7669221
Function Finding and Constants Creation Method in Evolutionary Algorithm Based on Overlapped Gene Expression
Evolutionary algorithm based on overlapped gene expression (EAOGE) is a new technology of evolutionary algorithm which is inspired by the overlap gene expression in biological research. Different from existing works, EAOGE suggests a new expression structure of genes, and these genes have a probability to overlapped express in some segments. It uses chromosomes of fixed length to represent expression trees of different shapes and sizes. It does unconstrained search in the genome space and still ensures validity of the expression. This paper implements EAOGE algorithm and proposes a new constants creation method. Extensive experiments show that the method significantly improves the precision in the problems of function finding, and the precision of the new method is about 12.8 times to traditional algorithm at least.
15894023
Evolutionary Algorithm Based on Overlapped Gene Expression
Inspired by the overlap gene expression in biological study, this paper proposes a novel evolutionary algorithm-EAOGE i.e. Evolutionary Algorithm based on Overlapped Gene Expression. Different from existing works, EAOGE suggests a new expression structure of genes with probabilities of overlapped expression for some segments. The main contributions are: (1) Proposing a novel model and an algorithm of gene expression while borrowing some ideas from artificial immunity algorithm; (2) Analyzing the expressing space and encode characteristic of the new model; (3) The extensive experiments in function finding shows that new model is 2.8~9.7 times faster than usual GEP method, and in higher-degree polynomial function finding, the success rate of EAOGE is over 10 times than usual GEP.
15454854
TCP Quick-Adjust by Utilizing Explicit Link Characteristic Information
This paper investigates the utilization of explicit bottleneck link characteristic information in order to enhance TCP behaviors. We propose the TCP Quick-Adjust algorithm as an extension of TCP Quick-Start, to allow end nodes to quickly adjust their sending rate for ongoing connections according to the reported bottleneck link bandwidth. Our scheme is considered to be especially suitable to use in a mobile operator's controlled network domain, where it is possible to provide a subscribed mobile node with reasonably accurate access link and path information. The link characteristic information is piggybacked in IP mobility signaling in this paper. Using simulations, we show that TCP Quick-Adjust provides good performance in terms of link capacity utilization in the scenarios where vertical handovers can happen between two links with very different characteristics.
8817054
The Application of Cultural Algorithm in Load Balancing of Hybrid P2P Network
This paper analyses the defect of the designing model of load balancing in hybrid P2P network, and proposes a new strategy of scheduling for load balancing, which based on culture algorithm of multilayer belief spaces. According to the current load status of each super-node in the system, it can calculate its load weight of the next time section by using the cultural algorithm, and assign the current requests of login with weighted round-robin. The extracted knowledge which is got by selecting the best belief space from the multilayer belief space is used to optimize the constrains of the evolutionary, in order to accelerate the optimization process of the calculation of load weight. Simulation experiments show that the allocation of login request to each node is to be balance much faster through using of cultural algorithm based on multilayer belief spaces.
7333588
Automating change evolution in model-driven engineering
The escalating complexity of software and system models is making it difficult to rapidly explore the effects of a design decision. Automating such exploration with model transformation and aspect-oriented techniques can improve both productivity and model quality. The combination of model transformation and aspect weaving provides a powerful technology for rapidly transforming legacy systems from the high-level properties that models describe. Further, by applying aspect-oriented techniques and program transformation, small changes at the modeling level can trigger very large transformations at the source code level. Thus, model engineers can explore alternative configurations using an aspect weaver targeted for modeling tools and then use the models to generate program transformation rules for adapting legacy source code on a wide scale.
4727524
A Novel Dimensionality Reduction Technique Based on Independent Component Analysis for Modeling Microarray Gene Expression Data
DNA microarray experiments generating thousands of gene 
expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. But one challenge of microarray studies is the fact that the number n of samples collected is relatively small compared to the number p of genes per sample which are usually in thousands. In statistical terms this very large number of predictors compared to a small number of samples or observations makes the classification problem difficult. This is known as the ”curse of dimensionality problem”. An efficient way to solve this problem is by using dimensionality reduction techniques. Principle Component Analysis(PCA) is a leading method for dimensionality reduction of gene expression data which is optimal in the sense of least square error. In this paper we propose a new dimensionality reduction technique for specific bioinformatics applications based on Independent component Analysis(ICA). Being able to exploit higher order statistics to identify a linear model result, this ICA based dimensionality reduction technique 
outperforms PCA from both statistical and biological 
significance aspects. We present experiments on NCI 60 
dataset to show this result.
5054397
The transient solution of time-dependent M/M/1 queues
The transient behavior of time-dependent M/M/1 queues is studied. The boundary probability function pi /sub 0/(t), which is the probability that the queue is empty at time t, is shown with analyticity arguments to satisfy a Volterra-type integral equation. The boundary integral equation is derived, and a numerical algorithm is used to solve the integral equation and to find the expected queue size from pi /sub 0/(t). The approach can be applied to many other types of time-dependent queues. Examples are given. >