The Novel Approach of Adaptive Twin Probability for Genetic Algorithm

The performance of GA is measured and analyzed in terms of its performance parameters against variations in its genetic operators and associated parameters. Since last four decades huge numbers of researchers have been working on the performance of GA and its enhancement. This earlier research work on analyzing the performance of GA enforces the need to further investigate the exploration and exploitation characteristics and observe its impact on the behavior and overall performance of GA. This paper introduces the novel approach of adaptive twin probability associated with the advanced twin operator that enhances the performance of GA. The design of the advanced twin operator is extrapolated from the twin offspring birth due to single ovulation in natural genetic systems as mentioned in the earlier works. The twin probability of this operator is adaptively varied based on the fitness of best individual thereby relieving the GA user from statically defining its value. This novel approach of adaptive twin probability is experimented and tested on the standard benchmark optimization test functions. The experimental results show the increased accuracy in terms of the best individual and reduced convergence time.Comment: 7 pages, International Journal of Advanced Studies in Computer Science and Engineering (IJASCSE), Volume 2, Special Issue 2, 201

Evolution of Co-operation When the Strategies are Hidden: The Human Mating Game

Defection is frequently seen in co-operative systems [1-3]. Game theoretical solutions to stabilize cooperation rely on reciprocity and reputation in iterated games[4-5]. One of the basic requirements for reciprocity or reputation building is that the strategies of players and the resulting payoffs should be open at the end of every interaction. For games in which the strategies and payoffs remain hidden, these stabilizing factors are unlikely to work. We examine the evolution of cooperation for hidden-strategy games using human mating game as an example. Here faithful parenting can be considered as cooperation and extra-pair mating (EPM) or cuckoldry as defection. Cuckoldry may get exposed only occasionally and the genetic benefits of cuckoldry also remain hidden from the players. Along with mate guarding, social policing is enabled in humans by language and gossiping. However, social policing can be invaded by second order free riders. We suggest that opportunistic blackmailing, which is unique to hidden strategy games can act as a keystone strategy in stabilizing co-operation. This can counteract free riding and stabilize policing. A game theoretical model results into a rock - paper – scissor (R-P-S) like situation with no evolutionary stable strategy (ESS). Simulations result into a stable or stably oscillating polymorphism. Obligate monogamy is an essential trait in the co-existence. In a gender difference model too, polymorphism is seen in both genders but with different traits predominating in the two genders. The model explains intra-gender, inter-gender as well as cross cultural variability in mating strategies in humans

Analysis of a Gibbs sampler method for model based clustering of gene expression data

Over the last decade, a large variety of clustering algorithms have been developed to detect coregulatory relationships among genes from microarray gene expression data. Model based clustering approaches have emerged as statistically well grounded methods, but the properties of these algorithms when applied to large-scale data sets are not always well understood. An in-depth analysis can reveal important insights about the performance of the algorithm, the expected quality of the output clusters, and the possibilities for extracting more relevant information out of a particular data set. We have extended an existing algorithm for model based clustering of genes to simultaneously cluster genes and conditions, and used three large compendia of gene expression data for S. cerevisiae to analyze its properties. The algorithm uses a Bayesian approach and a Gibbs sampling procedure to iteratively update the cluster assignment of each gene and condition. For large-scale data sets, the posterior distribution is strongly peaked on a limited number of equiprobable clusterings. A GO annotation analysis shows that these local maxima are all biologically equally significant, and that simultaneously clustering genes and conditions performs better than only clustering genes and assuming independent conditions. A collection of distinct equivalent clusterings can be summarized as a weighted graph on the set of genes, from which we extract fuzzy, overlapping clusters using a graph spectral method. The cores of these fuzzy clusters contain tight sets of strongly coexpressed genes, while the overlaps exhibit relations between genes showing only partial coexpression.Comment: 8 pages, 7 figure

Improved phase shedding technique in a multiphase converter system

Multiphase converters are increasingly gaining prominence in the field of power electronics. The main advantage of a multiphase converter is its increased efficiency in comparison to a single phase converter. The one major drawback of a multiphase converter is its light load efficiency. Light load efficiency in multiphase converters is very poor when compared to single phase converters. Phase shedding is one of the approaches used to improve this light load efficiency but the transient output voltage response of the system shows large deviations during the process of phase change. This thesis proposes a new technique, called the ramp control technique, to improve this transient behavior. Ramp control technique, proposes to gradually shed a phase or phases of the converter at light loads, instead of abruptly shutting it down. This is done by decreasing the duty cycle of the phase gradually to zero. In this thesis, a moving average model of the ramp control technique is constructed and the slope required for this technique is calculated on the basis of different parameters. The performance of the ramp control technique is also compared with the various conventional methods proposed in literature and it has been proved analytically and through simulation results that the ramp control technique has better dynamic performance when compared to the conventional methods. --Abstract, page iii

One Hundred Colors of Violence: Ethnic Conflict Variation Across Non-Democratic Regimes

HonorsUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/162599/1/apmulpur.pd

Uncovering Randomness and Success in Society

An understanding of how individuals shape and impact the evolution of society is vastly limited due to the unavailability of large-scale reliable datasets that can simultaneously capture information regarding individual movements and social interactions. We believe that the popular Indian film industry, 'Bollywood', can provide a social network apt for such a study. Bollywood provides massive amounts of real, unbiased data that spans more than 100 years, and hence this network has been used as a model for the present paper. The nodes which maintain a moderate degree or widely cooperate with the other nodes of the network tend to be more fit (measured as the success of the node in the industry) in comparison to the other nodes. The analysis carried forth in the current work, using a conjoined framework of complex network theory and random matrix theory, aims to quantify the elements that determine the fitness of an individual node and the factors that contribute to the robustness of a network. The authors of this paper believe that the method of study used in the current paper can be extended to study various other industries and organizations.Comment: 39 pages, 12 figures, 14 table