Site characterization model using least-square support vector machine and relevance vector machine based on corrected SPT data (N-c)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.

Minimizing total weighted tardiness on a batch-processing machine with non-agreeable release times and due dates

This study considers the scheduling problem observed in the burn-in operation of semiconductor final testing, where jobs are associated with release times, due dates, processing times, sizes, and non-agreeable release times and due dates. The burn-in oven is modeled as a batch-processing machine which can process a batch of several jobs as long as the total sizes of the jobs do not exceed the machine capacity and the processing time of a batch is equal to the longest time among all the jobs in the batch. Due to the importance of on-time delivery in semiconductor manufacturing, the objective measure of this problem is to minimize total weighted tardiness. We have formulated the scheduling problem into an integer linear programming model and empirically show its computational intractability. Due to the computational intractability, we propose a few simple greedy heuristic algorithms and meta-heuristic algorithm, simulated annealing (SA). A series of computational experiments are conducted to evaluate the performance of the proposed heuristic algorithms in comparison with exact solution on various small-size problem instances and in comparison with estimated optimal solution on various real-life large size problem instances. The computational results show that the SA algorithm, with initial solution obtained using our own proposed greedy heuristic algorithm, consistently finds a robust solution in a reasonable amount of computation time.

The Role of Interface Modification on Thermal Degradation and Crystallization Behavior of Composites from Commingled Polypropylene Fiber and Banana Fiber

The thermal degradation behavior of banana fiber and polypropylene/banana fiber composites has been studied by thermogravimetric analysis. Banana fiber was found to be decomposing in two stages, first one around 320 degrees C and the second one around 450 degrees C. For chemically treated banana fiber, the decomposition process has been at a higher temperature, indicating thermal stability for the treated fiber. Activation energies for thermal degradation were estimated using Coats and Redfern method. Calorific value of the banana fiber was measured using a constant volume isothermal bomb calorimeter. rystallization studies exhibited an increase in the crystallization temperature and crystallinity of polypropylene upon the addition of banana fiber. POLYM. COMPOS., 31:1113-1123, 2010. (C) 2009 Society of Plastics Engineers.

Ring-Opening-Induced Toughening of a Low-Permittivity Polymer-Metal Interface

Integrating low dielectric permittivity (low-k) polymers to metals is an exacting fundamental challenge because poor bonding between low-polarizability moieties and metals precludes good interfacial adhesion. Conventional adhesion-enhancing methods such as using intermediary layers are unsuitable for engineering polymer/metal interfaces for many applications because of the collateral increase in dielectric permittivity. Here, we demonstrate a completely new approach without surface treatments or intermediary layers to obtain an excellent interfacial fracture toughness of > 13 J/m(2) in a model system comprising copper. and a cross-linked polycarbosilane with k similar to 2.7 obtained by curing a cyclolinear polycarbosilane in air.Our results suggest that interfacial oxygen catalyzed molecularring-opening and anchoring of the opened ring moieties of the polymer to copper is the main toughening mechanism. This novel approach of realizing adherent low-k polymer/metal structures without intermediary layers by activating metal-anchoring polymer moieties at the interface could be adapted for applications such as device wiring and packaging, and laminates and composites.

Emerging trends at the interface of chemistry and biology: Applications to the design of human therapeutics

This article describes recent developments in the design and implementation of various strategies towards the development of novel therapeutics using first principles from biology and chemistry. Strategies for multi-target therapeutics and network analysis with a focus on cancer and HIV are discussed. Methods for gene and siRNA delivery are presented along with challenges and opportunities for siRNA therapeutics. Advances in protein design methodology and screening are described, with a focus on their application to the design of antibody based therapeutics. Future advances in this area relevant to vaccine design are also mentioned.

Fracture behavior of concrete–concrete interface using acoustic emission technique

The fracture behavior of concrete–concrete interface is characterized using acoustic emission (AE). Beams of different sizes having jointed interface between two different strengths of concrete are tested. The results of load, displacement, CMOD, AE-events and AE-energy are analyzed. The width of fracture process zone and damage zone are computed using AE-data and are found to be independent of size. It is observed that, as the difference in compressive strength of concrete on either side of interface increases, the load carrying capacity, number of AE-events, AE-energy, width of fracture process zone and damage zone decreases.

Kinetics and the mechanism of interaction of the endoplasmic reticulum chaperone, calreticulin, with monoglucosylated (Glc(1)Man(9)GlcNAc(2)) substrate

Calreticulin is a lectin-like molecular chaperone of the endoplasmic reticulum in eukaryotes. Its interaction with N-glycosylated polypeptides is mediated by the glycan, Glc(1)Man(9)GlcNAc(2), present on the target glycoproteins. In this work, binding of monoglucosyl IgG (chicken) substrate to calreticulin has been studied using real time association kinetics of the interaction with the biosensor based on surface plasmon resonance (SPR). By SPR, accurate association and dissociation rate constants were determined, and these yielded a micromolar association constant. The nature of reaction was unaffected by immobilization of either of the reactants. The Scatchard analysis values for K-a agreed web crith the one obtained by the ratio k(1)/k(-1). The interaction was completely inhibited by free oligosaccharide, Glc(1)Man(9)GlcNAc(2), whereas Man(9)GlcNAc(2) did not bind to the calreticulin-substrate complex, attesting to the exquisite specificity of this interaction. The binding of calreticulin to IgG was used for the development of immunoassay and the relative affinity of the lectin-substrate association was indirectly measured. The values are in agreement with those obtained with SPR. Although the reactions are several orders of magnitude slower than the diffusion controlled processes, the data are qualitatively and quantitatively consistent with single-step bimolecular association and dissociation reaction. Analyses of the activation parameters indicate that reaction is enthalpically driven and does not involve a highly ordered transition state. Based on these data, the mechanism of its chaperone activity is briefly discussed.

Cluster based core vector machine

Core Vector Machine(CVM) is suitable for efficient large-scale pattern classification. In this paper, a method for improving the performance of CVM with Gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. This method employs a selective sampling based training of CVM using a novel kernel based scalable hierarchical clustering algorithm. Empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

Scalable non-linear Support Vector Machine using hierarchical clustering

This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.

An SIMD machine for low-level vision

This paper presents an SIMD machine which has been tuned to execute low-level vision algorithms employing the relaxation labeling paradigm. Novel features of the design include: 1. (1) a communication scheme capable of window accessing under a single instruction. 2. (2) flexible I/O instructions to load overlapped data segments; and 3. (3) data-conditional instructions which can be nested to an arbitrary degree. A time analysis of the stereo correspondence problem, as implemented on a simulated version of the machine using the probabilistic relaxation technique, shows a speed up of almost N2 for an N × N array of PEs.

DTC Technique for Induction Machine based Integrated Starter-Generator of an Automobile

This paper mainly concentrates on the application of the direct torque control (DTC) technique for the induction machine based integrated startergenerator (ISG) for automobile applications. It also discusses in brief about the higher DC bus voltage requirements in the automobiles i.e. present 14V system vs. 42V system to meet the power requirements, modes of operation of ISG, electric machine and the drive selection for the ISG,description of DTC technique, simulation and experimental results, and implementation.

Communication: Evidence of dynamic heterogeneity in glassy polymer monolayers from interface microrheology measurements

We have developed a novel nanoparticle tracking based interface microrheology technique to perform in situ studies on confined complex fluids. To demonstrate the power of this technique, we show, for the first time, how in situ glass formation in polymers confined at air-water interface can be directly probed by monitoring variation of the mean square displacement of embedded nanoparticles as a function of surface density. We have further quantified the appearance of dynamic heterogeneity and hence vitrification in polymethyl methacrylate monolayers above a certain surface density, through the variation of non-Gaussian parameter of the probes. (C) 2010 American Institute of Physics. [doi:10.1063/1.3471584].

Chemical approaches of penicillin allergy—III Isolation of the penicillin-free carrier receptor protein (CRP) on a polymeric 7-deoxy penicillin analogue template and its role in penicillin immunogeneses in rabbit and man

Specific penicillin-carrier receptor proteins (CRP) have been isolated from the sera of penicillin allergic rabbits and human subjects in the unconjugated native state in electrophoretically homogeneous form by employing a synthetic polymeric affinity template containing the 7-deoxy analogue of penicillin G. The synthesis of the 7-deoxy analogue has been described. In this affinity system the antipenicillin-antibody is desorbed by 0·9M thiourea and the CRP in 8M urea. The CRP after incubation with penicillin is converted into the full-fledged antigen. Studies on the origin of CRP and the nature of antibody as well as comparative studies on the properties of the rabbit antibody and those of antibodies elicited by a BSA-BPO conjugate are reported.