PYRAMIDAL MULTIPHASE LEVEL SET FRAMEWORK FOR BRAIN TUMOR DETECTION USING GENERALIZED TECHNIQUE OF PAINTING BACKGROUND

The pyramidal multiphase level set framework （PMLSF） based on the technique of painting background （TPBG） and the Chan-Vese model can detect multiple objects on a given image. However, the boundaries of the sub-object obtained by PMLSF-TPBG are not variable since a specialcolor parameter is used in TPBG. To solve the problem, a new technique utilizing a varying parameter is proposed to ensure that PMLSF is effective for the detection of the desired boundaries of the sub-object. The interval of the variable color parameter is proved and the effects of the parameter are also discussed. Experimental results for the brain tumor detection show that different boundaries of the brain tumors can be detected with different color parameters. It is especially useful for clinical diagnoses.

散文的诗质和小说化——观当代台湾散文

提出这个问题的时候,先说明一下诗质和小说化在此的含义。诗质指的是一种审美境界,诗是最能达到审美极至的一种文体,故以此指称散文的审美性。对散文来说,其美感作用发生需要达到一定诗质的高度,诗质是散文的美质,散文的灵魂。小说化指散文文体结构的现代化、开放性。当代散文作者思维方式变革,在遣词造意,谋篇布局上吸收其它文体的优点和长处,兼容并包,使散文外包装呈现丰富多样的面容。 台湾的散文作家一直兢兢业业地在这块园地里耕耘着,对散文的技巧、形式、内容深为用心。

Motion Geometric Active Contours: Tracking Nonrigid Objects in Clutter Background

MGAC (Motion Geometric Active Contours), a new variational framework of geometric active contours to track multiple nonrigid moving objects in the clutter background in image sequences is presented. This framework, incorporating with the motion edge information, consists of motion detection and tracking stages. At the motion detection stage, the motion edge map provides an approximate edge map of the moving objects. Then, a tracking stage, merely using the static edge information, is considered to improve the motion detection result. Force field regularization method is used to extend the capture range of the edge attraction force field in both stages. Experiments demonstrate that the proposed framework is valid for tracking multiple nonrigid objects in the clutter background.

Contour Laser Guiding for the Mechanized ＂Vallerani＂ Micro-catchment Water Harvesting Systems

Mechanized construction of micro-catchments for water harvesting （WH） was successfully tested in the Badia （dry rangeland） areas in Syria and Jordan, using the ＂Vallerani＂ plow, model Delfino （50 MI/CM）, manufactured by Nardi, Italy. The plow was able to construct intermittent and continuous contour ridges, and could potentially be used to rehabilitate degraded rangelands. However, one major issue for large-scale implementation is the high cost and time required to manually identify contours for the plow to follow. Most existing auto-guiding systems, as usually used in road construction and agricultural land leveling, were expensive or impractical. The objective, therefore, was to add, adapt, and evaluate an auto-guiding system to enable a tractor to follow contours without demarcation through conventional surveying. A low-cost Contour Laser Guiding （CLG） system, with specifications that suit the contour ridging in undulating topographic conditions of dry rangelands, was chosen, adapted, mounted, and tested, under actual field conditions. The system consisted mainly of a portable laser transmitter and a tractor-mounted receiver, connected to a guidance display panel. The system was field-tested on 95 ha of land where the system capacity was determined under different terrains, slopes （1-8%）, and ridge spacings （4-12 m）. The easy adaptation and implementation of the CLG to the ＂Vallerani＂ unit tripled the system capacity, improved efficiency and precision, and substantially reduced the cost of constructing micro-catchments for WH. The system is recommended for large-scale rangeland rehabilitation projects in the dry areas, not only in West Asia, but worldwide.

Water Profile over an Ogee-Shaped Crest and the Reynolds Fractional Equations

Weir crest must have the correct shape in the concave side of an ogee-shaped crest to diminish erosion. This shape can be obtained using an approximation of the fractional Reynolds equations when the water interacts with the surface. A model is introduced for the Reynolds stresses complemented with a closure relation of fractional origin. A power type solution is obtained for the main velocity and stress. Velocity profile is found based on the assumption of a steady flow and the energy conservation equation. A Froude number and the cubic equation of the weir are built. The dimensionless upstream velocity head is also determined which allow graphically showing the exponent and coefficient of the water-profile over an ogee-shaped crest. It is possible to estimate the occupied-space index trough an exponents＇ ratio of profile over the velocity head.

Constructing confidence intervals of extreme rainfall quantiles using Bayesian,bootstrap,and profile likelihood approaches

Hydrological risk is highly dependent on the occurrence of extreme rainfalls.This fact has led to a wide range of studies on the estimation and uncertainty analysis of the extremes.In most cases,confidence intervals(CIs)are constructed to represent the uncertainty of the estimates.Since the accuracy of CIs depends on the asymptotic normality of the data and is questionable with limited observations in practice,a Bayesian highest posterior density(HPD)interval,bootstrap percentile interval,and profile likelihood(PL)interval have been introduced to analyze the uncertainty that does not depend on the normality assumption.However,comparison studies to investigate their performances in terms of the accuracy and uncertainty of the estimates are scarce.In addition,the strengths,weakness,and conditions necessary for performing each method also must be investigated.Accordingly,in this study,test experiments with simulations from varying parent distributions and different sample sizes were conducted.Then,applications to the annual maximum rainfall(AMR)time series data in South Korea were performed.Five districts with 38-year(1973–2010)AMR observations were fitted by the three aforementioned methods in the application.From both the experimental and application results,the Bayesian method is found to provide the lowest uncertainty of the design level while the PL estimates generally have the highest accuracy but also the largest uncertainty.The bootstrap estimates are usually inferior to the other two methods,but can perform adequately when the distribution model is not heavy-tailed and the sample size is large.The distribution tail behavior and the sample size are clearly found to affect the estimation accuracy and uncertainty.This study presents a comparative result,which can help researchers make decisions in the context of assessing extreme rainfall uncertainties.

Application of profile likelihood function to the uncertainty analysis of hydrometeorological extreme inference

Profile likelihood function is introduced to analyze the uncertainty of hydrometeorological extreme inference and the theory of estimating confidence intervals of the key parameters and quantiles of extreme value distribution by profile likelihood function is described.GEV(generalized extreme value)distribution and GP(generalized Pareto)distribution are used respectively to fit the annual maximum daily flood discharge sample of the Yichang station in the Yangtze River and the daily rainfall sample in10 big cities including Guangzhou.The parameters of the models are estimated by maximum likelihood method and the fitting results are tested by probability plot,quantile plot,return level plot and density plot.The return levels and confidence intervals of flood and rainstorm in different return periods are calculated by profile likelihood function.The results show that the asymmetry of the profile likelihood function curve increases with the return period,which can reflect the effect of the length of sample series and return periods on confidence interval.As an effective tool for estimating confidence interval of the key parameters and quantiles of extreme value distribution,profile likelihood function can lead to a more accurate result and help to analyze the uncertainty of extreme values of hydrometeorology.