An experimental investigation on the nature of reverse current of silicon power pn-junctions

At this time, little importance is given to the surface component of reverse leakage current of silicon pn-junctions although reliability issues reveal device blocking weakness when performing at high voltage and temperature. Junctions which have almost the same perimeter but different area have been realized and their reverse current has been measured at room temperature and high temperature both for standard recovery and fast recovery (gold-doped or electron irradiated) pn-junctions. It is shown that for standard recovery junctions the surface component of the reverse current is the primary component from room temperature up to above 150/spl deg/C and has influence on reaching high permissible working voltages. For gold-doped or electron irradiated junctions, the bulk component is dominant at high junction temperature, but it is shown that a comparatively negligible surface component can impose lower reverse working voltages or lower junction operation temperature. The surface component may be a cause of limitation on the operation of power silicon diodes at high reverse voltage above 175-200/spl deg/C junction temperature.     

Predictive control architecture for real-time image moments based servoing of robot manipulators

This paper presents a real-time architecture for visual servoing of robot manipulators using nonlinear based predictive control. In order to increase the robustness of the control algorithm, image moments were chosen to be the visual features which describe the objects from the image. A visual predictive architecture is designed to solve tasks addressed to robot manipulators with an eye-in-hand configuration. An implementation of the proposed architecture is done so that the capabilities of a 6 d.o.f robot manipulator are extended. The results of different experiments conducted with two types of image moments based controllers (proportional and predictive with reference trajectory) are presented and discussed.     

A search space “cartography” for guiding graph coloring heuristics

We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, we introduce the following clustering hypothesis: the high quality solutions are not randomly scattered in the search space, but rather grouped in clusters within spheres of specific diameter. We first provide intuitive evidence for this hypothesis by presenting a projection of a large set of local minima in the 3D space. An experimental confirmation is also presented: we introduce two algorithms that exploit the hypothesis by guiding an underlying Tabu Search (TS) process. The first algorithm (TS-Div) uses a learning process to guide the basic TS process toward as-yet-unvisited spheres. The second algorithm (TS-Int) makes deep investigations within a bounded region by organizing it as a tree-like structure of connected spheres. We experimentally demonstrate that if such a region contains a global optimum, TS-Int does not fail in eventually finding it. This pair of algorithms significantly outperforms the underlying basic TS algorithm; it can even improve some of the best-known solutions ever reported in the literature (e.g. for dsjc1000.9).     

Deblurring by Matching

Restoration of the photographs damaged by the camera shake is a challenging task that manifested increasing attention in the recent period. Despite of the important progress of the blind deconvolution techniques, due to the ill-posed nature of the problem, the finest details of the kernel blur cannot be recovered entirely. Moreover, the additional constraints and prior assumptions make these approaches to be relative limited.
In this paper we introduce a novel technique that removes the undesired blur artifacts from photographs taken by hand-held digital cameras. Our approach is based on the observation that in general several consecutive photographs taken by the users share image regions that project the same scene content. Therefore, we took advantage of additional sharp photographs of the same scene. Based on several invariant local feature points, filtered from the given blurred/non-blurred images, our approach matches the keypoints and estimates the blur kernel using additional statistical constraints.
We also present a simple deconvolution technique that preserves edges while minimizing the ringing artifacts in the restored latent image. The experimental results prove that our technique is able to infer accurately the blur kernel while reducing significantly the artifacts of the spoilt images.     

Low-voltage improved accuracy Gaussian function generator with fourth-order approximation

An original realization of a CMOS Gaussian function generator is presented. The proposed method is based on a new approximation function that is able to fourth-order match the Gaussian function. The current-mode operation of the circuit strongly reduces the technological-caused errors and the errors introduced by temperature variations, with the result of an important increasing of the accuracy for the squaring circuit that represents the functional core of the Gaussian generator (0.1%). Additionally, the bandwidth of the generator is increased as a result of its current-mode operation. Because of the utilization of the new fourth-order approximation function, the deviation from the ideal Gaussian function is smaller than 1 dB for an extended range of the input variable. The circuit is designed for implementing in 0.18 μm CMOS technology, its proposed architecture being compatible with a low-voltage operation (V_DD=1 V). The proposed Gaussian function generator based on the new approximation function allows to extend its capability of generating any continuous mathematical functions, this feature being obtained by changing the approximation function coefficients.     

3D reconstruction of existing concrete bridges using optical methods

Routine bridge inspections usually consist of visual observations. These inspections are time-consuming and subjective. There is a need to identify new inspection techniques for infrastructure that reduce traffic disturbance, and improve the efficiency and reliability of the acquired data. This study compared the performance of three different imaging technologies for the three-dimensional (3D) geometric modeling of existing structures: terrestrial laser scanning, close-range photogrammetry, and infrared scanning. Each technology was used to assess six existing concrete railway bridges. The technologies were compared in terms of geometric deviations, visualization capabilities, the level of the inspector’s experience, and degree of automation. The results suggest that all methods investigated can be used to create 3D models, however, with different level of completeness. Measurements such as span length, deck widths, etc. can be extracted with good accuracy. Although promising, a full off-site inspection is currently not feasible as some areas of the bridges were difficult to capture mainly due to restricted access and narrow spaces. Measurements based on terrestrial laser scanning were closer to the reality compared to photogrammetry and infrared scanning. The study indicates the no special training is needed for photogrammetry and infrared scanning to generate a 3D geometric model.     

Novel Design of Neuropeptide-Based Drugs with β-Sheet Breaking Potential in Amyloid-Beta Cascade: Molecular and Structural Deciphers

Our work discusses the investigation of 75 peptide-based drugs with the potential ability to break the β-sheet structures of amyloid-beta peptides from senile plaques. Hence, this study offers a unique insight into the design of neuropeptide-based drugs with β-sheet breaker potential in the amyloid-beta cascade for Alzheimer’s disease (AD). We started with five peptides (¹⁵QKLVFF²⁰, ¹⁶KLVFF²⁰, ¹⁷LVFF²⁰, ¹⁶KLVF¹⁹ and ¹⁵QKLV¹⁸), to which 14 different organic acids were attached at the N-terminal. It was necessary to evaluate the physiochemical features of these sequences due to the biological correlation with our proposal. Hence, the preliminary analysis of different pharmacological features provided the necessary data to select the peptides with the best biocompatibility for administration purposes. Our approaches demonstrated that the peptides ¹⁷LVFF²⁰, NA-¹⁷LVFF²⁰, ¹⁶KLVF¹⁹ and NA-¹⁶KLVF¹⁹ (NA-nicotinic acid) have the ability to interfere with fibril formation and hence improve the neuro and cognitive functions. Moreover, the peptide conjugate NA-¹⁶KLVF¹⁹ possesses attractive pharmacological properties, demonstrated by in silico and in vitro studies. Tandem mass spectrometry showed no fragmentation for the spectra of ¹⁶KLVF¹⁹. Such important results suggest that under the action of protease, the peptide cleavage does not occur at all. Additionally, circular dichroism confirmed docking simulations and showed that NA-¹⁶KLVF¹⁹ may improve the β-sheet breaker mechanism, and thus the entanglement process of amyloid-beta peptides can be more effective.