• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.194-203
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• 2021

With the recent increase in maintenance works on water and sewer pipes as well as district heating supply pipes, pavement cutting work using pavement cutter is on the rise. The pavement cutting operation generates considerable dust (cutting sludge) as well as noise; therefore, it is necessary to apply eco-friendly technologies that have low noise and dust recovery capability. Thus far, various equipment for recovering dust have been developed; however, there is a limitation in that the environmental friendliness is not quantified. Therefore, in this study, we developed a low-noise, dust-recovery type pavement cutter that can fundamentally remove the causes of environmental hazards such as noise and dust and evaluated the eco-friendliness of the pavement cutting process performed by this cutter. To this end, an integrated water cooling-sludge recovery system composed of a vacuum device and a sludge suction unit was developed, and the developed system was applied to a pavement cutter. Subsequently, the developed equipment was applied to the test bed, and data related to its eco-friendliness were collected and evaluated. The results showed that the cutting sludge recovery rate of the developed equipment was greater than 83%, the noise level was approximately 82 - 83 dB, and the sound power level was 115 dB. The results of this study will be used as basic data to develop improved pavement cutters in the future with improved cutting sludge recovery performance and lower noise.

• Journal of the Korea Fashion and Costume Design Association
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• v.19 no.4
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• pp.93-104
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• 2017

This study is a basic study to develop shoe last design technology to enhance and revitalize the competitiveness of the handmade shoes. In-depth interviews were conducted with four manufacturers in Seongsu-dong to identify the production status and design technology of shoe lasts. The result of the research is as follows. Firstly, shoe lasts for adults are produced at intervals of 5mm between 245mm-285mm for men's shoes, and between 220-260mm for women's shoes. The production rate of women's shoes was high in the order of general type, boot type, and sandal type while men's shoes mainly produce general type. Secondly, the master last size and ball girth rating for men's and women's shoes were analyzed to EE-EEE grade at 260mm and D grade at 235mm. The length of the master last for men's shoes is 276-290mm, the heel width is 60-65mm, the ball width is 88-90mm, the ball girth is 250mm, and the waist girth is 248mm. The length of the master shoe last for women's shoes is 236-245 mm, the heel width is 50-55mm, the ball width is 78-80mm, the ball girth is 211~213mm, and the waist girth is 213~215mm. Thirdly, the last grading deviation is 5mm in length, the heel width is 0.5mm, the ball girth is 3.5mm, and the ball with is 1.2mm. The ball girth dimensions of Oxford type, slip-on type, and sneakers type are made at 250mm, 248mm, and 245mm for men's shoes. For women's shoes, the ball girth dimensions of pump type, loafer & boot type, and sandal type are made at 211~213mm, 214~215mm, and 211mm. Fourthly, t+he construction of the automation system is insufficient and almost completely depends on manual production.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.409-418
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• 2021

As the amount of construction for aerial photography increases, the need for automation of quality inspection is emerging. In this study, an experiment was performed to classify or detect clouds in aerial photos using deep learning techniques. Also, classification and detection were performed by including satellite images in the learning data. As algorithms used in the experiment, GoogLeNet, VGG16, Faster R-CNN and YOLOv3 were applied and the results were compared. In addition, considering the practical limitations of securing erroneous images including clouds in aerial images, we also analyzed whether additional learning of satellite images affects classification and detection accuracy in comparison a training dataset that only contains aerial images. As results, the GoogLeNet and YOLOv3 algorithms showed relatively superior accuracy in cloud classification and detection of aerial images, respectively. GoogLeNet showed producer's accuracy of 83.8% for cloud and YOLOv3 showed producer's accuracy of 84.0% for cloud. And, the addition of satellite image learning data showed that it can be applied as an alternative when there is a lack of aerial image data.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.139-147
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• 2018

This study starts with the consciousness of what should be the public pension service that meets the 4th Industrial Revolution era. To do this, we review the current status of non-facing services of domestic and foreign public institutions, and draw out implications for revitalizing non-facing services of the National Pension over the medium to long term. First, we reviewed the status of non-face-to-face service and the authentication method of the National Pension Service. Next, we reviewed the status of non-facing services in public pension and private agencies in the United States, the United Kingdom, Canada, and Australia. Based on the results of the analysis, we needs to analyze the impact of the 4th Industrial Revolution on the National Pension Service and extract future strategies, to expand channels of non-facing by business, to introduce PinTech as a non-facing authentication method, and to propose a unified service channel through the construction of an internet integrated portal. In the 4th industrial revolution era, it is possible to secure the connectivity of government portal for civil affairs and intelligence and automation introducing artificial intelligence robots.

• Journal of the Korean GEO-environmental Society
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• v.21 no.10
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• pp.11-16
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• 2020

Korea's agricultural reservoir is one of the country's major infrastructures and plays an important role in people's lives. However, aging reservoirs are a risk for life and property. Currently, large and small dams and reservoirs have been constructed nationwide for more than 40 years of aging. Dams and reservoirs built nationwide are managed by various institutions. Therefore, it is difficult to manage all dams and reservoirs due to cost and time. Managers in the field with less management personnel and lack of expertise should be able to quickly identify risk factors for multiple reservoirs. In this study, risk factors such as seepage, leakage, settlement slide, crack and erosion were selected. To assess the risk of the items, we used the analytical hierarchical process (AHP), one of the Multi-Criteria Decision Making (MCDM) methods. The analysis showed that seepage has the greatest impact on reservoir collapse. It is judged that the priority of detailed diagnosis can be determined by evaluating the risk of dam reservoir collapse in a convenient way in advance using the calculated weight.

• Information Systems Review
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• v.11 no.2
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• pp.147-167
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• 2009

As global climate changes, the interest in environmental crisis is increasing and a number of international agreements and regulations against this crisis are being established. Global information technology(IT) corporations are building their own pro-environmental green IT strategies to cope with the regulatory measures. Green IT broadly refers to pro-environmental technologies designed to replace hazardous materials, maximize energy effectivity, and find alternative energies. In the current stage of the IT industry development, Green IT specifically refers to the technologies that deal with the server heat generation and the energy reduction in data center. This study defines the concept of Green IT and reviews its origin and necessity. Then, it examines the issues regarding Green IT industry in Korea as well as other countries and compares the Green IT strategies developed in each country. Reviewing the recent development of IT and data center market enables us to see that overall Green IT strategies focus on the establishment of Green Internet Data Centers. Therefore, this study analyzes the cases in which some domestic and foreign corporations introduced Green Data Centers in order to examine the protocol and legal requirements for building Green IT, the aspects of environmental evaluation and design, and specific strategies for launching Green IT strategies and its future assignments. The conclusions of this study are as follows. First, to introduce Green Data Center as a strategy to build Green IT, the government and corporations should cooperate with each other. Partial introduction at the initial stage is desirable because, through the process, mutual trust between the two parties can be built more smoothly. Second, CEO's determination to build Green IT and continue its operation is indispensable. CEO's are required to have clear understanding as to why Green IT needs to be built and how it should be constructed. Those who initiate the construction of Green Data Center for Green IT need to know the definition and necessity of Green IT while at the same time understanding the implicit meanings of Green IT. They also need to be aware of future-oriented values of Green Data Center and readjust their corporate business activities in the pro-environmental direction. Finally, not only the CEOs' pro-environmental activities but also the change of mind on the part of all corporate employees is required to realize Green IT. It should be remembered that pro-environmental Green IT starts with minor activities.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.97-110
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• 2007

A laser scanning technique has been attracting much attention as a new technology to acquire location information. This technique might be applicable to a wide range of areas, most notably in geomatics, due to its high accuracy of location and automation of high-density data acquisition. A alignment information extraction system on highway has been developed in this study by utilizing the advantages of the laser scanning technique. The system can accurately interpret the alignment information of highway and can be applied to actual works. To develop the alignment information extraction system on highway, an algorithm that can automatically separate a horizontal alignment into a straight line, a transition curve, and a circular curve was developed. It can increase its efficiency compared to the conventional methods. In addition, an algorithm that can automatically extract design elements of horizontal and vertical alignments of highway was developed and applied to an object highway. This yielded higher practicality with more accurate values compared to those from previous studies on the extraction of design elements of highway alignment. Furthermore, the extracted design elements were used to perform a virtual driving simulation on the object highway. Through this, data were provided for a visual judgment for judging visually whether the topography and structures were harmonized in a three-dimensional manner or not. The study also presents data that can serve as a basis to determine highway surface freezing sections and to analyze three-dimensional sight distance models. Through the establishment of a systematic database for diverse data on highway and the development of web-based operating programs, an efficient highway maintenance can be ensured and also they can provide important information to be used when estimating a highway safety in the future.