• Journal of the Korean Institute of Landscape Architecture
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• 제46권2호
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• pp.27-36
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• 2018

This study suggests the necessity of behavior analysis as changes to a park environment to reflect user desires can be implemented only by grasping the needs of park users. Online data (blog) were defined as the basic data of the study. After collecting data by 5 - year units, data mining was used to derive the characteristics of the time series behavior while the significance of the online data was verified through social network analysis. The results of the text mining analysis are as follows. First, primary results included 'walking', 'photography', 'riding bicycles'(inline, kickboard, etc.), and 'eating'. Second, in the early days of the collected data, active physical activity such as exercise was the main factor, but recent passive behavior such as eating, using a mobile phone, games, food and drinking coffee also appeared as a new behavior characteristic in parks. Third, the factors affecting the behavior of park users are the changes of various conditions of society such as internet development and a culture of expressing unique personalities and styles. Fourth, the special behaviors appearing at Olympic Park were derived from educational activities such as cultural activities including watching performances and history lessons. In conclusion, it has been shown that people's lifestyle changes and the behavior of a park are influenced by the changes of the various times rather than the original purpose that was intended during park planning and design. Therefore, it is necessary to create an environment tailored to users by considering the main behaviors and influencing factors of Olympic Park. Text mining used as an analytical method has the merit that past data can be collected. Therefore, it is possible to form analysis from a long-term viewpoint of behavior analysis as well as to measure new behavior and value with derived keywords. In addition, the validity of online data was verified through social network analysis to increase the legitimacy of research results. Research on more comprehensive behavior analysis should be carried out by diversifying the types of data collected later, and various methods for verifying the accuracy and reliability of large-volume data will be needed.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제38권1호
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• pp.81-90
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• 2018

The purpose of this study is to evaluate the effect of downward speed limit of urban arterial roads at 29 sites in Busan Metropolitan Police Agency to reduce road traffic accidents from '10 to '15. As a result of analyzing the traffic accidents occurred for 1~3 years after the decrease in the speed limit, the number of traffic accidents decreased by 3.09% and the number of injured persons decreased by 8.76%, but the number of deaths decreased by 36.73% The results of this study are as follows. The average speed reduction rate of 6.31km/h was decreased by investigating the change of the vehicle speed before and after the downward speed limit, and the change of average speed was statistically significant in most of the sections. The rate of compliance with the speed limit increased by 10.26% p, which is considered to have greatly improved overall traffic safety. A survey conducted by residents near the target area with a lower speed limit showed that 57.9% of the respondents felt the driving speed of the vehicle was lowered. However, this project was focused on vehicles with limited speed road signs and traffic safety signs, Only 25.8% of respondents said walking safety was improved. In the future, it is necessary to consider the safety of pedestrians by improving roads around roads such as road curvature and separation. In addition, there is a clear positive result in terms of decreasing the fatal accidents in the downward speed limit zone of Busan Metropolitan Subway. However, more detailed analysis is needed for the 29 accidents. Therefore, it is expected that traffic practitioners will be able to utilize it as a basis to increase the accident reduction effect by setting an appropriate speed limit based on the easy and objective grounds.

• Korean Journal of Heritage: History & Science
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• 제42권1호
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• pp.100-121
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• 2009

This study is subjected to those gardens of the Korean Folk Village 'Oeam-Ri' designed in 1920s. - transitional period of traditional gardens - and define socio-cultural change's influences and through documents on garden design, descendant's testimony and measured drawings, to understand that period's garden culture's characteristics according to garden design elements. This study applied following analysis methods and procedures to derive out characteristics of transitional garden culture. Analysis on socio-cultural characteristics in 1920s. Analysis on actual condition of transitional garden's design. In this point Outline of the Garden, Space formation, Garden designing elements are (1) water landscape, (2) plant, (3) structures, (4) paving, to derive out characteristics of the transitional garden. The results follow as below; First, during the transitional period 1920s, the economical development, fueled by opening nation's door to foreign countries and indication of collapse of statue systems together with idea of practical science and Enlightenment Thought, was element of changes in garden style. Second, Garden Designers of transitional gardens in 'Oeam-Ri' were limited to upper class of the society. They were wealthy enough to maintain their high social statue in rapidly changing society. As results, tendency of returning to nature developed gardens located in a site of scenic beauty and development of geographical features arranging techniques, and also showed copying foreign styles. Third, arrangement of garden and space composition, in most cases, composed of buildings and yards. Changes in water landscape features and garden spaces are centered to main-yard. Major changes of the garden spaces are water landscapes and plants that showing foreign influences. Fifth, scenic appearance techniques appears with dense garden space and emphasizing visual scenic view. Sixth, the characteristics of transitional garden design techniques are development of geographical feature arranging techniques, changes and mixture of the materials and garden types, emphasizing garden's decorative beauty, change of concept of yard within house into garden, changes from 'borrowing of landscapes' to 'selecting landscapes', changes of front garden from emptiness to fullness, changes of attitudes of enjoying gardens from 'staying calm in the garden' to 'moving or walking in the garden', changes to inner-oriented view, and changes from 'just watching and enjoying the nature' to 'enjoying specific objects'. This study is one of the efforts to restore the identity of Korean Traditional Garden by approaching and observing modern era which function as bridge between tradition and present day, and we observed transitional aspects of changes of traditional garden into modern garden. Hereafter, more studies will be needed to Modern Garden Design be recognized as part of Korean Garden Design History and these would be author's next assignment.

• Journal of the Korean Institute of Landscape Architecture
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• 제48권6호
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• pp.16-24
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• 2020

The purpose of this study is to analyze the usage behavior of Seoullo 7017, the first public garden in Korea, to understand the usage status by analyzing blogs, and to present usage behavior and improvement plans for Seoullo 7017. From June 2017 to May 2020, after Seoullo 7017 was open to citizens, character data containing 'Seoullo 7017' in the title and contents of NAVER and·DAUM blogs were converted to text mining and socialization, a Big Data technique. The analysis was conducted using social network analysis. The summary of the research results is as follows. First of all, the ratio of men and women searching for Seoullo 7017 online is similar, and the regions that searched most are in the order of Seoul and Gyeonggi, and those in their 40s and 50s were the most interested. In other words, it can be seen that there is a lack of interest in regions other than Seoul and Gyeonggi and among those in their 10s, 20s, and 30s. The main behaviors of Seoullo 7017 are' night view' and 'walking', and the factors that affect culture and art are elements related to culture and art. If various programs and festivals are opened and actively promoted, the main behavior will be more varied. On the other hand, the main behavior that the users of Seoullo 7017 want is 'sit', which is a static behavior, but the physical conditions are not sufficient for the behavior to occur. Therefore, facilities that can cause sitting behavior, such as shades and benches must be improved to meet the needs of visitors. The peculiarity of the change in the behavior of Seoullo 7017 is that it is recognized as a good place to travel alone and a good place to walk alone as a public multi-use facility and group activities are restricted due to COVID-19. Accordingly, in a situation like the COVD-19 pandemic, more diverse behaviors can be derived in facilities where people can take a walk, etc., and the increase of various attractions and the satisfaction of users can be increased. Seoullo 7017, as Korea's first public pedestrian area, was created for urban regeneration and the efficient use of urban resources in areas beyond the meaning of public spaces and is a place with various values such as history, nature, welfare, culture, and tourism. However, as a result of the use behavior analysis, various behaviors did not occur in Seoullo 7017 as expected, and elements that hinder those major behaviors were derived. Based on these research results, it is necessary to understand the usage behavior of Seoullo 7017 and to establish a plan for spatial system and facility improvement, so that Seoullo 7017 can be an important place for urban residents and a driving force to revitalize the city.

• The Journal of the Korean Institute of Forest Recreation
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• 제22권4호
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• pp.59-69
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• 2018

This is a cross-sectional study that suggests ways to activate forest welfare services (FWS) by investigating the infrastructure, service status, and perception on FWS in Korea. In August 2016, a structured email survey was conducted in nation widely. The respondents were mostly directors and general secretary (75.0%). The considerable number (16.3%) of nursing homes (NH) use some floors of the complex buildings that would be difficult to have FWS infrastructure and about 30% of those without forests near the facilities. The directors of NH recognize that FWS has positive effects on the elderly. However, FWS is not an requisite of the longterm care insurance benefit, and so costly and effort-intensive that FWS has not been activated so far. In order to activate FWS in NHs, it is necessary to develop and disseminate the guidelines on FWS that anyone can easily followed. In addition, when the National Health Insurance Corporation evaluates NHs, they should evaluate not only whether there is a wandering or walking space, but also whether it has forest healing factors such as forests. It is also necessary to create a barrier-free environment both inside and outside of NHs, increasing accessibility to the toilet in gardens, paving a passage for wheelchairs and lifts in forests near NHs. Through these efforts, it is expected that FWS will be activated to provide physical, mental rest and comfort, appropriate cognitive stimulation to the NH residents at the end of life.

• Journal of Intelligence and Information Systems
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• 제24권3호
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.