• Culinary science and hospitality research
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• v.22 no.4
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• pp.114-127
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• 2016

The study, focused on social commerce food service consumers, attempted to test the relationship between perceived risk and price consciousness, and suggested that perceived risk and price consciousness, the the degree to which price is considered when purchasing goods, affect reuse intention. Through such test results, the study aimed to provide useful practical implications for establishing marketing strategies of companies related to food service social commerce, and those looking into behavioral intentions of social commerce using food service consumers. The subjects of the study were male and female residents of Korea over 2-years of age who have had some experience purchasing a dining out item through social commerce. The social commerce company selected for sampling was Coupang, which was the number 1 shopping App in 2014 based on the number of yearly visitors. A questionnaire-based survey was conducted on respondents who had indicated that they had experience purchasing foodservice goods through Coupang. The results revealed that source risk, privacy risk, psychological risk, and time-loss risk had negative influences on reuse intention. However, social risk and financial risk did not exhibit any influences. Price consciousness had positive influences on reuse intention. The study explored perceived risk and price consciousness as elements to affect continuous use of social commerce of foodservice consumers.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.23-31
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• 2009

Recently, biometric techniques such as face recognition, finger-print recognition and iris recognition have been widely applied for various applications including door access control, finance security and electric passport. This paper presents the method of using finger-vein pattern for the personal identification. In general, when the finger-vein image is acquired from the camera, various conditions such as the penetrating amount of the infrared light and the camera noise make the segmentation of the vein from the background difficult. This in turn affects the system performance of personal identification. To solve this problem, we propose the novel and fast method for extracting the finger-vein region. The proposed method has two advantages compared to the previous methods. One is that we adopt a locally adaptive thresholding method for the binarization of acquired finger-vein image. Another advantage is that the simple morphological opening and closing are used to remove the segmentation noise to finally obtain the finger-vein region from the skeletonization. Experimental results showed that our proposed method could quickly and exactly extract the finger-vein region without using various kinds of time-consuming filters for preprocessing.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.1-9
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• 2008

As the security requirements of mobile phones have been increasing, there have been extensive researches using one biometric feature (e.g., an iris, a fingerprint, or a face image) for authentication. Due to the limitation of uni-modal biometrics, we propose a method that combines face and iris images in order to improve accuracy in mobile environments. This paper presents four advantages and contributions over previous research. First, in order to capture both face and iris image at fast speed and simultaneously, we use a built-in conventional mega pixel camera in mobile phone, which is revised to capture the NIR (Near-InfraRed) face and iris image. Second, in order to increase the authentication accuracy of face and iris, we propose a score level fusion method based on SVM (Support Vector Machine). Third, to reduce the classification complexities of SVM and intra-variation of face and iris data, we normalize the input face and iris data, respectively. For face, a NIR illuminator and NIR passing filter on camera are used to reduce the illumination variance caused by environmental visible lighting and the consequent saturated region in face by the NIR illuminator is normalized by low processing logarithmic algorithm considering mobile phone. For iris, image transform into polar coordinate and iris code shifting are used for obtaining robust identification accuracy irrespective of image capturing condition. Fourth, to increase the processing speed on mobile phone, we use integer based face and iris authentication algorithms. Experimental results were tested with face and iris images by mega-pixel camera of mobile phone. It showed that the authentication accuracy using SVM was better than those of uni-modal (face or iris), SUM, MAX, NIN and weighted SUM rules.

• Vending industry
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• v.3 no.1 s.9
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• pp.64-69
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• 2004

고수익을 미끼로 한 자판기 분양사기가 최근 급증하고 있어 큰 문제가 되고 있다. 무조건 자판기 수익성만을 과대포장하여 투자자들의 `묻지마` 투자를 유도한 후 돈만 챙기고 사업에서 손을 떼어버리는 사기행각은 그 피해대상이 대부분 서민이라는 점에서 문제의 심각성을 더한다. 자판기가 불법 자금 모집을 통해 사기의 대상으로 외부 인식이 악화되어 버린다면 자판기 산업의 입지 역시 크게 좁혀 질 수 밖에 없다. 자판기 품목에 있어서는 불법자금모집의 대표적인 사례가 되는 경우는 확정수익을 보장한다며 투자자를 모집하는 경우이다. 그 후 일정기간동안 수익을 보장하며 투자자를 안심시킨 다음 일순간 돌변하여 자금을 챙겨 잠적을 하는 수순을 밝는다. 선의의 투자자들은 이럴 경우 엄청난 피해를 입게 되는 게 보통이다. 대개의 경우 기계 1~2대의 소량물량이 아닌 5대~l0대 단위의 투자를 유도하기 때문이다. 이제는 자판기 산업에 있어 이러한 악성 불법자금 모집업체들이 근절되어야 한다. 이 불법 사기행각의 대상이 더 이상 자판기 분야에 발을 붙이지 못하도록 하는 제도적 비책이 시급히 강구 되어야 한다. 이러한 가운데 금융감독원 비은행감독국 비제도금융조사팀에서는 올들어 지난 9월말까지 고수익을 미끼로 투자자금을 모집하다가 금감원에 적발된 유사 금융업체 85개사 명단을 사법당국에 통보했다. 불법자금모집 업체들이 투자자들을 유혹하기위해 미끼로 내세운 사업을 종류별로 보면 자판기, 게임기, 컴퓨터단말기 등 특정상품 운영권 제공이 29개사로 가장 많고, 사이버 쇼핑몰 및 인터넷사업(18개사), 납골당 등 부동산 투자(12개사), 영화등 문화 및 레저사업(10개사), 영화문화 및 레저산업(10개사), 벤처투자사(9개사) 등이었다. 자판기 분야에 있어서는 주로 성인용품자판기, 복권자판기 등의 품목이 불법자금 모집의 집중 타킷이 되었다. 금감원은 최근들어 유사 금융업체의 자금모집이 전문가도 속을 정도로 지능화하고 있다며 개인투자자들이 피해를 예방할 수 있는 불법업체 식별법을 금감원 인터넷 사이트(www.fss.or.kr)에 게시했다. 금감원은 특히 사업현황에 대해 지나치게 보안을 유지하는 업체, 1백$\%$이상의 터무니없는 고수익을 보장한다고 광고하는 업체, 제도권 금융회사의 지급보증을 강조하는 업체에 대해서는 투자에 앞서 금감원이나 업종 관련 정부당국에 사실여부를 확인해 보고 투자여부를 결정하라고 통보했다. 아울러 금감원은 금융소비자들이나 자판기 업계에서 불법자금 모집업체를 발견하여 전화(02-3786-8155~9)나 인터넷소비자 보호센터와 경찰에 신고해줄 것을 요청했다. 이제는 산업계도 더 이상 자판기 분야의 불법자금업체를 방치하지 말고 적극적인 금감원 신고를 통해 시장을 정화할 수 있게 해야 한다. 미꾸라지 한두마리가 온 개천 물 다 흐려놓는 이치처럼 자판기불법자금업체들로 인해 전체 산업에 미치는 영향이 실로 심각함을 인식해야 할 때이다. 금호 산업정보에서는 산업계에서 불법자금업체 근절에 많은 관심을 가질 수 있게 하기 위해 금융감독원 비은행감독국 비제도금융조사팀에서 배포한 $\ulcorner$불법자금 모집업체 고수익 보장 유혹에 주의$\lrcorner$ 에 대한 보도자료의 세부내용을 게재한다.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.10-18
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• 2011

Medical asset protection is important in each medical institution especially because of the law on private medical record protection and face recognition for this protection is one of the most interesting and challenging problems. In recognizing human faces, the distortion of face images can be caused by the change of pose, illumination, expressions and scale. It is difficult to recognize faces due to the locations of lights and the directions of lights. In order to overcome those problems, this paper presents an analysis of coefficients of Gabor wavelets, kernel decision, feature point, size of kernel, for face recognition in CCTV surveillance. The proposed method consists of analyses. The first analysis is to select of the kernel from images, the second is an coefficient analysis for kernel sizes and the last is the measure of changes in garbo kernel sizes according to the change of image sizes. Face recognitions are processed using the coefficients of experiment results and success rate is 97.3%. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the satisfaction and the quality of services will be improved in the face recognition area.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.1-12
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• 2021

With the recent 4th Industrial Revolution, the growth and value of big data are continuously increasing, and the government is also actively making efforts to open and utilize public data. However, the situation still does not reach the level of demand for public data use by citizens, At this point, it is necessary to identify research trends in the public data field and seek directions for development. In this study, in order to understand the research trends related to public data, the analysis was performed using topic modeling, which is mainly used in text mining techniques. To this end, we collected papers containing keywords of 'Public data' among domestic and foreign research papers (1,437 domestically, 9,607 overseas) and performed topic modeling based on the LDA algorithm, and compared domestic and foreign public data research trends. After analysis, policy implications were presented. Looking at the time series by topic, research in the fields of 'personal information protection', 'public data management', and 'urban environment' has increased in Korea. Overseas, it was confirmed that research in the fields of 'urban policy', 'cell biology', 'deep learning', and 'cloud·security' is active.

• Informatization Policy
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• v.28 no.1
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• pp.22-42
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• 2021

The purpose of this study is to investigate the effects of privacy concerns on the use of mobile payment services. In particular, paying attention to the multidimensionality of consumer innovation, we analyzed the effects of hierarchical logistic regression by gender. The results show that there is a positive (+) relationship for hedonic innovativeness regardless of gender, and that there is a negative (-) relationship for functional innovativeness overall and in the female group. In all groups regardless of gender, a positive (+) relationship was found for the hedonic innovativeness, and one negative (-) relationship was found in the functional innovativeness overall group and the female group. Second, in the male group, there is a moderating effect of privacy concerns and functional innovativeness. This suggests that the relationship between privacy concerns and the usage of mobile payment services may vary depending on functional innovativeness. This study is useful in that it can explain and predict consumers' patterns of use of new technology-based services in various and balanced ways by taking privacy concerns and multidimensional consumer innovation into consideration. In addition, it suggests that mobile payment companies should make efforts to ensure that their services are secure, useful, and fun to use so that consumers can feel confident using the services in various situations.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.81-88
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• 2022

This study is to investigate the perception of domestic appraisers about the possibility of using artificial intelligence (AI) and related risks from the use of AI in the appraisal industry. We conducted a mobile survey of evaluators from February 10 to 18, 2022. We collected survey data from 193 respondents. Frequency analysis and multiple response analysis were performed for basic analysis. When AI is used in the appraisal industry, factor analysis was used to analyze various types of risks. Although appraisers have a positive perception of AI introduction in the appraisal industry, they considered collateral, consulting, and taxation, mainly in areas where AI is likely to be used and replaced, mainly negative effects related to job losses and job replacement. They were more aware of the alternative risks caused by AI in the field of human labor. I was very aware of responsibilities, privacy and security, and the risk of technical errors. However, fairness, transparency, and reliability risks were generally perceived as low risk issues. Existing studies have mainly studied analysis methods that apply AI to mass evaluation models, but this study focused on the use and risk of AI. Understanding industry experts' perceptions of AI utilization will help minimize potential risks when AI is introduced on a large scale.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.151-159
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• 2010

Currently, by using the Internet, We can do varius things such as Web surfing, email, on-line shopping, stock trading on your home or office. However, as being out of the concept of security from the beginning, it is the big social issues that malicious user intrudes into the system through the network, on purpose to steal personal information or to paralyze system. In addition, network intrusion by ordinary people using network attack tools is bringing about big worries, so that the need for effective and powerful intrusion detection system becomes very important issue in our Internet environment. However, it is very difficult to prevent this attack perfectly. In this paper we proposed the algorithm for the detection of DoS attacks, and developed attack detection tools. Through learning in a normal state on Step 1, we calculate thresholds, the number of packets that are coming to each port, the median and the average utilization of each port on Step 2. And we propose values to determine how to attack detection on Step 3. By programing proposed attack detection algorithm and by testing the results, we can see that the difference between the median of packet mounts for unit interval and the average utilization of each port number is effective in detecting attacks. Also, without the need to look into the network data, we can easily be implemented by only using the number of packets to detect attacks.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.143-159
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• 2017

Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.