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At least 253 records · Page 14Linked to original sources
PubMed2006

Optimizing selection on multiple identified quantitative trait loci in population with overlapping generations.

A method was developed to model and optimize selection on multiple identified quantitative trait loci (QTLs) and polygenic estimated breeding value, in order to maximize a weighted sum of cumulative response to selection over multiple years in a population with overlapping generations. The model allows for a population with multiple sex-age classes, different number of age class between sires and dams, and varied genetic contribution of the age class. The optimization problem was formulated as a multiple-stage optimal control problem and solved by a forward and backward iteration loop. The practical utility of this method was illustrated in an example of pig breeding population with overlapping generations. The selection response of this method was compared with standard QTL selection and conventional best linear unbiased prediction (BLUP) selection. Simulation results show that optimal selection achieved greater selection response than either standard QTL or conventional BLUP selections. The influence of population structure on optimal selection was significant. Optimal QTL selection and standard QTL selection were more favorable in a population with overlapping generations than discrete generations, and obtained more benefits relative to conventional BLUP selection in a population with overlapping generations. Optimal QTL selection relative to conventional BLUP selection is also more favorable following increase of genetic contribution of two-year-old boars and sows in a population with overlapping generations.

Algorithms↗
PubMed1998

Multiresolution texture based adaptive clustering algorithm for breast lesion segmentation.

OBJECTIVE: A specific algorithm is presented for the automatic extraction of breast tumors in ultrasonic imaging. METHOD: The algorithm involves two-dimensional adaptive K-means clustering of the gray scale and textural feature images. The segmentation problem is formulated as a maximum a posteriori (MAP) estimation problem. The MAP estimation is achieved using Besag's iterated conditional modes algorithm for the minimization of an energy function. This function has three components: the first constrains the region to be close to the data; the second imposes spatial continuity; and the third takes into consideration the texture of the various regions. A multiresolution implementation of the algorithm is performed using a waveless basis. RESULTS: Experiments were carried out on synthetic images and on in vivo breast ultrasound images. Various parameters involved in the algorithm are discussed to evaluate the robustness and accuracy of the segmentation method. CONCLUSION: Including textural features in the segmentation of ultrasonic data improves the robustness of the algorithm and makes the segmentation result less parameter dependent.

Adenocarcinoma↗
PubMed2001

A multiparametric and multiresolution segmentation algorithm of 3-D ultrasonic data.

An algorithm devoted to the segmentation of 3-D ultrasonic data is proposed. The algorithm involves 3-D adaptive clustering based on multiparametric information: the gray-scale intensity of the echographic data, 3-D texture features calculated from the envelope data, and 3-D tissue characterization information calculated from the local frequency spectra of the radio-frequency signals. The segmentation problem is formulated as a Maximum A posterior (MAP) estimation problem. A multi-resolution implementation of the algorithm is proposed. The approach is tested on simulated data and on in vivo echocardiographic 3-D data. The results presented in the paper illustrate the robustness and the accuracy of the proposed approach for the segmentation of ultrasonic data.

Algorithms↗
PubMed2006

Line detection in images through regularized Hough transform.

The problem of determining the location and orientation of straight lines in images is of great importance in the fields of computer vision and image processing. Traditionally the Hough transform, (a special case of the Radon transform) has been widely used to solve this problem for binary images. In this paper, we pose the problem of detecting straight lines in gray-scale images as an inverse problem. Our formulation is based on use of the inverse Radon operator, which relates the parameters determining the location and orientation of the lines in the image to the noisy input image. The advantage of this formulation is that we can then approach the problem of line detection within a regularization framework and enhance the performance of the Hough-based line detector through the incorporation of prior information in the form of regularization. We discuss the type of regularizers that are useful for this problem and derive efficient computational schemes to solve the resulting optimization problems enabling their use in large applications. Finally, we show how our new approach can be alternatively viewed as one of finding an optimal representation of the noisy image in terms of elements chosen from a dictionary of lines. This interpretation relates the problem of Hough-based line finding to the body of work on adaptive signal representation.

Algorithms↗
PubMed2006

Automated reassembly of file fragmented images using greedy algorithms.

The problem of restoring deleted files from a scattered set of fragments arises often in digital forensics. File fragmentation is a regular occurrence in hard disks, memory cards, and other storage media. As a result, a forensic analyst examining a disk may encounter many fragments of deleted digital files, but is unable to determine the proper sequence of fragments to rebuild the files. In this paper, we investigate the specific case where digital images are heavily fragmented and there is no file table information by which a forensic analyst can ascertain the correct fragment order to reconstruct each image. The image reassembly problem is formulated as a k-vertex disjoint graph problem and reassembly is then done by finding an optimal ordering of fragments. We provide techniques for comparing fragments and describe several algorithms for image reconstruction based on greedy heuristics. Finally, we provide experimental results showing that images can be reconstructed with high accuracy even when there are thousands of fragments and multiple images involved.

Algorithms↗
PubMedDate not supplied

A method to optimize selection on multiple identified quantitative trait loci.

A mathematical approach was developed to model and optimize selection on multiple known quantitative trait loci (QTL) and polygenic estimated breeding values in order to maximize a weighted sum of responses to selection over multiple generations. The model allows for linkage between QTL with multiple alleles and arbitrary genetic effects, including dominance, epistasis, and gametic imprinting. Gametic phase disequilibrium between the QTL and between the QTL and polygenes is modeled but polygenic variance is assumed constant. Breeding programs with discrete generations, differential selection of males and females and random mating of selected parents are modeled. Polygenic EBV obtained from best linear unbiased prediction models can be accommodated. The problem was formulated as a multiple-stage optimal control problem and an iterative approach was developed for its solution. The method can be used to develop and evaluate optimal strategies for selection on multiple QTL for a wide range of situations and genetic models.

Animals↗
PubMed2001

Optimal control by least squares support vector machines.

Support vector machines have been very successful in pattern recognition and function estimation problems. In this paper we introduce the use of least squares support vector machines (LS-SVM's) for the optimal control of nonlinear systems. Linear and neural full static state feedback controllers are considered. The problem is formulated in such a way that it incorporates the N-stage optimal control problem as well as a least squares support vector machine approach for mapping the state space into the action space. The solution is characterized by a set of nonlinear equations. An alternative formulation as a constrained nonlinear optimization problem in less unknowns is given, together with a method for imposing local stability in the LS-SVM control scheme. The results are discussed for support vector machines with radial basis function kernel. Advantages of LS-SVM control are that no number of hidden units has to be determined for the controller and that no centers have to be specified for the Gaussian kernels when applying Mercer's condition. The curse of dimensionality is avoided in comparison with defining a regular grid for the centers in classical radial basis function networks. This is at the expense of taking the trajectory of state variables as additional unknowns in the optimization problem, while classical neural network approaches typically lead to parametric optimization problems. In the SVM methodology the number of unknowns equals the number of training data, while in the primal space the number of unknowns can be infinite dimensional. The method is illustrated both on stabilization and tracking problems including examples on swinging up an inverted pendulum with local stabilization at the endpoint and a tracking problem for a ball and beam system.

Feedback↗
PubMed1980

The filling of molten and thixotropic formulations into hard gelatin capsules.

Problems in the formulation and manufacture of conventional solid dose form products include the variation of fill weight and drug content, dissolution control of poorly water soluble drugs and dust generated during manufacture giving rise to cross contamination. We have examined the application of a liquid filling technique for the manufacture of hard gelatin capsules as a means of overcoming some of these. Filling materials are based on water-soluble hot melt polymers such as polyethylene glycol or water-dispersible thixotropic systems of pharmaceutical oils with thixotropic additives. A Zanasi LZ64 capsule filling machine was adapted to fill liquids using filling pump. No dust is generated during filling and 20 microgram doses of drug can be accurately filled without extensive processing. The formulations are simple and do not require specialist ingredients such as lubricants, binders, disintegrants and flow aids. The method of manufacture is reduced to a simple mixing and direct filling operation. The system may be applied to promote the dissolution of poorly water soluble drugs using solid solutions or solid dispersions. Slow release formulations are also available using suitable retard excipients.

Capsules↗
PubMed1997

DT-Planner: an environment for managing dynamic decision problems.

The problem of formulating plans under uncertainty and coping with dynamic decision problems is a major task of both artificial intelligence and control theory applications in medicine. In this paper we will describe a software package, called DT-Planner, designed to represent and solve dynamic decision problems that can be modelled as Markov decision processes, by exploiting a novel graphical formalism, called influence view. An influence view is a directed acyclic graph that depicts the probabilistic relationships between the problem state variables in a generic time transition; additional variables, called event variables, may be added, in order to describe the conditional independencies between state variables. By using the specified conditional independence structure, an influence view may allow a parsimonious specification of a Markov decision process. DT-Planner lets the user specify and manage models through a user-friendly graphical interface, and implements efficient for policy determination algorithms. DT-Planner is written in C with Open Interface libraries and can be obtained, for non commercial use, via anonymous ftp without charge.

Algorithms↗
PubMed2000

Protein domain decomposition using a graph-theoretic approach.

MOTIVATION: Automatic decomposition of a multi-domain protein into individual domains represents a highly interesting and unsolved problem. As the number of protein structures in PDB is growing at an exponential rate, there is clearly a need for more reliable and efficient methods for protein domain decomposition simply to keep the domain databases up-to-date. RESULTS: We present a new algorithm for solving the domain decomposition problem, using a graph-theoretic approach. We have formulated the problem as a network flow problem, in which each residue of a protein is represented as a node of the network and each residue--residue contact is represented as an edge with a particular capacity, depending on the type of the contact. A two-domain decomposition problem is solved by finding a bottleneck (or a minimum cut) of the network, which minimizes the total cross-edge capacity, using the classical Ford--Fulkerson algorithm. A multi-domain decomposition problem is solved through repeatedly solving a series of two-domain problems. The algorithm has been implemented as a computer program, called DomainParser. We have tested the program on a commonly used test set consisting of 55 proteins. The decomposition results are 78.2% in agreement with the literature on both the number of decomposed domains and the assignments of residues to each domain, which compares favorably to existing programs. On the subset of two-domain proteins (20 in number), the program assigned 96.7% of the residues correctly when we require that the number of decomposed domains is two.

Algorithms↗