• Journal of Korean Society of Water and Wastewater
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• v.35 no.2
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• pp.163-174
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• 2021

Heatwaves are one of the most common phenomena originating from changes in the urban thermal environment. They are caused mainly by the evapotranspiration decrease of surface impermeable areas from increases in temperature and reflected heat, leading to a dry urban environment that can deteriorate aspects of everyday life. This study aimed to calculate daily maximum ground surface temperature affecting heatwaves, to quantify the effects of urban thermal environment control through water cycle restoration while validating its feasibility. The maximum surface temperature regression equation according to the impermeable area ratios of urban land cover types was derived. The estimated values from daily maximum ground surface temperature regression equation were compared with actual measured values to validate the calculation method's feasibility. The land cover classification and derivation of specific parameters were conducted by classifying land cover into buildings, roads, rivers, and lands. Detailed parameters were classified by the river area ratio, land impermeable area ratio, and green area ratio of each land-cover type, with the exception of the rivers, to derive the maximum surface temperature regression equation of each land cover type. The regression equation feasibility assessment showed that the estimated maximum surface temperature values were within the level of significance. The maximum surface temperature decreased by 0.0450℃ when the green area ratio increased by 1% and increased by 0.0321℃ when the impermeable area ratio increased by 1%. It was determined that the surface reduction effect through increases in the green area ratio was 29% higher than the increasing effect of surface temperature due to the impermeable land ratio.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.198-200
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• 2003

This study proved if the high resolution satellite imagery of IKONOS is suitable for preparing digital forest cover map. Three methods, the pixel based classification with maximum likelihood (PML), the segment based classification with majority principle(SMP), and the segment based classification with maximum likelihood(SML), were applied to classify and delimitate forest cover of IKONOS imagery taken in May 2000 in a forested area in the central Korea. The segment-based classification was more suitable for classifying and deliminating forest cover in Korea using IKONOS imagery. The digital forest cover map in which each class is delimitated in the form of a polygon can be prepared on the basis of the segment-based classification.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.425-432
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• 2004

In this paper, the results of the numerical analysis for the minimum depth of soil cover have been compared with those of currently suggested codes. Based on this comparison, the minimum depth of soil cover for the structures with long spans was suggested. Results showed that the actual depth of the soil cover required against soil failure over a circular and low-profile arch structure does not vary significantly with the size of the span and for the circular structure, the minimum depth of the soil cover was about 1.5m, and for the low-profile arch structures, below about 1.6m. And the previously established code in which the minimum depth of soil cover is defined to linearly increase with the increase in the span (CHBDC, 2001) was very conservative. For the structure with the relieving slab, the maximum live load thrust was reduced by about 36 percent and the maximum moment about 81 percent. The numerical analysis gave more conservative estimation of the live-load thrusts than the other design methods.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.315-327
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• 2004

Nowadays, interests in land cover classification using not only multi-sensor images but also thematic GIS information are increasing. Often, although useful GIS information for the classification is available, the traditional MLE (maximum likelihood estimation techniques) does not allow us to use the information, due to the fact that it cannot handle the GIS data properly. This paper propose two extended MLE algorithms that can integrate both remote sensing images and GIS thematic data for land-cover classification. They include modified MLE and Bayesian predictive likelihood estimation technique (BPLE) techniques that can handle both categorical GIS thematic data and remote sensing images in an integrated manner. The proposed algorithms were evaluated through supervised land-cover classification with Landsat ETM+ images and an existing land-use map in the Gongju area, Korea. As a result, the proposed method showed considerable improvements in classification accuracy, when compared with other multi-spectral classification techniques. The integration of remote sensing images and the land-use map showed that overall accuracy indicated an improvement in classification accuracy of 10.8% when using MLE, and 9.6% for the BPLE. The case study also showed that the proposed algorithms enable the extraction of the area with land-cover change. In conclusion, land cover classification results produced through the integration of various GIS spatial data and multi-spectral images, will be useful to involve complementary data to make more accurate decisions.

• Atmosphere
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• v.20 no.4
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• pp.415-426
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• 2010

A Land cover map over East Asian region (Kongju national university Land Cover map: KLC) is classified by using support vector machine (SVM) and evaluated with ground truth data. The basic input data are the recent three years (2006-2008) of MODIS (MODerate Imaging Spectriradiometer) NDVI (normalized difference vegetation index) data. The spatial resolution and temporal frequency of MODIS NDVI are 1km and 16 days, respectively. To minimize the number of cloud contaminated pixels in the MODIS NDVI data, the maximum value composite is applied to the 16 days data. And correction of cloud contaminated pixels based on the spatiotemporal continuity assumption are applied to the monthly NDVI data. To reduce the dataset and improve the classification quality, 9 phenological data, such as, NDVI maximum, amplitude, average, and others, derived from the corrected monthly NDVI data. The 3 types of land cover maps (International Geosphere Biosphere Programme: IGBP, University of Maryland: UMd, and MODIS) were used to build up a "quasi" ground truth data set, which were composed of pixels where the three land cover maps classified as the same land cover type. The classification results show that the fractions of broadleaf trees and grasslands are greater, but those of the croplands and needleleaf trees are smaller compared to those of the IGBP or UMd. The validation results using in-situ observation database show that the percentages of pixels in agreement with the observations are 80%, 77%, 63%, 57% in MODIS, KLC, IGBP, UMd land cover data, respectively. The significant differences in land cover types among the MODIS, IGBP, UMd and KLC are mainly occurred at the southern China and Manchuria, where most of pixels are contaminated by cloud and snow during summer and winter, respectively. It shows that the quality of raw data is one of the most important factors in land cover classification.

• Journal of Welding and Joining
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• v.32 no.2
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• pp.54-62
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• 2014

Manhole cover, which is usually made of grey cast iron and consists of frame and cover, should have enough strength to support the heavy traffic load. The manhole cover made of cast iron has heavy weight to handle manually and is vulnerable to impact force with its brittle characteristics. Moreover, its production process of casting has been regulated in terms of environmental pollution. In this study, steel manhole cover is proposed to substitute the cast cover with a series of structural analyses to confirm its strength to support the test load for manhole cover. The cover of the proposed steel manhole cover is made of thin circular pate and stiffeners below the plate. Rectangular columns and hollow circular plate were selected for the shape of the stiffener. In order to give enough strength for the cover to behave within elastic range in the loading, strengthening structures of the cover were varied with increasing the number and the size of the stiffeners. The results of the analyses revealed that when both the hollow circular stiffener and cross stiffeners were additionally applied at the same time to the steel cover with longitudinal stiffeners, the maximum stress level in the cover could be reduced to that level presented in the cast cover.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.6
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• pp.603-610
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• 2013

Finite element analysis is performed to evaluate stress and deformation of a wrinkle-type dust cover for the ball joints of tie rods of automotive steering system. Results of the analysis for assembly and operation condition show that sealing capability is good and the maximum stress on the body is smaller than the tensile strength. An optimal shape of the dust cover is obtained using the Taguchi method to reduce the maximum stress. The maximum stress of the optimal design under the operation condition is reduced by 22 per cent of that of the initial design. Results of the research show that performance evaluation and design of the dust covers can be effectively done using the proposed method.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.270-287
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• 2015

According to the increase of the operating cost and material cost of a ship due to the change of international oil price, a demand for the lightening of the ship weight is being made from various parties such as shipping companies, ship owners, and shipyards. To satisfy such demand, many studies for a light ship are being made. As one of them, an optimal design method of an existing hull structure, that is, a method for lightening the ship weight based on the optimization technique was proposed in this study. For this, we selected a hatch cover of a bulk carrier as an optimization target and formulated an optimization problem in order to determine optimal principal dimensions of the hatch cover for lightening the bulk carrier. Some dimensions representing the shape of the hatch cover were selected as design variables and some design considerations related to the maximum stress, maximum deflection, and geometry of the hatch cover were selected as constraints. In addition, the minimization of the weight of the hatch cover was selected as an objective function. To solve this optimization problem, we developed an optimization program based on the Sequential Quadratic Programming (SQP) using C++ programming language. To evaluate the applicability of the developed program, it was applied to a problem for finding optimal principal dimensions of the hatch cover of a deadweight 180,000 ton bulk carrier. The result shows that the developed program can decrease the hatch cover's weight by about 8.5%. Thus, this study will be able to contribute to make energy saving and environment-friendly ship in shipyard.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1531-1536
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• 2022

This paper considers a problem to find a set of intervals containing all the points for the given n points and m intervals on a line, This is a special case of the set cover problem, well known as an NP-hard problem. As optimization criteria of the problem, there are minimizing the number of intervals to cover the points, maximizing the number of points each of which is covered by exactly one interval, and so on. In this paper, the intervals have weights and the sum of weights of intervals to cover a point is defined as a membership of the point. We will study the problem to find an interval cover minimizing the maximum of memberships of points. Using the dynamic programming method, we provide an O(m²)-time algorithm to improve the time complexity O(nm log n) given in the previous work.

• ETRI Journal
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• v.21 no.4
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• pp.41-51
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• 1999

This research is an attempt to obtain more accurate land cover information from LANDSAT images. Canonical correlation analysis, which has not been widely used in the image classification community, was applied to the classification of a LANDSAT images. It was found that it is easy to select training areas on the classification using canonical correlation analysis in comparison with the maximum likelihood classifier of $ERDAS^{(R)}$ software. In other words, the selected positions of training areas hardly affect the classification results using canonical correlation analysis. when the same training areas are used, the mapping accuracy of the canonical correlation classification results compared with the ground truth data is not lower than that of the maximum likelihood classifier. The kappa analysis for the canonical correlation classifier and the maximum likelihood classifier showed that the two methods are alike in classification accuracy. However, the canonical correlation classifier has better points than the maximum likelihood classifier in classification characteristics. Therefore, the classification using canonical correlation analysis applied in this research is effective for the extraction of land cover information from LANDSAT images and will be able to be put to practical use.