Aggregating metasearch engine results based on maximal entropy OWA operator

The maximal entropy ordered weighted averaging （ME-OWA） operator is used to aggregate metasearch engine results, and its newly analytical solution is also applied. Within the current context of the OWA operator, the methods for aggregating metasearch engine results are divided into two kinds. One has a unique solution, and the other has multiple solutions. The proposed method not only has crisp weights, but also provides multiple aggregation results for decision makers to choose from. In order to prove the application of the ME-OWA operator method, under the context of aggregating metasearch engine results, an example is given, which shows the results obtained by the ME-OWA operator method and the minimax linear programming （ minimax-LP ） method. Comparison between these two methods are also made. The results show that the ME-OWA operator has nearly the same aggregation results as those of the minimax-LP method.

A Novel Method for Prediction of Protein Domain Using Distance-Based Maximal Entropy

Detecting the boundaries of protein domains is an important and challenging task in both experimental and computational structural biology. In this paper, a promising method for detecting the domain structure of a protein from sequence information alone is presented. The method is based on analyzing multiple sequence alignments derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence. Then they are combined into a single predictor using support vector machine. What is more important, the domain detection is first taken as an imbal- anced data learning problem. A novel undersampling method is proposed on distance-based maximal entropy in the feature space of Support Vector Machine （SVM）. The overall precision is about 80%. Simulation results demonstrate that the method can help not only in predicting the complete 3D structure of a protein but also in the machine learning system on general im- balanced datasets.

Oxidative reforming of methane for hydrogen and synthesis gas production:Thermodynamic equilibrium analysis

A thermodynamic analysis of methane oxidative reforming was carried out by Gibbs energy minimization （at constant pressure and temperature） and entropy maximization （at constant pressure and enthalpy） methods,to determine the equilibrium compositions and equilibrium temperatures,respectively.Both cases were treated as optimization problems （non-linear programming formulation）.The GAMS 23.1 software and the CONOPT2 solver were used in the resolution of the proposed problems.The hydrogen and syngas production were favored at high temperatures and low pressures,and thus the oxygen to methane molar ratio （O 2 /CH 4） was the dominant factor to control the composition of the product formed.For O 2 /CH 4 molar ratios higher than 0.5,the oxidative reforming of methane presented autothermal behavior in the case of either utilizing O 2 or air as oxidant agent,but oxidation reaction with air possessed the advantage of avoiding peak temperatures in the system,due to change in the heat capacity of the system caused by the addition of nitrogen.The calculated results were compared with previously published experimental and simulated data with a good agreement between them.

Stronger Version Sensitivity, Almost Finite to One Extension and Maximal Pattern Entropy

In this paper,we introduce thickr-sensitivity,multi-r-sensitivity and block thick r-sensitivity for r≥2.We first give a characterization of a minimal system which is block thickly r-sensitive.Then we obtain a sufficient condition of a minimal system which is thickly r-sensitive.The maximal pattern entropy of a multi-r-sensitive topological dynamical system is also discussed.

Measurable n-sensitivity and maximal pattern entropy

We introduce the notion of measurable n-sensitivity for measure preserving systems,and study the relation between measurable n-sensitivity and the maximal pattern entropy.We prove that,if(X,ℬ,μ,T)is ergodic,then(X,ℬ,μ,T)is measurable n-sensitive but not measurable(n+1)-sensitive if and only if h_(μ)^(*)(T)=log n,where h_(μ)^(*)(T)is the maximal pattern entropy of T.

Hurricane eye morphology extraction from SAR images by texture analysis

Tropical hurricanes are among the most devastating hazards on Earth.Knowledge about its intense inner-core structure and dynamics will improve hurricane forecasts and advisories.The precise morphological parameters extracted from high-resolution spaceborne Synthetic Aperture Radar(SAR)images,can play an essential role in further exploring and monitoring hurricane dynamics,especially when hurricanes undergo amplification,shearing,eyewall replacements and so forth.Moreover,these parameters can help to build guidelines for wind calibration of the more abundant,but lower resolution scatterometer wind data,thus better linking scatterometer wind fields to hurricane categories.In this paper,we develop a new method for automatically extracting the hurricane eyes from C-band SAR data by constructing Gray Level-Gradient Co-occurrence Matrices(GLGCMs).The hurricane eyewall is determined with a two-dimensional vector,generated by maximizing the class entropy of the hurricane eye region in GLGCM.The results indicate that when the hurricane is weak,or the eyewall is not closed,the hurricane eye extracted with this automatic method still agrees with what is observed visually,and it preserves the texture characteristics of the original image.As compared to Du’s wavelet analysis method and other morphological analysis methods,the approach developed here has reduced artefacts due to factors like hurricane size and has lower programming complexity.In summary,the proposed method provides a new and elegant choice for hurricane eye morphology extraction.

Trivial and Simple Spectrum for SL(d,R) Cocycles with Free Base and Fiber Dynamics

Let ACD（M, SL（d,R）） denote the pairs （f, A） so that f∈ A C Diff^1（M） is a C^1-Anosov transitive diffeomorphisms and A is an SL（d,R） cocycle dominated with respect to f. We prove that open and densely in ACD（M, SL（d,R））, in appropriate topologies, the pair （f,A） has simple spectrum with respect to the unique maximal entropy measure μf. Then, we prove prevalence of trivial spectrum near the dynamical cocycle of an area-preserving map and also for generic cocycles in AUtLeb（M） × LP（M, SL（d, R））.