• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.444-448
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• 2008

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2:image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.209-216
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• 2009

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• International Journal of Highway Engineering
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• v.17 no.2
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• pp.107-122
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• 2015

PURPOSES : The use of virtual driving tests to determine actual road driving behavior is increasing. However, the results indicate a gap between real and virtual driving under same road conditions road based on ergonomic factors, such as anxiety and speed. In the future, the use of virtual driving tests is expected to increase. For this reason, the purpose of this study is to analyze the gap between real and virtual driving on same road conditions and to use a calibration formula to allow for higher reliability of virtual driving tests. METHODS : An intelligent driving recorder was used to capture real driving. A driving simulator was used to record virtual driving. Additionally, a virtual driving map was made with the UC-Win/Road software. We gathered data including geometric structure information, driving information, driver information, and road operation information for real driving and virtual driving on the same road conditions. In this study we investigated a range of gaps, driving speeds, and lateral positions, and introduced a calibration formula to the virtual record to achieve the same record as the real driving situation by applying the effects of the main causes of discrepancy between the two (driving speed and lateral position) using a linear regression model. RESULTS: In the virtual driving test, driving speed and lateral position were determined to be higher and bigger than in the real Driving test, respectively. Additionally, the virtual driving test reduces the concentration, anxiety, and reality when compared to the real driving test. The formula includes four variables to produce the calibration: tangent driving speed, curve driving speed, tangent lateral position, and curve lateral position. However, the tangent lateral position was excluded because it was not statistically significant. CONCLUSIONS: The results of analyzing the formula from MPB (mean prediction bias), MAD (mean absolute deviation) is after applying the formula to the virtual driving test, similar to the real driving test so that the formula works. Because this study was conducted on a national, two-way road, the road speed limit was 80 km/h, and the lane width was 3.0-3.5 m. It works in the same condition road restrictively.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.833-845
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• 2011

This paper conducts a statistical analysis of extreme values for both daily log-returns and daily negative log-returns, which are computed using a collection of KOSPI data from January 3, 1998 to August 31, 2011. The Poisson-GPD model is used as a statistical analysis model for extreme values and the maximum likelihood method is applied for the estimation of parameters and extreme quantiles. To the Poisson-GPD model is also added the Bayesian method that assumes the usual noninformative prior distribution for the parameters, where the Markov chain Monte Carlo method is applied for the estimation of parameters and extreme quantiles. According to this analysis, both the maximum likelihood method and the Bayesian method form the same conclusion that the distribution of the log-returns has a shorter right tail than the normal distribution, but that the distribution of the negative log-returns has a heavier right tail than the normal distribution. An advantage of using the Bayesian method in extreme value analysis is that there is nothing to worry about the classical asymptotic properties of the maximum likelihood estimators even when the regularity conditions are not satisfied, and that in prediction it is effective to reflect the uncertainties from both the parameters and a future observation.

• Water for future
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• v.29 no.5
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• pp.185-202
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• 1996

The newly-developed method for estimating the instream flow, proposed by the authors (1996), was applied to the main channel reach of the Kum River basin in Korea. Performance of the suggested method was tested through the evaluations of the required flow, instream flow, and river-management flow which were estimated at five main reaches with each representative station. The mean drought flow was used as the object flow to evaluate the minimum instream flow for the mid- and large-size rivers. Water quality prediction by using the QUAL2E model was made for both cases that the planned wastewater treatment facilities may and may not be constructed. The required flow for the fish habitat was evaluated for 9 representative fish species. The instream flows required for the riverine aesthetics at Kong-ju and Puyo scenary points, for river navigation at natural channel conditions, and for current and potential recreation activities were evaluated, respectively. The instream flows required for other items are not quantified. On the whole, it is shown that the instream flow to maintain the natural riverine functions such as fish habitat, and riverine aesthetics govern the upstream reaches of the Kum River, and the artificial riverine functions such as conservation of water quality, navigation and recreations govern the middle and downstream reaches. Especially, it is found that the instream flow requirement depends largely upon the construction of wastewater treatment facilities at the Kum River basin.

• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.61-73
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• 2009

To efficiently carry out the flood management of a multipurpose dam, two flood forecasting models are developed, each of which has the capabilities of forecasting upstream inflows and flood discharges downstream of a dam, respectively. The models are calibrated, validated, and evaluated by comparison of the observed and the runoff forecasts upstream and downstream of Namgang Dam. The upstream inflow forecasting model is based on the Grey system theory and employs the sixth order differential equation. By comparing the inflows forecasted by the models calibrated using different data sets with the observed in validation, the most appropriate model is determined. To forecast flood discharges downstream of a dam, a Grey model is integrated with a modified Muskingum flow routing model. A comparison of the observed and the forecasted values in validation reveals that the model can provide good forecasts for the dam's flood management. The applications of the two models to forecasting floods in real situations show that they provide reasonable results. In addition, it is revealed that to enhance the prediction accuracy, the models are necessary to be calibrated and applied considering runoff stages; the rising, peak, and falling stages.

• Management & Information Systems Review
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• v.29 no.1
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• pp.49-78
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• 2010

Traditionally, self-efficacy, burnout and engagement are defined as work related states of mind, and formally speaking, students are not employees. But, we assume that from a psychological perspective, student core activities can be considered work. Therefore, based on SCT(social cognitive theory), we examine the mediating role of self-efficacy in the prediction of student burnout and engagement, and also the mediation of burnout and engagement between self-efficacy and performance(GPA). There is no research to date wether there would be mediating role of these variables between past success and performance. These effects were analysed in the context of mediating role of the variables in a university in a sample of 438 students. This study utilized a convenience sample drawn from various major scholar area. Results of structural equation modeling analyses were consist with a full mediation model in which academic past success predicts self-efficacy, which in turn, predicts student burnout and engagement. Also our proposed model showed that burnout and engagement are partial or full mediating variables between self-efficacy and performance. Our study's findings provide evidence that engagement fully accounted for the relationship between self-efficacy and performance, and burnout partially explained the relationships. These findings aligns with the general theorizing supported by JD-R model and SCT(social cognitive theory). More specifically, it builds on the JD-R literature as it tests one of the proposed mechanisms in the relationship between job resources and work engagement. Implications of study are discussed, together with limitations and suggestions for future research.

• Journal of Science and Technology Studies
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• v.16 no.1
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• pp.29-61
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• 2016

This paper explains the one of the most problematic factor in the society that leads to social inequality - increase in non-regular work. Theoretically, this expansion of non-regular work can be explained by technologies that are designed to save the labor force, especially since corporations in Korea have strategies to replace the regular workers with temporary workers, to save money. OECD also noted that Korea's income inequality is pretty high in ranking when compared with the rest of the OECD members, and says that globalization and technological innovation are the factors of this problem. To refine the argument, this study also looks at relationship between development made in sciences - which can be stated as a proxy variable to look at the advances made in technology - and expansion of temporary work force by using VAR methodology. Based on the results of this analysis in the future temporary/regular workers ratio started with decline, then turn to rise. These temporary/regular workers ratio sustained growth prediction shows that the expansion of the temporary expansion contributes to instability and social inequality in the labor market and technological change are interrelated.

• Journal of the Korea Concrete Institute
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• v.22 no.6
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• pp.777-786
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• 2010

This paper examines the flexural behavior of full-scale prestressed concrete girders that were constructed of steel fiber reinforced ultra high performance concrete (UHPC). This study is designed to provide more information about the bending characteristics of UHPC girders in order to establish a reasonable prediction model for flexural resistance and deflection for future structural design codes. Short steel fibers have been introduced into prestressed concrete T-girders in order to study their effects under flexural loads. Round straight high strength steel fibers were used at volume fraction of 2%. The girders were cast using 150~190 MPa steel fiber reinforced UHPC and were designed to assess the ability of steel fiber reinforced UHPC to carry flexural loads in prestressed girders. The experimental results show that steel fiber reinforced UHPC enhances the cracking behavior and ductility of beams. Moreover, when ultimate failure did occur, the failure of girders composed of steel fiber reinforced UHPC was observed to be precipitated by the pullout of steel fibers that were bridging tension cracks in the concrete. Flexural failure of girders occurred when the UHPC at a particular cross section began to lose tensile capacity due to steel fiber pullout. In addition, it was determined that the level of prestressing force influenced the ultimate load capacity.

• Spatial Information Research
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• v.20 no.1
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• pp.9-18
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• 2012

South Korea has many landslides caused by heavy rains during summer time recently and the landslides continue to cause damages in many places. These landslides occur repeatedly each year, and the frequency of landslides is expected to increase in the coming future due to dramatic global climate change. In Korea, 81.5% of the population is living in urban areas and about 1,055 million people are living in Seoul. In 2011, the landslide that occurred in Seocho-dong killed 18 people and about 9% of Seoul's area is under the same land conditions as Seocho-dong. Even the size of landslide occurred in a city is small, but it is more likely to cause a big disaster because of a greater population density in the city. So far, the effort has been made to identify landslide vulnerability and causes, but now, the new dem and arises for the prediction study about the areal extent of disaster area in case of landslides. In this study, the diffusion model of the landslide disaster area was established based on Cellular Automata(CA) to analyze the physical diffusion forms of landslide. This study compared the accuracy with the Seocho-dong landslide case, which occurred in July 2011, applying the SCIDDICA model and the CAESAR model. The SCIDDICA model involves the following variables, such as the movement rules and the topographical obstacles, and the CAESAR model is also applied to this process to simulate the changes of deposition and erosion.