7,295 research outputs found
Revisiting Radiation Patterns in Collisions
We propose four simple event-shape variables for semi-inclusive -jet events. The observables and cuts are designed to be especially sensitive
to subleading aspects of the event structure, and allow to test the reliability
of phenomenological QCD models in greater detail. Three of them, ,
, and , focus on soft emissions off three-jet topologies
with a small opening angle, for which coherence effects beyond the leading QCD
dipole pattern are expected to be enhanced. A complementary variable,
, measures the ratio of the hemisphere masses in 4-jet events with
a compressed scale hierarchy (Durham ), for which subleading
splitting effects are expected to be enhanced. We consider several
different parton-shower models, spanning both conventional and dipole/antenna
ones, all tuned to the same reference data, and show that a
measurement of the proposed observables would allow for additional significant
discriminating power between the models.Comment: 27 pages, 10 figure
Adaptive multimodal continuous ant colony optimization
Seeking multiple optima simultaneously, which multimodal optimization aims at, has attracted increasing attention but remains challenging. Taking advantage of ant colony optimization algorithms in preserving high diversity, this paper intends to extend ant colony optimization algorithms to deal with multimodal optimization. First, combined with current niching methods, an adaptive multimodal continuous ant colony optimization algorithm is introduced. In this algorithm, an adaptive parameter adjustment is developed, which takes the difference among niches into consideration. Second, to accelerate convergence, a differential evolution mutation operator is alternatively utilized to build base vectors for ants to construct new solutions. Then, to enhance the exploitation, a local search scheme based on Gaussian distribution is self-adaptively performed around the seeds of niches. Together, the proposed algorithm affords a good balance between exploration and exploitation. Extensive experiments on 20 widely used benchmark multimodal functions are conducted to investigate the influence of each algorithmic component and results are compared with several state-of-the-art multimodal algorithms and winners of competitions on multimodal optimization. These comparisons demonstrate the competitive efficiency and effectiveness of the proposed algorithm, especially in dealing with complex problems with high numbers of local optima
Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset
Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics
Markets, herding and response to external information
We focus on the influence of external sources of information upon financial
markets. In particular, we develop a stochastic agent-based market model
characterized by a certain herding behavior as well as allowing traders to be
influenced by an external dynamic signal of information. This signal can be
interpreted as a time-varying advertising, public perception or rumor, in favor
or against one of two possible trading behaviors, thus breaking the symmetry of
the system and acting as a continuously varying exogenous shock. As an
illustration, we use a well-known German Indicator of Economic Sentiment as
information input and compare our results with Germany's leading stock market
index, the DAX, in order to calibrate some of the model parameters. We study
the conditions for the ensemble of agents to more accurately follow the
information input signal. The response of the system to the external
information is maximal for an intermediate range of values of a market
parameter, suggesting the existence of three different market regimes:
amplification, precise assimilation and undervaluation of incoming information.Comment: 30 pages, 8 figures. Thoroughly revised and updated version of
arXiv:1302.647
A novel and universal method for microRNA RT-qPCR data normalization
Gene expression analysis of microRNA molecules is becoming increasingly important. In this study we assess the use of the mean expression value of all expressed microRNAs in a given sample as a normalization factor for microRNA real-time quantitative PCR data and compare its performance to the currently adopted approach. We demonstrate that the mean expression value outperforms the current normalization strategy in terms of better reduction of technical variation and more accurate appreciation of biological changes
Bibliometric Mapping of the Computational Intelligence Field
In this paper, a bibliometric study of the computational intelligence field is presented. Bibliometric maps showing the associations between the main concepts in the field are provided for the periods 1996–2000 and 2001–2005. Both the current structure of the field and the evolution of the field over the last decade are analyzed. In addition, a number of emerging areas in the field are identified. It turns out that computational intelligence can best be seen as a field that is structured around four important types of problems, namely control problems, classification problems, regression problems, and optimization problems. Within the computational intelligence field, the neural networks and fuzzy systems subfields are fairly intertwined, whereas the evolutionary computation subfield has a relatively independent position.neural networks;bibliometric mapping;fuzzy systems;bibliometrics;computational intelligence;evolutionary computation
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