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制度:新 ; 報告番号:甲3395号 ; 学位の種類:博士(国際情報通信学) ; 授与年月日:2011/7/6 ; 早大学位記番号:新571

Stabilization for equal-order polygonal finite element method for high fluid velocity and pressure gradient

This paper presents an adapted stabilisation method for the equal-order mixed scheme of finite elements on convex polygonal meshes to analyse the high velocity and pressure gradient of incompressible fluid flows that are governed by Stokes equations system. This technique is constructed by a local pressure projection which is extremely simple, yet effective, to eliminate the poor or even non-convergence as well as the instability of equal-order mixed polygonal technique. In this research, some numerical examples of incompressible Stokes fluid flow that is coded and programmed by MATLAB will be presented to examine the effectiveness of the proposed stabilised method

Depth of powers of edge ideals of Cohen-Macaulay trees

Let $I$ be the edge ideal of a Cohen-Macaulay tree of dimension $d$ over a polynomial ring $S = \mathrm{k}[x_1,\ldots,x_{d},y_1,\ldots,y_d]$. We prove that for all $t \ge 1$, $$\operatorname{depth} (S/I^t) = \operatorname{max} \{d -t + 1, 1 \}.$

New records and morphological assessments of long-nosed fruit bats (chiroptera: pteropodidae: Macroglossus spp.) from Vietnam

Long-nosed fruit bat is a common name of the genus Macroglossus which comprises two species: Dagger-toothed long-nosed fruit bat (M. minimus) and Greater long-nosed fruit bat (M. sobrinus). These two species were rarely recorded from Vietnam or neighboring countries. Within Vietnam, M. minimus has been recorded only from two localities in southern Vietnam while M. sobrinus was known from all northern, central and southern regions of the country. Morphological features of these species in Vietnam were poorly documented in previous publications. With results from a rapid examination of all specimens and recently captured individuals, we here confirm that M. sobrinus is distinctively larger than M. minimus in all external and craniodental measurements. Two species are also distinguishable by their nostril shapes and mandible symphyses. This paper provides new distributional records of both M. sobrinus and M. minimus from Vietnam with remarks on their ecology and habitats.

Investigating the elements influencing the psychological issues of reform school students

Reformatory students are those whose deviant behaviors and habits prevent them from receiving education under normal educational conditions. These students frequently lead a careless, undisciplined lifestyle, being unwilling to work and learn eager to play and demanding. Therefore, when they are admitted to reformatories with severe study and lifestyle requirements, they have great psychological difficulty adjusting to their new environment. Students’ psychological issues in adapting to reformatory learning and living regimes are difficult and psychological deficits make it challenging for students to adapt to reformatory learning and living conditions. In Vietnam, 665 students from reformatory schools were polled to determine the causes of psychological issues. According to the findings, a variety of elements contribute to students’ psychological difficulties. Individual student conditions such as health, awareness, attitudes and actions as well as inappropriate habits, living without goals or aspirations, etc. are on the subjective side of the equation. On the objective side are the students’ conditions, family, education and psychological obstacles brought on by less-than-ideal circumstances which will make it more difficult for community students to adapt. Both the new school and society must pay more attention to reformatory students in order to establish the conditions necessary for successful integration into the new school and ultimate readmission into society for these students

ARSENIC REMOVAL FROM WATER BY CHEMICAL OXIDATION AND ADSORPTION ON IN-SITU FORMED FERRIC HYDROXIDE

Joint Research on Environmental Science and Technology for the Eart

Ensemble of deep learning models with surrogate-based optimization for medical image segmentation.

Deep Neural Networks (DNNs) have created a breakthrough in medical image analysis in recent years. Because clinical applications of automated medical analysis are required to be reliable, robust and accurate, it is necessary to devise effective DNNs based models for medical applications. In this paper, we propose an ensemble framework of DNNs for the problem of medical image segmentation with a note that combining multiple models can obtain better results compared to each constituent one. We introduce an effective combining strategy for individual segmentation models based on swarm intelligence, which is a family of optimization algorithms inspired by biological processes. The problem of expensive computational time of the optimizer during the objective function evaluation is relieved by using a surrogate-based method. We train a surrogate on the objective function information of some populations and then use it to predict the objective values of each candidate in the subsequent populations. Experiments run on a number of public datasets indicate that our framework achieves competitive results within reasonable computation time