• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.330-337
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• 2018

Recently, there has been a growing interest in user-centered smart city services. In this study, user behavior analysis was performed as a preliminary study for user - centered smart city service planning. In particular, we will use GIS based location analysis data and video ethonography methodology to derive smart city service direction and needs. In this study, the area of Daejeon Design District selected as the Smart City Test bed was selected as the survey area and the location analysis data of the traffic accident analysis system of the road traffic corporation and the fixed camera We observed user's behavior type and change with image data extracted through the technique. Location analysis data is classified according to the type of accident, and image data is classified into 11 subdivided types of user activities. The problems and specificities observed were analyzed. The user behavior characteristics investigated through this study are meaningful to provide a basis for suggesting user - centered smart city services in the future.

• Journal of Internet Technology
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• v.22 no.4
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• pp.903-911
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• 2021

As cyber-attacks on Cyber-Physical System (CPS) become more diverse and sophisticated, it is important to quickly detect malicious behaviors occurring in CPS. Since CPS can collect sensor data in near real time throughout the process, there have been many attempts to detect anomaly behavior through normal behavior learning from the perspective of data-driven security. However, since the CPS datasets are big data and most of the data are normal data, it has always been a great challenge to analyze the data and implement the anomaly detection model. In this paper, we propose and evaluate the Clustered Deep One-Class Classification (CD-OCC) model that combines the clustering algorithm and deep learning (DL) model using only a normal dataset for anomaly detection. We use auto-encoder to reduce the dimensions of the dataset and the K-means clustering algorithm to classify the normal data into the optimal cluster size. The DL model trains to predict clusters of normal data, and we can obtain logit values as outputs. The derived logit values are datasets that can better represent normal data in terms of knowledge distillation and are used as inputs to the OCC model. As a result of the experiment, the F1 score of the proposed model shows 0.93 and 0.83 in the SWaT and HAI dataset, respectively, and shows a significant performance improvement over other recent detectors such as Com-AE and SVM-RBF.

• The Research Journal of the Costume Culture
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• v.32 no.2
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• pp.199-214
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• 2024

Until now, research on consumers' purchasing behavior has primarily focused on psychological aspects or depended on consumer surveys. However, there may be a gap between consumers' self-reported perceptions and their observable actions. In response, this study aimed to investigate consumer purchasing behavior utilizing a big data approach. To this end, this study investigated the purchasing patterns of fashion items, both online and in retail stores, from a data-driven perspective. We also investigated whether individual consumers switched between online websites and retail establishments for making purchases. Data on 516,474 purchases were obtained from fashion companies. We used association rule analysis and K-means clustering to identify purchase patterns that were influenced by customer loyalty. Furthermore, sequential pattern analysis was applied to investigate the usage patterns of online and offline channels by consumers. The results showed that high-loyalty consumers mainly purchased infrequently bought items in the brand line, as well as high-priced items, and that these purchase patterns were similar both online and in stores. In contrast, the low-loyalty group showed different purchasing behaviors for online versus in-store purchases. In physical environments, the low-loyalty consumers tended to purchase less popular or more expensive items from the brand line, whereas in online environments, their purchases centered around items with relatively high sales volumes. Finally, we found that both high and low loyalty groups exclusively used a single preferred channel, either online or in-store. The findings help companies better understand consumer purchase patterns and build future marketing strategies around items with high brand centrality.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.133-143
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• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.196-204
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• 2017

Behavior of intelligent video surveillance system is recognized by analyzing the pattern of the object of interest by using the frame information of video inputted from the camera and analyzes the behavior. Detection of object's certain behaviors in the crowd has become a critical problem because in the event of terror strikes. Recognition of object's certain behaviors is an important but difficult problem in the area of computer vision. As the realization of big data utilizing machine learning, data mining techniques, the amount of video through the CCTV, Smart-phone and Drone's video has increased dramatically. In this paper, we propose a multiple-sliding window method to recognize the cumulative change as one piece in order to improve the accuracy of the recognition. The experimental results demonstrated the method was robust and efficient learning units in the classification of certain behaviors.

• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.183-205
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• 2019

Among the various methods for identifying users's information needs, Log analysis methods can realistically reflect the users' actual search behavior and analyze the overall usage of most users. Based on the large quantity of query log big data obtained through the portal service of the National Archives of Korea, this study conducted an analysis by the information type and search result type in order to identify the users' information needs. The Query log used in analysis were based on 1,571,547 query data collected over a total of 141 months from 2007 to December 2018, when the National Archives of Korea provided search services via the web. Furthermore, based on the analysis results, improvement methods were proposed to improve user search satisfaction. The results of this study could actually be used to improve and upgrade the National Archives of Korea search service.

• Korean Journal of Schizophrenia Research
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• v.22 no.2
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• pp.34-41
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• 2019

Objectives: This study was performed to examine the effects of the public attention to 'crime of schizophrenia' on the use of mental health services in patients with schizophrenia using big data analysis. Methods: Data on the frequency of internet searches for 'crime of schizophrenia' and the patterns of mental health service utilization by patients with schizophrenia spectrum disorders by month were collected from Naver big data and the Health Insurance Review and Assessment Services in Korea, respectively. Their correlations in the same and following month for lagged effect were examined. Results: The number of outpatients correlated negatively with public attention to 'crime of schizophrenia' in the same month. The lagged relationship between public attention and the number of admissions in psychiatric wards was also found. In terms of sex differences, the use of outpatient services among female patients correlated negatively with public attention in the same month while the number of male patients' admissions in both same and following month correlated positively with public attention. Conclusion: These findings suggested that public attention to 'crime of schizophrenia' could negatively affect illness behavior in patients with schizophrenia.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.143-150
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• 2021

This study investigates and analyzes the difference in Indonesian banks' earnings quality in the pre-audit and post-audit period. This study also investigates the difference in audit quality done by public accounting firms. This study employs time series data taken from the unaudited and audited financial statements of banks listed on the Indonesia Stock Exchange in 2012-2016. Sample selection is made by using a purposive sampling method. The population of this study is 43 banks, and after checking the data for validity and reliability, the final sample size was 26 banks. Audit quality is operationalized with the size of the auditor. Earnings quality is proxied by accruals calculated using the Beaver and Engel (1996) model. The data analysis method used in this study is the paired-sample t-test and chow test. This study shows that there is no difference in earnings quality in the pre-audit and post-audit period. This study also reveals no difference in audit quality between the big four and non-big four auditors. These findings mean that independent auditors do not play a useful role in increasing the reliability of accounting information presented by management to stakeholders. Besides, this study's results do not verify the agency theory regarding auditors' role to minimize opportunistic management behavior in preparing financial statements.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.35 no.4
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• pp.258-265
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• 2024

Objectives: This study aimed to examine sex differences in the risk factors associated with generalized anxiety disorder (GAD) among Korean adolescents to provide insights for drafting more effective prevention strategies. Methods: Data from 51845 middle and high school students in the 18th Korea Youth Risk Behavior Web-based Survey were analyzed. GAD was assessed using the 7-item Generalized Anxiety Disorder tool, and factors such as grade, academic performance, economic status, living arrangements, smoking, drinking, sexual experience, and physical activity were included. The prevalence of GAD and its association with these factors were compared between male and female students using chi-square tests and logistic regression. Odds ratios were compared statistically to identify sex-specific differences. Results: GAD prevalence was higher among girls (42.1%) than boys (30.1%). Both sexes showed increased GAD risk with lower academic performance, lower economic status, smoking, drinking, and sexual experience. Boys living apart from their families had a higher GAD risk, but this was not significant for girls. Additionally, smoking and drinking were associated with a higher increase in GAD risk in girls than in boys. Conclusion: This study underscores the importance of considering sex differences in the prevention of GAD among adolescents. Tailored sex-specific interventions are crucial for effective prevention and management of GAD in Korean adolescents.

• Journal of Korean Academy of Nursing
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• v.21 no.1
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• pp.89-116
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• 1991

The purpose of this study was to describe mother -infant interacting behavior patterns related to newborn infant feeding and to explore the mother's cultural belief about their infant. The data collection was conducted by observation and interview. Twenty-five mothers and their newborn infants who were normally delivered and were also planned to breast feed were comprised as the subjects of this study. All subjects were interviewed and observed individuaily at 1 to 5 days after the delivery at the hospital, mid -wife's clinic, Maternal Child Health Center and their home throughout the country from remote area to big city, The observation data were recorded with symbolic letter on a recording sheet newly developed as a result of preliminary study. The interview data were taperecorded and then recorded in narrative form. Mother - infant interaction behaviors in early feeding period were analyzed based on 19 analytic sub-categories and their composing elements. Unit of analysis were mother, infant and mother -infant dyad. 8 analytic categories draw from the data. Each were preparation, instrument, interaction inducing, evaluation referred to mother's behavior, preparation, instrument, interaction inducing referred to infant's behavior and synchronic behaviors referred to mother - infant dyad. Frequencies of behavior items based on the categories were converted to percent. The result showed that in mother's preparation behavior, the breast condition of Korean mother can be an affecting factor for mother - infant interaction during feeding, and vocalization behavior was observed most frequently in interaction inducing behavior while the least frequent behavior observed was contacting. Subcultural characteristics of mother - infant interaction behaviors were analyzed for their relationships between groups of mothers who have lived in remote area vs urban area, and who were multipara vs primipara. Using a chi -square test, there were statistically significant relationships in the activity of psychological readiness in preparation behavior and the movement of extremities for the position of instrumental behavior in both groups. However, interaction inducing behaviors were not related with statistical significance in any set of groups. Accomplishment of marriage, bonding and emotional mediation of family members were the categories related to mother's cultural belief about the infant in aspect of functional values. Infant at birth is considered little more than a biological organism without social capabilities. Although the newborn infant is still be attached to his mother, he makes his mother extend her territoriality. The mother's interacting behavior toward her infant based on those beliefs appeared task oriented, separative behavioral series. On the other hand, it was seen that infant reacted independently to his mother's behavior by the in-nate perceptual abilities. Those independent behavioral series of mother and infant on the feeding situation were synchronized at any moment. Nurses are In a unique position to teach mothers about their infant's capabilities and help reducing some of uncertainty about infant's behaviors. Study results indicated that the informations infant's social capabilities and breast feeding should be given to the mothers. The results of this study have several implications for nursing. First, the study results will be used as fundamental resources for the development of the assessment tool about the early mother - infant interaction. Second, the results could be a relevant information in the fied. I of maternal child nursing education as real and useful data. Third, the behavioral patterns of early mother - infant interaction which were classified based on the qualitative analysis could be used for nursing theory development as very fundamental data.