Curve/surface representation and evolution using vector level sets with application to the shape-based segmentation problem

In this paper, we revisit the implicit front representation and evolution using the vector level set function (VLSF) proposed in (H. E. Abd El Munim, et al., Oct. 2005). Unlike conventional scalar level sets, this function is designed to have a vector form. The distance from any point to the nearest point on the front has components (projections) in the coordinate directions included in the vector function. This kind of representation is used to evolve closed planar curves and 3D surfaces as well. Maintaining the VLSF property as the distance projections through evolution will be considered together with a detailed derivation of the vector partial differential equation (PDE) for such evolution. A shape-based segmentation framework will be demonstrated as an application of the given implicit representation. The proposed level set function system will be used to represent shapes to give a dissimilarity measure in a variational object registration process. This kind of formulation permits us to better control the process of shape registration, which is an important part in the shape-based segmentation framework. The method depends on a set of training shapes used to build a parametric shape model. The color is taken into consideration besides the shape prior information. The shape model is fitted to the image volume by registration through an energy minimization problem. The approach overcomes the conventional methods problems like point correspondences and weighing coefficients tuning of the evolution (PDEs). It is also suitable for multidimensional data and computationally efficient. Results in 2D and 3D of real and synthetic data will demonstrate the efficiency of the framework     

Dynamic Control of Walking Cycle with Initiation Process for Humanoid Robot

This paper focuses on numerical method to solve the dynamic equilibrium of a humanoid robot during the walking cycle with the gait initiation process. It is based on a multi-chain strategy and a dynamic control/command architecture previously developed by Gorce. The strategy is based on correction of the trunk center of mass acceleration and force distribution of the forces exerced by the limbs on the trunk. This latter is performed by mean of a Linear Programming (LP) method. We study the gait initiation process when a subject, initially in quiet erect stance posture, performs a walking cycle. In this paper, we propose to adjust the method for the multiphases (from double support to single support) and multicriteria features of the studied movement. This is done by adapting some specific constraints and criteria in order to ensure the global stability of the humanoid robot along the task execution. For that, we use a Real-Time Criteria and Constraints Adaptation method. Simulation results are presented to demonstrate criteria and constraints influences on the dynamic stability.     

Wavelet approximation-based affine invariant shape representation functions

In this paper, new wavelet-based affine invariant functions for shape representation are presented. Unlike the previous representation functions, only the approximation coefficients are used to obtain the proposed functions. One of the derived functions is computed by applying a single wavelet transform; the other function is calculated by applying two different wavelet transforms with two different wavelet families. One drawback of the previously derived detail-based invariant representation functions is that they are sensitive to noise at the finer scale levels, which limits the number of scale levels that can be used. The experimental results in this paper demonstrate that the proposed functions are more stable and less sensitive to noise than the detail-based functions.     

On the generation of test patterns for multiple faults

This article presents a new method to generate test patterns for multiple stuck-at faults in combinational circuits. We assume the presence of all multiple faults of all multiplicities and we do not resort to their explicit enumeration: the target fault is a single component of possibly several multiple faults. New line and gate models are introduced to handle multiple fault effect propagation through the circuits. The method tries to generate test conditions that propagate the effect of the target fault to primary outputs. When these conditions are fulfilled, the input vector is a test for the target fault and it is guaranteed that all multiple faults of all multiplicities containing the target fault as component are also detected. The method uses similar techniques to those in FAN and SOCRATES algorithms to guide the search part of the algorithm, and includes several new heuristics to enhance the performance and fault detection capability. Experiments performed on the ISCAS'85 benchmark circuits show that test sets for multiple faults can be generated with high fault coverage and a reasonable increase in cost over test generation for single stuck-at faults.     

Effect of heat treatment on the structural and optical properties of CuInTe2 thin films

The CuInTe2 thin films were prepared by thermal vacuum evaporation of the bulk compound. The structural and optical properties in the temperature range 300–47 K of thin films grown on glass substrates and annealed in vacuum were studied. The films were investigated by X-ray diffraction and electron microscope techniques. The calculated lattice constants for CuInTe₂ powder were found to bea=0.619 nm andc –1,234 nm. From the reflection and transmission data, the optical constants, refractive indexn, absorption index,k, and the absorption coefficient, , werw computed. The optical energy gap was determined for CuInTe₂ thin films heat treated at different temparatures for different periods of time. It was found thatE _g increases with both increasing temperature and time of annealing.     

Explanation-Based Learning for Diagnosis

We present explanation-based learning (EBL) methods aimed at improving the performance of diagnosis systems integrating associational and model-based components. We consider multiple-fault model-based diagnosis (MBD) systems and describe two learning architectures. One, EBLIA, is a method for learning in advance. The other, EBL(p), is a method for learning while doing. EBLIA precompiles models into associations and relies only on the associations during diagnosis. EBL(p) performs compilation during diagnosis whenever reliance on previously learned associational rules results in unsatisfactory performance—as defined by a given performance threshold p. We present results of empirical studies comparing MBD without learning versus EBLIA and EBL(p). The main conclusions are as follows. EBLIA is superior when it is feasible, but it is not feasible for large devices. EBL(p) can speed-up MBD and scale-up to larger devices in situations where perfect accuracy is not required.     

Ferrimagnetic resonance and low temperature transition in Ni- and Co-substituted powder magnetite

The effects of nickel and cobalt substitution on ferrimagnetic resonance in high-purity magnetite powder have been investigated. The low-temperature transition temperature and damping parameter, , are found to decrease with increasing solute additions. The linewidth, H, varies in proportion to the anisotropy field of the ferrites, narrowing with increasing nickel content but broadening with increasing cobalt content. Theg factor increases with the dopant concentration, passing through a maximum around room temperature. Decreasing the deviation from stoichiometry by appropriate annealing decreases the transition temperature shift but slightly increases H, g and .     

Intracellular localization of samarium in the lactating mammary gland cells: ultrastructural and microanalytical study

The frequent use of some rare earths in the medical and industrial domains make us worry about their intracellular behavior into the body. Reason for which we have investigated the subcellular localization of one of these elements, the samarium, in the mammary gland of lactating female wistar rats using two very sensitive methods of observation and microanalysis, the transmission electron microscopy and the secondary ion mass spectrometry. The ultrastructural study showed the presence of electron dense deposits in the lactating mammary glandular epithelial cell lysosomes of the samarium-treated rats, but no loaded lysosomes were observed in those of control rats. The microanalytical study allowed both the identification of the chemical species present in those deposits as samarium isotopes ((152) Sm(+)) and the cartography of its distribution. Our results confirm the previous ones showing that lysosomes of the glandular epithelial cells are the site of the intracellular concentration of foreign elements such as gallium. The intralysosomal deposits observed in the mammary glandular cells of the samarium-treated rats are similar in their form and density to those observed with the same element in other varieties of cells, such as liver, bone marrow, and spleen cells. Our ultrastructural and microanalytical results and those obtained in previous studies allow deducing that the intralysosomal deposits are very probably composed of an insoluble samarium phosphate salt.     

Solving knapsack problems on GPU

A parallel implementation via CUDA of the dynamic programming method for the knapsack problem on NVIDIA GPU is presented. A GTX 260 card with 192 cores (1.4 GHz) is used for computational tests and processing times obtained with the parallel code are compared to the sequential one on a CPU with an Intel Xeon 3.0 GHz. The results show a speedup factor of 26 for large size problems. Furthermore, in order to limit the communication between the CPU and the GPU, a compression technique is presented which decreases significantly the memory occupancy.     

3D model based tracking for omnidirectional vision: A new spherical approach

The current work addresses the problem of 3D model tracking in the context of monocular and stereo omnidirectional vision in order to estimate the camera pose. To this end, we track 3D objects modeled by line segments because the straight line feature is often used to model the environment. Indeed, we are interested in mobile robot navigation using omnidirectional vision in structured environments. In the case of omnidirectional vision, 3D straight lines are projected as conics in omnidirectional images. Under certain conditions, these conics may have singularities.In this paper, we present two contributions. We, first, propose a new spherical formulation of the pose estimation withdrawing singularities, using an object model composed of lines. The theoretical formulation and the validation on synthetic images thus show that the new formulation clearly outperforms the former image plane one. The second contribution is the extension of the spherical representation to the stereovision case. We consider in the paper a sensor which combines a camera and four mirrors. Results in various situations show the robustness to illumination changes and local mistracking. As a final result, the proposed new stereo spherical formulation allows us to localize online a robot indoor and outdoor whereas the classical formulation fails.