• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.69-85
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• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.383-392
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• 2007

Karstic features and mining-related cavities not only lead to severe restrictions in land utilizations, but also constitute serious concern about geohazard and groundwater contamination. A microgravity survey was applied for detecting, mapping and monitoring karstic cavities in the test site at Muan prepared by KIGAM. The gravity data were collected using an AutoGrav CG-3 gravimeter at about 800 stations by 5 m interval along paddy paths. The density distribution beneath the profiles was drawn by two dimensional inversion based on the minimum support stabilizing functional, which generated better focused images of density discontinuities. We also imaged three dimensional density distribution by growing body inversion with solution from Euler deconvolution as a priori information. The density image showed that the cavities were dissolved, enlarged and connected into a cavity network system, which was supported by drill hole logs. A time-lapse microgravity was executed on the road in the test site for monitoring the change of the subsurface density distribution before and after grouting. The data were adjusted for reducing the effects due to the different condition of each survey, and inverted to density distributions. They show the change of density structure during the lapsed time, which implies the effects of grouting. This case history at the Muan test site showed that the microgravity with accuracy and precision of ${\mu}Gal$ is an effective and practical tool for detecting, mapping and monitoring the subsurface cavities.

• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.79-91
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• 2011

In this paper, a DS (Data Synchronization) server for mobile communication environments is constructed and the suitability and the performance of its operations are validated. The DS server provides a way to update the newest data and keep data consistency for clients (mobile devices). In addition, the DS server constructed in this paper supports various synchronization types, and detects all changes and conflicts. In case of data conflicts, the DS server resolves the conflicts according to the several policies implemented in this work. The DS server conforms to the OMA(Open Mobile Alliance) DS standard protocol for interoperability with other mobile devices and servers. In addition to the transmission-by record scheme proposed by the OMA DS standard protocol, the DS server constructed in this paper also provides the transmission-by field scheme for the enhancement transmission performance between the server and clients. In order to validate its operations, data synchronization between the DS server and the SCTS (SyncML Conformance Test Suit), the suitability validation tool provided by the OMA, is performed. The validation results show that the DS server constructed in this paper satisfies all of the test cases except the Large Object function. The Large Object function will be implemented later because the function is not needed for the personal information synchronization process which this paper aims for. Also, synchronization times of the DS server are measured while increasing the number of data and clients. The results of the performance evaluations demonstrate that the DS server is scalable, in the sense that it has not suffered from any serious bottlenecks with respect to the number of data and clients. We expect that this work will provide a framework for various studies in the future for improving mobile DS operations.

• Journal of East-West Nursing Research
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• v.5 no.1
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• pp.90-101
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• 2000

The study attempts to examine the degree of cognition and demand on health promotion center of oriental nursing. It puts unique nursing intervention using traditional health promotion connected with oriental medicine to practical use for residents' health promotion and prevention of disease. With the study design of cross-sectional descriptive study, 516 residents who live in 26 Dongs, Dongdaemoon-gu were selected. The tool of study consists of 30 questions which the study team made for the degree of cognition and demand on health promotion center of oriental nursing. Cronbach's $\alpha$ in the degree of cognition was .8028. Collection of research data had been done from October 1 to October 30, 1999 with help of Dongdaemoon-gu office after pretest from 20 residents. Collected data were analyzed into the number and percentage in the characteristic of a subject and connected with demand on the establishment of center, the mean and the standard deviation in the degree of cognition and F-tests in the difference of the degree of cognition by characteristics. The results were as follow; 1) The characteristic of subject of this study was male 50.6%, and average age was 38.5 years old and 30-39 years old occupied the highest percentage with 31.6%. The married were 71.8%, over high school graduates was 85.6%, monthly income from 500 thousand won to 2 million won was 86.1%. 50.8% was the type living with parents, children and sibling. 2) When they were sick, the institution which residents used at first was a pharmacy(69.2%) and hospital(27.5%), but oriental medicine hospital was just 1.4%. As for subjective health condition, 82.5% answered over average, and 28.7% answered that they had chronic illness such as arthritis, chronic digestion problem, hypertension and so on. As for information collection on health, mass communication(34.9%) and medically concerned people(28.1%) occupied relatively high rate. Free health diagnosis system(36.8%) and establishment of health promotion center(31.5%) among welfare programs that residents want to enjoy were high ranked. The rate using a special institution for health was 17.8%, and among these institutions, the rate using aerobic exercises, health center(7.0%) and steamed room(5.4%) was high. Besides, other institutions such as breathing at the abdomen, finger-pressure therapy, meridian massage, foot massage, and so on were being used. 3) As the average of the degree of cognition on health promotion center of oriental medicine was 2.92, the degree of cognition was medium. The description, "health promotion center of oriental medicine is necessary for health keeping of healthy people, including people who have a problem in health" showed the highest degree of cognition(3.04, ${\pm}0.64$). 4) As for the intention on using health promotion center of oriental nursing, 61.4% said "yes", "no" was just 1.4%. The services that people relatively high wanted to be served from the center were measures reducing stress(68.0%) (relaxation therapy, meditation, breathing at the abdomen and so on), acupuncture(66.5%), finger-pressure(61.6%), moxibustion(57.6%), meridian massage(44.2%), postpartum care(40.3%) and so on. 5) As for the degree of cognition on the establishment of health promotion center of oriental nursing by characteristics of subject, there was significant difference(F=4.03, p=.046) between male(3.01) and female(2.91). But there was no significant difference by age, marital status, level of educational achievement and monthly income. As the above result, cognition on the establishment of health promotion center of oriental nursing was relatively low because people were not familiar with about the health promotion center of oriental nursing yet. However once the center will be established, the degree of demand on the center will be relatively high. So positive advertisement will be necessary, and the management of useful programs will be also required in order to make people recognize the advantage when they actually will use the center. On the other hand, as the subject of the study consists of many young people of below 30, the health problem came to be low. And in the case of sampling, the study using random sampling that can represent population will be required.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.29-39
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• 2015

This study has attempted to determine the micro-discourse from blogs as personal media that reflect citizens' actual opinions of the Seoul Forest without intervention of experts. Furthermore, a qualitative research method discourse analysis was selected to analyze the micro-discourse regarding the Seoul Forest in a time series. The extracted samples of blogs by year were intended to identify the comment section of the process of change and the discursive structure. The results are as follows; first, from the beginning of the development of the Seoul Forest to the present, it is divided into four chronological periods along with individuals' micro-discourse with social changes. During the beginning of the development of the Seoul Forest, the social discourse was formed, and in the next period, the micro-discourse was developed with a more emotional and complex discourse. In the formative period, four or five years later, the discourse reflected the civic consciousness of development more than ever, showing the diversity of participation in the program at the Seoul Forest. In the growth period, as the users' experiences had been accumulated, the users started writing about the role of the Seoul Forest in their own words. This can also be called place discourse. From the individuals' micro-discourse, this study shows the discourse structure of how individuals think about the Seoul Forest in each period. Unlike the experts, the micro-discourse contains specific daily interactions, experiences, and the stories of individuals who actually use the parks. It also shows how users reproduce and understand the space. In this respect, this is the most significant finding of this study. Based on this research, this study has demonstrated that the emotional description of a place that actually functions as a discourse about city parks, and confirms that blogs could be used as a space to form discourse and as a research tool to read the trends. In accordance with these results, this study has described not only the discourse of experts, but also how the discourse of individuals' comments can be an important part of the discourse of modern urban parks.

• Korean Journal of Community Nutrition
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• v.9 no.2
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• pp.173-182
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• 2004

We carried out a validation-calibration study of the food frequency questionnaire (FFQ) that we had previously developed for a community-based cohort of the Korean Genome and Health Study of the Korea National Genome Research Institute. We have collected a total of 254 3-day diet records (DRs) from 400 subjects, 200 each randomly selected from the two study cohorts of Ansung and Ansan. FFQ was administered at the time of cohort recruitment in 2001, and DRs were collected during a two month period from January through February of 2002. The mean age was 52.2 years. Farming for men and housewife for women were the most common occupations. The majority of the subjects had undergone 6∼12 years of education. The general characteristics including demographic and other data were not different from the total cohort subjects. Absolute levels of consumed nutrients including total energy (energy), protein, fat, carbohydrate, calcium, phosphorus, sodium, potassium, iron, retinol, carotene, vitamin A, thiamin, riboflavin, niacin and vitamin C were compared. The average of energy intake was not significantly different between the data collected by the 2 methods. However, consumptions of protein and fat were higher in data of DRs, whereas that of carbohydrate was higher in FFQ data. Significant correlation of each nutrient consumption between the data sets was observed (p ＜ 0.05) except in the case of iron, while the average correlation coefficient between them was 0.22 ranging from 0.33 for energy to 0.11 for iron. The results of cross classification by quantile for exact classification ranged from 25.2% (carotene) to 35.0% (phosphorus), and from 64.6% (vitamin A) to 76.4% (retinol) for adjacent classification. The proportion of completely opposite classification was 8.1% in average. Calibration slope was estimated by regression and calibration parameters ranged from 0.025 for carotene to 0.423 for niacin. We conclude that the FFQ we have developed is an appropriate tool for assessing the nutrient intakes as ranking exposures in epidemiology studies in view that amounts of consumed nutrients obtained by FFQ were similar to those collected by DRs, that correlations between consumed nutrients collected by these methods were significant, and that classification results were relatively fair. The correlation coefficients, however, were lower than expected, which may be mainly due to the survey season. In fact, any short-term dietary survey cannot accurately reflect the overall dietary intakes that change heavily depending on seasons. Further studies including the analysis of chemical indices would be helpful for the studies of causal relationship between the diet and disease.

• Archives of design research
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• v.18 no.3 s.61
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• pp.85-94
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• 2005

Most of product designers use 3D CAD system as a inevitable design tool nowadays and many new products are developed through a concurrent engineering process. However, it is very difficult for novice designers to get the sense of reality from modeling objects shown in the computer screens. Such a intangibility problem comes from the lack of haptic interactions and contextual information about the real space because designers tend to do 3D modeling works only in a virtual space of 3D CAD system. To address this problem, this research investigate the possibility of a interactive quantified structure simulation for product design using AR(augmented reality) which can register a 3D CAD modeling object on the real space. We built a quantified structure simulation system based on AR and conducted a series of experiments to measure how accurately human perceive and adjust the size of virtual objects under varied experimental conditions in the AR environment. The experiment participants adjusted a virtual cube to a reference real cube within 1.3% relative error(5.3% relative StDev). The results gave the strong evidence that the participants can perceive the size of a virtual object very accurately. Furthermore, we found that it is easier to perceive the size of a virtual object in the condition of presenting plenty of real reference objects than few reference objects, and using LCD panel than HMD. We tried to apply the simulation system to identify preference characteristics for the appearance design of a home-service robot as a case study which explores the potential application of the system. There were significant variances in participants' preferred characteristics about robot appearance and that was supposed to come from the lack of typicality of robot image. Then, several characteristic groups were segmented by duster analysis. On the other hand, it was interesting finding that participants have significantly different preference characteristics between robot with arm and armless robot and there was a very strong correlation between the height of robot and arm length as a human body.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.157-175
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• 2012

It is difficult to evaluate the performance of process innovation of e-procurement which has large scale and complex processes. The existing evaluation methods for measuring the effects of process innovation have been mainly done with statistically quantitative methods by analyzing operational data or with qualitative methods by conducting surveys and interviews. However, these methods have some limitations to evaluate the effects because the performance evaluation of e-procurement process innovation should consider the interactions among participants who are active either directly or indirectly through the processes. This study considers the e-procurement process as a complex system and develops a simulation model based on MAS(Multi-Agent System) to evaluate the effects of e-procurement process innovation. Multi-agent based simulation allows observing interaction patterns of objects in virtual world through relationship among objects and their behavioral mechanism. Agent-based simulation is suitable especially for complex business problems. In this study, we used Netlogo Version 4.1.3 as a MAS simulation tool which was developed in Northwestern University. To do this, we developed a interaction model of agents in MAS environment. We defined process agents and task agents, and assigned their behavioral characteristics. The developed simulation model was applied to G2B system (KONEPS: Korea ON-line E-Procurement System) of Public Procurement Service (PPS) in Korea and used to evaluate the innovation effects of the G2B system. KONEPS is a successfully established e-procurement system started in the year 2002. KONEPS is a representative e-Procurement system which integrates characteristics of e-commerce into government for business procurement activities. KONEPS deserves the international recognition considering the annual transaction volume of 56 billion dollars, daily exchanges of electronic documents, users consisted of 121,000 suppliers and 37,000 public organizations, and the 4.5 billion dollars of cost saving. For the simulation, we analyzed the e-procurement of process of KONEPS into eight sub processes such as 'process 1: search products and acquisition of proposal', 'process 2 : review the methods of contracts and item features', 'process 3 : a notice of bid', 'process 4 : registration and confirmation of qualification', 'process 5 : bidding', 'process 6 : a screening test', 'process 7 : contracts', and 'process 8 : invoice and payment'. For the parameter settings of the agents behavior, we collected some data from the transactional database of PPS and some information by conducting a survey. The used data for the simulation are 'participants (government organizations, local government organizations and public institutions)', 'the number of bidding per year', 'the number of total contracts', 'the number of shopping mall transactions', 'the rate of contracts between bidding and shopping mall', 'the successful bidding ratio', and the estimated time for each process. The comparison was done for the difference of time consumption between 'before the innovation (As-was)' and 'after the innovation (As-is).' The results showed that there were productivity improvements in every eight sub processes. The decrease ratio of 'average number of task processing' was 92.7% and the decrease ratio of 'average time of task processing' was 95.4% in entire processes when we use G2B system comparing to the conventional method. Also, this study found that the process innovation effect will be enhanced if the task process related to the 'contract' can be improved. This study shows the usability and possibility of using MAS in process innovation evaluation and its modeling.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.905-916
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• 2018

The purpose of this study is to evaluate the climate change impact on watershed hydrology and flow duration in Geum River basin ($9,645.5km^2$) especially by extreme scenarios. The rainfall related extreme index, STARDEX (STAtistical and Regional dynamical Downscaling of EXtremes) was adopted to select the future extreme scenario from the 10 GCMs with RCP 8.5 scenarios by four projection periods (Historical: 1975~2005, 2020s: 2011~2040, 2050s: 2041~2070, 2080s: 2071~2100). As a result, the 5 scenarios of wet (CESM1-BGC and HadGEM2-ES), normal (MPI-ESM-MR), and dry (INM-CM4 and FGOALS-s2) were selected and applied to SWAT (Soil and Water Assessment Tool) hydrological model. The wet scenarios showed big differences comparing with the normal scenario in 2080s period. The 2080s evapotranspiration (ET) of wet scenarios varied from -3.2 to +3.1 mm, the 2080s total runoff (TR) varied from +5.5 to +128.4 mm. The dry scenarios showed big differences comparing with the normal scenario in 2020s period. The 2020s ET for dry scenarios varied from -16.8 to -13.3 mm and the TR varied from -264.0 to -132.3 mm respectively. For the flow duration change, the CFR (coefficient of flow regime, Q10/Q355) was altered from +4.2 to +10.5 for 2080s wet scenarios and from +1.7 to +2.6 for 2020s dry scenarios. As a result of the flow duration analysis according to the change of the hydrological factors of the Geum River basin applying the extreme climate change scenario, INM-CM4 showed suitable scenario to show extreme dry condition and FGOALS-s2 showed suitable scenario for the analysis of the drought condition with large flow duration variability. HadGEM2-ES was evaluated as a scenario that can be used for maximum flow analysis because the flow duration variability was small and CESM1-BGC was evaluated as a scenario that can be applied to the case of extreme flood analysis with large flow duration variability.