• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.15-22
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• 2002

Transportation project appraisal should be precise in order to increase the social welfare and efficiency, and it has been evaluated by only a single criterion analysis such as benefit/cost analysis. However, this method cannot assess some qualitative items, and cannot get a proper solution for the clash of interests among various groups. Therefore, the multi-criteria analysis, which can control these problems, is needed, and then Saaty has developed one of these methods, AHP(Analytic Hierarchy Process) method. In AHP, the project is evaluated through weighted score of the criteria and the alternatives, which is surveyed by a questionnaire of specialists. It is based on some strict suppositions such as reciprocal comparison, homogeneity, expectation, independence relationship between multi-criteria, but supposing that each criterion has independence relation with others is too difficult in two reasons. First, in real situation, there cannot be perfect independence relationship between standards. Second, individuals, even though they are specialists of that area, do not feel the degree of independence relation as same as others. This paper develops a modified AHP method for solving this dependence relationship between multi-criteria. First of all. in this method, the degree of dependence relationship between multi-criteria that the specialist feels is surveyed and included to the weighted score of multi-criteria This study supposes three methods to implement this idea. The first model products the degree of dependence relationship in the first step for calculating the weighted score, and the others adjust the result of weighted score from the basic AHP method to the dependence relationship. One of the second methods distributes the cross weighted score to each standard by constant ratio, and the other splits them using Fuzzy measure such as Bel and Pl. Finally, in order to validate these methods, this paper applies them to evaluate the alternatives which can control public resentments against Korean rail path in a city area.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.237-237
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• 2015

The district of Marlborough has had more than its share of river management projects over the past 150 years, each one uniquely affecting the geomorphology and flood hazard of the Wairau Plains. A major early project was to block the Opawa distributary channel at Conders Bend. The Opawa distributary channel took a third and more of Wairau River floodwaters and was a major increasing threat to Blenheim. The blocking of the Opawa required the Wairau and Lower Wairau rivers to carry greater flood flows more often. Consequently the Lower Wairau River was breaking out of its stopbanks approximately every seven years. The idea of diverting flood waters at Tuamarina by providing a direct diversion to the sea through the beach ridges was conceptualised back around the 1920s however, limits on resources and machinery meant the mission of excavating this diversion didn't become feasible until the 1960s. In 1964 a 10 m wide pilot channel was cut from the sea to Tuamarina with an initial capacity of $700m^3/s$. It was expected that floods would eventually scour this 'Wairau Diversion' to its design channel width of 150 m. This did take many more years than initially thought but after approximately 50 years with a little mechanical assistance the Wairau Diversion reached an adequate capacity. Using the power of the river to erode the channel out to its design width and depth was a brilliant idea that saved many thousands of dollars in construction costs and it is somewhat ironic that it is that very same concept that is now being used to deal with the aggradation problem that the Wairau Diversion has caused. The introduction of the Wairau Diversion did provide some flood relief to the lower reaches of the river but unfortunately as the Diversion channel was eroding and enlarging the Lower Wairau River was aggrading and reducing in capacity due to its inability to pass its sediment load with reduced flood flows. It is estimated that approximately $2,000,000m^3$ of sediment was deposited on the bed of the Lower Wairau River in the time between the Diversion's introduction in 1964 and 2010, raising the Lower Wairau's bed upwards of 1.5m in some locations. A numerical morphological model (MIKE-11 ST) was used to assess a number of options which led to the decision and resource consent to construct an erodible (fuse plug) bank at the head of the Wairau Diversion to divert more frequent scouring-flows ($+400m^3/s$)down the Lower Wairau River. Full control gates were ruled out on the grounds of expense. The initial construction of the erodible bank followed in late 2009 with the bank's level at the fuse location set to overtop and begin washing out at a combined Wairau flow of $1,400m^3/s$ which avoids berm flooding in the Lower Wairau. In the three years since the erodible bank was first constructed the Wairau River has sustained 14 events with recorded flows at Tuamarina above $1,000m^3/s$ and three of events in excess of $2,500m^3/s$. These freshes and floods have resulted in washout and rebuild of the erodible bank eight times with a combined rebuild expenditure of $80,000. Marlborough District Council's Rivers & Drainage Department maintains a regular monitoring program for the bed of the Lower Wairau River, which consists of recurrently surveying a series of standard cross sections and estimating the mean bed level (MBL) at each section as well as an overall MBL change over time. A survey was carried out just prior to the installation of the erodible bank and another survey was carried out earlier this year. The results from this latest survey show for the first time since construction of the Wairau Diversion the Lower Wairau River is enlarging. It is estimated that the entire bed of the Lower Wairau has eroded down by an overall average of 60 mm since the introduction of the erodible bank which equates to a total volume of $260,000m^3$. At a cost of $$0.30/m^3$ this represents excellent value compared to mechanical dredging which would likely be in excess of $$10/m^3$. This confirms that the idea of using the river to enlarge the channel is again working for the Wairau River system and that in time nature's "excavator" will provide a channel capacity that will continue to meet design requirements.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• 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.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Economic and Environmental Geology
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• v.54 no.6
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• pp.689-698
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• 2021

Since the mine reclamation scheme was implemented from 2007 in Korea, various remediation programs have been decontaminated the pollution associated with mining and 254 mines were managed to reclamation from 2011 to 2015. However, as the total amount of contaminated mine drainage has been increased due to the discovery of potential hazards and contaminated zone, more efficient and economical treatment technology is required. Therefore, in this study, the adsorption properties of arsenic was evaluated according to the adsorbents which were derived from water treatment sludge(Alum based adsorbent, ABA-500) and granular ferric hydroxide(GFH), already commercialized. The alum sludge and GFH adsorbents consisted of aluminum, silica materials and amorphous iron hydroxide, respectively. The point of zero charge of ABA-500 and GFH were 5.27 and 6.72, respectively. The result of the analysis of BET revealed that the specific surface area of GFH(257 m²·g^-1) was larger than ABA-500(126~136 m²·g^-1) and all the adsorbents were mesoporous materials inferred from N₂ adsorption-desorption isotherm. The adsorption capacity of adsorbents was compared with the batch experiments that were performed at different reaction times, pH, temperature and initial concentrations of arsenic. As a result of kinetic study, it was confirmed that arsenic was adsorbed rapidly in the order of GFH, ABA-500(granule) and ABA-500(3mm). The adsorption kinetics were fitted to the pseudo-second-order kinetic model for all three adsorbents. The amount of adsorbed arsenic was increased with low pH and high temperature regardless of adsorbents. When the adsorbents reacted at different initial concentrations of arsenic in an hour, ABA-500(granule) and GFH could remove the arsenic below the standard of drinking water if the concentration was below 0.2 mg·g^-1 and 1 mg·g^-1, respectively. The results suggested that the ABA-500(granule), a low-cost adsorbent, had the potential to field application at low contaminated mine drainage.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.471-480
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• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.697-703
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• 2023

As a part of the global industrial efforts to reduce environmental pollution owing to air pollution, regulations have been established by the International Maritime Organization (IMO). The IMO has implemented various regulations such as EEXI, EEDI, and CII to reduce air pollution emissions from ships. They are also promoting measures to decrease the power consumption in ships, aiming to conserve energy. Most of the power used in ships is consumed by electric motors. Among the motors installed on ships, the engine room blower that takes up a significant load, operates at a constant irrespective of demand. Therefore, energy savings can be expected through frequency control. In this study, we demonstrated the efficacy of energy savings by controlling the frequency of the electric motor of the generator blower that supplies combustion air to the generator's turbocharger. The system was modeled based on the output data of the turboharger outlet temperature in response to the blower frequency inpu. A PI control system was established to control the frequency with the target being the turbocharger outlet temperature. By maintaining the turbocharger design standard outlet temperature and controlling the blower frequency, we achieved an annual energy saving of 15,552kW in power consumption. The effectiveness of energy savings through frequency control of blower fans was verified during the summer (April to September) and winter (March to October) periods. Based on this, we achieved annual fuel cost savings of 6,091 thousand won and reduction of 8.5 tons of carbon dioxide, 2.4 kg of SOx, and 7.8 kg of NOx air pollutants on the training ship.

• Korean small business review
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• v.31 no.4
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• pp.67-93
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• 2009

The purpose of this paper is to explore the relations between financial constraints and dividend smoothing of innovative small and medium sized enterprises(SMEs) listed on Korea Securities Market and Kosdaq Market of Korea Exchange. The innovative SMEs is defined as the firms with high level of R&D intensity which is measured by (R&D investment/total sales) ratio, according to Chauvin and Hirschey (1993). The R&D investment plays an important role as the innovative driver that can increase the future growth opportunity and profitability of the firms. Therefore, the R&D investment have large, positive, and consistent influences on the market value of the firm. In this point of view, we expect that the innovative SMEs can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. And also, we expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Aivazian et al.(2006) exert that the financial unconstrained firms with the high accessibility to capital market can adjust dividend payment faster than the financial constrained firms. We collect the sample firms among the total SMEs listed on Korea Securities Market and Kosdaq Market of Korea Exchange during the periods from January 1999 to December 2007 from the KIS Value Library database. The total number of firm-year observations of the total sample firms throughout the entire period is 5,544, the number of firm-year observations of the dividend firms is 2,919, and the number of firm-year observations of the non-dividend firms is 2,625. About 53%(or 2,919) of these total 5,544 observations involve firms that make a dividend payment. The dividend firms are divided into two groups according to the R&D intensity, such as the innovative SMEs with larger than median of R&D intensity and the noninnovative SMEs with smaller than median of R&D intensity. The number of firm-year observations of the innovative SMEs is 1,506, and the number of firm-year observations of the noninnovative SMEs is 1,413. Furthermore, the innovative SMEs are divided into two groups according to level of financial constraints, such as the financial unconstrained firms and the financial constrained firms. The number of firm-year observations of the former is 894, and the number of firm-year observations of the latter is 612. Although all available firm-year observations of the dividend firms are collected, deletions are made in the case of financial industries such as banks, securities company, insurance company, and other financial services company, because their capital structure and business style are widely different from the general manufacturing firms. The stock repurchase was involved in dividend payment because Grullon and Michaely (2002) examined the substitution hypothesis between dividends and stock repurchases. However, our data structure is an unbalanced panel data since there is no requirement that the firm-year observations data are all available for each firms during the entire periods from January 1999 to December 2007 from the KIS Value Library database. We firstly estimate the classic Lintner(1956) dividend adjustment model, where the decision to smooth dividend or to adopt a residual dividend policy depends on financial constraints measured by market accessibility. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between current payout rato and target payout ratio each year. In the Lintner model, dependent variable is the current dividend per share(DPS_t), and independent variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t). We hypothesized that firms adjust partially the gap between the current dividend per share(DPS_t) and the target payout ratio(Ω) each year, when the past dividend per share(DPS_t-1) deviate from the target payout ratio(Ω). We secondly estimate the expansion model that extend the Lintner model by including the determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory. In the expansion model, dependent variable is the current dividend per share(DPS_t), explanatory variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t), and control variables are the current capital expenditure ratio(CEA_t), the current leverage ratio(LEV_t), the current operating return on assets(ROA_t), the current business risk(RISK_t), the current trading volume turnover ratio(TURN_t), and the current dividend premium(DPREM_t). In these control variables, CEA_t, LEV_t, and ROA_t are the determinants suggested by the residual dividend theory and the agency theory, ROA_t and RISK_t are the determinants suggested by the dividend signaling theory, TURN_t is the determinant suggested by the transactions cost theory, and DPREM_t is the determinant suggested by the catering theory. Furthermore, we thirdly estimate the Lintner model and the expansion model by using the panel data of the financial unconstrained firms and the financial constrained firms, that are divided into two groups according to level of financial constraints. We expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, because the former can finance more easily the investment funds through the market accessibility than the latter. We analyzed descriptive statistics such as mean, standard deviation, and median to delete the outliers from the panel data, conducted one way analysis of variance to check up the industry-specfic effects, and conducted difference test of firms characteristic variables between innovative SMEs and noninnovative SMEs as well as difference test of firms characteristic variables between financial unconstrained firms and financial constrained firms. We also conducted the correlation analysis and the variance inflation factors analysis to detect any multicollinearity among the independent variables. Both of the correlation coefficients and the variance inflation factors are roughly low to the extent that may be ignored the multicollinearity among the independent variables. Furthermore, we estimate both of the Lintner model and the expansion model using the panel regression analysis. We firstly test the time-specific effects and the firm-specific effects may be involved in our panel data through the Lagrange multiplier test that was proposed by Breusch and Pagan(1980), and secondly conduct Hausman test to prove that fixed effect model is fitter with our panel data than the random effect model. The main results of this study can be summarized as follows. The determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend policy of the innovative SMEs. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between the current payout ratio and the target payout ratio each year. In the core variables of Lintner model, the past dividend per share has more effects to dividend smoothing than the current earnings per share. These results suggest that the innovative SMEs maintain stable and long run dividend policy which sustains the past dividend per share level without corporate special reasons. The main results show that dividend adjustment speed of the innovative SMEs is faster than that of the noninnovative SMEs. This means that the innovative SMEs with high level of R&D intensity can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. The other main results show that dividend adjustment speed of the financial unconstrained SMEs is faster than that of the financial constrained SMEs. This means that the financial unconstrained firms with high accessibility to capital market can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Futhermore, the other additional results show that dividend adjustment speed of the innovative SMEs classified by the Small and Medium Business Administration is faster than that of the unclassified SMEs. They are linked with various financial policies and services such as credit guaranteed service, policy fund for SMEs, venture investment fund, insurance program, and so on. In conclusion, the past dividend per share and the current earnings per share suggested by the Lintner model explain mainly dividend adjustment speed of the innovative SMEs, and also the financial constraints explain partially. Therefore, if managers can properly understand of the relations between financial constraints and dividend smoothing of innovative SMEs, they can maintain stable and long run dividend policy of the innovative SMEs through dividend smoothing. These are encouraging results for Korea government, that is, the Small and Medium Business Administration as it has implemented many policies to commit to the innovative SMEs. This paper may have a few limitations because it may be only early study about the relations between financial constraints and dividend smoothing of the innovative SMEs. Specifically, this paper may not adequately capture all of the subtle features of the innovative SMEs and the financial unconstrained SMEs. Therefore, we think that it is necessary to expand sample firms and control variables, and use more elaborate analysis methods in the future studies.