• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.76-83
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• 2022

With the recent development of IT technology, research and interest in various biosignal measuring devices is increasing. As an aging society is in full swing, research on the elderly population using IT-related technologies is continuously developing. This study is about the development of life pattern detection and fall detection algorithm, which is one of the medical service areas for the elderly, who are rapidly developing as they enter a super-aged society. This study consisted of a system using a 3-axis accelerometer and an electrocardiogram sensor, collected data, and then analyzed the data. It was confirmed that behavioral patterns could be classified from the actual research results. In order to evaluate the usefulness of the human activity monitoring system implemented in this study, experiments were performed under various conditions, such as changes in posture and walking speed, and signal magnitude range and signal vector magnitude parameters reflecting the acceleration of gravity of the human body and the degree of human activity. was extracted. And the possibility of discrimination according to the condition of the subject was examined by these parameter values.

• Korean Journal of Culture and Social Issue
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• v.8 no.1
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• pp.17-40
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• 2002

The purpose of this study is to investigate the differences in the traffic environments and driving behaviors in 5 regions of Korea. Data were collected through the survey research from 1387 passenger car drivers in 14 locations in Korea. The main findings of this research are as followings: First of all, There were significant differences in traffic environment factors(road topography, construction, road & safety facilities, pedestrian behaviors, surrounding drivers) among 5 regional areas. When we examined drivers factors, there were significant differences among 5 metropolitan areas on wearing seat belt, most of constructions related to drink driving, speed-limit violation. There were many differences in driving habits, intentions, behaviors including wearing seat belt, driving after drinking according to metropolitan area, and also in case of speed-limit violation and careless driving behavior. These results suggested that there are many differences in traffic environments and driver's behaviors among regional areas. These result suggests that traffic safety policy and practice should be prepared based upon the peculiarities of regional area. We discussed these resulte in terms of the regional traffic policy and the suggestions for future studies were added.

• 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.

• Archives of design research
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• v.20 no.3 s.71
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• pp.151-162
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• 2007

How can new media devices and networks provide an effective response to the world's growing sector of cultural and historically-minded travelers? This study emerged from the question of how mobile handsets can change the nature of cultural and historical tourism in ubiquitous city environments. As wireless network and mobile IT have rapidly developed, it becomes possible to deliver cultural and historical information on the site through mobile handset as a tour guidance system. The paper describes the development of a new type of mobile tourism platform for site-specific cultural and historical information. The central objective of the project was to organize this cultural and historical walking tour around the mobile handset and its unique advantages (i.e. portability, multi-media capacity, access to wireless internet, and location-awareness potential) and then integrate the tour with a historical story and role-playing game that would deepen the mobile user's interest in the sites being visited, and enhance his or her overall experience of the area. The project was based on twelve locations that were culturally and historically significant to Korean War era in Busan. After the mobile tour game prototype was developed for this route, it was evaluated at the 10th PIFF (Pusan International Film Festival). After use test, some new strategies for developing mobile "edutainment content" to deliver cultural historical contents of the location were discussed. Combining 'edutainment' with a cultural and historical mobile walking tour brings a new dimension to existing approaches of the tourism and mobile content industry.

• Archives of design research
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• v.20 no.1 s.69
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• pp.5-20
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• 2007

The aim of this research is to find out the flows of mega-trends and design trends by analyzing the factors that influence trend and design trends in the late 20th century. Moreover, it is to forecast and recommend design color trends by evaluating color trends in design trends for the near future. Secondary and primary research were used in parallel. In the late 20th century, mega-trends were analyzed from secondary research based on PEST. Design trends were analyzed from case studies in fashion, space, product and visual design. On this basis, design color trends were analyzed. Also, color trends were forecast for the near future. The results are as follows. Firstly, the main trends in the late 20th century were 'female thinking', 'back to the nature' and 'heaven of peace'. Second, main design trends in the 1970s were modernism, post-modernism and high-tech. In the 1980s, with those of the 1970s, ecology was introduced In the late 1980s. In the 1990s, modernism rose again and ecology had an influence. The trends of 'female thinking' and 'back to the nature' controled the design in the early 2000s. Third, design colors in the late 20th century changed from Red to Purple Blue. Tones changed from 'grayish' to 'dull' Finally, it was forecast that Purple Blue, Yellow Red and Green colors with 'grayish', 'dull' and 'deep' tones were going to be used mainly in the near future. Also, achromatic colors with female and warm nuances would be reflected in design parts. This research will be very useful in that it has built a concrete database reflected on design trends forecasting in the near future by organizing academically a methodology to identify trends reflected on design and identifying relation between mega-trends and design trends based on analyzing factors that influence trend.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.6
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• pp.41-51
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• 2015

The purpose of the Follies that were constructed for the Gwangju-Biennale were for urban regeneration, to activate the empty old-town areas, and to strengthen the tradition and sense of place of the city. However, the ten Follies constructed around the wall of the old castle reveal many problems including that of leaving Follies alone instead of actively using them, damage to shop-keepers nearby, and pedestrian inconvenience, which is different from the original purposes. This study is meant to help understand the source of the negative phenomena, and to offer plans that will be conductive to the role of urban regeneration through activating the Follies and the spaces around them. As results of the investigation, there was no context giving uniformity among the various Follies. Also, the study showed that the insufficience of designers' understanding of the circumference near the Follies and lack of a consensus between the citizens and designers in the process of making the Follies. The crucial solution for solving these problems, and bringing to life the original purpose of creating the Follies was derived as applying "human activity" to the Follies. This study suggested 'street performance' as an effective device for application to human activity. While a Folly has no fixed function, the development of space program categories based on the applied characteristics of each Folly, and the simulation thereof showed effective potential for attracting people and activating those stagnated spaces. Recently, Gwangju city depicted the second Follies in applications such as reading roon, toilet, and movable food cart, which have clear purpose and different characteristics from the first ones. However, the first Follies will not be moved or demolished. As they are located around the National Asia Culture Center, some of them are supposed to be used to view the center. Consequently, a counterplan for the continuous and efficient use of those Follies is needed. Gwangju has a plan for the installation of 100 Follies throughout the city and it is expected that this study will be a meaningful guide line for improved Follies in the future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.3
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• pp.247-262
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• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.