Catálogo de publicaciones - libros

In order to achieve a high performance in a real implementation of the non-repudiation service it is necessary to estimate timeouts, TTP features, publication key time, number of originators and recipients, and other relevant parameters. An initial work of the authors focused on a basic event-oriented simulation model for the estimation of timeouts. In the actual work, we present a set of extensions to that basic model for the estimation of the TTP features (storage capacity and ftp connection capacity). We present and analyze the new and valuable results obtained.

For address the issue of key management in the large-scale wireless sensor networks, we propose TLKMS(Two-Level Key Management Scheme)which will be used in clustered sensor networks based on EBS system. In this paper, we show the detail of dynamic keys management scheme which has master and slayer two levels. It works from the deployment of sensor nodes to the end of networks to manage all of the sensor nodes’ keys. And regarding of the specialty of sensor networks, the scheme is separated to three phases which are initialization phase, steady phase and update phase. The experiment shows that the sensor nodes in our scheme only need to store fewer keys and the whole network performs good ability in keep network elasticity.

Sensor networks are often deployed in hostile environments, thus leaving these networks vulnerable to false data injection attacks in which adversaries inject forged reports into the network through compromised nodes, with the goal of deceiving the base station or depleting the limited energy resources of forwarding nodes. The commutative cipher based en-route filtering scheme was proposed to detect and drop such forged reports during the forwarding process. In this scheme, the choice of a security parameter represents a trade-off between detection capability and overhead. In this paper, we propose a fuzzy based adaptive parameter determining method in which the security parameter is adaptively determined by a fuzzy rule based system. False traffic ratio, distance, and energy level are used to determine the security parameter. The effectiveness of the proposed method against false data injection attacks is shown by the simulation results.

This research focuses on the making the smart factory of supporting utility machine for real-time environment using wireless sensor network architecture. The purpose of this research is the extending lifetime of the utility machines like motors, water-pumps and compressor machine by checking the white noise, illegal vibration and high temperature. We present the monitoring system to provide a smart solution to the factory maintenance through making and installing the tiny sensor nodes which support the self-coordinating wireless sensor network. We also present the simple application of this system for CMMS (Computerized Maintenance Management System). Last we compare this one to existing PLC based Sensor measuring system.

Since sensor nodes inter-work with one another on Ubiquitous Sensor Networks (USNs) to transfer data to the sink node, the lifetime of each sensor becomes an important factor for determining that of the USN. The users cannot recognize the scattered sensor nodes; thus, any sensor node cannot be recharged or replaced. The lifetime of a sensor node is determined by its battery. Accordingly, the lifetime of the entire communication network is required to increase by decreasing energy usage as much as possible to enable all of the sensor nodes to operate for a long time. Much energy is used in the following process: Initialization process where clusters are built, the normal operations of collecting data and transferring them to the sink node, or while the routing table is updated when an error occurs on a node during normal operation. In order to extend the entire lifetime of the USN, a technology for minimizing energy consumption is required in a variety of areas. In this study, an algorithm is introduced in order to decrease the energy required to update a routing table while recovering a fault from a node.

Monte Carlo is the only choice for a physically correct method to do global illumination in the field of realistic image synthesis. Generally Monte Carlo based algorithms require a lot of time to eliminate the noise to get an acceptable image. Adaptive sampling is an interesting tool to reduce noise, in which the evaluation of homogeneity of pixel’s samples is the key point. In this paper, we propose a new homogeneity measure, namely the arithmetic mean - geometric mean difference (abbreviated to  −  difference), which is developed to execute adaptive sampling efficiently. Implementation results demonstrate that our novel adaptive sampling method can perform significantly better than classic ones.

This paper presents a novel data-driven method for creating realistic face models based on estimated high-level feature control models. Our method takes as examples 3D face scans. By bringing scanned models into full correspondence with a model fitting approach, we apply principal component analysis (PCA) to the exemplar shapes of each facial feature to build a shape space. We compute a set of face anthropometric measurements to parameterize example feature shapes in the measurement spaces. Using the PCA coefficients as a compact shape representation, we approach the shape synthesis problem by forming scattered data interpolation functions that are devoted to the generation of desired shape by taking the anthropometric parameters as input. The correspondence among all exemplar textures is obtained by parameterizing a 3D generic mesh over a 2D image domain. The new feature texture with desired attributes is synthesized by interpolating the example textures.

We present a method of synthesising a texture using dynamic neighbourhood matching. Like existing pixel-based methods, the output is synthesised by comparing neighbourhoods of sample and target pixels. However unlike most methods, we do not specify a fixed neighbourhood size a priori. Instead the window size is determined dynamically for each pixel that is synthesised. Typically the output image is initialised with noise. In our approach, we use patches as a seed with which to guide the matching process. The patches are retrieved using the watershed method to isolate texture elements. As a result our outputs have reduced smudging, and fewer jagged drawn out texture anomalies that are problematic in existing pixel-based methods.

The area of molecular biology opens new applications for the communities of computer graphics, geometric modeling and computational geometry. It has been a usual understanding that the structure of a molecule is one of the major factors determining the functions of the molecule and therefore the efforts to better understand the molecular structure have been made.

It turns out that the analysis and the prediction of the spatial structure of a molecule usually takes a significant amount of computation even though the number of atoms involved in the molecule is relatively small. Examples are the protein-ligand docking, protein folding, etc.

In many molecules, however, the number of atoms is quite large. The number of atoms in the system varies from hundreds to thousands of thousand. The problem size gets even larger by both incorporating more details of a model and expanding the scope of the model from a single protein to a whole cell. This trend will continue as the computational resource gets more powerful and therefore the computational requirement will always remain critical.

In this paper, we propose a multi-resolution model for a protein (MRPM) to find a seemingly optimal trade-off between the computational requirement and the solution quality. There are two aspects of the proposal: The avoidance of computation and the delay of computation until it is really necessary.

Computational origami is the computer assisted study of origami as a branch of science of shapes. The origami construction is a countably finite sequence of fold steps, each consisting in folding along a line. In this paper, we formalize origami construction. We model origami paper by a set of faces over which we specify relations of overlay and adjacency. A fold line is determined by a specific fold method. After folding along the fold line, the structure of origami is transformed; some faces are divided and moved, new faces are created and therefore the relations over the faces change. We give a formal method to construct the model origami. The model furthermore induces a graph of layers of faces. We give two origami examples as the application of our model. They exhibit non-trivial aspects of origami which are revealed only by formal modeling. The model is the abstraction of the implemented core of the system of computational origami called (E-origami system).