to exchange data between adapters and applications. A Java-based prototype system implementation of the proposed MDO framework is presented.
33950497
An Effective Method for Chinese Grammar Rule Learning
A new method of Chinese grammar rules learning is put forward in this paper. The key point of this method is to use part-of-speech (POS), semantic and contextual information together in learning and expressing Chinese grammar rules. In this way, not only Context Free Grammar (CFG) rules can be learnt, but also the ambiguous structures in POS can be identified automatically. Furthermore, non-ambiguous semantic rules and forbidden rules can be produced from ambiguous rules by using semantic and contextual information. Experimental results demonstrate that the complexity of Chinese parsing is greatly reduced using the different rules learnt by our method.