We introduce an inheritance concept into a specification method of a concurrent system in order to reuse and refine existing specifications. Reusability by inheritance is emphasized in this paper. We take multiple inheritance to enable to reuse several specifications at a time. An upper specification can be skillfully reused by dividing inherited parts and non-inherited ones if the specification contains unnecessary parts for a lower specification. As an application, we specify the FIPA contract net interaction protocol (IP) with the function of an agent authentication. This is accomplished by using multiple inheritance. We also specify the FIPA iterated contract net IP by reusing the FIPA contract net IP. We have been developing a validation support tool for specifications described with the proposed method.

A workflow definition containing errors might cause serious problems for an enterprise especially when it involves mission critical business processes or inter-organizational interaction. So workflow definitions should be defined in a strict and rigorous way. In this paper, we develop a workflow definition language and analysis methods for the language to support strict and rigorous workflow definitions. Faults or mistakes causing communication deadlock, access conflicts, and improper exception specification in workflow definitions can be detected and notified automatically using the methods. The proposed workflow definition language borrows structured constructs of conventional programming languages because many good features of conventional programming languages also can be used effectively in expressing workflow processes. With slight modifications and scope restrictions, the developed analysis techniques in this paper can be used in any workflow definition languages and they can help workflow designers define workflow processes in much more safe and reliable manner.

In future high-speed networks, provision of diverse multimedia services with strict quality-of-service (QoS) requirements, such as bandwidth, delay and so on, is desired. QoS routing is a possible solution to handle these services. Generally, a path selection for QoS routing is formulated as a shortest path problem subject to multiple constraints. However, it is known to be NP-complete when more than one QoS constraint is imposed. As a result, many heuristic algorithms have been proposed so far. The authors proposed a path selection algorithm Fallback+ for QoS routing, which focuses not only on the path selection with multiple constraints but also on the efficient use of network resources. This paper proposes an enhanced version of Fallback+, named Enhanced Fallback+, where in a shrewd way, it keeps tentative paths produced in the conventional Fallback algorithm with Dijkstra's algorithm. Simulation experiments prove the excellent performance of Enhanced Fallback+, compared with the original Fallback+ and other existing path selection algorithms.

In this paper, the design of signature waveforms for asynchronous CDMA systems equipped with a correlation receiver is first considered. Optimal signature waveforms that minimize the average multiple access interference (MAI) at the output of a correlation receiver are found, while satisfying the constraint on available transmission bandwidth. Comparison to signature waveforms previously obtained for synchronous systems is also made to justify the superior performance of the designed signature waveforms in asynchronous systems. Furthermore, for direct-sequence CDMA (DS-CDMA) systems with random signature sequences, the use of multiple chip waveforms is also proposed as a means of suppressing MAI. Bandwidth constrained multiple chip waveforms that maximize the signal-to-interference ratio (SIR) at the output of each correlation receiver are found. Numerical results show that by using double chip waveforms instead of a single chip waveform, it is possible to reduce the MAI by 10% for a fixed transmission bandwidth (or equivalently, to save about 10% of transmission bandwidth for a given SIR requirement). The advantage of using double chip waveforms is also demonstrated in terms of the bit error rate (BER), whose calculation is based on our extension to Holtzman's approximation in.

In this paper, we introduce the following m-layered hard constrained convex feasibility problem HCF(m): Find a point u m, where 0:=H (a real Hilbert space), i: = arg min gi(i-1) and gi(u):=wi,jd 2(u,Ci,j) are defined for (i) nonempty closed convex sets Ci,jH and (ii) weights wi,j > 0 satisfying wi,j=1 (i {1,,m}, j {1,,Mi}. This problem is regarded as a natural extension of the standard convex feasibility problem: find a point u Ci, where Ci H (i {1,, M}) are closed convex sets. Unlike the standard problem, HCF(m) can handle the inconsistent case; i.e., i,j Ci,j = , which unfortunately arises in many signal processing, estimation and design problems. As an application of the hybrid steepest descent method for the asymptotically shrinking nonexpansive mapping, we present an algorithm, based on the use of the metric projections onto Ci,j, which generates a sequence (un) satisfying limn d(un,3) = 0 (for M1 = 1) when at least one of C1,1 or C2,j's is bounded and H is finite dimensional. An application of the proposed algorithm to the pulse shaping problem is given to demonstrate the great flexibility of the method.

In this paper, we propose two fast codebook generation algorithms for entropy-constrained vector quantization. The first algorithm uses the angular constraint to reduce the search area and to accelerate the search process in the codebook design. It employs the projection angles of the vectors to a reference line. The second algorithm has feature of using a suitable hyperplane to partition the codebook and image data. These algorithms allow significant acceleration in codebook design process. Experimental results are presented on image block data. These results show that our new algorithms perform better than the previously known methods.

We propose using SQP (Sequential Quadratic Programming) to directly recover 3D quadratic surface parameters from multiple views. A surface equation is used as a constraint. In addition to the sum of squared reprojection errors defined in the traditional bundle adjustment, a Lagrangian term is added to force recovered points to satisfy the constraint. The minimization is realized by SQP. Our algorithm has three advantages. First, given corresponding features in multiple views, the SQP implementation can directly recover the quadratic surface parameters optimally instead of a collection of isolated 3D points coordinates. Second, the specified constraints are strictly satisfied and the camera parameters and 3D coordinates of points can be determined more accurately than that by unconstrained methods. Third, the recovered quadratic surface model can be represented by a much smaller number of parameters instead of point clouds and triangular patches. Experiments with both synthetic and real images show the power of this approach.

In databases based on a multi-aspects object data model whcih enables multiple aspects of a real-world entity to be represented and to be acquired/lost dynamically, Object Migration (OM) updating membership relationships between an object and classes occurs, as the properties of the object evolve in its lifetime. We have proposed an OM behavior modeling framework using Colored Petri Nets (CPN) to analyze OM behavior. Based on the proposed framework, this paper presents a technique for constructing OM behavior models from OM constraint descriptions and class schemas as its input. The presented technique makes it easy to construct consistent and complete OM behavior models, since OM constraints are described in a simple, modular, and declarative form.

Edge linking is a fundamental computer vision task, yet presents difficulties arising from the lack of information in the image. Viewed as a constrained optimization problem, it is NP hard-being isomorphic to the classical Traveling Salesman Problem. This paper proposes a gradient ascent learning algorithm of the elastic net approach for edge linking of images. The learning algorithm has two phases: an elastic net phase, and a gradient ascent phase. The elastic net phase minimizes the path through the edge points. The procedure is equivalent to gradient descent of an energy function, and leads to a local minimum of energy that represents a good solution to the problem. Once the elastic net gets stuck in local minima, the gradient ascent phase attempts to fill up the valley by modifying parameters in a gradient ascent direction of the energy function. Thus, these two phases are repeated until the elastic net gets out of local minima and produces the shortest or better contour through edge points. We test the algorithm on a set of artificial images devised with the aim of demonstrating the sort of features that may occur in real images. For all problems, the systems are shown to be capable of escaping from the elastic net local minima and producing more meaningful contours than the original elastic net.

Constraints have been used extensively for the construction of graphical user interfaces. User interface constraints that are declarative are more favorable but require sophisticated constraint planning algorithms. Constraint planning algorithms proposed previously are getting more and more complicated as they were asked to handle more general requirements. We believe that the difficulty is mainly caused by the complicated data structure that is translated directly from the problem. By a transformation, we propose a simplified graph model for the problem and prove that the constraint planning problem can be reduced to finding feedback vertex sets on the simplified graph model. We also consider the general problem of handling non-uniform user interface constraints.

A low energy plasma based on an electron discharge was investigated for the pre-epi clean of silicon wafers and for plasma enhanced homo and hetero epitaxial growth of Si and SiGe layers. VS were produced in a short, completely dry process sequence consisting of LEPC and LEPECVD only. The wafer/epilayer interface obtained in this process sequence was suitable to grow high quality VS with low surface roughness and dislocation densities. Based on this process and its implementation in a 200/300 mm single wafer cluster tool, a high volume and economical production of VS seems possible.

In an optical time domain reflectometer type strain measurement system, we theoretically derive the shape of the Brillouin gain spectrum produced in an optical fiber under a parabolic strain distribution which is formed in a uniformly loaded beam. Based on the derived result, we investigate the effects of the parabolic strain distribution parameters and the measurement conditions such as the launched pulse width and the measurement position on the beam on the deformation of the Brillouin backscattered-light power spectrum shape. In addition, we investigate the strain measurement error resulting from the deformation of the power spectrum shape by analyzing the peak-power frequency at which the power spectrum is maximized.

Analog Hopfield neural networks (HNNs) have so far been used to solve many kinds of optimization problems, in particular, combinatorial problems such as the TSP, which can be described by an objective function and some equality constraints. When we solve a minimization problem with equality constraints by using HNNs, however, the constraints are satisfied only approximately. In this paper we propose a circuit which rigorously realizes the equality constraints and whose energy function corresponds to the prescribed objective function. We use the SPICE program to solve circuit equations corresponding to the above circuits. The proposed method is applied to several kinds of optimization problems and the results are very satisfactory.

This study describes the feasibility of using the penalty-function nonlinear programming neural network method to find the optimal power generating output which minimizes both the costs of generating power and power transmission losses. This method depends on neural network technology in acquiring exterior penalty function. Employing nonlinear function in equality and inequality constraints, the model is established using a neural network and additional objective functions; these additional objective functions expand cost function by using an appropriate penalty function. In this study, a 26-busbar including six generators was used to test the penalty function nonlinear programming neural network method. A comparison with the sequential unconstrained minimization technique (SUMT) demonstrates the reliability and precision of the optimal solution obtained using the new method.

We present a new approach to the loop scheduling problem, which excels previous solutions in two important aspects: The resource constraints are formulated using flow graphs, and the initiation interval λ is treated as a rational variable. The approach supports heterogeneous processor architectures and pipelined functional units, and the Integer Linear Programming implementation produces an optimum loop schedule, whereby a minimum λ is achieved. Our flow graph model facilitates the cyclic binding of loop operations to functional units. Compared to previous research results, the solution can provide faster loop schedules and a significant reduction of the problem complexity and solution time.

In this paper, a spatio-temporal error concealment method of transmission errors for improving visual quality over the wireless channel is proposed, which makes use of geometric information extracted from the surrounding blocks. The geometric information is an isophote that is curves of constant intensity of image. To improve visual quality during video communication, the proposed method smoothly connects the isophotes disconnected due to transmission error using a genetic algorithm (GA) with an isophote constraint. In the proposed method, the error concealment problem is modeled as an optimization problem, which in our case, is solved by a cost function with isophotes constraint that is minimized using a GA. Experimental results shows more visually realistic than other error concealment methods.

12 on/off power splitters at λ=0.63µm have been produced in LiNbO3 substrates using strain-induced channel waveguides formed by magnetron deposition of surface metal films and lift-off technology. The static strain resulting from thermal expansion mismatch between the substrate and the metal films induces a localized increase in the refractive index via the strain-optic effect. On/off voltage of about 25V has been demonstrated.

In many applications of Independent Component Analysis (ICA) and Blind Source Separation (BSS) estimated sources signals and the mixing or separating matrices have some special structure or some constraints are imposed for the matrices such as symmetries, orthogonality, non-negativity, sparseness and specified invariant norm of the separating matrix. In this paper we present several algorithms and overview some known transformations which allows us to preserve several important constraints.

Monte Carlo simulation of the low field electron mobility of strained Si and SiGe active layers on Si and SiGe substrates is considered. The Ge mole fractions of both the active layer and the substrate are varied in a wide range. The linear deformation potential theory is used to calculate the shifts of the conduction band minima due to uniaxial strain along [001]. The energy shifts and the effective masses are assumed to be functions of the Ge mole fraction. It is shown that in spite of the fact that the L-valleys remain degenerate under strain conditions considered here, they play an important role at very high Ge compositions especially when SiGe as substrate is used. We found that in this case the repopulation effects of the X-valleys affect electron mobility much stronger than the alloy scattering. We also generalize the ionized impurity scattering rate to include strain effects for doped materials and show that some of the important parameters such as effective density of states, inverse screening length, and the screening function are split due to strain and must be properly modified. Finally, we perform several simulations for undoped and doped materials using Si and SiGe substrates.

New physical models, algorithms, and parameters are needed to accurately model emerging silicon-on-insulator (SOI) devices. The modeling approaches for various emerging SOI technologies are discussed in this paper.