Hyperconnected attribute filters based on k-flat zones

In this paper, we present a new method for attribute filtering, combining contrast and structural information. Using hyperconnectivity based on k-flat zones, we improve the ability of attribute filters to retain internal details in detected objects. Simultaneously, we improve the suppression of small, unwanted detail in the background. We extend the theory of attribute filters to hyperconnectivity and provide a fast algorithm to implement the new method. The new version is only marginally slower than the standard Max-Tree algorithm for connected attribute filters, and linear in the number of pixels or voxels. It is two orders of magnitude faster than anisotropic diffusion. The method is implemented in the form of a filtering rule suitable for handling both increasing (size) and nonincreasing (shape) attributes. We test this new framework on nonincreasing shape filters on both 2D images from astronomy, document processing, and microscopy, and 3D CT scans, and show increased robustness to noise while maintaining the advantages of previous methods.     

DoS attacks exploiting signaling in UMTS and IMS

The Universal Mobile Telecommunication Standard (UMTS) is continuously evolving to meet the growing demand of modern mobile and Internet applications for high capacity and advanced features in security and quality of service. Although admittedly enhanced in terms of security when compared to 2G systems, UMTS still has weaknesses that can lead to security incidents. In this paper, we investigate the vulnerabilities of the UMTS security architecture that can be exploited by a malicious individual to mount Denial of Service (DoS) attacks. Our focus is on signaling-oriented attacks above the physical layer. We describe and analyze several novel attacks that can be triggered against both core UMTS architecture as well as hybrid UMTS/WLAN realms. An additional contribution of this paper is the presentation of an extensive survey of similar attacks in UMTS and related protocol infrastructures such as IP Multimedia Subsystem (IMS). Finally, we offer some suggestions that would provide greater tolerance to the system against DoS attacks.     

Three-dimensional face recognition in the presence of facial expressions: an annotated deformable model approach

In this paper, we present the computational tools and a hardware prototype for 3D face recognition. Full automation is provided through the use of advanced multistage alignment algorithms, resilience to facial expressions by employing a deformable model framework, and invariance to 3D capture devices through suitable preprocessing steps. In addition, scalability in both time and space is achieved by converting 3D facial scans into compact metadata. We present our results on the largest known, and now publicly available, face recognition grand challenge 3D facial database consisting of several thousand scans. To the best of our knowledge, this is the highest performance reported on the FRGC v2 database for the 3D modality     

Forecasting and trading the EUR/USD exchange rate with Gene Expression and Psi Sigma Neural Networks

The motivation for this paper is to investigate the use of two promising classes of artificial intelligence models, the Psi Sigma Neural Network (PSI) and the Gene Expression algorithm (GEP), when applied to the task of forecasting and trading the EUR/USD exchange rate. This is done by benchmarking their results with a Multi-Layer Perceptron (MLP), a Recurrent Neural Network (RNN), a genetic programming algorithm (GP), an autoregressive moving average model (ARMA) plus a naïve strategy. We also examine if the introduction of a time-varying leverage strategy can improve the trading performance of our models.     

The effect of two types of C-S-H on the elasticity of cement-based materials: Results from nanoindentation and micromechanical modeling

It has long been recognized, in cement chemistry, that two types of calcium-silicate-hydrate (C-S-H) exist in cement-based materials, but less is known about how the two types of C-S-H affect the mechanical properties. By means of nanoindentation tests on nondegraded and calcium leached cement paste, the paper confirms the existence of two types of C-S-H, and investigates the distinct role played by the two phases on the elastic properties of cement-based materials. It is found that (1) high-density C-S-H are mechanically less affected by calcium leaching than low density C-S-H, and (2) the volume fractions occupied by the two phases in the C-S-H matrix are not affected by calcium leaching. The nanoindentation results also provide quantitative evidence, suggesting that the elastic properties of the C-S-H phase are intrinsic material properties that do not depend on mix proportions of cement-based materials. The material properties and volume fractions are used in a novel two-step homogenization model, that predicts the macroscopic elastic properties of cement pastes with high accuracy. Combined with advanced physical chemistry models that allow, for a given w/c ratio, determination of the volume fractions of the two types of C-S-H, the model can be applied to any cement paste, with or without Portlandite, Clinker, and so on. In particular, from an application of the model to decalcified cement pastes, it is shown that that the decalcification of the C-S-H phase is the primary source of the macroscopic elastic modulus degradation, that dominates over the effect of the dissolution of Portlandite in cement-based material systems.     

Crack and flaw identification in elastodynamics using Kalman filter techniques

Filter-driven optimization based on the extended Kalman filter concept is used here for the numerical solution of crack and flaw identification problems in elastodynamics. The mechanical modeling of the studied two-dimensional problem, which includes the effect of unilateral contact along the sides of the crack, is done with the help of the boundary element method. The effect of various dynamical test loads and the applicability of this method for crack and defect identification in disks are investigated. The work has been supported by the German Research Foundation (DFG). Partial support has been provided by a Greek-German Research Cooperation Grant (IKYDA2001). This support is greatfully acknowledged.     

Defect identification in 3-D elastostatics using a genetic algorithm

An inverse problem in engineering mechanics is considered where the position and the geometry of three-dimensional, ellipsoidal defects are identified by using measurements of the mechanical response under static loading on the external surface of the structure. The problem is solved by appropriate combination of genetic optimization (GO) and boundary element method (BEM) and following previously published two-dimensional problems. The three-dimensional case presents some additional difficulties. Furthermore, the function of several genetic operators and the effect of the parameters of genetic optimization on the efficiency of the solution has been numerically examined.     

A heuristic algorithm for the just-in-time single machine scheduling problem with setups: a comparison with simulated annealing

This paper addresses the single machine early/tardy problem with unrestricted common due date and sequence-dependent setup times. Two algorithms are introduced to reach near-optimum solutions: the SAPT, a heuristic tailored for the problem, and a simulated annealing (SA) algorithm. It will be shown that SA provides solutions with slightly better quality; however, SAPT requires much less computational time. SAPT-SA is a hybrid heuristic that combines both approaches to obtain high quality solutions with low computational cost. Solutions provided by the three algorithms were compared to optimal solutions for problems with up to 25 jobs and to each other for larger problems.