The present study aims to analyze factors of brand equity in the retail stores in Vietnam; to recognize sub-dimensions connected with the forms of brand equity and thereby study the extent of the relationship among bases of market segmentation and brand equity. The present research made a collection of data by conducting a preliminary study. Responses were collected from the customers through a structured questionnaire to buy goods and services from the retail store in Vietnam. The sample size selected for the study was 196. The study applied various statistical tools, namely, Cronbach’s Alpha for reliability checking, correlation and regression statistics with the support of SPSS Software. The brand association is treated as a vital determinant of brand equity that significantly influences the bases of market segmentation. Further, the study also recognized the fact that the majority of consumers who prefer to buy from retail stores are young and in the age-group of 18-24 years. The present study made an initial attempt to study the relationship among bases of market segmentation with the factors related to brand equity; thereby to offer a novel conceptual framework designed for retail stores in Vietnam for brand positioning.

산업의 발달로 인한 생활습관과 신체활동 부족 등으로 한국인의 비만인구가 급증하고 있다. 전산화단층 영상을 이용한 기존의 지방량 계산 프로그램에서 반자동방식의 프로그램이 사용되고 있다. 관련 문제를 해결하기 위한 방법들이 제시되고 있으나 본 연구에서는 모폴로지 연산을 이용한 알고리즘을 제시하고 절차가 간단하고 비교적 계산량이 적은 새로운 방법으로 문제를 해결하고자 한다. 모폴로지 연산을 통해 침식과 팽창을 반복한 결과 영상으로부터 문제점이 해결된 것을 알 수 있어 결과로부터 각 조직 간의 경계를 더욱 정교하게 얻을 수 있었다. LoG (Laplace of Gaussian) 함수를 이용해서 각 조직간 경계 부분을 분할하였다. 각 경계는 명확하게 구분이 되었으며, 피하지방을 계산하기 위해 충분한 정보를 제공하였다. 개발된 분할결과를 사용하여 향후 자동 지방량 계산을 할 수 있다. 정확한 분할 도구를 제공함으로써 의사에게 편리함을 주고 재검사로 인한 피폭과 검사비용을 줄이는데 도움이 될 것으로 판단한다.

Pavement condition deteriorates due to various environmental issues. This can be seen on the pavement surface as a form of distress. A crack can be considered as a typical form of pavement distress in which it may reveal a critical condition of the road. Therefore, automatic and accurate detection of pavement crack and segmentation are crucial for pavement condition assessment and maintenance.

A robot usually adopts ANN (artificial neural network)-based object detection and instance segmentation algorithms to recognize objects but creating datasets for these algorithms requires high labeling costs because the dataset should be manually labeled. In order to lower the labeling cost, a new scheme is proposed that can automatically generate a training images and label them for specific objects. This scheme uses an instance segmentation algorithm trained to give the masks of unknown objects, so that they can be obtained in a simple environment. The RGB images of objects can be obtained by using these masks, and it is necessary to label the classes of objects through a human supervision. After obtaining object images, they are synthesized with various background images to create new images. Labeling the synthesized images is performed automatically using the masks and previously input object classes. In addition, human intervention is further reduced by using the robot arm to collect object images. The experiments show that the performance of instance segmentation trained through the proposed method is equivalent to that of the real dataset and that the time required to generate the dataset can be significantly reduced.

Purpose - This study surveys factors such as lifestyles, nutritional status, physical indicators, and physical fitness levels that affect the health of seniors over the age of 65 and based on the collected data attempts to create a senior health index model that provides health service information, help support seniors’ successful aging, and improve their quality of life. Research design, data, and methodology – This paper conducted the development for senior health index model and the cross validity verification to examine the status of senior health level, and aimed at setting the health status evaluation criteria. Seniors 384 usable data were analyzed. Results – As an attempt to segment the senior health service market, I divided the results of this study based on measurability, accessibility, disparity between groups, and the size of the potential client base. I divided the senior market into five subgroups: very healthy, healthy, normal, weak, and very weak. Conclusions - The findings of this study may prove useful in preparing for the forthcoming super-aged society through segmentation of the senior market, understanding differences between groups with different health conditions, and discovering effective marketing strategies that meet the demands of different senior groups.

Fruit trees are a key part of agriculture in rural areas and have recently been a part of ecotourism or agrotourism. This study analyzes user segmentation based on user motivation to determine characteristics of potential customers in fruit tree farms, and thereby develop fruit tree experience and educational programs. We conducted a survey of 253 potential customers of fruit tree experience programs in September 2017. Data were evaluated using factor and cluster analyses. The results of the cluster analysis identified four distinct segments based on potential customers' motivations, that is, activity-oriented, learning-oriented, leisure-oriented, and purchase-oriented. These clusters showed that significant differences in the preference of potential customers exist. Different markets were segmented based on the benefits sought by users. The segments’ characteristics were identified and activities relevant to each segment were proposed for rural tourism. Lastly, this study suggests directions for development of fruit tree farm experience and educational programs.

It is known that traffic volume, which is representative of live bridge, has a significant effect on service level (LOS: level of service) and structural displacement of bridge. In particular, if the traffic volume is distributed in the traffic congestion time zone on the toll road, it is possible to manage efficiently in terms of customer satisfaction and maintenance management operation such as improvement of service level and structural integrity. To do this, it is necessary to induce the distribution of traffic in the congestion time zone, and it is necessary to apply the differential pricing system such as the congestion charge and the difference of toll by time. In this study, we analyzed traffic aggregation by time zone for the subdivision and advancement of the Gwangan bridge uniform fare system.

청소기 제품을 구매하는데 중요한 요소는 디자인이다. 시각적인 매력과 흥미를 유발해야 관심을 끌게 되기 때문이다. 하지만 다양한 계층의 소비자를 하나의 디자인으로 대체할 수는 없다. 따라서, 많은 소비자에게 다양한 청소기 디자인제품을 제공하기 위하여 청소기 제품의 인식구조분석을 통한 청소기 시장의 세분화를 분석한다. 그리고 전략을 연구하여 소비자의 계층별 디자인 방향을 제안하는 것이 연구의 방향과 목적이다. 연구범위 및 방법은 우선 소비자의 다양한 계층에 따른 행 동 및 청소기 제품에 관한 환경을 연구한다. 제품 구매과정을 탐색하고 제품 보유 및 사용실태를 연구한다. 이에 따른 제품의 인식구조를 분석한다. 청소기에 대한 이미지와 청소기 제품의 속성 및 소비자의 지각을 분석하는 것이다. 따라서 시장의 세분화 전략을 세우는 것이다. 시장의 세분화 방법과 군집성향을 분석하여 연구한다. 청소기 디자인에 대한 인식구조를 통 한 소비자의 세분화 계층을 분석, 연구하여 디자인의 개선된 방향을 제안하는 것이다.

This paper proposes a convolutional neural network model for distinguishing areas occupied by obstacles from a LiDAR image converted from a 3D point cloud. The channels of a LiDAR image used as input consist of the distances to 3D points, the reflectivities of 3D points, and the heights of 3D points from the ground. The proposed model uses a LiDAR image as an input and outputs a result of a segmented LiDAR image. The proposed model adopts refinement modules with skip connections to segment a LiDAR image. The refinement modules with skip connections in the proposed model make it possible to construct a complex structure with a small number of parameters than a convolutional neural network model with a linear structure. Using the proposed model, it is possible to distinguish areas in a LiDAR image occupied by obstacles such as vehicles, pedestrians, and bicyclists. The proposed model can be applied to recognize surrounding obstacles and to search for safe paths.

본 논문에서는 구면 영상에서 영역 분할 정보를 사용하여 바닥 영역을 검출하는 방법을 제시 한다. 평면 영상에서의 Watershed 영역 분할 방법을 수정하여 구면 영상의 영역 분할에 적용할 수 있도록 하였다. 영역들을 분할한 뒤 가정된 바닥 영역 픽셀의 색상과 질감을 그 외의 영역 들과 비교하여 바닥 영역을 검출한다. 구면 파노라마 영상에서는 구면 왜곡으로 인하여 평면에 서의 바닥 검출 방법을 그대로 적용할 수 없다. 구면 왜곡을 고려한 바닥 영역 검출을 위하여 바닥 영역의 외곽선을 검출하는 알고리즘을 설계하였다. 실험에서 지상물이 없는 경우와 있는 경우의 모두에서 적절하게 바닥 영역을 검출할 수 있는 결과를 보였다.

This paper proposes a method to segment urban scenes semantically based on location prior information. Since major scene elements in urban environments such as roads, buildings, and vehicles are often located at specific locations, using the location prior information of these elements can improve the segmentation performance. The location priors are defined in special 2D coordinates, referred to as road-normal coordinates, which are perpendicular to the orientation of the road. With the help of depth information to each element, all the possible pixels in the image are projected into these coordinates and the learned prior information is applied to those pixels. The proposed location prior can be modeled by defining a unary potential of a conditional random field (CRF) as a sum of two sub-potentials: an appearance feature-based potential and a location potential. The proposed method was validated using publicly available KITTI dataset, which has urban images and corresponding 3D depth measurements.

We present a region-based approach for accurate pose estimation of small mechanical components. Our algorithm consists of two key phases: Multi-view object co-segmentation and pose estimation. In the first phase, we explain an automatic method to extract binary masks of a target object captured from multiple viewpoints. For initialization, we assume the target object is bounded by the convex volume of interest defined by a few user inputs. The co-segmented target object shares the same geometric representation in space, and has distinctive color models from those of the backgrounds. In the second phase, we retrieve a 3D model instance with correct upright orientation, and estimate a relative pose of the object observed from images. Our energy function, combining region and boundary terms for the proposed measures, maximizes the overlapping regions and boundaries between the multi-view co-segmentations and projected masks of the reference model. Based on high-quality co-segmentations consistent across all different viewpoints, our final results are accurate model indices and pose parameters of the extracted object. We demonstrate the effectiveness of the proposed method using various examples.

The role of rural towns as a leisure space has recently been increasing with changes in the consumption trends in domestic tourism. Based on the tourists visiting the town of Sunheul-ri, Jocheon-eup, a rural Village in Jeju Island, this study categorized the market according to the images formed by the tourists of rural towns, and analyzed the preferred mode of participation in rural field activities for each category. We analyzed the characteristic factors of the images of rural tourism formed by the tourists, extracted three factors for cluster analysis, and then formed three groups: “Group of Rural Experience Activity” “Group of Rural Environment and Service” and “Group of Rest in the Rural” After analyzing the preferred activity in each image-category group, we found no significant differences among the groups in ordinary activities such as viewing the scenery, experiencing and learning about the natural environment, and culinary experiences. However, there were significant differences among the groups regarding participation in experiential tour programs with the purpose of active tourism. The “Group of Rural Experience Activity” sought to actively participate in various activity programs, whereas the “Group of Rest in the Rural” comparatively had a weaker preference for such active programs. We thus learnt that tourists’ preferred activities are different according to the types of images formed by the tourists visiting rural towns. Therefore, to strengthen the competitive advantage of the rural tourist destinations of Jeju Island, it is necessary to provide various activity programs that are appropriate for the rural regions of Jeju and to accord with the expectations associated with each market segment category by positioning the programs according to the characteristics of the images held by the tourists.

일반적으로수위-유량관계곡선식은선형성과등분산성가정을기반으로구축되지만, 측정단면의형태, 단면상·하류의지형요인등으로 인하여 영향을 받기 때문에 실질적인 수위 및 유량의 관계는 관계식 구축에 이용되는 가정에 위배된다. 이로 인한 오차를 줄이기 위하여 곡선식을분할하여이용하고있으나, 측정단면의변화를 고려한관계자의주관적인판단이구간분할의주요근거로이용되고있다. 따라서 본연구에서는이러한주관성을배제하고관측데이터를기반으로객관화된분할근거를제시하고자한다. 곡선식의구간분할을위하여변동계수 를이용한기존의연구를바탕으로변동계수가정규분포를따르는것으로가정하여, 계산된변동계수가전단계에서계산된95%신뢰구간 이내에존재하지않는경우구간을분할하였다. 즉, 변동계수를이용하여집단간의특성을비교하였으며, 변동계수의분포를이용하여분할을 위한기준값을제시하였다. 방법론의추정능력검토를위하여가상의곡선으로부터생성된데이터에제안된방법론을적용하였고, 실제유역에 적용성 검토를 위하여 금강에 위치한 무주 및 산계교 수위관측소 지점에 적용하였다. 결과적으로 자동으로 분할된 관계곡선식을 사용하여 추정의정확도를높일수있을뿐만아니라외삽을하는경우역시그정확도를향상할수있음을확인하였다. 마지막으로실측값을활용한 수위-유량관계곡선식의구축시구간분할전·후의잔차데이터에대하여Shapiro-wilk 정규성검정을수행하였으며, 구간분할후잔차가 정규성을 갖게 되는 것으로 나타났다.

The purpose of this study is to segment foreign tourists who are visiting rural tourism village based on importance attributes of rural experiences tourism. From the literature review, rural experience tourism and its' importance attributes were discussed and these are, peculiar cultural experience, rural experience tourism price, food, natural scenery, accessibility, accommodation and convenient facility. On-site survey was conducted to collect the data from 8 rural tourism villages and a total of 258 useful samples were collected and analyzed. Frequent, cluster analysis, MDA, and MANOVA were performed to produce the results. The cluster analysis showed that three clusters solution was appropriate and named as moderated satisfaction group, high satisfaction group, and highly satisfaction group. The results of MANOVA showed that there were differences among the groups in terms of satisfaction and loyalty of rural experiences tourism. Theoretical and practical implications were discussed in the conclusion section.

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot’s surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.

This paper proposes a building recognition algorithm using watershed image segmentation algorithm and integrated region matching (IRM). To recognize a building, a preprocessing algorithm which is using Gaussian filter to remove noise and using canny edge extraction algorithm to extract edges is applied to input building image. First, images are segmented by watershed algorithm. Next, a region adjacency graph (RAG) based on the information of segmented regions is created. And then similar and small regions are merged. Second, a color distribution feature of each region is extracted. Finally, similar building images are obtained and ranked. The building recognition algorithm was evaluated by experiment. It is verified that the result from the proposed method is superior to color histogram matching based results.

본 논문에서는 동작인식 위한 정확한 배경 분할 및 특징점 추출 방법을 제안한다. 배경 분할 과정에서는 먼저, HSV 입력 이미지를 RGB 색상 공간에서 HSV 색상 공간으로 변환한 뒤, H와 S 값에 대한 두 개의 임계치를 사용하여 살색 영역을 분할, 프레임간의 차영상을 이용하여 움직임이 있는 영역을 추출한다. 차영상에서 발생하는 잔상 영역을 제거하기 위하여 헤시안 어파인 영역 검출기를 적용하고, 잡음이 제거된 차 영상과 살색 영역의 이진화 영상을 이용하여 사람의 동작이 나타나는 영역을 분할한다. 특징점 추출 과정은 전체 영상을 블록 단위로 나눠서 각 블록 안에서 분할된 영상에 포함되는 픽셀들의 중점을 구하여 특징점을 추출한다. 실험결과 복잡한 환경에서도 정확한 배경 분할과 사용자 동작을 대표하는 특징점 추출이 약 12 fps로 가능함을 알 수 있었다.

심근영상의 SPECT(Single Photon Emission Computed tomography)검사는 감마선을 방출하는 방사성의약품을 환 자에게 정맥주사한 후 이 의약품이 심장에 고루 퍼지면 관심부위를 촬영하여 질병으로 인한 변화를 컴퓨터를 이용하여 진단하는 검사법이다. 기능적인 정보를 담고 있는 심근관류 영상은 비침습적인 심근질환 검사에 유용한 방법이지만, 물리적 인자들에 의해 잡음과 낮은 해상도는 판도하는데 어려움을 주게 된다. 본 논문은 심근영상을 레벨 셋 알고리즘 을 이용하여 영상을 분할하고 분할된 영역을 3차원으로 구현하여 판독에 도움을 주는 방안을 제안하였다. 판독의 어려 움을 해결하기 위하여 레벨 셋을 이용하여 관심부위인 좌심실 영역을 분할하였고 분할된 영역을 3차원영상으로 모델 링하였다.