Automated inspection of aircraft parts using a modified ICP algorithm

The application of computer-aided inspection integrated with the coordinate measuring machine and laser scanners to inspect manufactured aircraft parts using robust registration of two-point datasets is a subject of active research in computational metrology. This paper presents a novel approach to automated inspection by matching shapes based on the modified iterative closest point (ICP) method to define a criterion for the acceptance or rejection of a part. This procedure improves upon existing methods by doing away with the following, viz., the need for constructing either a tessellated or smooth representation of the inspected part and requirements for an a priori knowledge of approximate registration and correspondence between the points representing the computer-aided design datasets and the part to be inspected. In addition, this procedure establishes a better measure for error between the two matched datasets. The use of localized region-based triangulation is proposed for tracking the error. The approach described improves the convergence of the ICP technique with a dramatic decrease in computational effort. Experimental results obtained by implementing this proposed approach using both synthetic and practical data show that the present method is efficient and robust. This method thereby validates the algorithm, and the examples demonstrate its potential to be used in engineering applications.

Deep Packet Inspection Using Message Passing Networks

We propose a solution based on message passing bipartite networks, for deep packet inspection, which addresses both speed and memory issues, which are limiting factors in current solutions. We report on a preliminary implementation and propose a parallel architecture.

AIWIN - A fast and jigless inspection technique for machined parts

Precision inspection of manufactured components having multiple complex surfaces and variable tolerance definition is an involved, complex and time-consuming function. In routine practice, a jig is used to present the part in a known reference frame to carry out the inspection process. Jigs involve both time and cost in their development, manufacture and use. This paper describes 'as is where is inspection' (AIWIN), a new automated inspection technique that accelerates the inspection process by carrying out a fast registration procedure and establishing a quick correspondence between the part to inspect and its CAD geometry. The main challenge in doing away with a jig is that the inspection reference frame could be far removed from the CAD frame. Traditional techniques based on iterative closest point (ICP) or Newton methods require either a large number of iterations for convergence or fail in such a situation. A two-step coarse registration process is proposed to provide a good initial guess for a modified ICP algorithm developed earlier (Ravishankar et al., Int J Adv Manuf Technol 46(1-4):227-236, 2010). The first step uses a calibrated sphere for local hard registration and fixing the translation error. This transformation locates the centre for the sphere in the CAD frame. In the second step, the inverse transformation (involving pure rotation about multiple axes) required to align the inspection points measured on the manufactured part with the CAD point dataset of the model is determined and enforced. This completes the coarse registration enabling fast convergence of the modified ICP algorithm. The new technique has been implemented on complex freeform machined components and the inspection results clearly show that the process is precise and reliable with rapid convergence. © 2011 Springer-Verlag London Limited.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Testing threshold functions using implied minterm structure

A geometrical structure called the implied minterm structure (IMS) has been developed from the properties of minterms of a threshold function. The IMS is useful for the manual testing of linear separability of switching functions of up to six variables. This testing is done just by inspection of the plot of the function on the IMS.

Structural effects of a dimer interface mutation on catalytic activity of triosephosphate isomerase.The role of conserved residues and complementary mutations

The active site of triosephosphate isomerase (TIM, EC: 5.3.1.1), a dimeric enzyme, lies very close to the subunit interface. Attempts to engineer monomeric enzymes have yielded well-folded proteins with dramatically reduced activity. The role of dimer interface residues in the stability and activity of the Plasmodium falciparum enzyme, PfTIM, has been probed by analysis of mutational effects at residue 74. The PfTIM triple mutant W11F/W168F/Y74W (Y74W*) has been shown to dissociate at low protein concentrations, and exhibits considerably reduced stability in the presence of denaturants, urea and guanidinium chloride. The Y74W* mutant exhibits concentration-dependent activity, with an approximately 22-fold enhancement of kcat over a concentration range of 2.5–40 μm, suggesting that dimerization is obligatory for enzyme activity. The Y74W* mutant shows an approximately 20-fold reduction in activity compared to the control enzyme (PfTIM WT*, W11F/W168F). Careful inspection of the available crystal structures of the enzyme, together with 412 unique protein sequences, revealed the importance of conserved residues in the vicinity of the active site that serve to position the functional K12 residue. The network of key interactions spans the interacting subunits. The Y74W* mutation can perturb orientations of the active site residues, due to steric clashes with proximal aromatic residues in PfTIM. The available crystal structures of the enzyme from Giardia lamblia, which contains a Trp residue at the structurally equivalent position, establishes the need for complementary mutations and maintenance of weak interactions in order to accommodate the bulky side chain and preserve active site integrity.

Hamilton's theory of turns revisited

We present a new approach to Hamilton's theory of turns for the groups SO(3) and SU(2) which renders their properties, in particular their composition law, nearly trivial and immediately evident upon inspection. We show that the entire construction can be based on binary rotations rather than mirror reflections.

Estimation of remaining life of power transformers

Inadvertent failure of power transformers has serious consequences on the power system reliability, economics and the revenue accrual. Insulation is the weakest link in the power transformer prompting periodic inspection of the status of insulation at different points in time. A close Monitoring of the electrical, chemical and such other properties on insulation as are sensitive to the amount of time-dependent degradation becomes mandatory to judge the status of the equipment. Data-driven Diagnostic Testing and Condition Monitoring (DTCM) specific to power transformer is the aspect in focus. Authors develop a Monte Carlo approach for augmenting the rather scanty experimental data normally acquired using Proto-types of power transformers. Also described is a validation procedure for estimating the accuracy of the Model so developed.

Microstructural stability and creep in nanocrystals

Microstructural stability is an important consideration during high temperature deformation and processing of nanomaterials. We will address issues relating to triple junctions in limiting grain growth during creep as well as densification. Although early studies on deformation have considered diffusion creep as a possible rate controlling deformation mechanism in nanocrystals, a critical inspection of available data indicates that there is no strong evidence for conventional diffusion creep in such materials. The possibility of diffusion creep by rapid diffusion along triple junctions will be analyzed, and interface controlled diffusion creep will also be discussed critically. It is shown that the critical grain size for dislocation activity is similar to that for occurrence of conventional diffusion creep.

A new approach for simple and rapid shape measurement of objects with surface discontinuities

A new approach for unwrapping phase maps, obtained during the measurement of 3-D surfaces using sinusoidal structured light projection technique, is proposed. "Takeda's method" is used to obtain the wrapped phase map. Proposed method of unwrapping makes use of an additional image of the object captured under the illumination of a specifically designed color-coded pattern. The new approach demonstrates, for the first time, a method of producing reliable unwrapping of objects even with surface discontinuities from a single-phase map. It is shown to be significantly faster and reliable than temporal phase unwrapping procedure that uses a complete exponential sequence. For example, if a measurement with the accuracy obtained by interrogating the object with S fringes in the projected pattern is carried out with both the methods, new method requires only 2 frames as compared to (log(2)S +1) frames required by the later method.

Thermodynamic and kinetic studies on the mechanism of binding of methylumbelliferyl galactosides to the basic agglutinin from winged bean (Psophocarpus tetragonolobus)

The binding of winged bean basic agglutinin (WBA I) to 4-methylumbelliferyl (MeUmb) galactosides was examined by extrinsic fluorescence titration and stopped-flow spectrofluorimetry. Upon binding to WBA I, MeUmb alpha-galactosides show quenching in fluorescence intensity, decrease in UV absorbance with a concomitant blue shift, and decrease in fluorescence excited-state lifetimes. However, their beta-analogues show enhancement in fluorescence intensity, increase in UV absorbance with a red shift, and an increase in fluorescence excited-state lifetimes. This implies that the umbelliferyl groups of alpha- and beta-galactosides experience non-polar and polar microenvironments, respectively, upon binding to WBA I. Replacement of the anomeric hydroxyl group of galactose by 4-methylumbelliferyl moiety increases the affinity of resulting saccharides. Substitution of C-2 hydroxyl of galactose by an acetamido group leads to increased affinity due to a favorable entropy change. This suggests that acetamido group of MeUmb-alpha/beta-GalNAc binds to a relatively non-polar subsite of WBA I. Most interestingly, this substitution also reduces the association rate constants dramatically. Inspection of the activation parameters reveals that the enthalpy of activation is the limiting factor for the differences in the forward rate constants for these saccharides and the entropic contribution to the activation energy is small

Design of a FIR filter for image restoration using principal component neural networks

The neural network finds its application in many image denoising applications because of its inherent characteristics such as nonlinear mapping and self-adaptiveness. The design of filters largely depends on the a-priori knowledge about the type of noise. Due to this, standard filters are application and image specific. Widely used filtering algorithms reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design a finite impulse response filter based on principal component neural network (PCNN) is proposed in this study for image filtering, optimized in the sense of visual inspection and error metric. This algorithm exploits the inter-pixel correlation by iteratively updating the filter coefficients using PCNN. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions. Further, the number of unknown parameters is very few and most of these parameters are adaptively obtained from the processed image.

Tracking Random Walk of Individual Domain Walls in Cylindrical Nanomagnets with Resistance Noise

The stochasticity of domain-wall (DW) motion in magnetic nanowires has been probed by measuring slow fluctuations, or noise, in electrical resistance at small magnetic fields. By controlled injection of DWs into isolated cylindrical nanowires of nickel, we have been able to track the motion of the DWs between the electrical leads by discrete steps in the resistance. Closer inspection of the time dependence of noise reveals a diffusive random walk of the DWs with a universal kinetic exponent. Our experiments outline a method with which electrical resistance is able to detect the kinetic state of the DWs inside the nanowires, which can be useful in DW-based memory designs.

A glossary of DNA structures from A to Z

The right-handed double-helical Watson-Crick model for B-form DNA is the most commonly known DNA structure. In addition to this classic structure, several other forms of DNA have been observed and it is clear that the DNA molecule can assume different structures depending on the base sequence and environment. The various forms of DNA have been identified as A, B, C etc. In fact, a detailed inspection of the literature reveals that only the letters F, Q, U, V and Y are now available to describe any new DNA structure that may appear in the future. It is also apparent that it may be more relevant to talk about the A, B or C type dinucleotide steps, since several recent structures show mixtures of various different geometries and a careful analysis is essential before identifying it as a 'new structure'. This review provides a glossary of currently identified DNA structures and is quite timely as it outlines the present understanding of DNA structure exactly 50 years after the original discovery of DNA structure by Watson and Crick

Leak Detection In Pressure Tubes Of A Pressurized Heavy-Water Reactor By Acoustic-Emission Technique

Leak detection in the fuel channels is one of the challenging problems during the in-service inspection (ISI) of Pressurised Heavy Water Reactors (PHWRs). In this paper, the use of an acoustic emission (AE) technique together with AE signal analysis is described, to detect a leak that was ncountered in one (or more) of the 306 fuel channels of the Madras Atomic Power Station (PHWR), Unit I. The paper describes the problems encountered during the ISI, the experimental methods adopted and the results obtained. Results obtained using acoustic emission signal analysis are compared with those obtained from other leak detection methods used in such cases.