• International conference on construction engineering and project management
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• 2022.06a
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• pp.304-311
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• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• Computers and Concrete
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• v.32 no.6
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• pp.577-594
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• 2023

Engineered cementitious composites with calcined clay limestone cement (LC³-ECC) as a kind of green, low-carbon and high toughness concrete, has recently received significant investigation. However, the complicated relationship between potential influential factors and LC³-ECC compressive strength makes the prediction of LC³-ECC compressive strength difficult. Regarding this, the machine learning-based prediction models for the compressive strength of LC³-ECC concrete is firstly proposed and developed. Models combine three novel meta-heuristic algorithms (golden jackal optimization algorithm, butterfly optimization algorithm and whale optimization algorithm) with support vector regression (SVR) to improve the accuracy of prediction. A new dataset about LC³-ECC compressive strength was integrated based on 156 data from previous studies and used to develop the SVR-based models. Thirteen potential factors affecting the compressive strength of LC³-ECC were comprehensively considered in the model. The results show all hybrid SVR prediction models can reach the Coefficient of determination (R²) above 0.95 for the testing set and 0.97 for the training set. Radar and Taylor plots also show better overall prediction performance of the hybrid SVR models than several traditional machine learning techniques, which confirms the superiority of the three proposed methods. The successful development of this predictive model can provide scientific guidance for LC³-ECC materials and further apply to such low-carbon, sustainable cement-based materials.

• Economic and Environmental Geology
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• v.55 no.6
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• pp.737-760
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• 2022

For the geological disposal of high-level radioactive wastes (HLW), an understanding of deep subsurface environment is essential through geological, hydrogeological, geochemical, and geotechnical investigations. Although South Korea plans the geological disposal of HLW, only a few studies have been conducted for characterizing the geochemistry of deep subsurface environment. To guide the hydrogeochemical research for selecting suitable repository sites, this study overviewed the status and trends in hydrogeochemical characterization of deep groundwater for the deep geological disposal of HLW in developed countries. As a result of examining the selection process of geological disposal sites in 8 countries including USA, Canada, Finland, Sweden, France, Japan, Germany, and Switzerland, the following geochemical parameters were needed for the geochemical characterization of deep subsurface environment: major and minor elements and isotopes (e.g., ³⁴S and ¹⁸O of SO₄^2-, ¹³C and ¹⁴C of DIC, ²H and ¹⁸O of water) of both groundwater and pore water (in aquitard), fracture-filling minerals, organic materials, colloids, and oxidation-reduction indicators (e.g., Eh, Fe²⁺/Fe³⁺, H₂S/SO₄^2-, NH₄⁺/NO₃^-). A suitable repository was selected based on the integrated interpretation of these geochemical data from deep subsurface. In South Korea, hydrochemical types and evolutionary patterns of deep groundwater were identified using artificial neural networks (e.g., Self-Organizing Map), and the impact of shallow groundwater mixing was evaluated based on multivariate statistics (e.g., M3 modeling). The relationship between fracture-filling minerals and groundwater chemistry also has been investigated through a reaction-path modeling. However, these previous studies in South Korea had been conducted without some important geochemical data including isotopes, oxidationreduction indicators and DOC, mainly due to the lack of available data. Therefore, a detailed geochemical investigation is required over the country to collect these hydrochemical data to select a geological disposal site based on scientific evidence.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.29 no.5
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• pp.689-700
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• 1996

Fisheries products have to be produced and maintained by work processes from the environment, sometimes helped by people. In Korean fisheries both environmental production and its economic use are included within the windows of system approach. EMERGY is the sum of all inputs expressed as one form of solar energy required directly and indirectly to make a product. Calculating EMERGY flows into Korean fisheries evaluates the real wealth contributed by environmental production and its economic use. Several indices calculated from EMERGY analysis table and a three-arm diagram give perspective on the type and efficiency of the environmental uses. Net EMERGY yield ratio is a measure of its net contribution to the economy beyond its own operation. For adjacent waters fisheries in Korea, the net contribution to the economy is 11.85 or higher, which is a stimulus to the economy that is able to purchase it. EMERGY investment ratio measures the intensity of the economic development and the loading of the environment. The ratio for Korean fisheries as a whole is 0.50, for the adjacent waters fisheries 0.09 and for the shallow-sea cultures 1.28, which is lower than the same index for the industry of the developed country (7.0). The component of environment drawn into production are large compared to purchased investment in Korean fisheries. Much more EMERGY is contained in fisheries products than in the paid services used to process the products. The EMERGY exchange ratio for Korean fisheries as a whole is 6.98, for the adjacent waters fisheries is 10.69 and for the shallow-sea cultures is 1.25. Using market values to evaluate wealth of environment resources is found to be many times too small. Money is paid only to people for their contribution, and never to the environment for its contribution. Macroeconomic value is the appropriate measure for discussing large-scale considerations of an economy, including environment and human goods & services.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.665-673
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• 2011

In order to estimate the hydrocarbon reserves, the porosity of the reservoir must be determined. The porosity of the area without a well is generally calculated by extrapolating the porosity logs measured at wells. However, if not only well logs but also seismic data exist on the same site, the more accurate pseudo porosity log can be obtained through artificial neural network technique by extracting the relations between the seismic data and well logs at the site. In this study, we have developed a module which creates pseudo porosity logs by using the polynomial neural network method. In order to obtain more accurate pseudo porosity logs, we selected the seismic attributes which have high correlation values in the correlation analysis between the seismic attributes and the porosity logs. Through the training procedure between selected seismic attributes and well logs, our module produces the correlation weights which can be used to generate the pseudo porosity log in the well free area. To verify the reliability and the applicability of the developed module, we have applied the module to the field data acquired from F3 Block in the North Sea and compared the results to those from the probabilistic neural network method in a commercial program. We could confirm the reliability of our module because both results showed similar trend. Moreover, since the pseudo porosity logs from polynomial neural network method are closer to the true porosity logs at the wells than those from probabilistic method, we concluded that the polynomial neural network method is effective for the data sets with insufficient wells such as F3 Block in the North Sea.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.333-343
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• 2012

In-stream large wood (LW) has a critical impact on the geomorphic characteristics relevant to ecosystem management and disaster prevention, yet relatively little is known about variations in its dynamics and subsequent export on the watershed-scale perspective in Korea. Here we review variations in the dynamics and subsequent export of LW as a function of stream size, which is appropriate for Korean mountain streams. In upstream channels with narrow bankfull widths and low stream discharges, a massive amount of LW, resulting from forest dynamics and hillslope processes, may persist for several decades on valley floor. These pieces, however, are eventually transported during infrequent debris flows from small tributaries, as well as peak hydrology in main-stem channels. During the transport, these pieces suffer fragmentation caused by frictions with boulders, and stream bank and bed. Although infrequent, these events can be dominant processes in the export of significant amounts of LW from upstream channel networks. In downstream channels with wide bankfull widths and high stream discharges, LW is dominantly recruited by forest dynamics and bank erosion only at locations where the channel is adjacent to mature riparian forests. With the LW pieces that are supplied from the upstream, these pieces are continuously transported downstream during rainfall events. This leads to further fragmentation of the LW pieces, which increases their transportability. With decreasing stream-bed slope, these floated LW pieces, however, can be stored and form logjams at various depositional sites, which were developed by interaction between channel forms and floodplains. These pieces may decay for decades and be subsequently transported as particulate or dissolved organic materials, resulting in the limitation of LW fluvial export from the systems. However, in Korea, such depositional sites were developed in the extremely limited streams with a large dimension and no flood history for decades, and thus it does not be expected that the reduction of LW export amount, which can be caused by the long-term storage. Our review presents a generalized view of LW processing and is relevant to ecosystem management and disaster prevention for Korean mountain streams.

• Economic and Environmental Geology
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• v.54 no.5
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• pp.581-594
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• 2021

In 2020, about 132 million m³ of aggregate was produced in Korea. Of the total domestic aggregates produced in 2020, about 33.3 % was sand and about 66.7% was gravel. It estimated that of the 132 million m³ of aggregates in Korea in 2020, about 52% was produced by screening crushed aggregate, by 36% by forest aggregate, 3% by land aggregate, 5.6% by sea aggregate and 2.5% by washing each other, and 0.4% by river aggregate. This indicates that screening crushed aggregate and forest aggregate are the main producers of domestic aggregates. Leading producing metropolitan cities were Gyeonggi-do, Gyeongsangnam-do, Chungcheongbuk-do, Gangwon-do, Chungcheongnam-do, Incheon in order decreasing volume, which together accounted for about 72.4% of total product. In 2020, aggregates were produced in 153 cities, about 67% of the 231 cities of Korea, 38 local governments have developed aggregates of more than 1 million m³, and the combined production of the 38 cities accounted for about 65% of national total. This means that the aggregate extraction trend of local governments is becoming larger and more concentrated. In 2020, at 153 local governments, a total of 889 operations produced aggregates with 420 operations by permission, 469 operations by declaration. A review of production by size of operation indicated that about 17 million m³ (12.8% of the total aggregate) was produced by 14 operations reporting production of more than 1 million m³. In about 420 operations, the maximum period of permit is 32 years to at least 2 months. When the remaining period of permit is taken into account, only about 55% of active operations can be developed the aggregate after 2021. In order to maintain the permitted aggregate volume by 2020 level, it will be necessary to obtain an extension permit or find new operation sites for at least 200 or more operations.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1339-1348
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• 2021

In accordance with the River Law, the basic river maintenance plan is established every 5-10 years with a considerable national budget for domestic rivers, and various river surveys such as the river section required for HEC-RAS simulation for flood level calculation are being conducted. However, river survey data are provided only in the form of a pdf report to the River Management Geographic Information System (RIMGIS), and the original data are distributedly owned by designers who performed the river maintenance plan in CAD format. It is a situation that the usability for other purposes is considerably lowered. In addition, when using surveyed CAD-type cross-sectional data for HEC-RAS, tools such as 'Dream' are used, but the reality is that time and cost are almost as close as manual work. In this study, RAUT (River Information Auto Upload Tool), a tool that can solve these problems, was developed. First, the RAUT tool attempted to automate the complicated steps of manually inputting CAD survey data and simulating the input data of the HEC-RAS one-dimensional model used in establishing the basic river plan in practice. Second, it is possible to directly read CAD survey data, which is river spatial information, and automatically upload it to the river spatial information DB based on the standard data model (ArcRiver), enabling the management of river survey data in the river maintenance plan at the national level. In other words, if RIMGIS uses a tool such as RAUT, it will be able to systematically manage national river survey data such as river section. The developed RAUT reads the river spatial information CAD data of the river maintenance master plan targeting the Jeju-do agar basin, builds it into a mySQL-based spatial DB, and automatically generates topographic data for HEC-RAS one-dimensional simulation from the built DB. A pilot process was implemented.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.177-198
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• 2018

Recently, as economic property it has become necessary to acquire and utilize the framework for water resource measurement and performance management as the property of water resources changes to hold "public property". To date, the evaluation of water technology has been carried out by feasibility study analysis or technology assessment based on net present value (NPV) or benefit-to-cost (B/C) effect, however it is not yet systemized in terms of valuation models to objectively assess an economic value of technology-based business to receive diffusion and feedback of research outcomes. Therefore, K-water (known as a government-supported public company in Korea) company feels the necessity to establish a technology valuation framework suitable for technical characteristics of water resources fields in charge and verify an exemplified case applied to the technology. The K-water evaluation technology applied to this study, as a public interest goods, can be used as a tool to measure the value and achievement contributed to society and to manage them. Therefore, by calculating the value in which the subject technology contributed to the entire society as a public resource, we make use of it as a basis information for the advertising medium of performance on the influence effect of the benefits or the necessity of cost input, and then secure the legitimacy for large-scale R&D cost input in terms of the characteristics of public technology. Hence, K-water company, one of the public corporation in Korea which deals with public goods of 'water resources', will be able to establish a commercialization strategy for business operation and prepare for a basis for the performance calculation of input R&D cost. In this study, K-water has developed a web-based technology valuation model for public interest type water resources based on the technology evaluation system that is suitable for the characteristics of a technology in water resources fields. In particular, by utilizing the evaluation methodology of the Institute of Advanced Industrial Science and Technology (AIST) in Japan to match the expense items to the expense accounts based on the related benefit items, we proposed the so-called 'K-water's proprietary model' which involves the 'cost-benefit' approach and the FCF (Free Cash Flow), and ultimately led to build a pipeline on the K-water research performance management system and then verify the practical case of a technology related to "desalination". We analyze the embedded design logic and evaluation process of web-based valuation system that reflects characteristics of water resources technology, reference information and database(D/B)-associated logic for each model to calculate public interest-based and profit-based technology values in technology integrated management system. We review the hybrid evaluation module that reflects the quantitative index of the qualitative evaluation indices reflecting the unique characteristics of water resources and the visualized user-interface (UI) of the actual web-based evaluation, which both are appended for calculating the business value based on financial data to the existing web-based technology valuation systems in other fields. K-water's technology valuation model is evaluated by distinguishing between public-interest type and profitable-type water technology. First, evaluation modules in profit-type technology valuation model are designed based on 'profitability of technology'. For example, the technology inventory K-water holds has a number of profit-oriented technologies such as water treatment membranes. On the other hand, the public interest-type technology valuation is designed to evaluate the public-interest oriented technology such as the dam, which reflects the characteristics of public benefits and costs. In order to examine the appropriateness of the cost-benefit based public utility valuation model (i.e. K-water specific technology valuation model) presented in this study, we applied to practical cases from calculation of benefit-to-cost analysis on water resource technology with 20 years of lifetime. In future we will additionally conduct verifying the K-water public utility-based valuation model by each business model which reflects various business environmental characteristics.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.887-900
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• 2012

Drought is a non-negligible disaster of nature and it is mainly caused by rainfall shortage for a long time though there are many definitions of drought. 'Standard Precipitation Index' (SPI) that is widely used to express the level of meteorological drought intensity has a limit of not being able to consider the hydrological changes such as rainfall and evapotranspiration caused by climate change, because it does not consider the temperature-related variables other than the precipitation. Recently, however, 'Standardized Precipitation Evapotranspiration Index' (SPEI), a drought index of new concept which is similar to SPI but can reflect the effect of temperature variability as well as the rainfall change caused by climate variation, was developed. In this study, the changes of drought occurrence in South Korea were analyzed by applying SPEI for meteorological data (1973~2011) of 60 climate observatories under Korea Meteorological Administration (KMA). As the result of application, both of SPI and SPEI showed the trend of deepening drought in spring and winter and mitigating drought in summer for the entire nation, with SPI showing greater drought intensity than SPI. Also, SPI and SPEI with 12 months of duration showed that severe droughts with low frequency of around 6 years are generally being repeated.