Integrating trust into the CyberCraft Initiative via the Trust Vectors model [Application Notes]

This research supports the hypothesis that the Trust Vector model can be modified to fit the CyberCraft Initiative, and that there are limits to the utility of historical data. This research proposed some modifications and expansions to the Trust Model Vector, and identified areas for future research.     

Evolving artificial neural network ensembles

Using a coordinated group of simple solvers to tackle a complex problem is not an entirely new idea. Its root could be traced back hundreds of years ago when ancient Chinese suggested a team approach to problem solving. For a long time, engineers have used the divide-and-conquer strategy to decompose a complex problem into simpler sub-problems and then solve them by a group of solvers. However, knowing the best way to divide a complex problem into simpler ones relies heavily on the available domain knowledge. It is often a manual process by an experienced engineer. There have been few automatic divide-and-conquer methods reported in the literature. Fortunately, evolutionary computation provides some of the interesting avenues to automatic divide-and-conquer methods. An in-depth study of such methods reveals that there is a deep underlying connection between evolutionary computation and ANN ensembles. Ideas in one area can be usefully transferred into another in producing effective algorithms. For example, using speciation to create and maintain diversity had inspired the development of negative correlation learning for ANN ensembles, and an in-depth study of diversity in ensembles. This paper will review some of the recent work in evolutionary approaches to designing ANN ensembles.     

Toward Human Level Machine Intelligence - Is It Achievable? The Need for a Paradigm Shift

Officially, AI was born in 1956. Since then, very impressive progress has been made in many areas - but not in the realm of human level machine intelligence. During much of its early history, AI "was rife "with exaggerated expectations. A headline in an article published in the late forties of last century was headlined, "Electric brain capable of translating foreign languages is being built". Today, more than half a century later, we do have translation software, but nothing that can approach the quality of human translation. Clearly, achievement of human level machine intelligence is a challenge that is hard to meet. A prerequisite to achievement of human level machine intelligence is mechanization of these capabilities and, in particular, mechanization of natural language understanding. To make significant progress toward achievement of human level machine intelligence, a paradigm shift is needed. More specifically, what is needed is an addition to the armamentarium of AI of two methodologies: (a) a nontraditional methodology of computing with words (CW) or more generally, NL-Computation; and (b) a countertraditional methodology "which involves a progression from computing with numbers to computing with words. The centerpiece of these methodologies is the concept of precisiation of meaning. Addition of these methodologies to AI would be an important step toward the achievement of human level machine intelligence and its applications in decision-making, pattern recognition, analysis of evidence, diagnosis, and assessment of causality. Such applications have a position of centrality in our infocentric society.     

Reliability assessment of an automated distribution system

Automation can greatly enhance distribution-network reliability by speeding up service restoration and thus significantly reduce customer-outage time. The paper presents an approach to assess quantitatively the adequacy of a particular automated distribution scheme designated as the `low interruption system' (LIS). Owing to the use of a high-speed communication system and line sensors, this automated scheme can reduce drastically the number of interruptions, the service interruption time and also the area affected by the fault. This scheme provides a simple and cost-effective way to automate distribution systems in which the remotely controlled switches speed up isolation of faulted sections and the restoration of healthy sections through alternative routes. The step-by-step calculation procedure is presented using a typical small automated distribution system. The proposed technique is then applied to a larger distribution system to examine the effectiveness of the technique and also to examine the level of reliability improvement achieved by automation     

Learning user preferences of route choice behaviour for adaptive route guidance

As the use of navigation systems becomes more widespread, the demand for advanced functions of navigation systems also increases. In the light of user satisfaction, personalisation of route guidance by incorporating user preferences is one of the most desired features. A user model applied to personalised route guidance is presented. The user model adaptively updates route selection rules when it discovers the predicted choice differs from the actual choice of the driver. This study employs a decision tree learning algorithm, the C4.5 algorithm, which has advantages over other data mining methods in terms of its comprehensible model structure. Simulation experiments with a real-world network were conducted to analyse the applicability of the model to adaptive route guidance and the accuracy of its prediction     

QoS assessment of 3G video-phone calls by tracing watermarking exploiting the new colour space `YST?

Tracing watermarking has been recently proposed as a technique to provide a blind measure of the quality of service of the communication link, focusing on multimedia communication scenarios. 3G communication scenarios, where each customer transmits both voice and MPEG-4 video sequences in real time, have been considered. Typical video-phone call consists of close shots of speakers, framing their face in the foreground. For such particular application, a novel colour space (YST) is adopted to minimise the perceptual distortions on face coding introduced by watermarking. In the YST space, the luminance component (Y) is the same as in conventional YUV space, whereas the vectors S and T lie within the chrominance (UV) plane. The S (skin) component is a linear combination of U and V obtained as the 'average' chrominance estimated from an assorted set human faces to achieve a reasonable generalisation. The third component, T, is defined as orthogonal to the YS plane. The results show the benefits obtained in digital watermarking by the new representation against the conventional approach. In fact, the sensitivity of the YST representation outperforms the conventional one in terms of objective (mean square error, peak signal-to-noise ratio) and subjective (video-quality metrics) indicators.     

Investigation of Maximum and Minimum Satisfiability Problems Using L-Partition

Problems of the maximum and the minimum satisfiability on the basis of the integer linear programming and L-partition are studied. The L-structure of polyhedrons of the problems is investigated. Families are set up of unweighted problems of the maximum and the minimum satisfiability, the powers of L-coverings of which grow exponentially with an increase in the number of variables in a formula.     

A quantitative study of firewall configuration errors

The protection that firewalls provide is only as good as the policy they are configured to implement. Analysis of real configuration data show that corporate firewalls are often enforcing rule sets that violate well established security guidelines. Firewalls are the cornerstone of corporate intranet security. Once a company acquires a firewall, a systems administrator must configure and manage it according to a security policy that meets the company's needs. Configuration is a crucial task, probably the most important factor in the security a firewall provides.     

Guest Editors' Introduction: Overview of Sensor Networks

Wireless sensor networks could advance many scientific pursuits while providing a vehicle for enhancing various forms of productivity, including manufacturing, agriculture, construction, and transportation.     

Phase change process with free convection in a circular enclosure: numerical simulations

A numerical study of unsteady natural convection flow during freezing of water in a circular enclosure is presented. Mathematical model for phase change is based on apparent capacity method formulation and the governing equations are discretized on a fixed grid by means of finite element method. Water’s temperature is initially higher than its freezing temperature. Then, the temperature of the enclosure’s boundary is dropped to a temperature lower than freezing temperature. Ice forms at the enclosure boundary while natural convection flow is induced in the liquid region. Calculations have been made for the rate of change of solid fraction and temperature distributions, for conduction and conduction plus convection modes of heat transfer, and density inversion near freezing temperature phenomenon of water is considered. High resolution capturing of solid/liquid moving boundary as well as the details of flow structure is presented. The results indicate that the effect of natural convection is dominant over conduction if the Rayleigh number is higher than 5 × 10⁶ and relatively insignificant if the Rayleigh number is less than 1 × 10⁶.