On some optimal algorithms.

Thesis - University of Illinois at Urbana-Champaign.

Hand-held calculator algorithms for coastal engineering /

"January 1982."

Hand-held calculator algorithms for coastal engineering : (second series) /

"November 1982."

Process design and cost estimating algorithms for the computer assisted procedure for design and evaluation of wastewater treatment systems (CAPDET) /

"PB 82-190455."

Automatic traffic advisory and resolution service (ATARS) multi-site algorithms /

Mode of access: Internet.

Analysis of edge detection algorithms on DIAL /

Mode of access: Internet.

Genetic algorithms in statistical tolerancing

An important aspect in manufacturing design is the distribution of geometrical tolerances so that an assembly functions with given probability, while minimising the manufacturing cost. This requires a complex search over a multidimensional domain, much of which leads to infeasible solutions and which can have many local minima. As well, Monte-Carlo methods are often required to determine the probability that the assembly functions as designed. This paper describes a genetic algorithm for carrying out this search and successfully applies it to two specific mechanical designs, enabling comparisons of a new statistical tolerancing design method with existing methods. (C) 2003 Elsevier Ltd. All rights reserved.

Genetic algorithms with applications in wireless communications

Genetic algorithms (GAs) are known to locate the global optimal solution provided sufficient population and/or generation is used. Practically, a near-optimal satisfactory result can be found by Gas with a limited number of generations. In wireless communications, the exhaustive searching approach is widely applied to many techniques, such as maximum likelihood decoding (MLD) and distance spectrum (DS) techniques. The complexity of the exhaustive searching approach in the MLD or the DS technique is exponential in the number of transmit antennas and the size of the signal constellation for the multiple-input multiple-output (MIMO) communication systems. If a large number of antennas and a large size of signal constellations, e.g. PSK and QAM, are employed in the MIMO systems, the exhaustive searching approach becomes impractical and time consuming. In this paper, the GAs are applied to the MLD and DS techniques to provide a near-optimal performance with a reduced computational complexity for the MIMO systems. Two different GA-based efficient searching approaches are proposed for the MLD and DS techniques, respectively. The first proposed approach is based on a GA with sharing function method, which is employed to locate the multiple solutions of the distance spectrum for the Space-time Trellis Coded Orthogonal Frequency Division Multiplexing (STTC-OFDM) systems. The second approach is the GA-based MLD that attempts to find the closest point to the transmitted signal. The proposed approach can return a satisfactory result with a good initial signal vector provided to the GA. Through simulation results, it is shown that the proposed GA-based efficient searching approaches can achieve near-optimal performance, but with a lower searching complexity comparing with the original MLD and DS techniques for the MIMO systems.

System for foreign exchange trading using genetic algorithms and reinforcement learning

Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

Countering cooperative effects in protease inhibitors using constrained b-strand-mimicking templates in focused combinatorial libraries

A major problem in de novo design of enzyme inhibitors is the unpredictability of the induced fit, with the shape of both ligand and enzyme changing cooperatively and unpredictably in response to subtle structural changes within a ligand. We have investigated the possibility of dampening the induced fit by using a constrained template as a replacement for adjoining segments of a ligand. The template preorganizes the ligand structure, thereby organizing the local enzyme environment. To test this approach, we used templates consisting of constrained cyclic tripeptides, formed through side chain to main chain linkages, as structural mimics of the protease-bound extended beta-strand conformation of three adjoining amino acid residues at the N- or C-terminal sides of the scissile bond of substrates. The macrocyclic templates were derivatized to a range of 30 structurally diverse molecules via focused combinatorial variation of nonpeptidic appendages incorporating a hydroxyethylamine transition-state isostere. Most compounds in the library were potent inhibitors of the test protease (HIV-1 protease). Comparison of crystal structures for five protease-inhibitor complexes containing an N-terminal macrocycle and three protease-inhibitor complexes containing a C-terminal macrocycle establishes that the macrocycles fix their surrounding enzyme environment, thereby permitting independent variation of acyclic inhibitor components with only local disturbances to the protease. In this way, the location in the protease of various acyclic fragments on either side of the macrocyclic template can be accurately predicted. This type of templating strategy minimizes the problem of induced fit, reducing unpredictable cooperative effects in one inhibitor region caused by changes to adjacent enzyme-inhibitor interactions. This idea might be exploited in template-based approaches to inhibitors of other proteases, where a beta-strand mimetic is also required for recognition, and also other protein-binding ligands where different templates may be more appropriate.

Evaluation of cosmic ray rejection algorithms on single-shot exposures

To maximise data output from single-shot astronomical images, the rejection of cosmic rays is important. We present the results of a benchmark trial comparing various cosmic ray rejection algorithms. The procedures assess relative performances and characteristics of the processes in cosmic ray detection, rates of false detections of true objects, and the quality of image cleaning and reconstruction. The cosmic ray rejection algorithms developed by Rhoads (2000, PASP, 112, 703), van Dokkum (2001, PASP, 113, 1420), Pych (2004, PASP, 116, 148), and the IRAF task xzap by Dickinson are tested using both simulated and real data. It is found that detection efficiency is independent of the density of cosmic rays in an image, being more strongly affected by the density of real objects in the field. As expected, spurious detections and alterations to real data in the cleaning process are also significantly increased by high object densities. We find the Rhoads' linear filtering method to produce the best performance in the detection of cosmic ray events; however, the popular van Dokkum algorithm exhibits the highest overall performance in terms of detection and cleaning.