• 한국의류학회지
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• 제23권2호
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• pp.284-295
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• 1999

The purpose of this study was to investigate characteristics on Department stores consumers and to compare consumer characteristics among shopper types and department store types. For this purpose an ethnographic approach which is a kind of qualitative analysis was performed first. And then The data were collected from 600 female consumers over twenties and residing in Pusan Finally 499 data were used for the statistical analysis. 1. The results of clothing shopping orientations study were as follows : As a result of qualitative analysis those who patronize department stores were recreational/convenience shoppers. From quantitative analysis clothing shopping orientations were factor analyzed. which resulted in eight factors ; Recreational Shopping Convenience Shopping. Sensibility Seeking Well-Known Brand Preference Fashion Seeking Economic Shopping Sel-confidence in clothing shopping Convenient store shopping. 2. The results of store choice criteria study were as follows: As a result of concentrative observation eight store choice criteria dimensions were categorized : Service Store Atmosphere Promotion/Facilities Product Convenience Advertisement VMD Traffic/Location Convenience. From quantitative analysis eight store choice criteria factors emerged; Service Store Atmosphere Promotion/Facilities Assortment Shopping Convenience Advertisement VMD Traffic/Location Convenience. 3. According to the factor scores of recreational shopping and Convenience shopping consumers were segmented into four shopper types ; High Shopping-involved Shopper Recreational Shopper Convenience Shopper and Low Shopping-involved Shopper. Department types were divided into a large enterprise department stores and local department stores. Consumer characteristics such as clothing shopping orientations store choice criteria purchase behavior variables and demographic variables were significantly different in shopper types and department store types were significantly different in clothing shopping orientations and tore choice criteria.

• 한국해양학회지:바다
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• 제26권1호
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• pp.1-10
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• 2021

최근 10년(2009년~2018년)간의 해수범람 기록정보와 해양 및 해양기상 관측정보를 수집하고 기계학습 알고리즘을 3종을 종합·활용해 해수범람 유형과 유형별 관측정보의 특징을 분류하였다. 해수범람의 기록정보는 국립해양조사원의 침수조사 보고서와 국토정보공사의 침수흔적도를 통해 수집하였으며 해양 및 해양기상관측 정보는 국립해양조사원과 기상청의 부이, 관측소 정보를 수집하였다. 해수범람 발생 유형 분류는 크게 4개의 유형으로 분류되며 4개의 유형의 조합을 통해 5개의 발생 유형으로 분류하였다. 이 유형은 해양기상 환경에 따라 해수범람의 발생 유형을 구분할 수 있었다. 유형별 주요 특징은 대조기, 저기압, 강풍, 태풍으로 구분되었다. 또한, 지리적인 해양특성을 고려하여 지역 및 유형별 해수범람 발생 판단을 위한 해양요소 임계치를 도출하였다.

• 응용통계연구
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• 제28권6호
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• pp.1147-1161
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• 2015

오늘날 데이터는 p-차원의 공간에서 점들로써 표현되는 전통적인 형태를 벗어나 시그널(signal), 함수, 이미지(image), 모양(shape) 등과 같은 다양한 형태의 자료들이 데이터로써 고려되고 분석되고있다. 그러한 종류의 새로운 종류의 데이터 중 하나로 심볼릭 데이터(symbolic data)를 고려할 수 있다. 심볼릭 데이터는 구간(interval), 히스토그램(histogram), 목록(list), 통계표, 분포, 또는 모형 등과 같은 다양한 형태들을 가질 수 있다. 지금까지의 연구가 주로 심볼릭 데이터의 각각의 형태별 자료를 고려했다면, 본 연구에서는 이를 확장하여 수집된 히스토그램과 멀티모달의 혼합된 형태로 이루어진 자료에 대한 계층 분할적 군집분석방법을 소개하고 이를 업종별 산업재해자료의 분석을 위해 이용한다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권1호
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• pp.55-60
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• 2020

Adaptive recommendation systems have been developed with big data processing as a system that provides services tailored to users based on user information and usage patterns. Deep learning can be used in these adaptive recommendation systems to handle big data, providing more efficient user-friendly recommendation services. In this paper, we propose a system that uses deep learning to categorize and recommend tourism types to suit the user's personality. The system was divided into three layers according to its core role to increase efficiency and facilitate maintenance. Each layer consists of the Service Provisioning Layer that real users encounter, the Recommendation Service Layer, which provides recommended services based on user information entered, and the Adaptive Definition Layer, which learns the types of tourism suitable for personality types. The proposed system is highly scalable because it provides services using deep learning, and the adaptive recommendation system connects the user's personality type and tourism type to deliver the data to the user in a flexible manner.

• 한국정밀공학회지
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• 제21권12호
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• pp.100-108
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• 2004

In reverse engineering, data acquisition methodology can generally be categorized into contacting and non-contacting types. Recently, researches on hybrid or sensor fusion of the two types have been increasing. In addition, efficient construction of a geometric model from the measurement data is required, where considerable amount of user interaction to classify and localize regions of interest is inevitable. Our research focuses on the classification of each bounded region into a pre-defined feature shape fer a hybrid measuring scheme, where the overall procedures are described as fellows. Firstly, the physical model is digitized by a non-contacting laser scanner which rapidly provides cloud-of-points data. Secondly, the overall digitized data are approximated to a z-map model. Each bounding curve of a region of interest (featured area) can be 1.aced out based on our previous research. Then each confined area is systematically classified into one of the pre-defined feature types such as floor, wall, strip or volume, followed by a more accurate measuring step via a contacting probe. Assigned to each feature is a specific digitizing path topology which may reflect its own geometric character. The research can play an important role in minimizing user interaction at the stage of digitizing path planning.

• 패션비즈니스
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• 제24권6호
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• pp.120-134
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• 2020

Recently, the beauty industry has implemented personalized services based on skin big data. To increase competitiveness in the beauty industry, systematic data measurement and evaluation indicators are necessary to select data and obtain necessary knowledge. In response, this study sought to stably enhance the accuracy of skin diagnosis based on satisfaction and reliability. To this end, the research was conducted through focus group interviews (FGI), a case study of brands, and analysis of prior research results. In particular, as a result of analyzing keywords that classify skin types by brand, common survey items for skin types were oiliness and using moisturizer, cosmetic use and vascular of skin, external stimulus and blemish & freckles, facial wrinkle, outside activities, self-consciousness, and smoke. In additioin to the common questions of the preceding study and the brand survey items, the questions concerning complex skin types, seasonal change, facial color, wrinkles and elasticity were added, and the questions were presented in a total of 40 items. In particular, it suggested that skin measurement could be conducted by focusing on elasticity and pigmentation items by reflecting the results of prior research and the opinions of FGI, and based on this, a customized service with high satisfaction and high accuracy of beauty care based on this could be proposed. We hope that this study will facilitate active self-care by providing more satisfying skin stones and personalized cosmetics proposals, thus laying the foundation for the further development of the cosmetics industry.

• 로봇학회논문지
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• 제7권3호
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• pp.171-181
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• 2012

Outdoor mobile robots are faced with various terrain types having different characteristics. To run safely and carry out the mission, mobile robot should recognize terrain types, physical and geometric characteristics and so on. It is essential to control appropriate motion for each terrain characteristics. One way to determine the terrain types is to use non-contact sensor data such as vision and laser sensor. Another way is to use contact sensor data such as slope of body, vibration and current of motor that are reaction data from the ground to the tire. In this paper, we presented experimental results on terrain classification using contact sensor data. We made a mobile robot for collecting contact sensor data and collected data from four terrains we chose for experimental terrains. Through analysis of the collecting data, we suggested a new method of terrain feature extraction considering physical characteristics and confirmed that the proposed method can classify the four terrains that we chose for experimental terrains. We can also be confirmed that terrain feature extraction method using Fast Fourier Transform (FFT) typically used in previous studies and the proposed method have similar classification performance through back propagation learning algorithm. However, both methods differ in the amount of data including terrain feature information. So we defined an index determined by the amount of terrain feature information and classification error rate. And the index can evaluate classification efficiency. We compared the results of each method through the index. The comparison showed that our method is more efficient than the existing method.

• 경영과학
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• 제20권2호
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• pp.1-16
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• 2003

Previous research on data extraction and integration for data warehousing has concentrated mainly on the relational DBMS or partly on the object-oriented DBMS. Mostly, it describes issues related with the change data (deltas) capture and the incremental update by using the triggering technique of active database systems. But, little attention has been paid to data extraction approaches from other types of source systems like hierarchical DBMS, etc. and from source systems without triggering capability. This paper argues, from the practical point of view, that we need to consider not only the types of information sources and capabilities of ETT tools but also other factors of source systems such as operational characteristics (i.e., whether they support DBMS log, user log or no log, timestamp), and DBMS characteristics (i.e., whether they have the triggering capability or not, etc), in order to find out appropriate data extraction techniques that could be applied to different source systems. Having applied several different data extraction techniques (e.g., DBMS log, user log, triggering, timestamp-based extraction, file comparison) to S bank's source systems (e.g., IMS, DB2, ORACLE, and SAM file), we discovered that data extraction techniques available in a commercial ETT tool do not completely support data extraction from the DBMS log of IMS system. For such IMS systems, a new date extraction technique is proposed which first creates Index database and then updates the data warehouse using the Index database. We illustrates this technique using an example application.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.435-438
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• 2001

Reverse engineering technology refers to the process that creates a CAD model of an existing part using measuring devices. Recently, non-contact scanning devices have become more accurate and the speed of data acquisition has increased drastically. However, they generate thousands of points per second and various types of point data. Therefore, it becomes a major issue to handle the huge amount and various types of point data. To generate a CAD model from scanned point data efficiently, these point data should be well arranged through point data handling processes such as data reduction and segmentation. This paper proposes a new point data handling method using 3D grids. The geometric information of a part is extracted from point cloud data by estimating normal values of the points. The non-uniform 3D grids for data reduction and segmentation are generated based on the geometric information. Through these data reduction and segmentation processes, it is possible to create CAD models autmatically and efficiently. The proposed method is applied to two quardric medels and the results are discussed.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1251-1259
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• 2006

The headline of advertisements holds the important position in advertisement recognition and receptivity. The mobile advertisements show an immediate reaction of customers because it is possible to do 'one-to-one communication'. And this makes the mobile advertisement as important as any kind of traditional marketing channel, like TV, Radio, Print. In this paper, we classified the headlines as several types and measured the effect of headline types.