Earticle

본 연구는 외국의 방과후 돌봄 서비스를 국가별로 유형화하여 그 특성을 파악하고, 이를 바탕으로 우리나라 방과후 돌봄 서비스 정책에 시사점을 제공하고자 하였다. 이를 위해 돌봄서비스 주 이용자인 부모와 아동의 노동권과 아동권 보장에 대한 국가의 지원 수준을 기반으로 퍼지셋 이상형 분석을 활용하여 8개국을 대상으로 유형화를 시도하였고, 결과적으로 3가지 서비스 유형(부모⋅아동 권리지원형, 아동권 지원형, 권리 미지원형)이 도출되었다. 추가적으로 이러한 3가지 국가유형에 따른 사회적 성과(35세-44세 여성의 경제활동 참가율, 아동 빈곤율)를살펴본 결과, 부모⋅아동 권리지원형 국가군에서 사회적 성과가 가장 높은 것으로 나타났다. 이상의 연구결과를 바탕으로 한국의 방과후 돌봄 서비스의 방향성에 대한 정책적 시사점을 제시하였다.

This study aims to identify various types of after-school care services and draw implications for the direction of Korean out-of-school care policy. For this, two indicators were selected: the level of state support for the guarantee of parents’ right to work and of child’s right, which are the main goals of care policies. The fuzzy set ideal analysis method was used. As a result of categorization, 8 countries were classified into three types (parent and child rights support type, child rights support type, and rights not supported type). In addition, as a result of examining the social performance according to these three types of countries (35-44-year-old women’s participation in economic activities, child poverty rate), social performance was the highest in the ‘parent and child rights support type countries’. Based on the above research results, policy implications for the direction of after-school care services in Korea were presented.

특징 혹은 차원 자극벌(Garner, 1978)이 복합 자극의 전역 혹은 국지 수준으로의 주의 전환 양상에 미치는 영향을 조사하기 위해 두 실험이 수행되었다. 실험 1에서, 시행간에 걸쳐 주의 받은 수준의 전환에 대한 분석은 특징 자극벌에서는 수준 전환 효과를 보였으나, 차원 자극벌에서는 그런 효과를 발견하지 못하였다. 실험 2에서, 복합 자극의 두 수준의 정체를 순차적으로 제시함으로써 수준간 주의 전환이 강제되었다. 특징 자극벌에서 국지 수준으로의 주의 전환이 전역 수준으로의 주의 전환보다 더 쉬웠다. 그러나, 차원 자극벌에서는 전역 수준으로의 전환이 국지 수준으로의 전환보다 더 쉬웠으며, 각 수준에 대한 주의가 신속하고 안정적인 것으로 보였다. 이 결과는, 전역 수준의 주의 및 지각이 선행함을 주장하는, 전역 선행성(Navon, 1977)이 일반적 규칙이 아니며 자극 구조가 선행성 연구에서 중요한 요인으로 고려되어야 함을 시사한다. 수준 준비성 효과(Ward, 1982) 및 공간 주의 전환의 단계들(Posner, 1988)이 종합논의에서 고찰되었다.

Two experiments examined the effect of stimulus set, feature or dimension (Garner, 1978), on modes of attention shift to global and local level of a compound stimulus. In Experiment 1, an analysis of inter-trial transitions of attended levels showed a level shift effect in the feature set compared to no such effect in the dimension set. In Experiment 2, attention shift between levels of the compound stimulus was forced by presenting identities of the two levels in sequence. Attention shift to the local was easier in the feature set than that to the global. In the dimension set, however, shift to the global was easier than shift to the local, and giving attention to either level appeared to be fast and stable. These results imply global precedence (Navon, 1977) is not a general rule and stimulus structure should be considered as an important factor in the study of precedence. The level?readiness effect (Ward, 1982) and the stages of spatial attention shift (Posner, 1988) were considered in the general discussion.

In the unconstrained environment for video tracking is essential for many applications, such as video surveillance, man-machine interaction. In fact, moving object in the sequences generally has the context information of others or the different moments of its own state. Our research focus on the complex scenes, tracking multiple articulated targets, obtaining the features of the target, getting the precise target segmentation and improving the accuracy and reliability of tracking. We propose using top-down segmentation to feedback object detection, also contains the shape information. And the local appearance information is embedded into the framework of the level set. Then we propose a method to solve the interference of similar appearance target and multi-target tracking, by using context information to create two auxiliary items: Misleading items and support items. Both of them are using continuous random ferns. We experimentally evaluate our proposed approach on challenging sequences and video in real-world demonstrate its good performance in practice.

Level set methods have been widely used in image processing specially in image segmentation. This paper presents a new region based active contour model in a variational level set formulation for segmentation of real world images in the presence of intensity in-homogeneity and noise. In this paper, we derive a local intensity clustering property in the image domain with better distance regularization function. The level set methods sometimes develop irregularities during its evolution state, which may cause numerical complexity and destroy the stability of evolution. This distance regularization function is able to maintain the desired shape of level set function smoothly and eliminates the need of re-initialization of LSF. The local clustering criterion function is defined for image intensities in neighborhood of each point. Now, this local clustering criterion of point is then integrated with respect to the neighborhood of entire points for global clustering criterion of image segmentation. In which bias function is also evaluated to intensity inhomogeneity correction. Implementation of our method shows that, it is more robust to initialization, and more accurate than conventional model.

A Level Set Evolution with Morphology (LSEM) based segmentation algorithm is proposed in this work to segment all the possible lung nodules from a series of CT scan images. All the segmented nodule candidates were not cancerous in nature. Initially the vessels and calcifications were also segmented as nodule candidates. The structural feature analysis was carried out to remove the vessels. The nodules with more centroid shift in the consecutive slices were eliminated since malignant nodule’s resultant position did not usually deviate. The calcifications were eliminated by frequency domain analysis. DC constant of nodule candidates were computed in frequency domain. The nodule candidates with high DC constant value could be the calcifications as the calcification patterns were homogeneous in nature. This algorithm was applied on a database of 40 patient cases with 58 malignant nodules. The algorithms proposed in this paper precisely detected 55 malignant nodules and failed to detect 3 with a sensitivity of 95%. Further, this algorithm correctly eliminated 778 tissue clusters that were initially segmented as nodules, however, 79 non-malignant tissue clusters were detected as malignant nodules. Therefore, the false positive of this algorithm was 1.98 per patient.

The image segmentation result based on level set typically depends on the appropriate manual initial contour. In this paper, we introduce an autonomous approach for deciding the initial level set contour to be close to the actual boundary as far as possible, and the decided initial contour can be directly evolved by various level set methods. Such an improvement can speed up the evolution and lead to a more robust segmentation result. Then, we consider the statistical information of three distinct regions to construct a new level set model, including contour, contour inside and outside. Combining the two steps above is helpful to obtain a pretty ideal segmentation effect. Some remarkable results and shorter execution time for some difficult segmentation tasks shown in this paper demonstrate the potential of our innovative approach.

Region-based level set segmentation is a paradigm for the automatic segmentation of brain tumor image. Unfortunately, region-based segmentation, which is relied on the intensity difference of different regions, has been of limited used in presence of complex background. In fact, the evoluting curve may leak out the boundary of tumor to reach a steady state by the global region force. In this work, we propose a new hybrid approach for brain tumor segmentation, which is relied on the approach of global intensity difference, local edge properties, curve evolution, and level set method. The regional information drives the contour to converge to the global minimum. By combining the edge information into the region-based framework, the images with intensity inhomogeneity and complex background can be efficiently segmented. To improve the accuracy of brain tumor segmentation, a skull-stripped method for brain images is proposed by utilizing the new morphological process. In addition, a penalizing energy is used for avoiding the time-consuming re-initialization step of the level set method. Finally, experiments are preformatted on some synthetic and real images. By visually assessments, results on patients demonstrate the new method can segment tumors with few iteration times. Moreover, comparisons with the most similar methods also show that the proposed method is effective for the segmentation of tumor in MR image.

The prior knowledge of face scale and shape are introduced into active contour model for face contour segmentation. Based on the variance of each column about image and the gradient of variance, the face outline size and central coordinates are obtained. The level set functions of the collected shapes are used as training data, which are projected onto a low dimension subspace. The attribute reduction of training set by PCA method is approximated Gaussian distribution. A constructed shape prior model with facial personality traits is incorporated into variational level set model based on boundary and region to constrain the contour evolution process, and then model can be accurately evolved into the face boundary. Experimental results validate the efficiency of this method.

Prostate segmentation from MRI is a necessary first step and plays a key role in different stages of clinical decision making process. In this paper, we propose a MR T1 Image segmentation method of the prostate based on distance regularized level set evolution with a deformable shape prior. To smooth the prostate image to reduce the noise, we introduce a prostate image with Gaussian kernel and get an edge indicator. To avoid the leakage induced on account of prostate boundaries missing, or blending with surrounding tissues, we introduce priori shape information to construct an energy function with a distance regularization term and an external shape energy term containing the edge indicator and minimize it by solving the gradient flow which can be implemented with a finite difference scheme. To verify the MRI segmentation method of a prostate presented in this paper, we utilize the optimal value of parameters λ, μ, α and ε in the distance regularized level set evolution model and the deformable shape prior of prostate to segment a part of images from normal prostate, benign hyperplasia prostate and cancer prostate. The experiment results show that the MRI segmentation method of prostate presented in this paper is effective for different situation of different patients.

Prostate segmentation from MRI is a necessary first step and plays an important role in clinical decision making process. A MR T1 Image segmentation method of the prostate based on distance regularized level set evolution (DRLSE) is proposed. To smooth the prostate image to reduce the noise, a preprocessed prostate image with Gaussian kernel and get an edge indicator is convolved. We construct an energy function with a distance regularization term and an external energy term containing the edge indicator and minimize it by solving the gradient flow which can be implemented with a finite difference scheme. In segmentation experiments, the impact of parameters λ , μ , α and ε in DRLSE model on the image segmentation is analyzed, and an optimal value of these parameters is given. The experiment results confirm the effectiveness of the MRI segmentation method of prostate for different situation of different patients.

This paper aims to analyze the relationships between early childhood education policies of 14 OECD countries and their national happiness level, using fuzzy set qualitative comparative analysis method. The variables employed for this comparative study are GDP per capita, enrollment rate in early childhood education, amount of public budget per infant, ratio of total public fund for infants as percentage of total national budget, and national happiness level. The method used in this study is fuzzy set qualitative comparative analysis by which the complexity of data sets regarding infant policy can be reduced and minimized. The analysis results show that there are four combinations of causal conditions in supporting high national happiness level and two combinations in supporting low national happiness level. It is important to point out that the approach employed in this study offers a new way to conduct comparative analysis of infant education statistics. Finally, this study puts forward policy implications to strengthen infant welfare policies in Korea, based on the comparative analysis of OECD statistics on early childhood.

This paper presents a topological shape optimization for electromagnetic system using a level set method. The optimization is progressed by updating the implicit level set function from the Hamilton-Jacobi equation. The up-wind scheme is used for numerical implementation of the Hamilton-Jacobi equation. In order to validate the proposed optimization, the core part of a C-core actuator is optimized by three cases using different materials; (single steel), (two steels), and (steel and magnet).

A prediction of binary droplets collision is important in the formation of falling drops and the evolution of sprays. The droplet velocity, impact parameter and drop-size ratio have influence on the interaction of the droplets. By the effect of these parameter, the collision processes are generated with the complicated phenomena. The droplet collision can be classified into four interactions such as the bouncing, coalescence, reflexive separation and stretching separation. In this study, the two-phase flow of the droplet collision was simulated numerically by using the Level Set method. 2D axi-symmetric simulations on the head-on collisions in the coalescence and reflexive separation, and 3D simulation on the off-center collisions in the coalescence and stretching separation were performed. These numerical results showed good agreements with the experimental and analytical results. For tracking the identity of droplets after the collision, transport equation for the volume fraction of the each initial droplet were used. From this, the identities of droplets were analyzed on the collision of droplets having different size.

Numerical simulations for dendritic growth of crystals are conducted in this study by the level set method. The effect of order of difference is tested for reinitialization error in simple problems and authors founded in case of 1st order of difference that very fine grids have to be used to minimize the error and higher order of difference is desirable to minimize the reinitialization error The 2nd and 4th order Runge-Kutta scheme in time and 3rd and 5th order of WENO schemes with Godunov scheme are applied for space discretization. Numerical results are compared with the analytical theory, phase-field method and other researcher's level set method.

Level Set방법을 사용하여 액체와 기체의 서로 다른 상을 함께 해석하는 연구를 수행하였다. Level Set함수는 상의 경계면에서부터 부호를 갖는 거리함수로 정의되며,계산 격자에서 함수 값의 부호에 따라 각 상을 구분하고 물성치를 부여한다. 본 논문에서는 비압축성 유체의 보존식에 Level Set함수의 이동식을 연계하여 이상유동을 모사하는 지배방정식을 구성하였으며, 이를 pseudo-compressibility 방법으로 함께 풀었다. 이 때 다양한 문제에 적용이 가능하도록 일반 곡선 좌표계에서 식을 유도하였고, 수치해석을 위한 행렬식들을 함께 유도하였다. 개발된 해석 코드를 표면장력이 있는 기포 동역학 문제와 수중익에 의한 파도 발생 문제에 적용하여 타당한 결과를 얻을 수 있었다.

In order to analyze incompressible two-phase flow, Level Set method was applied on pseudo-compressibility formulation. Level Set function is defined as a signed distance function from the phase interface, and gives the information of the each phase location and the geometric data to the flow. In this study, Level Set function transport equation was coupled with flow conservation equations, and owing to pseudo-compressibility technique we could solve the resultant vector equation iteratively. Two-phase flow analysis code was developed on general curvilinear coordinate, and numerical tests of bubble dynamics and surging wave problems demonstrate its capability successfully.

Partial quenching structure of turbulent diffusion flames in a turbulent mixing layer is investigated by the method of flame hole dynamics to develope a prediction model for the turbulent lift off. The present study is specifically aimed to remedy the problem of the stiff transition of the conditioned partial burning probability across the crossover condition by adopting level-set method which describes propagating or retreating flame front with specified propagation speed. In light of the level-set simulations with two model problems for the propagation speed, the stabilizing conditions for a turbulent lifted flame are suggested. The flame hole dynamics combined with level-set method yields a temporally evolving turbulent extinction process and its partial quenching characteristics is compared with the results of the previous model employing the flame-hole random walk mapping. The probability to encounter reacting' state, conditioned with scalar dissipation rate, demonstrated that the conditional probability has a rather gradual transition across the crossover scalar dissipation rate in contrast to the stiff transition of resulted from the flame-hole random walk mapping and could be attributed to the finite response of the flame edge propagation.

Partial quenching structure of diffusion flames in a turbulent mixing layer has been investigated by the method of flame hole dynamics in oder to develope a prediction model for the phenomenon of turbulent flame lift off. The present study is specifically aimed to remedy the shortcoming of the stiff transition of the conditioned partial burning probability across the crossover condition by employing the level-set method which enables us to include the effect of finite flame edge propagation speed. In light of the level-set simulation results with two models for the edge propagation speed, the stabilizing conditions for turbulent lifted flame are suggested. The flame hole dynamics combined with the level-set method yields a temporally evolving turbulent extinction process and its partial quenching characteristics is compared with the results of the previous model employing the flame-hole random walk mapping based on three critical scalar dissipation rates. The probability to encounter reacting state, conditioned with scalar dissipation rate, demonstrated that the conditional probability has a rather gradual transition across the crossover scalar dissipation rate. Such a smooth transition is attributed to the finite response of the flame edge propagation.