A Biologically-Parameterized Feather Model

Feathers, unlike other cutaneous appendages such as hair, fur, or scales have a definite structure. Variation in feather structure creates a wide range of resulting appearances. Collectively, feather structure determines the appearance of the feather coat, which can largely affect the resulting look of a feathered object (bird). In this paper we define the structure of individual feathers using a parameterization based on biological structure and substructures of actual feathers. We show that our parameterization can generate a large variety of feathers at multiple levels of detail and provide an initial step to semi‐automatically generating a wide range of feather coats. his is achieved by specifying an intuitive interpolation between different structures and ages of feathers.     

A practical controller for explicit rate congestion control

This paper examines congestion control for explicit rate data networks. The available bit rate (ABR) service category of asynchronous transfer mode (ATM) networks serves as an example system, however, the results of this paper are applicable to other explicit rate systems as well. After a plant model is established, an adaptive control strategy is presented. Several algorithm enhancements are then introduced. These enhancements reduce convergence time, improve queue depth management, and reduce parameter bias. This work differentiates itself from the other contributions in the area of rate-based congestion control in its balanced approach of retaining enough complexity as to afford attractive performance properties, but not so much complexity as to make implementation prohibitively expensive     

Cluster analysis in industrial market segmentation through artificial neural network

Market segmentation has commonly applied cluster analysis. This study intends to make the comparison of conventional two-stage method with proposed two-stage method through the simulated data. The proposed two-stage method is the combination of self-organizing feature maps and K-means method. The simulation results show that the proposed scheme is better than the conventional two-stage method based on the rate of misclassification.     

A Refinement Calculus for Shared-Variable Parallel and Distributed Programming

Parallel computers have not yet had the expected impact on mainstream computing. Parallelism adds a level of complexity to the programming task that makes it very error-prone. Moreover, a large variety of very different parallel architectures exists. Porting an implementation from one machine to another may require substantial changes. This paper addresses some of these problems by developing a formal basis for the design of parallel programs in the form of a refinement calculus. The calculus allows the stepwise formal derivation of an abstract, low-level implementation from a trusted, high-level specification. The calculus thus helps structuring and documenting the development process. Portability is increased, because the introduction of a machine-dependent feature can be located in the refinement tree. Development efforts above this point in the tree are independent of that feature and are thus reusable. Moreover, the discovery of new, possibly more efficient solutions is facilitated. Last but not least, programs are correct by construction, which obviates the need for difficult debugging. Our programming/specification notation supports fair parallelism, shared-variable and message-passing concurrency, local variables and channels. The calculus rests on a compositional trace semantics that treats shared-variable and message-passing concurrency uniformly. The refinement relation combines a context-sensitive notion of trace inclusion and assumption-commitment reasoning to achieve compositionality. The calculus straddles both concurrency paradigms, that is, a shared-variable program can be refined into a distributed, message-passing program and vice versa. Received July 2001 / Accepted in revised form May 2002     

Creating and Justifying Research and Development Value: Scope,Scale, Skill and Social Networking of R&D

In this paper we describe a framework for analysing the creation and justification of Research & Development. The 4S framework is developed for analysing the scope, scale, skills and social network aspects of Research & Development value. The framework is based on social system theory, a process contingency model, and recent Research & Development metrics. We present a first empirical assessment based on a workshop using the 4S framework for leveraging Research & Development. Results that assist in the assessment of value creation utilising R & D within networks are very relevant in high tech industries. The multi–dimensional process approach of this framework seems promising for understanding and managing R&D value creation, but needs further operationalisation. Case studies are described and a Dutch network on leveraging R&D has been initiated.     

Mathematical analysis of dynamic channel selection in indoor mobilewireless communication systems

Dynamic channel selection (DCS) is an algorithm for flexible resource sharing in mobile radio systems. The digital enhanced cordless telecommunications (DECT) standard implements a version of DCS based on time as well as frequency multiplexing. In this paper, mathematical models are developed to evaluate the probabilities of channel availability, desired carrier power, and the carrier-to-interference ratio (CIR) for a constant traffic load. These results can be used to compute the call setup blocking probability. The models reported in this study are based on a decentralized DCS according to the DECT standard specifications. The results show that blocking due to availability of a channel (resource blocking), not interference blocking, generally is the most important factor in overall call blocking. Furthermore, it is seen that resource blocking is sensitive to the implementation of portable sets. Also, with homogeneous static traffic, this type of DCS ran be as good as fixed channel allocation (FCA) with respect to resource blocking     

Textural evolution in electrodeposits under the influence of adsorbed foreign species: Part I Textural evolution in iron electrodeposits affected by hydrogen co-deposition

Textural evolution in electrodeposits is strongly affected by foreign species in the electrolyte and also by the co-deposition of hydrogen. The effects of foreign species on textural development in electrodeposits were studied by employing a Monte Carlo model. This model is based on physical principles and incorporates parameters which are used to control electrodeposition processes. An attempt was made in the simulation to reflect the basic process of the deposit growth, and to identify the factors responsible for the texture formation and its variation with the deposition condition. It is assumed that the texture of the deposit results from the minimization of the free energy of the system. Based on this assumption, it was demonstrated that the surface-energy anisotropy played an important role in the formation of fibre texture. In particular, the model can be used to simulate textural evolution under the influence of adsorbed foreign species, because the surface-energy anisotropy is modified by the adsorbed foreign species. Part I of the paper presents results of our studies on iron electrodeposition with the emphasis on the effect of hydrogen adsorption on iron deposit texture. Relevant experimental results have also been presented to corroborate the simulation study. Part II of the paper presents simulation studies of textural evolution in copper deposits under the influence of adsorbed potassium and chloride ions. This revised version was published online in November 2006 with corrections to the Cover Date.     

Object-oriented H.263 compatible video coding platform forconferencing applications

This paper describes a prototype video coding platform meant for the conception and testing of multimedia products such as next-generation videophones. The platform is largely based on ITU-T Recommendation H.263, with a number of additional object-oriented quality enhancement features which make it especially well suited for very low bit-rate coding of “head-and-shoulders” video material typical of real-time multimedia applications, video teleconferencing, and video telephony. These features consist of: (1) segmentation into objects of interest, (2) segmentation-based prefiltering, (3) model-assisted rate control, (4) adaptive vector quantization, and finally (5) segmentation-based postfiltering. In the spirit of Recommendation H.263, these enhancements are modular and can be selectively turned on or off, thereby enabling a wide variety of coding modes     

The effect of surface roughness on the radiative properties ofpatterned silicon wafers

The radiative properties of patterned silicon wafers have a major impact on the two critical issues in rapid thermal processing (RTP), namely wafer temperature uniformity and wafer temperature measurement. The surface topography variation of the die area caused by patterning and the roughness of the wafer backside can have a significant effect on the radiative properties, but these effects are not well characterized. We report measurements of room temperature reflectance of a memory die, logic die, and various multilayered wafer backsides. The surface roughness of the die areas and wafer backsides is characterized using atomic force microscopy (AFM). These data are subsequently used to assess the effectiveness of thin film optics in providing approximations for the radiative properties of patterned wafers for RTP applications     

Entropy Optimization Models with Convex Constraints

In this paper, we study the minimum cross-entropy optimization problem subject to a general class of convex constraints. Using a simple geometric inequality and the conjugate inequality we demonstrate how to directly construct a "partial" geometric dual program which allows us to apply the dual perturbation method to derive the strong duality theorem and a dual-to-primal conversion formula. This approach generalizes the previous results of linearly, quadratically, and entropically constrained cross-entropy optimization problems and provides a platform for using general purpose optimizers to generate ε-optimal solution pair to the problem.