A completely open cavity, which is formed by three 60-degree wedges of a photonic crystal with negative effective index, is introduced. Such a realizable design for a completely open cavity (i.e., without any reflective wall in the radial direction) is the first of its kind ever been reported. Due to the negative effective refraction index of the photonic crystal and the high transmission at the photonic crystal/air interfaces, a closed path with zero optical path is formed for the resonance. The present open cavity is very suitable for use as a biosens as it has large air wedges into which a liquid measurand can flow easily.

This paper proposes a practical algorithm for systematically generating strong Boolean functions (f:GF(2)n?úGF(2)) with cryptographic meaning. This algorithm takes bent function as input and directly outputs the resulted Boolean function in terms of truth table sequence. This algorithm was used to develop two classes of balanced Boolean functions, one of which has very good cryptographic properties: nl(f)=22k-1-2k+2k-2 (n=2k), with the sum-of-squares avalanche characteristic of f satisfying |òf=24k+23k+2+23k+23k-2 and the absolute avalanche characteristic of |¤f satisfying |¤f=2k+1. This is the best result up to now compared to existing ones. Instead of bent sequences, starting from random Boolean functions was also tested in the algorithm. Experimental results showed that starting from bent sequences is highly superior to starting from random Boolean functions.

The proton exchange membrane generation technology is highly efficient and clean, and is considered as the most hopeful ?°green?± power technology. The operating principles of proton exchange membrane fuel cell (PEMFC) system involve thermodynamics, electro

This paper briefly reviews other people?ˉs works on negative selection algorithm and their shortcomings. With a view to the real problem to be solved, authors bring forward two assumptions, based on which a new immune algorithm, multi-level negative selection algorithm, is developed. In essence, compared with Forrest?ˉs negative selection algorithm, it enhances detector generation efficiency. This algorithm integrates clonal selection process into negative selection process for the first time. After careful analyses, this algorithm was applied to network intrusion detection and achieved good results.

The maintaining overheads of Distributed Hash Table (DHT) topology have recently received considerable attention. This paper presents a novel SHT (Session Heterogeneity Topology) model, in which DHT is reconstructed with session heterogeneity. SHT clusters nodes by means of session heterogeneity among nodes and selects the stable nodes as the participants of DHT. With an evolving process, this model gradually makes DHT stable and reliable. Therefore the high maintaining overheads for DHT are effectively controlled. Simulation with real traces of session distribution showed that the maintaining overheads are reduced dramatically and that the data availability is greatly improved.

This article describes an Internet based laboratory (NETLAB) developed at Zhejiang University for electrical engineering education. A key feature of the project is the use of real experimental systems rather than simulation or virtual reality. NELTAB provides remote access to a wide variety of experiments, including not only basic electrical and electronic experiments but also many innovative control experiments. Students can effectively use the laboratory at any time and from anywhere. NETLAB has been in operation since July 2003.

In this paper, the authors present a novel mutual authentication and key agreement protocol based on the Number Theory Research Unit (NTRU) public key cryptography. The symmetric encryption, hash and ?°challenge-response?± techniques were adopted to build t

New challenges are introduced when people try to build a general-purpose mobile agent middleware in Grid environment. In this paper, an instance-oriented security mechanism is proposed to deal with possible security threats in such mobile agent systems. T

This paper presents a type system, called Location System (L-S), to control the interferences in the ambient-like calculi. The L-S allows well-behaved (non-interfering) processes to run in parallel if they do not access shared location during their execution life cycle. This approach is designed for a variant of Mobile Ambient (MA), called Safe Mobile Resources (SR), but it can be also used in other ambient-like calculi which are also discussed in this paper.

A new iris feature extraction approach using both spatial and frequency domain is presented. Steerable pyramid is adopted to get the orientation information on iris images. The feature sequence is extracted on each sub-image and used to train Support Vect

Support Vector Machine (SVM) is a machine learning algorithm based on the Statistical Learning Theory (SLT), which can get good classification effects with a few learning samples. SVM represents a new approach to pattern classification and has been shown

Used for industrial process with different degree of nonlinearity, the two predictive control algorithms presented in this paper are based on least squares Support Vector Machines (LS-SVM) model. For the weakly nonlinear system, the system model is built

A novel combined personalized feature framework is proposed for face recognition (FR). In the framework, the proposed linear discriminant analysis (LDA) makes use of the null space of the within-class scatter matrix effectively, and Global feature vectors (PCA-transformed) and local feature vectors (Gabor wavelet-transformed) are integrated by complex vectors as input feature of improved LDA. The proposed method is compared to other commonly used FR methods on two face databases (ORL and UMIST). Results demonstrated that the performance of the proposed method is superior to that of traditional FR approaches

In this paper the authors present a novel semi-automatic feature line detection technique for meshes. Taking into account the distance and orientation between two vertices on meshes and the curvature information of vertices, they first find an initial feature line which connects some user-specified vertices on meshes; then parameterize the ?°feature strip?± surrounding the feature line onto a planar domain using a vertex flattening technique; and refine the flattened feature strip using the 2D snakes approach to make the feature line smoother and more accurate; lastly they get the feature line by mapping the refined line back to the original meshes. Experimental results showed that their method can extract the feature line rapidly and precisely. As an application, they propose a mesh decomposition method based on the detected feature line.

An effective ensemble should consist of a set of networks that are both accurate and diverse. We propose a novel clustering-based selective algorithm for constructing neural network ensemble, where clustering technology is used to classify trained networks according to similarity and optimally select the most accurate individual network from each cluster to make up the ensemble. Empirical studies on regression of four typical datasets showed that this approach yields significantly smaller ensemble achieving better performance than other traditional ones such as Bagging and Boosting. The bias variance decomposition of the predictive error shows that the success of the proposed approach may lie in its properly tuning the bias/variance trade-off to reduce the prediction error (the sum of bias² and variance).

A multi-objective particle swarm optimization (MOPSO) approach for multi-objective economic load dispatch problem in power system is presented in this paper. The economic load dispatch problem is a non-linear constrained multi-objective optimization problem. The proposed MOPSO approach handles the problem as a multi-objective problem with competing and non-commensurable fuel cost, emission and system loss objectives and has a diversity-preserving mechanism using an external memory (call 鈥渞epository鈥? and a geographically-based approach to find widely different Pareto-optimal solutions. In addition, fuzzy set theory is employed to extract the best compromise solution. Several optimization runs of the proposed MOPSO approach were carried out on the standard IEEE 30-bus test system. The results revealed the capabilities of the proposed MOPSO approach to generate well-distributed Pareto-optimal non-dominated solutions of multi-objective economic load dispatch. Comparison with Multi-objective Evolutionary Algorithm (MOEA) showed the superiority of the proposed MOPSO approach and confirmed its potential for solving multi-objective economic load dispatch.

An information model is defined to support sharing scientific information on Web for archaeological pottery. Apart from non-shape information, such as age, material, etc., the model also consists of shape information and shape feature information. Shape information is collected by Lasers Scanner and geometric modelling techniques. Feature information is generated from shape information via feature extracting techniques. The model is used in an integrated storage, archival, and sketch-based query and retrieval system for 3D objects, native American ceramic vessels. A novel aspect of the information model is that it is totally implemented with XML, and is designed for Web-based visual query and storage application.

This paper presents an automatic non-photorealistic rendering approach to generating technical illustration from 3D models. It first decomposes the 3D object into a set of CSG primitives, and then performs the hidden surface removal based on the prioritized list, in which the rendition order of CSG primitives is sorted out by depth. Then, each primitive is illustrated by the pre-defined empirical lighting model, and the system mimics the stroke-drawing by user-specified style. In order to artistically and flexibly modulate the illumination, the empirical lighting model is defined by three major components: parameters of multi-level lighting intensities, parametric spatial occupations for each lighting level, and an interpolation method to calculate the lighting distribution over primitives. The stylized illustration is simulated by a grid-based method, in which we ‘fill’ the desirable pictorial units into the spatial occupation of CSG primitives, instead of “pixel-by-pixel” painting. This region-by-region shading facilitates the simulation of illustration styles.

Based on the framework of evidence theory, data fusion aims at obtaining a single Basic Probability Assignment (BPA) function by combining several belief functions from distinct information sources. Dempster’s rule of combination is the most popular rule of combinations, but it is a poor solution for the management of the conflict between various information sources at the normalization step. Even when it faces high conflict information, the classical Dempster-Shafer’s (D-S) evidence theory can involve counter-intuitive results. This paper presents a modified averaging method to combine conflicting evidence based on the distance of evidences; and also gives the weighted average of the evidence in the system. Numerical examples showed that the proposed method can realize the modification ideas and also will provide reasonable results with good convergence efficiency.