• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.1247-1248
• /
• 2022

Due to rapid urbanization and population growth, it has become crucial to analyze the various volumes and characteristics of pedestrian pathways to understand the capacity and level of service (LOS) for pathways to promote a better walking environment. Different indicators have been developed to measure pedestrian volume. The pedestrian level of service (PLOS), tailored to analyze pedestrian pathways based on the concept of the LOS in transportation in the Highway Capacity Manual, has been widely used. PLOS is a measurement concept used to assess the quality of pedestrian facilities, from grade A (best condition) to grade F (worst condition), based on the flow rate, average speed, occupied space, and other parameters. Since the original PLOS approach has been criticized for producing idealistic results, several modified versions of PLOS have also been developed. One of these modified versions is perceived PLOS, which measures the LOS for pathways by considering pedestrians' awareness levels. However, this method relies on survey-based measurements, making it difficult to continuously deploy the technique to all the pathways. To measure PLOS more quantitatively and continuously, researchers have adopted computer vision technologies to automatically assess pedestrian flows and PLOS from CCTV videos. However, there are drawbacks even with this method because CCTVs cannot be installed everywhere, e.g., in alleyways. Recently, a technique to monitor bio-signals, such as electrodermal activity (EDA), through wearable sensors that can measure physiological responses to external stimuli (e.g., when another pedestrian passes), has gained popularity. It has the potential to continuously measure perceived PLOS. In their previous experiment, the authors of this study found that there were many significant EDA responses in crowded places when other pedestrians acting as external stimuli passed by. Therefore, we hypothesized that the EDA responses would be significantly higher in places where relatively more dynamic objects pass, i.e., in crowded areas with low PLOS levels (e.g., level F). To this end, the authors conducted an experiment to confirm the validity of EDA in inferring the perceived PLOS. The EDA of the subjects was measured and analyzed while watching both the real-world and virtually created videos with different pedestrian volumes in a laboratory environment. The results showed the possibility of inferring the amount of pedestrian volume on the pathways by measuring the physiological reactions of pedestrians. Through further validation, the research outcome is expected to be used for EDA-based continuous measurement of perceived PLOS at the alley level, which will facilitate modifying the existing walking environments, e.g., constructing pathways with appropriate effective width based on pedestrian volume. Future research will examine the validity of the integrated use of EDA and acceleration signals to increase the accuracy of inferring the perceived PLOS by capturing both physiological and behavioral reactions when walking in a crowded area.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.50 no.6
• /
• pp.42-57
• /
• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Journal of the Korean Geotechnical Society
• /
• v.23 no.5
• /
• pp.111-129
• /
• 2007

The standard construction manual of the SDA(Separated Doughnut Auger) piling method was proposed so that the resisting capacity of the augered piles could work effectively. 405 dynamic pile load tests and 30 static pile load tests were performed for 265 test piles, which were installed by the SDA piling method in 33 sites in Korea. The results of the pile load tests showed that the end bearing capacity of the SDA augered piles depended on the property of various soil stratums and did not agree with ones estimated by the existing formula based on several standard design codes. On the basis of the pile load test results, four formulas were presented according to bearing stratums to estimate quantitatively the unit end bearing capacity of the SDA augered piles. The formulas for the unit end bearing capacity of piles on soils or weathered rocks were related to N-value given by SPT(Standard Penetration Test), while the unit end bearing capacity on bedrock was suggested to be more than 1500 $tf/m^2$. The presented formulas were compared with the existing formulas, which were presented by several standard design codes to design the augered piles. In order to use correctly the presented formulas, the quality of Standard Penetration Test should be controlled precisely. Also it is desirable to choose a pilot construction site, where both dynamic and static pile load tests are performed.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.33 no.1
• /
• pp.71-94
• /
• 2022

While small libraries have steadily increased in quantity, parts of qualitative growth such as lack of manpower and poor operation have been pointed out as problems. Accordingly, with the aim of establishing a foundation for linkage and cooperation between public libraries and small libraries, the small library itinerant librarians project has been promoted since 2010, and its scale has been continuously expanding. However, the lack of manpower and poor operation still remain tasks to be solved, and the poor treatment and job environment of itinerant librarians have not improved. In this context, this study aims to examine the problems of small libraries and job problems experienced by itinerant librarians and to find ways to improve the job environment of itinerant librarians based on this. Through the analysis of previous studies, small libraries and net companies were investigated, and in-depth interviews were conducted with participants related to itinerant librarians and small libraries. Through interview data analysis, a total of 17 meaning topics were extracted, including 'lack of work authority', 'lack of work manual', 'lack of communication, community', 'lack of integrated operating system', 'poor treatment and working environment', 'malicious user', and 'lack of belonging'. Based on this, four improvement measures were proposed, including the improvement of the job authority and standard regulations of itinerant librarians, the establishment of a community organization, job security guarantees, and job education reinforcement.

• Journal of Intelligence and Information Systems
• /
• v.29 no.2
• /
• pp.219-240
• /
• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.

• Journal of Christian Education in Korea
• /
• v.73
• /
• pp.117-137
• /
• 2023

This is a case study of an extra-curricular program that designed and implemented maker education based on design thinking to foster a Christian worldview. The program was designed at K university in the course of 10 sessions as following stages; tinkering, providing a special lecture for motivation, finding issues, empathizing, making, sharing and reflecting. A total of 15 students in 5 teams participated in the program, progressed through each stage in the process of solving the problems they found around them so that their neighbors and the creative world could become better. As a result of operating this program, the participants became concerned about their neighbors and community and reflected on the change of perspective of the world from a Christian worldview. As a suggestion for follow-up research and projects, to develop a model of maker education based on design thinking for cultivating a Christian view of the world is proposed in order to support to easy design and management of the program even if there is a lack of professional related knowledge and experience. In addition, it is needed to develop a manual and guide book including a facilitator's role and an assessment tool like a rubric that can give feedback on the performance of the program and make improvement.

• Korean Journal of Ecology and Environment
• /
• v.56 no.2
• /
• pp.161-171
• /
• 2023

The medium-large cladoceran species Simocephalus spp. predominantly occur in habitats with developed aquatic vegetation. Accordingly, due to Simocephalus' high contribution to zooplankton community biomass in the lake's littoral zone and wetland habitats, estimating their biomass is important to understand the matter cycling based on biological interactions within the aquatic food web. In this study, we reviewed the length-weight regression equations used previously to estimate Simocephalus biomass, directly measured S. serrulatus' body specification (length, width and area) and their biomass(dry weight) using instruments such as a microscopic digital camera and a microscale, and performed regression analysis between each other. When S. serrulatus biomass was estimated using the equation (Kawabata and Urabe, 1998) presented in 『Biomonitoring Survey and Assessment Manual』, Korea, errors between estimates and measures were relatively large compared to the S. serrulatus species-specific biomass estimate equation developed by Lemke and Benke (2003). In addition, both equations showed not only increasing trends in error (estimate-measure) with increasing S. serrulatus' body length, but also in error variance among similar-sized individuals. The results of regression analysis with dry weight by body specifications indicated that the most appropriate equation for estimating the biomass of S. serrulatus was derived from the width-dry weight exponential regression equation (R²=0.9555). The review and development study of such species-specific biomass estimation equations for zooplankton can be used as a tool to understand their role and function in aquatic ecosystem food webs.

• The Korean Journal of Franchise Management
• /
• v.9 no.3
• /
• pp.19-29
• /
• 2018

Purpose - Due to the increase in coffee consumption and competition, domestic coffee franchise companies are currently entering the overseas market. Therefore, coffee franchise companies are pursuing a variety of marketing strategies to meet customer needs and gain competitive advantage in overseas markets. From this perspective, overseas franchise companies need to ensure that their servicescapes meet the needs of their overseas customers. For these purposes, the study is to identify the impact servicescapes on customer satisfaction and customer loyalty focused on Global Coffee Franchise Company "C", which extended its business worldwide in Mongolia. Research design, data, and methodology - The data were collected from customers who had visited the stores of 'C' company in Ulaanbaatar, Mongolia. 435 valid questionnaires collected through online survey coded and analyzed using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 24 and SmartPLS 3.0. Result - Firstly, seating comfort, facility aesthetics, and cleanliness, ambient conditions among servicescapes influenced customer satisfaction. Secondly, servicescapes didn't affect the loyalty directly. Third, customer satisfaction had positive effect on loyalty. Fourthly, cleanliness which was ranked lower in Korea had a great effect on customer satisfaction in Mongolia. Fifthly, IPMA(Importance-performance map analysis) shows that the importance of servicescapes is higher for women than for men, and facility aesthetics for female and cleanliness is the most important for male. Conclusions - The results of this study show that there is a positive (+) effect on customer satisfaction in order of cleanliness, ambient conditions, aesthetics, and seating comfort. Therefore, franchise companies considering or advancing into Mongolia should consider importance in order of cleanliness, ambient conditions and aesthetics when entering Mongolia market. For example, franchise managers should select Monday as a "clean day," and all merchants should spend all of their open hours and keep their stores clean in accordance with the head office manual. In addition, franchise managers need to hire a VMD (visual merchandising) experts to build up a physical environment that will effectively highlight the space-specific display of the store so that Mongolian local customers can have a satisfactory climate and aesthetics. And, the IMPA analysis between servicescapes and customer satisfaction shows that women are more susceptible to servicescapes than men. Especially, in the case of women, the importance of esthetics is high, but the performance is low. Thus, if the aesthetics are actively improved, customer satisfaction can be effectively increased.

• Journal of the Korea Computer Graphics Society
• /
• v.29 no.3
• /
• pp.117-125
• /
• 2023

In the development of clothing design through virtual simulation, it is essential to minimize the differences between the virtual and the real world as much as possible. The most critical task to enhance the similarity between virtual and real garments is to find simulation parameters that can closely emulate the physical properties of the actual fabric in use. The simulation parameter optimization process requires manual tuning by experts, demanding high expertise and a significant amount of time. Especially, considerable time is consumed in repeatedly running simulations to check the results of applying the tuned simulation parameters. Recently, to tackle this issue, artificial neural network learning models have been proposed that swiftly estimate the results of drape test simulations, which are predominantly used for parameter tuning. In these earlier studies, relatively simple linear stiffness models were used, and instead of estimating the entirety of the drape mesh, they estimated only a portion of the mesh and interpolated the rest. However, there is still a scarcity of research on non-linear stiffness models, which are commonly used in actual garment design. In this paper, we propose a learning model for estimating the results of drape simulations for non-linear stiffness models. Our learning model estimates the full high-resolution mesh model of drape. To validate the performance of the proposed method, experiments were conducted using three different drape test methods, demonstrating high accuracy in estimation.

• Korean Journal of Construction Engineering and Management
• /
• v.24 no.4
• /
• pp.3-13
• /
• 2023

The purpose of this study is to compare and analyze the performance and work productivity of wet type pavement cutters and sludge suction type pavement cutters (hereinafter referred to as automatic pavement cutters) developed to reduce scattering dust. We first investigated the development status of wet type manual pavement cutters that are mainly used in Korea and automatic pavement cutters, and analyzed the pavement cutting work in detail. And the standard cutting performance was derived by measuring the cutting time by depth by applying the two equipment to the test bed under the same conditions. However, there is a limitation that the data measured in the test bed does not reflect the various variables of the actual pavement cutting site. Therefore, in this study, data was collected through field surveys, and the correlation between cutting distance and time was analyzed, and then a model for calculating the productivity of pavement cutters was presented through simple regression analysis. As a result of comparative analysis of the values derived from the regression equation with the standard cutting performance derived from the test bed, the cutting performance derived through the regression equation showed a similar trend to the standard cutting performance. Finally, we verified the usability of the automated pavement cutter developed by qualitatively analyzing three tasks that are difficult to measure quantitatively but affect productivity.