• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.720-734
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• 2013

In this paper, we suggest an augmented reality authoring tool system that users can easily make augmented reality contents using hand gesture and marker-based interaction methods. The previous augmented reality authoring tools are focused on augmenting a virtual object and to interact with this kind of augmented reality contents, user used the method utilizing marker or sensor. We want to solve this limited interaction method problem by applying marker based interaction method and gesture interaction method using depth sensing camera, Kinect. In this suggested system, user can easily develop simple form of marker based augmented reality contents through interface. Also, not just providing fragmentary contents, this system provides methods that user can actively interact with augmented reality contents. This research provides two interaction methods, one is marker based method using two markers and the other is utilizing marker occlusion. In addition, by recognizing and tracking user's bare hand, this system provides gesture interaction method which can zoom-in, zoom-out, move and rotate object. From heuristic evaluation about authoring tool and compared usability about marker and gesture interaction, this study confirmed a positive result.

• Korean Institute of Interior Design Journal
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• v.23 no.6
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• pp.115-124
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• 2014

This study has carried out scanning tests in order to figure out the features of scanning search by sex of space users, with the result of which the validity of data has been estimated. In this research, the scanning patterns were set up for verifying the typology of scanning paths and then the reason for determining scanning paths and the validity of estimation method were reviewed. Since the observation features depends on sex, the analysis of visual activities for acquiring any information in a space will reveal the intention and purpose of space users. The findings by analyzing the features of scanning pattern by sex which were found at the determination of scanning patterns can be defined as the followings. First, for estimating the process of space-information search, the movement distance at each point of continuative-observation data from the angle of eye-movement has been extracted, on the ground of which the fixation and movement of eye have been defined for the establishment of scanning-cut characteristics. Second, the scanning times were estimated for the extraction of effective observation data that would be used for comparative analysis, which showed that men had more data (3,398.2/64.4%) than women (2,998.2/55.6%). This enables the acknowledgment that the scanning cut of men was relatively less, which indicates that men will acquire more information on space than women in the process of observing any space. Third, men's scanning times (58.0 times/2.02 seconds) were less than those of women (71.9 times/1.39 seconds) while the scanning time of the former was longer than that of the latter, which shows the feature that it takes longer for men than women in scanning while the scanning times of the former is less than those of the latter. Fourth, the observation features can be determined that the combination of this result with the predominance character by sex for a general viewpoint to be employed indicates that while men employ mixed-scanning for observation activities to acquire space-information spending for longer time, women, by concentrated-scanning, focus on a single point for shorter time or stay at one location for a considerably long time for space-information acquirement.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.1-8
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• 2017

In this paper, we introduce a technique to retarget human motion data to the humanoid body in a constrained environment. We assume that the given motion data includes detailed interactions such as holding the object by hand or avoiding obstacles. In addition, we assume that the humanoid joint structure is different from the human joint structure, and the shape of the surrounding environment is different from that at the time of the original motion. Under such a condition, it is also difficult to preserve the context of the interaction shown in the original motion data, if the retargeting technique that considers only the change of the body shape. Our approach is to separate the problem into two smaller problems and solve them independently. One is to retarget motion data to a new skeleton, and the other is to preserve the context of interactions. We first retarget the given human motion data to the target humanoid body ignoring the interaction with the environment. Then, we precisely deform the shape of the environmental model to match with the humanoid motion so that the original interaction is reproduced. Finally, we set spatial constraints between the humanoid body and the environmental model, and restore the environmental model to the original shape. To demonstrate the usefulness of our method, we conducted an experiment by using the Boston Dynamic's Atlas robot. We expected that out method can help the humanoid motion tracking problem in the future.

• Journal of Distribution Science
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• v.13 no.10
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• pp.123-133
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• 2015

Purpose - The Korean government has devised intermodal transportation policies and granted subsidies to shippers and logistics companies that made a conversion of transportation means through the policies. This provides support by expanding the complex uniform railroad transportation and overhauling the deteriorated railroad facilities. As for 2013, however, the freight transportation percentage of railroad was 4.5% in tons and 8.5% in ton kilometers. Meanwhile, since the 1990s, developed countries such as the U.S. and Europe have been trying to expand intermodal freight transport with a legal and institutional support to build a logistics system corresponding with social and economic environmental changes. In this study, I set out to examine the effects of the intermodal freight transport policies in the EU and the U.S., and to explore the direction of setting up a rail intermodal transport system in South Korea. Research design, data, and methodology - The paper used a qualitative research methodology through the literature review. First, was an overview of Intermodal transportation in the EU, U.S. and UN. Second, it describes the development of transport in Europe and the U.S. with particular emphasis on intermodal freight transport. Third, it explores the direction of setting up a intermodal freight transport in South Korea. The last section contains concluding remarks. Results - As for the EU, it has been promoting integration between transport and intermodal logistics network designs while utilizing ITS or ICT and supports for rail freight intermodal by giving reduction to a facilities fee or subsidizing for rail freight in order to minimize the cost of external due to freight transport. On the other hand, as for the U.S., it has been made up of an industrial-led operating project and has been promoting it to improve accessibility between intermodal hubs and cargo terminals through intermodal corridor program, and an intermodal cargo hub access corridor projects, etc. Moreover, it has tried to construct intermodal transport system using ITS or ICT and to remove Barrier. As a result, in these countries, the proportion of intermodal freight transport is going to be the second significant transport compared with rail and maritime transport. An Effective rail intermodal transport system is needed in South Korea, as seen in the case of these countries. In order to achieve this object, the following points are required to establish radical infrastructure policy; diversify investment financing measures taken under public-private partnerships, legal responsibilities, improvement of utilization of existing facilities to connect the railway terminal and truck terminal, and enhancement service competitiveness through providing cargo tracking and security information that combines the ITS and ICT. Conclusions - This study will be used as a basis for policy and support for intermodal freight transport in South Korea. In the future, it is also necessary to examine from the perspective of the shipper companies using the rail intermodal transport, ie, recognition of shipper, needed institutional supports, and transportation demand forecasting and cost-effective analysis of the railway infrastructure systems improvement.

• Journal of The Korean Association For Science Education
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• v.33 no.4
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• pp.778-793
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• 2013

The purpose of this study is to analyze observation characteristics through eye movement according to cognitive styles. To do this, we developed observation tasks that show the differences between wholistic cognitive style group and analytic cognitive style group, measured eye movement of university students with different cognitive styles after being given an observation task. The difference between two cognitive style groups is confirmed by analysing gathered statistics and visualization data. The findings of this study are as follows: First, to compare fixation time and frequency, we compared the average value of total time used in the observation task by the wholistic cognitive style group and analytic cognitive style group. The numbers of Fixation (total) and number of Fixations (30s), is based on the fact that the wholistic cognitive style group has more numbers of fixation (Total) and number of fixations (30s) means the wholistic cognitive style group can observe more points or overall features than the analytic cognitive style group, in contrast, the analytic cognitive style group tend to focus on a particular detail, and observe less numbers of points. Second, to compare observation object and area by cognitive style, the outcome of analysing visualization data shows that wholistic cognitive style group observes the surrounding environment of spider and web on a wider area, on the other hand, the analytic cognitive style group observes by focusing on the spider itself. Through the result of this study, there are differences in observation time, frequency, object, area, and ratio from the two cognitive styles. It also shows the reason why each student has varied outcome, from the difference of information following their cognitive styles, and the result of this study helps to figure out and give direction as to what observation fulfillment is more suitable for each student.

• Journal of Science Education
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• v.37 no.1
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• pp.142-156
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• 2013

The purpose of this study was to analyze observation characteristics through eye movement according to cognitive style. For this, developed observation task that can be shown the difference between wholistic cognitive style group and analytic cognitive style group, measured eye movement of university students who has different cognitive style, as given observation task. It is confirmed the difference between two cognitive style groups by analysing gathered statistics and visualization data. The findings of this study were as follows; First, Compared observation sequence and pattern by cognitive style, analytic cognitive style group is concerned with spider first and moving on surrounding environment, whereas wholistic cognitive style group had not fixed pattern as observing spider itself and surrounding area of spider alternately or looking closely on particular part at first. When observing entire feature and partial feature, wholistic cognitive style group was moving on Fixation from outstanding factor without fixed pattern, analytic cognitive style had certain directivity and repetitive investigation. Second, compared the ratio of observation, analytic cognitive style group gave a large part to spider the very thing, wholistic cognitive style group gave weight to surrounding area of spider, and analytic group shown higher concentration on observing partial feature, wholistic cognitive style group shown higher concentration on observing wholistic feature. Wholistic cognitive style group gave importance to partial features in surrounding area, and wholistic feature of spider than analytic cognitive style group, analytic cognitive style group was focus on partial features of spider than wholistic cognitive style group. Through the result of this study, there are differences of observing time, frequency, object, area, sequence, pattern and ratio from cognitive styles. It is shown the reason why each student has varied outcome, from the difference of information following their cognitive style, and the result of this study help to figure out and give direction to what observation fulfillment is suitable for each student.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.