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.

Multi-threading and message communication in Qu-Prolog

This paper presents the multi-threading and internet message communication capabilities of Qu-Prolog. Message addresses are symbolic and the communications package provides high-level support that completely hides details of IP addresses and port numbers as well as the underlying TCP/IP transport layer. The combination of the multi-threads and the high level inter-thread message communications provide simple, powerful support for implementing internet distributed intelligent applications.

Design and implementation of a windows-based parallel computing environment for large scale optimization

A parallel computing environment to support optimization of large-scale engineering systems is designed and implemented on Windows-based personal computer networks, using the master-worker model and the Parallel Virtual Machine (PVM). It is involved in decomposition of a large engineering system into a number of smaller subsystems optimized in parallel on worker nodes and coordination of subsystem optimization results on the master node. The environment consists of six functional modules, i.e. the master control, the optimization model generator, the optimizer, the data manager, the monitor, and the post processor. Object-oriented design of these modules is presented. The environment supports steps from the generation of optimization models to the solution and the visualization on networks of computers. User-friendly graphical interfaces make it easy to define the problem, and monitor and steer the optimization process. It has been verified by an example of a large space truss optimization. (C) 2004 Elsevier Ltd. All rights reserved.

Validation and patient acceptance of a computer touch screen version of the WOMAC 3.1 osteoarthritis index

Objectives: To validate the WOMAC 3.1 in a touch screen computer format, which applies each question as a cartoon in writing and in speech (QUALITOUCH method), and to assess patient acceptance of the computer touch screen version. Methods: The paper and computer formats of WOMAC 3.1 were applied in random order to 53 subjects with hip or knee osteoarthritis. The mean age of the subjects was 64 years ( range 45 to 83), 60% were male, 53% were 65 years or older, and 53% used computers at home or at work. Agreement between formats was assessed by intraclass correlation coefficients (ICCs). Preferences were assessed with a supplementary questionnaire. Results: ICCs between formats were 0.92 (95% confidence interval, 0.87 to 0.96) for pain; 0.94 (0.90 to 0.97) for stiffness, and 0.96 ( 0.94 to 0.98) for function. ICCs were similar in men and women, in subjects with or without previous computer experience, and in subjects below or above age 65. The computer format was found easier to use by 26% of the subjects, the paper format by 8%, and 66% were undecided. Overall, 53% of subjects preferred the computer format, while 9% preferred the paper format, and 38% were undecided. Conclusion: The computer format of the WOMAC 3.1 is a reliable assessment tool. Agreement between computer and paper formats was independent of computer experience, age, or sex. Thus the computer format may help improve patient follow up by meeting patients' preferences and providing immediate results.

Diversification and extensible networks: The strategies of Chinese businesses in Australia

The paper reports on a study of 28 ethnic Chinese businesses in Brisbane, Adelaide, and Perth, carried out in 2000 and 2001. It focuses on their strategies of vertical, horizontal, and unrelated diversification often combining different activities, products, and markets at the same time. It demonstrates how these practices are socially embedded in their preference for using personal networks. Non-related diversification, in particular, promotes and is facilitated by using weak ties that serve as bridges, leading into new networks (Granovetter, 1973). This can create links to Chinese of different national and dialect origins and to those of other ethnicities. It is suggested that open networks and diversification mutually interact to support each other and may have evolved in tandem from earlier, more closed and niche bound business cultures and practices.

Prediction of subcellular localization using sequence-biased recurrent networks

Motivation: Targeting peptides direct nascent proteins to their specific subcellular compartment. Knowledge of targeting signals enables informed drug design and reliable annotation of gene products. However, due to the low similarity of such sequences and the dynamical nature of the sorting process, the computational prediction of subcellular localization of proteins is challenging. Results: We contrast the use of feed forward models as employed by the popular TargetP/SignalP predictors with a sequence-biased recurrent network model. The models are evaluated in terms of performance at the residue level and at the sequence level, and demonstrate that recurrent networks improve the overall prediction performance. Compared to the original results reported for TargetP, an ensemble of the tested models increases the accuracy by 6 and 5% on non-plant and plant data, respectively.