• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.117-127
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• 2020

Recently, proving insurance fraud has become increasingly difficult because it occurs intentionally and secretly via organized and intelligent conspiracy by specialists such as medical personnel, maintenance companies, insurance planners, and insurance subscribers. In the case of car accidents, it is difficult to prove intentions; in particular, an insurance company with no investigation rights has practical limitations in proving the suspicions. This paper aims reveal that the detection of organized and conspired insurance fraud, which had previously been difficult, could be dramatically improved through conspiring insurance fraud detection modeling using social network analysis and visualization of the relation between suspected group entities and by seeking developmental research possibilities of data analysis techniques.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.306-312
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• 2008

In a goal-oriented dialogue, speaker's intention can be approximated by a semantic structure that consists of a pair of a speech act and a concept sequence. Therefore, it is very important to correctly identify the semantic structure of an utterance for implementing an intelligent dialogue system. In this paper, we propose a model to efficiently analyze the semantic structures based on an active teaming method. To reduce the burdens of high-level linguistic analysis, the proposed model only uses morphological features and previous semantic structures as input features. To improve the precisions of semantic structure analysis, the proposed model adopts CRFs(Conditional Random Fields), which show high performances in natural language processing, as an underlying statistical model. In the experiments in a schedule arrangement domain, we found that the proposed model shows similar performances(92.4% in speech act analysis and 89.8% in concept sequence analysis) to the previous models although it uses about a third of training data.

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.3
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• pp.447-458
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• 1999

The purpose of this study was to analyze jeans market faced with economic difficulties to provide jean's maker with a large representative data base for jeans marketing strategy. This study surveyed jeans market and analyzed brand awareness. brand image and consumer's seeking image for 700 young adults. The 700 questionnaires were distributed at the five locations(Opkujung Shinchon Munjungdong, Shinrimdong '||'&'||' Suwon) and 656 reliable ones were used for statistical analysis. A. SAS statistical package including frequency table factor analysis. analysis of variance. and Duncan's multiple range test was used. The results are as follows : 1. Brand awareness involves "brand recall" based on asking a person to name recalled first and "brand rcognition" based on asking to identify brand name from 30 given brands. The result indicated that "Levis" was dominant for brand recall and Guess was dominant for brand recognition. 2. Regarding the brand image the result showed that "Vov" was best represented for sophisticated '||'&'||' trendy brand images "Storm" for characteristics brand image "Jambangee" for reasonable price '||'&'||' comfortable brand images and "Levis" for classic '||'&'||' design/color brand images. 3. As a result of factor analysis on consumer's seeking image six factors(characteristic/gay, intelligent/sexy, feminine/sophisticated , active/functional, cute/young, simple/comfortable) were found. Several factors had a relationship with demographic variables and preferred design. 4 Many young adults favored following design details ; low waist relaxed thigh with straight leg and long length up to the end of shoes. Also they preferred basic pocket to cargo pocket and simple logo accessories to metal ones.simple logo accessories to metal ones.

• Asian Journal of Atmospheric Environment
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• v.5 no.4
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• pp.228-236
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• 2011

Since most Green House Gases (GHGs) and air pollutants are generated from the same sources, it will be cost-effective to develop a GHGs reduction plan in combination with simultaneous removal of air pollutants. However, effects on air pollutants reduction according to implementing any GHG abatement plans have been rarely studied. Reflecting simultaneous removal of air pollutants along with the GHGs emission reduction, this study investigated relative cost effectiveness among GHGs reduction action plans in Busan Metropolitan City. We employed the Data Envelopment Analysis (DEA), a methodology that evaluates relative efficiency of decision-making units (DMUs) producing multiple outputs with multiple inputs, for the investigation. Assigning each GHGs reduction action plan to a DMU, implementation cost of each GHGs reduction action plan to an input, and reduction potential of GHGs and air pollutants by each GHGs reduction action plan to an output, we calculated efficiency scores for each GHGs reduction action plan. When the simultaneous removal of air pollutants with the GHGs reduction were considered, green house supply-insulation improvement and intelligent transportation system (ITS) projects had high efficiency scores for cost-positive action plans. For cost-negative action plans, green start network formation and running, and daily car use control program had high efficiency scores. When only the GHGs reduction was considered, project priority orders based on efficiency scores were somewhat different from those when both the removal of air pollutants and GHGs reduction were considered at the same time. The expected action plan priority difference is attributed to great difference of air pollutants reduction potential according to types of energy sources to be reduced.

• Journal of Korean Academy of Nursing
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• v.28 no.2
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• pp.510-518
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• 1998

It was assumed that the maternal identity in primi-gravida is one of the most attribute of the motherhood, that is not biological but cognitive phenomena, appears active process as intelligent human being. The purposes of this study were that the identification the cognitive structure and the influencing factors of the maternal identity in primi-gravida. Theoretical framework in this study, maternal identity in primi-gravida was constructed as a cognitive output, has the cognitive structure of cognitive-perceptual factor, cognitive-behavioral factor, and cognitive-emotional factor. Influencing factors of maternal identity was constructed as a cognitive input, which were pregnancy related perceptions (pregnancy intention, minor discomfort, value of motherhood), interpersonal relationship(relationship with mother, relationship with husband, relationship with social network), preparation to motherhood(maternal knowledge, antenatal self care), and biological factor (gestation period). This study was the descriptive correlational research design, was done from the 3rd January to the 15th March 1996, and the research subjects were selected conviniently 226 the primi-gravida during the gestation period, data collection method was self reported questionnaire cross-sectionally. Descriptive data analysis was done by SAS PC$^{+}$, testing the hypothetical model was done by covariance structural analysis using LISREL 8.03 program. The result of the hypothesis testing, the value of motherhood(y=.650, T=4.26) the maternal knowledge (y=.137, T=2.030), the gestation period( y=.113, T=2.621), showed significant causal effect on the maternal identity in primi-gravida. In conclusion, the maternal identity in primi-gravida had interrelated cognitive structure consist of perceptual, behavioral, and emotional factors. Significant causal factors influencing the maternal identity were value identified. It seems to contribute toward the understanding the characteristics of the maternal identity as a cognitive domains that has been regarded highly abstract concept, so has not been validated empirically.y.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1325-1334
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• 2016

The video incident detection System is a probe for rapid detecting the walker, falling, stopped, backwards, smoke situation in tunnel. Recently, the importance is increases from the downtown double deck tunnel in great depth underground space[1], but the legal basis is weak and the vulnerable situation experimental data. So, In this paper, we introduce a long-term log data analysis information in the tunnenl video incident detection system installed and experimental results in order to verify the feasibility of apply to video incident detection system for the double deck tunnel. It is proposed a few things about derives the problem of existing video incident detection system, improvements and reflect attributes for double deck tunnel. The contents described in this paper will contribute to refine the prototype of video incident detection system will apply to future double deck multi-layer tunnels.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.9
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• pp.808-815
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• 2005

A technical analysis was conducted to predict the development trends for heat pump system. This study was based on submitted patents from 1983 to 2002 in Korea, USA, and Japan. The total number of raw data from the registered database was 19,261 and the obtained data to be analyzed through the filtering process was 5,143. Japan's technical development for the heat pump system was more dominant than the other countries. Approximately $54\%$ of the total patents related with the heat pump system was registered by Japan. The number of patents for the heat pump system registered by Korea was very low in 1980's, but it increased rapidly in 1990's. As a result, the number of patents applied by Korea was $21\%$ of all patents. When the patent was categorized into compression, absorption/ad-sorption, and chemical type, the technology of compression type made up over $80\%$ in each country. Approximately $93\%$ of the patents surveyed in this study was developed for air or water source heat pumps because of easy applications compared with other heat sources. The $89\%$ of all patents was applied by companies when applicants were divided into three groups of company, individual, and the others (national institute, university, and so on).

• Journal of Biomedical Engineering Research
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• v.30 no.3
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• pp.213-220
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• 2009

In this study, we have developed a novel step detection algorithm for gait evaluation of patients with hemiplegia based on trunk accelerometry device. For this, we have used a bandpass filter and a least square acceleration (LSA) filter which is characterized by emphasizing the peak or valley point of the acceleration signals for each 3-axis accelerometer signals. To evaluate the algorithm, the detected steps by developed algorithm and real steps by the motion analysis system were compared. As a result, we could obtain the sensitivity of 96.44%, the specificity of 99.94% and the accuracy of 99.90% for the patients' data sets and the sensitivity of 100%, the specificity of 99.93% and the accuracy of 99.93% for the normal data sets. In conclusion, the developed algorithm is useful for the step detection for patients with hemiplegia as well as normal subjects.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.3-11
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• 2006

The need for edge detection about topography data from the high resolution satellite imagery is happening with increasing frequency according to many people utilize the its imagery as various fields recently. Many experts is recognizing of other GIS will make use of the road detection from the high resolution satellite imagery, including ITS (Intelligent Transportation Systems) and urban planning. This paper is comparative analysis of LPF (Low Pass Filtering) and HPF (High Pass Filtering) for roads edge detection from high resolution satellite imagery. As a result, LPF and HPF can be highlight selective pixels at edge area about input data. In case or applying to other techniques such as LPF for the same purpose, they aye more effective for wide road width which often cause the slight distortion of boundary or overall change of brightness values on the whole Image. Whereas, HPF has ability to enhance selectively detailed components in a target image.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.65-74
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• 2011

With the rapid development of cites, urban facilities have rapidly been increasing, and the task of managing them have also become complicated more and more. In this paper, we propose and design an intelligent context awareness system that effectively operates underground facilities in u-City. The suggested system consists of three major steps. The information acquisition step receives alarm information of sensors from the integrated platform. The analysis and inference step analyzes the alarm data and related information and infers the reason why the alarm happens. The information transmission step sends the final results of context awareness to the platform and other related modules. We produced some design products such as data flow diagram, function diagram, etc. We expect that the proposed context awareness system will be embedded in the integrated platform and used for an active management strategy of urban facilities.