• Clean Technology
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• v.27 no.4
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• pp.297-305
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• 2021

In the domestic aluminum industry, the extrusion process is a major process accounting for more than 40% of the total production. However, most domestic aluminum extrusion companies produce aluminum using old equipment that is more than 30 years old. Extrusion press is when the equipment is not replaced before the wear and breakage of major parts occur, reducing productivity and increasing the defect rate compared to new equipment. The old extrusion press often loses part drawings, so it is difficult to repair them properly on-site and to remanufacture them due to the lack of technical skills for maintenance. Therefore, a systematic remanufacturing plan must be designed from dismantling the equipment. In this study, remanufacturing FMEA was devised to remanufacture old extrusion press. The risk priority was analyzed by considering the degree of damage to the recycled parts, the cycle due to breakage/damage during the extrusion process, and the value of recycling resources due to remanufacturing. To standardize the remanufacturing process, remanufactured FMEA was performed through part analysis according to the structural analysis of the extrusion press. In addition, remanufacturing priorities were selected for each part, while remanufacturing itself was studied for efficiency of resource circulation and product quality stabilization.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.11-19
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• 2021

A software system is required to change during its life cycle due to various requirements such as adding functionalities, fixing bugs, and adjusting to new computing environments. Such program code modification should be considered as carefully as a new system development becase unexpected software errors could be introduced. In addition, when reusing open source programs, we can expect higher quality software if code changes of the open source program are predicted in advance. This paper proposes a Convolutional Neural Network (CNN)-based deep learning model to predict source code changes. In this paper, the prediction of code changes is considered as a kind of a binary classification problem in deep learning and labeled datasets are used for supervised learning. Java projects and code change logs are collected from GitHub for training and testing datasets. Software metrics are computed from the collected Java source code and they are used as input data for the proposed model to detect code changes. The performance of the proposed model has been measured by using evaluation metrics such as precision, recall, F1-score, and accuracy. The experimental results show the proposed CNN model has achieved 95% in terms of F1-Score and outperformed the multilayer percept-based DNN model whose F1-Score is 92%.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.413-418
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• 2020

It is necessary to manage the prediction accuracy of the machine learning model to prevent the decrease in the performance of the grid network condition prediction model due to overfitting of the initial training data and to continuously utilize the prediction model in the field by maintaining the prediction accuracy. In this paper, we propose an automation technique for maintaining the performance of the model, which increases the accuracy and reliability of the prediction model by considering the characteristics of the power grid state data that constantly changes due to various factors, and enables quality maintenance at a level applicable to the field. The proposed technique modeled a series of tasks for maintaining the performance of the power grid condition prediction model through the application of the workflow management technology in the form of a workflow, and then automated it to make the work more efficient. In addition, the reliability of the performance result is secured by evaluating the performance of the prediction model taking into account both the degree of change in the statistical characteristics of the data and the level of generalization of the prediction, which has not been attempted in the existing technology. Through this, the accuracy of the prediction model is maintained at a certain level, and further new development of predictive models with excellent performance is possible. As a result, the proposed technique not only solves the problem of performance degradation of the predictive model, but also improves the field utilization of the condition prediction model in a complex power grid system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.570-578
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• 2019

In this era of big data, a variety of government organizations are trying to create new added value via Information Integration. Therefore, several projects related to government agencies' information sharing have activated system connection/integration. The risk factors of system operation, however, have increased as the volume of Information Integration System grows. The interference in information sharing is predicted to affect the operation of the agencies, and the issue will grow even worse with massive impact on civil society when the agency operation is interrupted due to system failures in terms of infrastructure, software, data quality, and security. Diverse studies related to the maintenance of Information System have been conducted, but there is currently no evaluation framework for the operational system of Information Integration between various government agencies. In this respect, this study distinguishes each of the Information System components, Data, IT, People, Process, systematizes with Plan-Do-See, and finally presents a maturity model for Information Integration. Nine derived processes were analyzed through interview and questionnaires from Information Integration System officials, further suggesting maturity stage applying CMMI. This model allows diagnosis of the maturity level of an Information Integration System, and is expected to be utilized as resource for improving organizational processes.

• Journal of the Korean Institute of Rural Architecture
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• v.21 no.3
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• pp.69-75
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• 2019

The purpose of this study is to provide the conservation management direction about cultural landscape of the traditional villages in the area of Huizhou through the importance-performance analysis. The results of the survey on the importance - performance of 261 people who had many visits to various cultural landscapes of Huizhou villages such as Hongchun, Sidichun etc. are as follows. It was appeared that the item of 'good air' is the highest level of importance and satisfaction and is best condition. The item of 'historical conservation' is the high level of importance, but the level of satisfaction is low, so continuous improvement is necessary. The item of 'Old garden conservation' has high satisfaction but low importance, so it needs to improve its importance through subsequent improvement. The item of 'Keeping of old cemetary and old tower' has low importance and satisfaction but it is above average, so continuous maintenance is needed. The items of 'Preservation of stone gate' and 'Preservation of famous man's birth house' all have slightly higher satisfaction and lower importance. Both items are highly satisfied with their importance, so they should avoid excessive efforts and maintain the present status. Satisfaction with the item of 'water environment and water quality' was the lowest, and the problem of the present condition is the most serious, and a major improvement is needed. The importance and satisfaction of 'Commercial development of old villages' was the lowest among all items. This item is causing serious problems and should provide an overall improvement way to drastically improve the importance and satisfaction. Concentration is necessary to improve the environment of the whole villages, to protect the ecological plants and animals in old villages, to transfer and improve the culture of old villages, to maintain sustainability of the villages, and to protect old temple and old rock in old villages. As the level of satisfaction with sustainability is the lowest in the part of 'Concentrate here', there is a great concern about sustainability. Therefore, it is necessary to focus on sustainability and concentrate on sustainable development.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.3
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• pp.110-121
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• 2021

The importance of tidal flats lost due to industrialization has recently received attention, and attention is being paid to the creation of artificial tidal flats and maintenance of natural tidal flats. However, there is still a lack of understanding about the behavioral characteristics of mud, mud, and sand that form tidal flats. Although research on the movement characteristics of mixed soils such as tidal flats has been conducted through field investigations and hydraulic experiments, interest in developing a numerical model based on these results has not yet reached. In this paper, the purpose of this paper is to establish a mixed soil model that can efficiently manage the low quality of the tidal flats. In constructing a model for reproducing the surface movement of mixed soil, the numerical stability of the reproduction and movement of sand and mud constituting the mixed soil in the numerical model should be considered first, so first, the volume of sand and mud constituting the mixed soil A mixed soil model representing the relationship was proposed based on a topographical diagram representing the geometric structure of the mixed soil. In order to consider the dry bulk density of the mixed soil, it was possible to consider the dry bulk density of the mud by introducing the water content of the mud containing water. In addition, it was confirmed that the mud and sand movement calculation according to the slope collapse of the mixed soil was stably performed through the calculation of the slope collapse of the mixed soil through the numerical analysis model to which the proposed mixed soil model was applied.

• Journal of Wetlands Research
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• v.23 no.1
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• pp.35-43
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• 2021

The application of nature-based solutions, such as low impact development (LID) techniques and green infrastructures, for stormwater management continue to increase in urban areas. Plants are usually utilized in LID facilities to improve their pollutant removal efficiency through phytoremediation. Plants can also reduce maintenance costs and frequency by means of reducing the accumulation of pollutants inside the facility. Plants have long been used in different LID facilities; however, proper plant-selection should be considered since different species tend to exhibit varying pollutant uptake capabilities. This study was conducted to investigate the pollutant uptake capabilities of plants by comparing the dry matter and nutrient contents of different plant species in roadsides, LID facilities, and landscape areas. The dry matter content of the seven herbaceous plants, shrubs, and arboreal trees ranged from 60% to 90%. In terms of nutrient content, the total nitrogen (TN) concentration in the tissues of herbaceous plants continued to increase until the summer season, but gradually decreased in the succeeding periods. TN concentrations in shrubs and trees were observed to be high from early spring up to the late summer seasons. All plant samples collected from the LID facility exhibited high TP content, indicating that the vegetative components of LID systems are efficient in removing phosphorus. Overall, the nutrient content of different plant species was found to be highly influenced by the urban environment which affected the stormwater runoff quality. The results of this study can be beneficial for establishing plant selection criteria for LID facilities.

• Journal of Wetlands Research
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• v.23 no.1
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• pp.44-53
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• 2021

Urban stormwater runoff contains heavy metals that accumulate in on-site treatment systems, thus resulting to facility deterioration and maintenance problems. In order to resolve these problems, low impact development (LID) technologies that promote natural materials circulation are widely used. LID facilities are capable of treating heavy metals in the runoff by means of plant uptake; however, the uptake or phytoremediation capabilities of plants have not been studied extensively, making it difficult to select the most suitable plant species for a certain LID design. This study investigated the vegetative components of an LID facility, roadside plants, and plants in landscape areas with different heavy metal exposure and frequency to determine the uptake capabilities of different plant species. The plants harvested inside the LID facilities and roadsides with high vehicular traffic exhibited greater heavy metal concentrations in their tissues as compared with the plants in landscape areas. Generally, the accumulation of heavy metals in the plant tissues were found to be influenced by the environmental characteristics (i.e. influent water quality, air pollution level, etc.). Dianthus, Metasequoia, Rhododendron lateritium, and Mugwort were found to be effective in removing Zn in the urban stormwater runoff. Additionally, Dianthus, Metasequoia, Mugwort, and Ginkgo Biloba exhibited excellent removal of Cu. Cherry Tree, Metasequoia, and mugwort efficiently removed Pb, whereas Dianthus was also found to be effective in treating As, Cr, and Cd in stormwater. Overall, different plant species showed varying heavy metal uptake capabilities. The results of this study can be used as an effective tool in selecting suitable plant species for removing heavy metals in the runoff from different land use types.

• Journal of the Korean Regional Science Association
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• v.38 no.1
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• pp.21-32
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• 2022

The purpose of this study is two things. First, it is to develop and demonstrate a sharong taxi platform. To this end, the implications for platform development were derived by analyzing consumers' perceptions of existing taxi services using IPA. As a result, abnormal business activities and safe services in the maintenance area were found to be safe rides and easy rides in the key improvement area. Safety such as usage fee level and driver information provision were derived in the areas subject to improvement, and friendly response and internal and external cleanliness were derived in the areas of excessive investment. The second purpose of this study is to estimate the value given to users for sharing taxi service platforms using the CVM. As a result of estimating the value of the demonstration service of the shared taxi platform developed through this study, the WTP was 3,621 won/per household/per year when expanding throughout Gimhae-si, and 2,515 won/per household/per year. Compared to the willingness to pay for empirical services, only 69.5% of the willingness to pay for the spread project in Gimhae-si. This is the result of a combination of service spread to an unspecified number of people and concerns about service quality due to spatial expansion. This suggests that it is necessary to build data through continuous demonstration and to carefully build a roadmap for spread by upgrading services based on this.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.194-208
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• 2021

The Hwanggang Dam in North Korea is located upstream of the Imjin River which is a shared river in the border area. It is known to have a reservoir capacity of 350 million cubic meters and releases a discharge primarily for generating hydroelectric power and partly for transferring to the Yesung River basin. Due to the supply of water from the Hwanggang Dam to another basin, the flow of the Imjin River has decreased, which has a negative impact on the water supply, river maintenance flow, water quality, and ecological environment in Korea. However, due to the special national security issue of the South and North Korea border region, the hydrological data is not shared, and the operation method of the Hwanggang Dam is unknown, so there is a risk of damage to the southern part of the downstream area. In this study, the monthly diversion as the long-term runoff concept was derived through the calibrated hydrological model based on optical remotely sensed Images and water balance analysis. As a result of the water balance analysis from January 2019 to September 2021, the average diversion of the Hwanggang Dam was 29.2m³/s, which is equivalent to 922 million tons per year and 45.6% of the annual inflow of 2.02 million tons into the Hwanggang Dam.