Cubic Bézier approximation of a digitized curve

In this paper we present an efficient technique for piecewise cubic Bézier approximation of digitized curve. An adaptive breakpoint detection method divides a digital curve into a number of segments and each segment is approximated by a cubic Bézier curve so that the approximation error is minimized. Initial approximated Bézier control points for each of the segments are obtained by interpolation technique i.e. by the reverse recursion of De Castaljau's algorithm. Two methods, two-dimensional logarithmic search algorithm (TDLSA) and an evolutionary search algorithm (ESA), are introduced to find the best-fit Bézier control points from the approximate interpolated control points. ESA based refinement is proved to be better experimentally. Experimental results show that Bézier approximation of a digitized curve is much more accurate and uses less number of points compared to other approximation techniques.     

Target differentiation with simple infrared sensors using statistical pattern recognition techniques

This study compares the performances of various statistical pattern recognition techniques for the differentiation of commonly encountered features in indoor environments, possibly with different surface properties, using simple infrared (IR) sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the differentiation process. We construct feature vectors based on the parameters of angular IR intensity scans from different targets to determine their geometry and/or surface type. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. Parametric differentiation correctly identifies six different surface types of the same planar geometry, resulting in the best surface differentiation rate (100%). However, this rate is not maintained with the inclusion of more surfaces. The results indicate that the geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. The results demonstrate that simple IR sensors, when coupled with appropriate processing and recognition techniques, can be used to extract substantially more information than such devices are commonly employed for.     

Robust control of polytopic systems by convex optimization

Robust control synthesis of linear time-invariant SISO polytopic systems is investigated using the polynomial approach. A convex set of all stabilizing controllers for a polytopic system is given over an infinite-dimensional space. A finite-dimensional approximation of this set is obtained using the orthonormal basis functions and represented by a set of LMIs thanks to the KYP lemma. Then, an LMI based convex optimization problem for robust pole placement with sensitivity function shaping in two- and infinity-norm is proposed. The simulation results show the effectiveness of the proposed method.     

Information cut for clustering using a gradient descent approach

We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between probability density functions. We propose to optimize the Information Cut using a gradient descent-based approach. Our algorithm has several advantages compared to many other graph-based methods in terms of determining an appropriate affinity measure, computational complexity, memory requirements and coping with different data scales. We show that our method may produce clustering and image segmentation results comparable or better than the state-of-the art graph-based methods.     

3D model retrieval using principal plane analysis and dynamic programming

Three dimensional models play an important role in many applications; the problem is how to select the appropriate models from a 3D database rapidly and accurately. In recent years, a variety of shape representations, statistical methods, and geometric algorithms have been proposed for matching 3D shapes or models. In this paper, we propose a 3D shape representation scheme based on a combination of principal plane analysis and dynamic programming. The proposed 3D shape representation scheme consists of three steps. First, a 3D model is transformed into a 2D image by projecting the vertices of the model onto its principal plane. Second, the convex hall of the 2D shape of the model is further segmented into multiple disjoint triangles using dynamic programming. Finally, for each triangle, a projection score histogram and moments are extracted as the feature vectors for similarity searching. Experimental results showed the robustness of the proposed scheme, which resists translation, rotation, scaling, noise, and destructive attacks. The proposed 3D model retrieval method performs fairly well in retrieving models having similar characteristics from a database of 3D models.     

Strains of Synechocystis sp. PCC 6803 with altered PsaC. II. EPR and optical spectroscopic properties of FA and FB in aspartate, serine, and alanine replacements of cysteines 14 and 51

A psaC deletion mutant of the unicellular cyanobacterium Synechocystis sp. PCC 6803 was utilized to incorporate site-specific amino acid substitutions in the cysteine residues that ligate the FA and FB iron-sulfur clusters in Photosystem I (PS I). Cysteines 14 and 51 of PsaC were changed to aspartic acid (C14DPsaC, C51DPsaC, C14D/C51DPsaC), serine (C14SPsaC, C51SPsaC), and alanine (C14APsaC, C51APsaC), and the properties of FA and FB were characterized by electron paramagnetic resonance spectroscopy and time-resolved optical spectroscopy. The C14DPsaC-PS I and C14SPsaC-PS I complexes showed high levels of photoreduction of FA with g values of 2.045, 1. 944, and 1.852 after illumination at 15 K, but there was no evidence of reduced FB in the g = 2 region. The C51DPsaC-PS I and C51SPsaC-PS I complexes showed low levels of photoreduction of FB with g values of 2.067, 1.931, and 1.881 after illumination at 15 K, but there was no evidence of reduced FA in the g = 2 region. The presence of FB was inferred in C14DPsaC-PS I and C14SPsaC-PS I, and the presence of FA was inferred in C51DPsaC-PS I and C51SPsaC-PS I by magnetic interaction in the photoaccumulated spectra and by the equal spin concentration of the irreversible P700(+) cation generated by illumination at 77 K. Flash-induced optical absorbance changes at 298 K in the presence of a fast electron donor indicate that two electron acceptors function after FX in the four mutant PS I complexes at room temperature. These data suggest that a mixed-ligand [4Fe-4S] cluster is present in the mutant sites of C14X-PS I and C51X-PS I (where X = D or S), but that the proposed spin state of S = 3/2 renders the resonances undetectable in the g = 2 region. The C14APsaC-PS I, C51APsaC-PS I and C14D/C51DPsaC-PS I complexes show only the photoreduction of FX, consistent with the absence of PsaC. These results show that only those PsaC proteins that contain two [4Fe-4S] clusters are capable of assembling onto PS I cores in vivo.     

Robust pole clustering in a good ride quality region of aircraft for matrices with structured uncertainties

This paper presents a general analysis of robust pole clustering in a good ride quality region (GRQR) of aircraft for matrices with structured uncertainties. This region is an intersection of a ring and a horizontal strip, located in the left half-plane, which is a specific non-Ω-transformable region providing good ride quality of aircraft. The paper applies the Rayleigh principle along the norm theory to analyze robust pole clustering within this region since the generalized Lyapunov theory is not valid for non-Ω-transformable regions. Concerned uncertainties are structured/parametric uncertainties, including interval matrices. The results are useful for robust control analysis and design, especially, of robust good ride quality of aircraft, shuttles, vehicles and space station, as well as some industrial systems. An example of the F-16 dynamics for which GRQR is suitable is included to illustrate the results.     

Integrated modelling under uncertainty in watershed-level assessment and management.

Uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modelling system (modified-BASINS) under uncertainty is described and demonstrated for use in receiving-water quality prediction and watershed management. A Monte Carlo simulation was used to investigate the effect of various uncertainty types on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorus (T-P) in the Hwaong Reservoir, considering three uncertainty types, would be less than about 4.4 and 0.23 mg L(-1), respectively, in 2012, with 90% confidence. The effects of two watershed management practices, wastewater treatment plants (WWTP) and constructed wetlands (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaong Reservoir to less than 3.4 and 0.14 mg L(-1), 24 and 41% improvements, respectively, with 90% confidence. Overall, the Monte Carlo simulation in the integrated modelling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on the probability and level of risk, and its application is recommended.     

Central GABAA and GABAB receptor modulation of basal and stress-induced plasma interleukin-6 levels in mice

The development of control strategies for loiasis is of crucial importance in endemic areas and depends heavily on the accurate identification of occult-infected individuals. A polymerase chain reaction (PCR) and nested polymerase chain reaction (nested PCR) were developed and based on sequences of the repeat 3 region (15r3) of the gene encoding a Loa loa 15-kD protein. The assays was performed on 20 blood samples from occult-infected subjects and 30 from field-collected amicrofilaremic individuals. The size of the initial PCR product was 396 basepairs (bp). When this initial amplification using primers 15r3(1) and 15r3(2) was carried out for 30 cycles, the PCR products from three of the 20 occult-infected and five of the 30 amicrofilaremic individuals were visualized after electrophoresis by staining the gel with ethidium bromide. Subsequent Southern blotting and hybridization with the specific probe revealed hybridization in 19 of 20 occult-infected and 23 of 30 amicrofilaremic samples but only after two days of exposure of the blot to the x-ray film. When the nested PCR was carried out (product size = 366 bp, primers 15r3(3) and 15r3(4)), 19 of 20 occult-infected and 23 of 30 amicrofilaremic samples that were positive by Southern hybridization of the initial PCR products were strongly positive by staining with ethidium bromide. Qualitative Southern blotting of the nested PCR products using the same probe previously described confirmed the ethidium bromide staining results after a very short exposure time of 4 hr. These results demonstrate that the nested PCR amplification product is specific and that its sensitivity in detecting occult loiasis is 95%. This approach has significant promise for the screening of large human populations for active loiasis without the requirement for blotting and hybridization of the PCR products.