• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.319-325
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• 2018

The use of 3D printing (Additive Manufacturing) technology has expanded from initial model production to the mass production of parts in the industrial field based on the continuous research and development of materials and process technology. As a representative polymer material for 3D printing, the polyamide-based material, which is one of the high-strength engineering plastics, is used mainly for manufacturing parts for automobiles because of its light weight and durability. In this study, the specimens were fabricated using Selective Laser Sintering, which has excellent mechanical properties, and the flexural characteristics were analyzed according to the temperature of the two types of polyamide 12 and glass bead reinforced PA12 materials. The test specimens were prepared in the directions of $0^{\circ}$, $45^{\circ}$, and $90^{\circ}$ based on the work platform, and then subjected to a flexural test in three test temperature environments of $-25^{\circ}C$, $25^{\circ}C$, and $60^{\circ}C$. As a result, PA12 had the maximum flexural strength in the direction of $90^{\circ}$ at $-25^{\circ}C$ and $0^{\circ}$ at $25^{\circ}C$ and $60^{\circ}C$. The glass bead-reinforced PA12 exhibited maximum flexural strength values at all test temperatures in the $0^{\circ}$ fabrication direction. The tendency of the flexural strength changes of the two materials was different due to the influence of the plane direction of the lamination layer depending on the type of stress generated in the bending test.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.44-57
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• 2019

Various studies have been conducted to solve traffic congestions in many metropolitan cities through accurate traffic flow prediction. Most studies are based on the assumption that past traffic patterns repeat in the future. Models based on such an assumption fall short in case irregular traffic patterns abruptly occur. Instead, the approaches such as predicting traffic pattern through big data analytics and artificial intelligence have emerged. Specifically, deep learning algorithms such as RNN have been prevalent for tackling the problems of predicting temporal traffic flow as a time series. However, these algorithms do not perform well in terms of long-term prediction. In this paper, we take into account various external factors that may affect the traffic flows. We model the correlation between the multi-dimensional context information with temporal traffic speed pattern using deep neural networks. Our model trained with the traffic data from TOPIS system by Seoul, Korea can predict traffic speed on a specific date with the accuracy reaching nearly 90%. We expect that the accuracy can be improved further by taking into account additional factors such as accidents and constructions for the prediction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.434-442
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• 2019

Low Impact Development(LID) techniques has been attracting attention as a countermeasure to solve frequent flood damage in urban areas. LID is a techniques for returning to the natural hydrological cycle system by infiltrating the runoff from the impervious surface into the soil. The Bio-retention, one of the LID element technology has outflow reduction effect by reserving and infiltrating storm water runoff from watersheds. Recently, a number of studies have been carried out as interest in the reduction of storm water runoff and non-point pollutants in Bio-retention has increased. However, quantitative analysis on the outflow reduction of Bio-retention applied to small watershed is insufficient. In this study, Bio-retention model was constructed in a small watershed using K-LIDM which is capable of hydrologic analysis. When the storage capacity was increased or dividing the Bio-retention and watershed, the outflow reduction effect was 20% according to the storage capacity increase and 5~15% in the distributed Bio-retention system. The results of this analysis will be used as the basic data of future Bio-retention research related to watershed characteristics, vegetation type and soil condition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.96-110
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• 2018

As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.109-118
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• 2019

The purpose of this study is to deliver both market-practical and civil-centric political implication for sharing economy by investigating the nature of consumer-adoption for car-sharing service. With the global interest and market proliferation of the sharing economy, various service models for sharing idle resources have also been released in Korea. Particularly, in case of car sharing service, public - private partnership projects are spreading rapidly in various local governments including Seoul, along with the growing demand for alternative transportation system centering on the urban area. This study conducted an empirical study on the process of accepting the car sharing service by analyzing the data collected from users of the car sharing service "Sharing Car(Nanum Car)" of Seoul Metropolitan Government. A survey was conducted on 281 users in their twenties who are in the age of main use among the experienced users of the "Sharing Car(NaNum)" residing in Seoul. The result of analysis on the relationship between these users' perceived value and intention to use the vehicle sharing service would provide implications for establishing consumer(citizen)-centeric policies as well as market implications.

• Journal of the Korean Society for Environmental Technology
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• v.19 no.6
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• pp.576-585
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• 2018

Systematic management during the whole life cycle from construction to operation and maintenance is very important for the seven underground pipelines (waterworks, sewerage, electricity, telecommunications, gas, heating, oil including waterworks and sewerage). Especially, it is the construction process that affects the whole life cycle of underground buried pipeline. In order to construct a new city or to maintain different underground pipes, it is always necessary to dig the ground and carry out construction and related work. There is a possibility that secondary and tertiary breaks frequently occur in the pipeline construction process after the piping constructed first in this process. To solve this problem, a system is needed which can monitor damage in real time. However, the supply of electric power for continuous operation of the system is limited according to the environment of underground buried pipelines, so it is necessary to develop a stable electric power supply system using natural energy rather than existing electric power. In this study, we developed a system that can operate the pipeline monitoring system for long time (24 hours and 15 days) using natural energy using wind and solar light.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.163-168
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• 2021

The growth experiment under shading condition has been performed to understand the eco-physiological responses of crops to light in terms of photosynthesis. There are two types of shading: overall shading and partial shading. In this study, the chlorophyll fluorescence of soybean was observed under the overall shading of the box made by polyresin and the partial shading at agrivoltaic system. The overall shading condition during vegetative growth induced lower SPAD and Electron transport rate (ETR). These lower values recovered after removal of shading box. However, the Non-photochemical fluorescence quenching (NPQ) became lower under overall shading and higher under partial shading. Such increase in NPQ limited crop photosynthesis even though the ETR was almost same to the control without shading treatment. Under the condition of partial shading, the values of SP AD and ETR for soybean did not change. However, the NPQ was higher than control condition. This suggests that the crop photosynthesis under both types of shading would be decreased by different eco-physiological processes which are the lower ETR in overall shading and the higher NP Q in partial shading despite the reduced light under shading conditions.

• Agribusiness and Information Management
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• v.13 no.1
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• pp.26-40
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• 2021

During the pandemic status of COVID-19 since 2019 December, demands and attention on various convergence services with non-contact technologies and social adoption are increasing. Along with these increased demands and attention, the digital divide issues should be concerned to understand the informatization degrees of rural area residences, the elderly, the disabled, and the low-income. Furthermore, rural area residences may be the elderly, the disabled, and the low-income also. It may mean that the rural area should be considered as in noticeable status of the digital divide. This study focuses on the policy alternatives to reduce the digital divide in rural areas with a literature review methodology and on the factors on informatization issues in rural areas. For the aims, this study analyzes the EU cases of informatization in rural areas to find out the advantages and disadvantages of the suggested policies. As the analysis result, it is clear that the EU countries try to enhance the economic and growth powers rather to reduce the digital divide gaps. Also, it can be considered that the EU countries focus on supporting the rural area to adopt the non-contact information services newly rather on maintaining the IT education services and the infrastructures in off-line environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.58-64
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• 2021

As the number of registered vehicles increases, traffic congestion will worsen worse, which may act as an inhibitory factor for urban social and economic development. Through accurate traffic flow prediction, various AI techniques have been used to prevent traffic congestion. This paper uses the data from a VDS (Vehicle Detection System) as input variables. This study predicted traffic flow in five levels (free flow, somewhat delayed, delayed, somewhat congested, and congested), rather than predicting traffic flow in two levels (free flow and congested). The Catboost model, which is a machine-learning algorithm, was used in this study. This model predicts traffic flow in five levels and compares and analyzes the accuracy of the prediction with other algorithms. In addition, the preprocessed model that went through RandomizedSerachCv and One-Hot Encoding was compared with the naive one. As a result, the Catboost model without any hyper-parameter showed the highest accuracy of 93%. Overall, the Catboost model analyzes and predicts a large number of categorical traffic data better than any other machine learning and deep learning models, and the initial set parameters are optimized for Catboost.

• Journal of the Korean Regional Science Association
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• v.36 no.4
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• pp.3-23
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• 2020

This study aims to conceptualize the settlement inclusivity for overcoming social exclusion and the decline in quality of life of older people and to examine its effects on their mental health. The concept of the settlement inclusivity for older people focuses on the immediate environment around the place where they live. We proposed two domains for the conceptual framework; social domain that provides opportunities for community cohesion; spatial domain that provides security of residential area and access to basic services within walking distance. The social domain was represented by participation and interdependence, while the spatial domain by security and accessibility in the settlement inclusivity. Zero-inflated negative binomial regression model was constructed with 2017 National Survey of Older Koreans data to analyze the factors influencing depressive symptoms of older adults. The empirical results demonstrate that increased level of neighborhood network and social participation is associated with a decrease in the number of depressive symptoms. In addition, higher satisfaction in neighborhood environment and good accessibility to public transport/stores are associated with fewer depressive symptoms. Finally, housing condition and home ownership have a moderating effect on the relationship between social network/participation and depressive symptoms level, whereas they have no direct effects on depressive symptoms. This study demonstrates multi-dimensionally and mutually significant associations between settlement inclusivity and depressive symptoms for older people providing implications for urban planning and policies to improve mental well-being of older population.