215341
Experimental results on user knowledge assessment with an evidential reasoning methodology
User modeling is a crucial element of intelligent interfaces. This paper presents some preliminary resultson a method for the assessment of user knowledge. Knowledge of an individual is modeled as a subset of a global set of knowledge units (KU). The KUS are interrelated among each other through implication relations, indicating that certain KUS are prerequisite to others. The structure of implications is induced algorithmically through an induction procedure utilizing empirical data on the knowledge state of a number of subjects. It is thereafter used in a knowledge assessment process based on the Dempster-Shafer evidential reasoning methodology. The preliminary results demonstrate that our approach can successfully assess knowledge by randomly sampling KUS in a knowledge state and infer which KUS are known and unknown.
5692814
Mining associated implication networks: computational intermarket analysis
Current attempts to analyze international financial markets include the use of financial technical analysis and data mining techniques. In this paper, we propose a new approach that incorporates implication networks and association rules to form an associated network structure. The proposed approach explicitly addresses the issue of local vs. global influences between financial markets.
18067929
Multiagent SAT (MASSAT): Autonomous Pattern Search in Constrained Domains
In this paper, we present an autonomous pattern search approachto solving Satisfiability Problems (SATs). Our approach is essentially a multiagent system. To solve a SAT problem, we first divide variables into groups, and represent each variable group with an agent. Then, we randomly place each agent onto a position in the correspoding local space which is composed of the domains of the variables that are represented by this agent. Thereafter, all agents will autonomously make searchdecisions guided by some reactive rules in their local spaces until a special pattern (i.e., solution) is found or a time step threshold is reached. Experimental results on some benchmark SAT test-sets have shown that by employing the MASSAT approach, we can obtain performances comparable to those of other popular algorithms.
37683026
Web Intelligence (WI)
The 21st century is the age of the Internet and the World Wide Web. The Web revolutionizes the way we gather, process, and use information. At the same time, it also redefines the meanings and processes of business, commerce, marketing, finance, publishing, education, research, development, as well as other aspects of our daily life. The revolution is just beginning. Although individual Web based information systems are constantly being deployed, advanced issues and techniques for developing and for benefiting from Web intelligence still remain to be systematically studied. The article defines a new research field, namely Web Intelligence (WI) by giving a complete picture of WI related topics for systematic study on advanced Web technology and developing Web based intelligent information systems. Roughly speaking, WI exploits AI and advanced information technology on the Web and Internet. It is the key and the most urgent research field of IT for business intelligence.
14178256
Distributed Problem Solving Without Communication - An Examination of Computationally Hard Satisfiability Problems
In this paper, we extend and modify the ERA approach proposed in Ref. 13 to solve Propositional Satisfiability Problems (SATs). The new ERA approach involves a multiagent system where each agent only senses its local environment and applies some self-organizing rules for governing its movements. The environment, which is a two-dimensional cellular environment, records and updates the local values that are computed and affected according to the movements of individual agents. In solving a SAT with the ERA approach, we first divide variables into several groups, and represent each variable group with an agent whose possible positions correspond to the elements in a Cartesian product of variable domains, and then randomly place each agent onto one of its possible positions. Thereafter, the ERA system will keep on dispatching agents to choose their movements until an exact or approximate solution emerges. The experimental results on some benchmark SAT test-sets have shown that the ERA approach can obtain comparable results as well as stable performances for SAT problems. In particular, it can find approximate solutions for SAT problems in only a few steps. The real value of this approach is that it is a distributed asynchronous approach without any centralized control or evaluation, where the agents can cooperate to solve problems without explicit communication.
33842812
Anycast-Based Cooperative Proxy Caching
As one of the most popular applications currently running on the Internet, the World Wide Web is of an exponential growth in size, which results in the network congestion and server overloading. Web caching as an important technique aims at reducing network traffic, server load, and user-perceived retrieval delays by replicating popular contents on proxy caches. In our paper, we develop an anycast-based cooperative web proxy caching mechanism. It puts response time, hop counts, self-organized load balancing, adaption, and self-configuration as primary concerns. In our scheme, anycast is used to bring a server “nearest” to a client to improve overall performance, all proxies in a local network consists an anycast group. The object placement and replacement problems are formulated as an optimization problem and the solution is obtained by using an anycast-based cooperative proxy caching algorithm. Some simulation experiments have been conduced to evaluate the proposed scheme in terms of a wide range of performance metrics. Analytical and experimental results show that our algorithm outperforms some existing algorithms in response time, hop counts.
269541
TinyGALS: a programming model for event-driven embedded systems
Networked embedded systems such as wireless sensor networks are usually designed to be event-driven so that they are reactive and power efficient. Programming embedded systems with multiple reactive tasks is difficult due to the complex nature of managing the concurrency of execution threads and consistency of shared states. This paper describes a globally asynchronous and locally synchronous model (TinyGALS) for programming event-driven embedded systems. Software components are composed locally through synchronous method calls to form modules, and asynchronous message passing is used between modules to separate the flow of control. In addition, a guarded yet synchronous model (TinyGUYS) is designed to allow thread-safe sharing of global state by multiple modules without explicitly passing messages. This programming model is structured such that all asynchronous message passing code and module triggering mechanisms can be automatically generted from a high-level specification. We have implemented the programming model and code generation facilities on a wireless sensor network platform known as the Berkeley motes. As an example, we have redesigned a multi-hop ad hoc communication protocol using the TinyGALS model.
1410914
Collective problem solving through coordinated reaction
We present a methodology, called Constraint Partition and Coordinated Reaction (CP&CR), for collective, evolutionary problem solving. Problem solving is viewed as an emergent functionality from the evolving process of a group of diverse, interacting, and well-coordinated reactive agents. Cheap and effective search knowledge is extracted from local interactions and embedded in the coordination mechanism. Our domain of problem solving is constraint satisfaction problems. We have applied the methodology to job shop scheduling, an NP-complete constraint satisfaction problem. Experimental results on a benchmark suite of problems show that CP&CR outperformed three other state-of-the-art direct search scheduling techniques, in both efficiency and number of problems solved. In addition, CP&CR was experimentally tested on problems of larger sizes and showed favorable scaling-up characteristics.<<ETX>>
16580627
Handling Safety-Related Feature Interaction in Safety-Critical Product Lines
The variation management of software product lines is currently handled without adequately taking safety or other system-level properties into account. This is largely due to (1) the fact that the available product-line variation-management techniques lack sufficient support for representing the combined effect of different features, and (2) the existing feature interaction techniques do not suffice for handling one-to-many feature interactions typical of many safety-critical product lines. The challenge is that we need to track the safety-related feature interactions while still promoting reuse. The expected contribution of this work is to demonstrate how safety-related feature interactions can be better investigated and managed by the safety-analysis guided, model-based approach described in this paper.
4908568
Insignificant shadow detection for video segmentation
To prevent moving cast shadows from being misunderstood as part of moving objects in change detection based video segmentation, this paper proposes a novel approach to the cast shadow detection based on the edge and region information in multiple frames. First, an initial change detection mask containing moving objects and cast shadows is obtained. Then a Canny edge map is generated. After that, the shadow region is detected and removed through multiframe integration, edge matching, and region growing. Finally, a post processing procedure is used to eliminate noise and tune the boundaries of the objects. Our approach can be used for video segmentation in indoor environment. The experimental results demonstrate its good performance.
2696332
A boosting approach for motif modeling using ChIP-chip data
MOTIVATION
Building an accurate binding model for a transcription factor (TF) is essential to differentiate its true binding targets from those spurious ones. This is an important step toward understanding gene regulation.


RESULTS
This paper describes a boosting approach to modeling TF-DNA binding. Different from the widely used weight matrix model, which predicts TF-DNA binding based on a linear combination of position-specific contributions, our approach builds a TF binding classifier by combining a set of weight matrix based classifiers, thus yielding a non-linear binding decision rule. The proposed approach was applied to the ChIP-chip data of Saccharomyces cerevisiae. When compared with the weight matrix method, our new approach showed significant improvements on the specificity in a majority of cases.