46,110 research outputs found
Two-stage hybrid feature selection algorithms for diagnosing erythemato-squamous diseases
This paper proposes two-stage hybrid feature selection algorithms to build the stable and efficient diagnostic models where a new accuracy measure is introduced to assess the models. The two-stage hybrid algorithms adopt Support Vector Machines (SVM) as a classification tool, and the extended Sequential Forward Search (SFS), Sequential Forward Floating Search (SFFS), and Sequential Backward Floating Search (SBFS), respectively, as search strategies, and the generalized F-score (GF) to evaluate the importance of each feature. The new accuracy measure is used as the criterion to evaluated the performance of a temporary SVM to direct the feature selection algorithms. These hybrid methods combine the advantages of filters and wrappers to select the optimal feature subset from the original feature set to build the stable and efficient classifiers. To get the stable, statistical and optimal classifiers, we conduct 10-fold cross validation experiments in the first stage; then we merge the 10 selected feature subsets of the 10-cross validation experiments, respectively, as the new full feature set to do feature selection in the second stage for each algorithm. We repeat the each hybrid feature selection algorithm in the second stage on the one fold that has got the best result in the first stage. Experimental results show that our proposed two-stage hybrid feature selection algorithms can construct efficient diagnostic models which have got better accuracy than that built by the corresponding hybrid feature selection algorithms without the second stage feature selection procedures. Furthermore our methods have got better classification accuracy when compared with the available algorithms for diagnosing erythemato-squamous diseases
Geochemistry of reduced inorganic sulfur, reactive iron, and organic carbon in fluvial and marine surface sediment in the Laizhou Bay region, China
Understanding the geochemical cycling of sulfur in sediments is important because it can have implications for both modern environments (e.g., deterioration of water quality) and interpretation of the ancient past (e.g., sediment C/S ratios can be used as indicators of palaeodepositional environment). This study investigates the geochemical characteristics of sulfur, iron, and organic carbon in fluvial and coastal surface sediments of the Laizhou Bay region, China. A total of 63 sediment samples were taken across the whole Laizhou Bay marine region and the 14 major tidal rivers draining into it. Acid volatile sulfur, chromium (II)-reducible sulfur and elemental sulfur, total organic carbon, and total nitrogen were present in higher concentrations in the fluvial sediment than in the marine sediment of Laizhou Bay. The composition of reduced inorganic sulfur in surface sediments was dominated by acid volatile sulfur and chromium (II)-reducible sulfur. In fluvial sediments, sulfate reduction and formation of reduced inorganic sulfur were controlled by TOC and reactive iron synchronously. High C/S ratios in the marine sediments indicate that the diagenetic processes in Laizhou Bay have been affected by rapid deposition of sediment from the Yellow River in recent decades
Entropy and its state of arts on research of spatial data uncertainty
2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
Electromagnetic decays of vector mesons as derived from QCD sum rules
We apply the method of QCD sum rules in the presence of external
electromagnetic fields to the problem of the electromagnetic
decays of various vector mesons, such as , and . The induced condensates obtained previously
from the study of baryon magnetic moments are adopted, thereby ensuring the
parameter-free nature of the present calculation. Further consistency is
reinforced by invoking various QCD sum rules for the meson masses. The
numerical results on the various radiative decays agree very well with the
experimental data.Comment: To appear in Phys. Lett.
Possible discovery of the r-process characteristics in the abundances of metal-rich barium stars
We study the abundance distributions of a sample of metal-rich barium stars
provided by Pereira et al. (2011) to investigate the s- and r-process
nucleosynthesis in the metal-rich environment. We compared the theoretical
results predicted by a parametric model with the observed abundances of the
metal-rich barium stars. We found that six barium stars have a significant
r-process characteristic, and we divided the barium stars into two groups: the
r-rich barium stars (, [La/Nd]\,) and normal barium stars. The
behavior of the r-rich barium stars seems more like that of the metal-poor
r-rich and CEMP-r/s stars. We suggest that the most possible formation
mechanism for these stars is the s-process pollution, although their abundance
patterns can be fitted very well when the pre-enrichment hypothesis is
included. The fact that we can not explain them well using the s-process
nucleosynthesis alone may be due to our incomplete knowledge on the production
of Nd, Eu, and other relevant elements by the s-process in metal-rich and super
metal-rich environments (see details in Pereira et al. 2011).Comment: 5 pages, 5 figures, accepted for publication in A&
Light Fan Driven by a Relativistic Laser Pulse
When a relativistic laser pulse with a high photon density interacts with a specially tailored thin foil target, a strong torque is exerted on the resulting spiral-shaped foil plasma, or “light fan.” Because of its structure, the latter can gain significant orbital angular momentum (OAM), and the opposite OAM is imparted to the reflected light, creating a twisted relativistic light pulse. Such an interaction scenario is demonstrated by particle-in-cell simulation as well as analytical modeling, and should be easily verifiable in the laboratory. As an important characteristic, the twisted relativistic light pulse has a strong torque and ultrahigh OAM density
Extending twin support vector machine classifier for multi-category classification problems
© 2013 – IOS Press and the authors. All rights reservedTwin support vector machine classifier (TWSVM) was proposed by Jayadeva et al., which was used for binary classification
problems. TWSVM not only overcomes the difficulties in handling the problem of exemplar unbalance in binary classification problems, but also it is four times faster in training a classifier than classical support vector machines. This paper proposes one-versus-all twin support vector machine classifiers (OVA-TWSVM) for multi-category classification problems by utilizing the strengths of TWSVM. OVA-TWSVM extends TWSVM to solve k-category classification problems by developing k TWSVM where in the ith TWSVM, we only solve the Quadratic Programming Problems (QPPs) for the ith class, and get the ith nonparallel hyperplane corresponding to the ith class data. OVA-TWSVM uses the well known one-versus-all (OVA) approach to construct a corresponding twin support vector machine classifier. We analyze the efficiency of the OVA-TWSVM theoretically, and perform experiments to test its efficiency on both synthetic data sets and several benchmark data sets from the UCI machine learning repository. Both the theoretical analysis and experimental results demonstrate that OVA-TWSVM can outperform the traditional OVA-SVMs classifier. Further experimental comparisons with other multiclass classifiers demonstrated that comparable performance could be achieved.This work is supported in part by the grant
of the Fundamental Research Funds for the Central Universities of GK201102007 in PR China, and is also supported by Natural Science Basis Research Plan in Shaanxi Province of China (Program No.2010JM3004), and is at the same time supported by Chinese Academy of Sciences under the Innovative
Group Overseas Partnership Grant as well as Natural Science Foundation of China Major International Joint Research Project (NO.71110107026)
Magnetic Moments of Pentaquarks
If the of and pentaquarks is really found to
be by future experiments, they will be accompanied by
partners in some models. It is reasonable to expect that
these states will also be discovered in the near future with
the current intensive experimental and theoretical efforts. We estimate
pentaquark magnetic moments using different models.Comment: 13 page
The linear quadratic regulator problem for a class of controlled systems modeled by singularly perturbed Ito differential equations
This paper discusses an infinite-horizon linear quadratic (LQ) optimal control problem involving state- and control-dependent noise in singularly perturbed stochastic systems. First, an asymptotic structure along with a stabilizing solution for the stochastic algebraic Riccati equation (ARE) are newly established. It is shown that the dominant part of this solution can be obtained by solving a parameter-independent system of coupled Riccati-type equations. Moreover, sufficient conditions for the existence of the stabilizing solution to the problem are given. A new sequential numerical algorithm for solving the reduced-order AREs is also described. Based on the asymptotic behavior of the ARE, a class of O(√ε) approximate controller that stabilizes the system is obtained. Unlike the existing results in singularly perturbed deterministic systems, it is noteworthy that the resulting controller achieves an O(ε) approximation to the optimal cost of the original LQ optimal control problem. As a result, the proposed control methodology can be applied to practical applications even if the value of the small parameter ε is not precisely known. © 2012 Society for Industrial and Applied Mathematics.Vasile Dragan, Hiroaki Mukaidani and Peng Sh
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