Effect of Flavourzyme(®) on Angiotensin-Converting Enzyme Inhibitory Peptides Formed in Skim Milk and Whey Protein Concentrate during Fermentation by Lactobacillus helveticus.

Angiotensin-converting enzyme inhibitory (ACE-I) activity as affected by Lactobacillus helveticus strains (881315, 881188, 880474, and 880953), and supplementation with a proteolytic enzyme was studied. Reconstituted skim milk (12% RSM) or whey protein concentrate (4% WPC), with and without Flavourzyme(®) (0.14% w/w), were fermented with 4 different L.

Matching of complex patterns by energy minimization.

Two patterns are matched by putting one on top of the other and iteratively moving their individual parts until most of their corresponding parts are aligned. An energy function and a neighborhood of influence are defined for each iteration. Initially, a large neighborhood is used such that the movements result in global features being coarsely aligned.

Lane detection by orientation and length discrimination.

This paper describes a novel lane detection algorithm for visual traffic surveillance applications under the auspice of intelligent transportation systems. Traditional lane detection methods for vehicle navigation typically use spatial masks to isolate instantaneous lane information from on-vehicle camera images. When surveillance is concerned, complete lane and multiple lane information is essential for tracking vehicles and monitoring lane change frequency from overhead cameras, where traditional methods become inadequate.

An intelligent mobile vehicle navigator based on fuzzy logic and reinforcement learning.

In this paper, an alternative training approach to the EEM-based training method is presented and a fuzzy reactive navigation architecture is described. The new training method is 270 times faster in learning speed; and is only 4% of the learning cost of the EEM method. It also has very reliable convergence of learning; very high number of learned rules (98.

Postprocessing statistical language models for handwritten Chinese character recognizer.

Two statistical language models have been investigated on their effectiveness in upgrading the accuracy of a Chinese character recognizer. The baseline model is one of lexical analytic nature which segments a sequence of character images according to the maximum matching of words with consideration of word binding forces. A model of bigram statistics of word-classes is then investigated and compared against the baseline model in terms of recognition rate improvement on the image recognizer.

Integer lapped transforms and their applications to image coding.

This paper proposes new integer approximations of the lapped transforms, called the integer lapped transforms (ILT), and studies their applications to image coding. The ILT are derived from a set of orthogonal sinusoidal transforms having short integer coefficients, which can be implemented with simple integer arithmetic. By employing the same scaling constants in these integer sinusoidal transforms, integer versions of the lapped orthogonal transform (LOT), the lapped biorthogonal transform (LBT), and the hierarchical lapped biorthogonal transform (HLBT) are developed.

Defect detection in textured materials using optimized filters.

The problem of automated defect detection in textured materials is investigated. A new approach for defect detection using linear FIR filters with optimized energy separation is proposed. The performance of different feature separation criteria with reference to fabric defects has been evaluated.

Data hiding watermarking for halftone images.

In many printer and publishing applications, it is desirable to embed data in halftone images. We proposed some novel data hiding methods for halftone images. For the situation in which only the halftone image is available, we propose data hiding smart pair toggling (DHSPT) to hide data by forced complementary toggling at pseudo-random locations within a halftone image.

A compact 3D VLSI classifier using bagging threshold network ensembles.

A bagging ensemble consists of a set of classifiers trained independently and combined by a majority vote. Such a combination improves generalization performance but can require large amounts of memory and computation, a serious drawback for addressing portable real-time pattern recognition applications. We report here a compact three-dimensional (3D) multiprecision very large-scale integration (VLSI) implementation of a bagging ensemble.

Using function approximation to analyze the sensitivity of MLP with antisymmetric squashing activation function.

Sensitivity analysis on a neural network is mainly investigated after the network has been designed and trained. Very few have considered this as a critical issue prior to network design. Piche's statistical method (1992, 1995) is useful for multilayer perceptron (MLP) design, but too severe limitations are imposed on both input and weight perturbations.

Modeling of a rotary motor driven by an anisotropic piezoelectric composite laminate.

This paper proposes an analytical model of a rotary motor driven by an anisotropic piezoelectric composite laminate. The driving element of the motor is a three-layer laminated plate. A piezoelectric layer is sandwiched between two anti-symmetric composite laminae.

Linear dependency between /spl epsi/ and the input noise in /spl epsi/-support vector regression.

In using the /spl epsi/-support vector regression (/spl epsi/-SVR) algorithm, one has to decide a suitable value for the insensitivity parameter /spl epsi/. Smola et al. considered its "optimal" choice by studying the statistical efficiency in a location parameter estimation problem.

Gene selection for brain cancer classification.

With the introduction of microarray, cancer classification, diagnosis and prediction are made more accurate and effective. However, the final outcome of the data analyses very much depend on the huge number of genes with relatively small number of samples present in each experiment. It is thus crucial to select relevant genes to be used for future specific cancer markers.

A novel active contour model using local and global statistics for vessel extraction.

Vessel extraction is one of the critical tasks in clinical practice. Most of the deformable models used in these applications are based on either image gradient or global statistics of the intensity as their curve evolution and stopping criteria. However, the models using global statistic alone are not adaptive to the uneven intensity distribution since they do not take local variations in the area of interest into consideration.

Shear waves induced by moving needle in MR elastography.

Magnetic resonance elastography (MRE) is a phase contrast-based method for observing shear wave propagation in a material to determine its stiffness. The objective of this study was to determine whether shear waves suitable for MRE could be induced using a moving acupuncture needle. Tissue-simulating bovine gel phantom and a 0.

First synthesis of perfluorinated corrole and its mn=o complex.

A novel perfluorinated corrole, 2,3,7,8,12,13,17,18-octafluoro-5,10,15-tris(pentafluorophenyl)corrole, and its manganese(III) and oxomanganese(V) derivatives have been synthesized. The perfluorinated manganese corrolate exhibited excellent reactivity and stability in the catalytic oxidation of alkenes with iodosylbenzene.

Objective functions for training new hidden units in constructive neural networks.

In this paper, we study a number of objective functions for training new hidden units in constructive algorithms for multilayer feedforward networks. The aim is to derive a class of objective functions the computation of which and the corresponding weight updates can be done in O(N) time, where N is the number of training patterns. Moreover, even though input weight freezing is applied during the process for computational efficiency, the convergence property of the constructive algorithms using these objective functions is still preserved.

Constructive algorithms for structure learning in feedforward neural networks for regression problems.

In this survey paper, we review the constructive algorithms for structure learning in feedforward neural networks for regression problems. The basic idea is to start with a small network, then add hidden units and weights incrementally until a satisfactory solution is found. By formulating the whole problem as a state-space search, we first describe the general issues in constructive algorithms, with special emphasis on the search strategy.

Nuclear matrix of human nasopharyngeal carcinoma cells in culture.

Nuclear matrix is a scaffold-like structure of the nucleus after sequential treatments with detergents, DNase, and high salt buffers. Its involvement in various cellular activities has been emphasised in various studies. In this study, nuclear matrix of two human nasopharyngeal carcinoma cell Lines were compared and analysed in terms of their morphological appearance and electrophoretic patterns of proteins.

Use of bias term in projection pursuit learning improves approximation and convergence properties.

In a regression problem, one is given a multidimensional random vector X, the components of which are called predictor variables, and a random variable, Y, called response. A regression surface describes a general relationship between X and Y. A nonparametric regression technique that has been successfully applied to high-dimensional data is projection pursuit regression (PPR).

Stable adaptive fuzzy controllers with application to inverted pendulum tracking.

An adaptive fuzzy controller is constructed from a set of fuzzy IF-THEN rules whose parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given-trajectory. In this paper, two adaptive fuzzy controllers are designed based on the Lyapunov synthesis approach. We require that the final closed-loop system must be globally stable in the sense that all signals involved (states, controls, parameters, etc.

Automated analysis of nerve-cell images using active contour models.

The number of nerve fibers (axons) in a nerve, the axon size, and shape can all be important neuroanatomical features in understanding different aspects of nerves in the brain. However, the number of axons in a nerve is typically in the order of tens of thousands and a study of a particular aspect of the nerve often involves many nerves. Potentially meaningful studies are often prohibited by the huge number involved when manual measurements have to be employed.

Optimal median-type filtering under structural constraints.

This paper presents a method for the design of median-type filters that achieve the maximum noise attenuation under structural constraints imposed by the requirement of preserving certain signal or image features. As compared with the design of optimal weighted median (WM) filters that calls for solving a set of linear inequalities, this method is extremely simple yet general enough. The filter is obtained by modifying directly the Boolean function of a median filter, and an analytic, closed-form representation of its Boolean function can be obtained.

Detailed deletion mapping on the short arm of chromosome-3 in nasopharyngeal carcinomas.

Allelic loss on the short arm of chromosome 3 is one of the most consistent molecular genetic alterations observed in primary nasopharyngeal carcinoma (NPC). Detailed mapping of the region of common deletion on chromosome 3p will help to locate the site of candidate tumor suppressor gene(s) involved in the pathogenesis of NPC. We have examined allelic deletion in 27 primary undifferentiated NPC at 11 chromosomal loci (spanning from 3p13-3p25) using microsatellite polymorphic markers.

Optimal parallel stack filtering under the mean absolute error criterion.

The authors extend the configuration of stack filtering to develop a new class of stack-type filters called parallel stack filters (PSFs). As a basis for the parallel stack filtering, the block threshold decomposition (BTD) is introduced, and its properties are investigated. The design of optimal PSHs under the mean absolute error (MAE) criterion is shown to be similar to the minimum MAE stack filtering theory.