Park, Jungsu;Park, Jae-Hyeoung;Choi, June-Seok;Heo, Tae-Young
Journal of Korean Society of Water and Wastewater
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v.35
no.1
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pp.53-61
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2021
The quantified analysis of damages to wastewater treatment plants by natural disasters is essential to maintain the stability of wastewater treatment systems. However, studies on the quantified analysis of natural disaster effects on wastewater treatment systems are very rare. In this study, a total disaster index (DI) was developed to quantify the various damages to wastewater treatment systems from natural disasters using two statistical methods (i.e., AHP: analytic hierarchy process and PCA: principal component analysis). Typhoons, heavy rain, and earthquakes are considered as three major natural disasters for the development of the DI. A total of 15 input variables from public open-source data (e.g., statistical yearbook of wastewater treatment system, meteorological data and financial status in local governments) were used for the development of a DI for 199 wastewater treatment plants in Korea. The total DI was calculated from the weighted sum of the disaster indices of the three natural disasters (i.e., TI for typhoon, RI for heavy rain, and EI for earthquake). The three disaster indices of each natural disaster were determined from four components, such as possibility of occurrence and expected damages. The relative weights of the four components to calculate the disaster indices (TI, RI and EI) for each of the three natural disasters were also determined from AHP. PCA was used to determine the relative weights of the input variables to calculate the four components. The relative weights of TI, RI and EI to calculate total DI were determined as 0.547, 0.306, and 0.147 respectively.
In this study, we evaluated the uncertainty in the process of selecting GCM and downscaling method for assessing the impact of climate change, and influence of user-centered climate change information on reproducibility of Chungju Dam inflow was analyzed. First, we selected the top 16 GCMs through the evaluation of spatio-temporal reproducibility of 29 raw GCMs using 30-year average of 10-day precipitation without any bias-correction. The climate extreme indices including annual total precipitation and annual maximum 1-day precipitation were selected as the relevant indices to the dam inflow. The Simple Quantile Mapping (SQM) downscaling method was selected through the evaluation of reproducibility of selected indices and spatial correlation among weather stations. SWAT simulation results for the past 30 years period by considering limitations in weather input showed the satisfactory results with monthly model efficiency of 0.92. The error in average dam inflow according to selection of GCMs and downscaling method showed the bests result when 16 GCMs selected raw GCM analysi were used. It was found that selection of downscaling method rather than selection of GCM is more is important in overall uncertainties. The average inflow for the future period increased in all RCP scenarios as time goes on from near-future to far-future periods. Also, it was predicted that the inflow volume will be higher in the RCP 8.5 scenario than in the RCP 4.5 scenario in all future periods. Maximum daily inflow, which is important for flood control, showed a high changing rate more than twice as much as the average inflow amount. It is also important to understand the seasonal fluctuation of the inflow for the dam management purpose. Both average inflow and maximum inflow showed a tendency to increase mainly in July and August during near-future period while average and maximum inflows increased through the whole period of months in both mid-future and far-future periods.
As a central part in smart construction, BIM has been rapidly spread in construction industry at large. However, the level of applying BIM in construction stage is still relatively lower than that in design stage due to unclear application method, inadequate design BIM model, technical faults of BIM itself, etc. Under these circumstances, public owners inevitably need to adjust the scope and pace in BIM application considering their internal support and capabilities of contractors. This study aims to suggest major BIM-applicable tasks during construction stage in the process of establishing gradual long-term and short-term introduction strategy for public apartment housing projects. Those major tasks were identified with the combination of the importance of tasks and the future benefits of BIM using IPA method. To do so, the degrees of contribution to achieving objectives in construction, current task execution, and communication requirement were investigated by internal site managers. On the other hand, the expected benefits and current level of using BIM were assessed by BIM experts. Among operational tasks by phases, design review, construction plan review, making as-built drawing, etc. were categorized as major tasks. In addition, progress control, regular meeting, master schedule development, work inspection, on-site quality check, etc. were also drawn as major tasks by management areas. The results of this study will provide the useful reference for owners concerned about the introduction of new technologies.
The decrease in the school-age population caused the closure of private universities, but the guidelines at closed private universities are ambiguous, causing confusion. Therefore, this study intends to suggest a plan to utilize the closed school university. The government aims to increase the possibility of selling closed schools by preventing alley slums through the recovery of alley commercial districts and local communities. The data were collected through a Google survey from September 30 to October 8, 2021 and an on-site interview conducted on October 2, 2021. A total of 84 nearby citizens of the closed school university were surveyed, and on-site interviews were conducted with a total of five people. The collected data suggested the direction of utilization plan for closed school building. This study will present a model for the use of closed school property in the future and contribute to the establishment of urban regeneration policies.
Background and objective: Urban topology can be characterized as impervious, which changes the hydrologic features of an area, increasing surface water flow during local heavy rain events. The pluvial flooding is also influenced by the vertical structures of the urban area. This study suggested a modified digital elevation model (DEM) to identify changes in urban hydrological conditions and segmentalized urban micro catchment areas using a geographical information system (GIS). Methods: This study suggests using a modified DEM creation process based on Rolling Ball Method concepts along with a GIS program. This method proposes adding realized urban vertical data to normal DEM data and simulating hydrological analyses based on RBM concepts. The most important aspect is the combination of the DEM with polygon data, which includes urban vertical data in three datasets: the contour polyline, the locations of buildings and roads, and the elevation point data from the DEM. DEM without vertical data (DCA) were compared with the DEM including vertical data (VCA) to analyze catchment areas in Shin-wol district, Seoul, Korea. Results: The DCA had 136 catchments, and the area of each catchment ranged from 3,406 m2 to 423,449 m2. The VCA had 2,963 catchments, with the area of each ranging from 50 m2 to 16,209 m2. The most important finding is that in the overlapped VCA; the boundary of areas directly affected by flooding and the direction of surface water flow could be identified. Flooding data from September 21, 2010 and July 27, 2011 in the Shin-wol district were applied as ground reference data. The finding is that in the overlapped VCA; the boundary of areas directly affected by flooding and the direction of surface water flow could be identified. Conclusion: The analysis of the area vulnerable to surface water flooding (SWF) was more accurately determined using the VCA than using the DCA.
One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.13
no.2
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pp.141-151
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1995
In generating DTM as basic data to GIS, the use of existing map is difficult to aquire current data and the method using airphotos needs cost for stereoplotting and ground control surveying. So, the method of DTM generation by satellite imagery is promising because satellite is able to observe wide area at once. In this study the program for SPOT bundle adjustment and image matching based on Coarse to Fine method is developed and various image enhancement algorithm is used for more accurate DTM generation and also evaluation of accuracy was carried out. Further more, orthophoto, a bird's eye-view, contour map producing, net-work analysis and terrain analysis were performed for GIS applications using generated DTM in this study. Generated DTM using SPOT stereo imagery is useful for GIS applications such as automated mapping, facility management, national geographic information system. Moreover developed automatic DTM generation pro-gram is studied, tested and verified more to be applicable to all the area.
Lots of previous researches on determinants of apartment prices in Korea consider spatial dependence while few studies regard endogeneity of spatial lag by adding a spatial lag to an OLS regression. Thus, this study intends to include this spatial lag in its analysis of determinants of apartment price in Busan by using a two-stage quantile regression. The empirical results are : the coefficient of spatial lag variable is more than 0.5 and is statistically significant at 1% level. From this result we can confirm that the effect of the price of nearby apartment on that of another apartment is very big. We also find that apartment buyers prefer larger size, height in both the total floors and living floor, south-facing living room with a ocean view, and proximity to metros, high school and coast. Unlike our expectation, however, mountain view is less favored than building view, which we can guess is because apartments with mountain views are mostly located in the low-priced apartment area where some of their living rooms face north. Quantile regression also explains the effect of hedonic characteristics on apartment price better than OLS estimation. For instance, the effect of south facing living room variable on the price is twice larger in high-price apartments than in low-price counterparts. And the effect of vicinity to the coast or the ocean is ten times bigger in high priced apartments.
Korean Journal of Construction Engineering and Management
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v.13
no.6
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pp.143-152
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2012
As the Public Procurement Service announced the compulsory of BIM adaption in every public construction from 2016, the importance of BIM is increasing. Besides, automatic code checking takes significance in terms of the quality control for BIM based design. In this study, rule-sets were defined for Act on the Promotion and Guarantee of Access for the Disabled, the Aged, and Pregnant Women to Facilities and Information. Three analytic steps were suggested to shortlist the objective clauses from the entire code; the frequency analysis using project reviews for architectural code compliance, the clause analysis on quantifiability, and the analysis for model checking possibilities. The shortlisted clauses were transformed into the machine readable rule-set definition. A case study was conducted to verify the adaptiveness and consistency of rule-set definitions. In future study, it is required the methodologies of selecting objective clauses to be specified and its indicators to be quantified. Also case studies should be performed to determine the pre-conditions in modeling and to check interoperability issues and other possible errors in models.
This study explores the determinants and processes of IT consolidation of Korean conglomerates. Through an extensive analysis of cases, this study identifies the drivers, benefits and critical success factors of IT consolidation, and observes the transition of vision for the IT service subsidiaries in the conglomerates. The results show that most firms in this analysis have completed the organizational, physical, and logical consolidation of their IT resources, and currently some of them are preparing for the next stage of IT consolidation such as rational consolidation and virtualization. It is also found that the strategic factor was one of the most significant determinants in consolidating IT resources which leaded the transition of vision of the IT service firms in the conglomerates from "cost center" to "profit center". The results of this study can provide a fundamental and empirical basis for building a theory of IT consolidation, and be used as a valuable benchmarking model for the organizations which consider starting a project of IT consolidation.
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