17502763
Alignment Of Protein Structures With A Memetic Evolutionary Algorithm
CATEGORY: Real-World Applications 
 
Structural comparison of proteins is a core problem in modern biomedical research. Identifying structural similarities is essential for the assessment of the relationship between structure and function in proteins, and structural comparison techniques play a key role in applications like rational drug design. In this paper we consider a technique for protein structure comparison known as the maximum contact map overlap problem. In this problem, the similarity between two protein structures is computed by aligning the proteins to maximize the number of shared contacts in their corresponding contact maps. 
 
We present a new approach to this problem that uses a Multimeme evolutionary algorithm. The best solution found by our algorithm provides a lower bound on the value of the optimal structural alignment between the proteins. We have evaluated the Multimeme algorithm on a range of benchmark problems and compared with previous heuristics. We apply a linear programming method, which provides an upper bound, to assess the accuracy of our solutions. Our experiments show that the Multimeme evolutionary algorithm represents a significant improvement on the current state of the art in metaheuristics for this problem.
3062981
Recombination strategy adaptation via evolution of gene linkage
Analyses recombination strategies resulting from evolving gene linkage on a variety of fitness landscapes with known properties. The evolution of "blocks" of linked genes within a gene-pool makes it possible for the recombination strategy to vary in both the amount of genetic material exchanged during the formation of a new individual and in the number of parents contributing genetic material. The strategies evolved are examined in the light of the known properties of the landscapes. The results obtained explain the previously recorded good performance of the algorithm as a self-adaptive mechanism for function optimisation, as the amount and type of recombination is able to adapt to suit the landscape being searched, unlike conventional "fixed" operators.
16664439
An alternative approach for the evaluation of the neocognitron
The neocognitron network is analysed from the point of view of the contribution of the di erent layers to the nal classi cation. A variation to the neocognitron which gives improved performance is suggested. This variant combines the low level feature extraction capabilities of the initial layers with alternative classi ers such as LVQ and Class Based Means Clustering. This is shown to give performance which is superior to the either of those classi ers acting on their own, and to the neocognitron in its standard form on two di erent instances of the letter recognition problem.
796697
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (Moscato, 1989). These methods are inspired by models of natural systems that combine the evolutionary adaptation of a population with individual learning within the lifetimes of its members. Additionally, MAs are inspired by Richard Dawkin's concept of a meme, which represents a unit of cultural evolution that can exhibit local refinement (Dawkins, 1976). In the case of MA's, "memes" refer to the strategies (e.g., local refinement, perturbation, or constructive methods, etc.) that are employed to improve individuals. In this paper, we review some works on the application of MAs to well-known combinatorial optimization problems, and place them in a framework defined by a general syntactic model. This model provides us with a classification scheme based on a computable index D, which facilitates algorithmic comparisons and suggests areas for future research. Also, by having an abstract model for this class of metaheuristics, it is possible to explore their design space and better understand their behavior from a theoretical standpoint. We illustrate the theoretical and practical relevance of this model and taxonomy for MAs in the context of a discussion of important design issues that must be addressed to produce effective and efficient MAs.
17447930
Incorporation of adaptive mutation based on subjective evaluation in an interactive evolution strategy
A rapidly emerging model in the field of adaptive computing is the symbiosis of human expertise with evolutionary algorithms for user controlled and directed search. The two aspects in any EA are the selection of individuals to reproduce based on some measure of their quality or fitness and the application of variation operators to produce new solutions. In the context of interactive evolution, these aspects are compounded by the need for rapid convergence to prevent user fatigue and to provide the user some control over the generation of new solutions. Elsewhere, in the work of the authors (2004), we have examined different policies for best incorporating the user into the evaluation and selection process. In this paper, we explore the hypothesis that user assigned fitness represents a source of information that can be used to control the variation process: effectively to broaden the search if none of the current solutions is promising, or focus the search and improve convergence speed in the vicinity of a good solution. The main aims of this study, therefore, are to analyse the advantages of using a user directed adaptive mutation strategy over fixed mutation step sizes in terms of time to converge and robustness of the resulting solution. We present results showing a qualitatively different type of search process can be obtained by using the user assigned fitness to control the nature of the mutation process. There is also a synergy between user-based selection and fitness-based mutation control which out performs either system on its own.
16182080
Self adaptation of mutation rates in a steady state genetic algorithm
This paper investigates the use of genetically encoded mutation rates within a "steady state" genetic algorithm in order to provide a self-adapting mutation mechanism for incremental evolution. One of the outcomes of this work will be a reduction in the number of parameters required to be set by the operator, thus facilitating the transfer of evolutionary computing techniques into an industrial setting. The NK family of landscapes is used to provide a variety of different problems with known statistical features in order to examine the effects of changing various parameters on the performance of the search. A number of policies are considered for the replacement of members of the population with newly created individuals and recombination of material between parents, and a number of methods of encoding for mutation rate are investigated. Empirical comparisons (using the "best-of current-population" metric) over a range of test problems show that a genetic algorithm incorporating the best "flavour" of the adaptive mutation operator outperformed the same algorithm when using any one of a variety of "standard" fixed mutation rates suggested by other authors.
14877105
Scalable multimedia delivery for pervasive computing
Growing numbers of pervasive devices are gaining access to the Internet and other information sources. However, much of the rich multimedia content cannot be easily handled by the client devices with limited communication, processing, storage and display capabilities. In order to improve access, we are developing a system for scalable delivery of multimedia. The system uses an InfoPyramid for managing and manipulating multimedia content composed of video, images, audio and text. The InfoPyramid manages the different variations of media objects with different fidelities and modalities and generates and selects among the alternatives in order to adapt the delivery to different client devices. We describe a system for scalable multimedia delivery for a variety of client devices, including PDAs, HHCs, smart phones, TV browsers and color PCs.
3251263
Semantic video clustering across sources using bipartite spectral clustering
Data clustering is an important technique for visual data management. Most previous work focuses on clustering video data within single sources. We address the problem of clustering across sources, and propose novel spectral clustering algorithms for multisource clustering problems. Spectral clustering is a new discriminative method realizing clustering by partitioning data graphs. We represent multi-source data as bipartite or K-partite graphs, and investigate the spectral clustering algorithm under these representations. The algorithms are evaluated using the TRECVID-2003 corpus with semantic features extracted from speech transcripts and visual concept recognition results from videos. The experiments show that the proposed bipartite clustering algorithm significantly outperforms the regular spectral clustering algorithm in capturing cross-source associations.
37305588
A dynamic programming algorithm for the conditional covering problem on tree graphs
In a previous article, we presented algorithms for solving the Conditional Covering Problem (CCP) on path and extended star graphs. The CCP on these graphs can be solved in O(n2) time, where n is the number of nodes in the graph. In this article, we propose a new dynamic programming procedure to solve the CCP on tree graphs. This recursion works from the leaf nodes of the tree up to the root node, using notions of protected and unprotected costs as done for the CCP path algorithm in our previous work. We introduce new preliminary routines and data structures to merge information from subpaths and subtrees, resulting in an O(n4) algorithm to optimally solve the problem. © 2005 Wiley Periodicals, Inc. NETWORKS, Vol. 46(4), 186–197 2005
7597155
MPEG-7 multimedia description schemes
MPEG-7 multimedia description schemes (MDSs) are metadata structures for describing and annotating audio-visual (AV) content. The description schemes (DSs) provide a standardized way of describing in XML the important concepts related to AV content description and content management in order to facilitate searching, indexing, filtering, and access. The DSs are defined using the MPEG-7 description definition language, which is based on the XML Schema language, and are instantiated as documents or streams. The resulting descriptions can be expressed in a textual form (i.e., human readable XML for editing, searching, filtering) or compressed binary form (i.e., for storage or transmission). In this paper, we provide an overview of the MPEG-7 MDSs and describe their targeted functionality and use in multimedia applications.
42385078
Using Earned Value Management for COTS-Based Systems: Issues and Recommendations
Earned value management (EVM) has long been used by organizations to plan, monitor, and control the development and evolution of custom developed systems. EVM was developed for managing such projects, and assumes a waterfall development model. COTS-based systems (CBS), on the other hand, are formed and evolved through the selection and composition of pre-existing, off-the-shelf packages or components with potentially some number of custom components. Experience indicates that a spiral or iterative development process is a key to success with CBS. While EVM has been applied to CBS projects, the results have not been uniformly satisfying. This paper explores the fundamental challenges in using EVM with CBS, and proposes adaptations to some of the principals of EVM to render it more suitable for CBS development.