• Journal of Construction Engineering and Project Management
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• v.8 no.4
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• pp.1-24
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• 2018

In the last decade, the use of Building Information Modeling (BIM) as a new technology has been applied with traditional Computer-aided design implementations in an increasing number of architecture, engineering, and construction projects and applications. Its employment alongside construction management, can be a valuable tool in helping move these activities and projects forward in a more efficient and time-effective manner. The traditional stakeholders, i.e., Owner, A/E and the Contractor are involved in this BIM system that is used in almost every activity of construction projects, such as design, cost estimate and scheduling. This article extracts major features of the application of BIM from perspective of participating BIM components, along with the different phrases, and applies to them a logistic analysis using a fuzzy performance tree, quantifying these phrases to judge the effectiveness of the BIM techniques employed. That is to say, these fuzzy performance trees with fuzzy logic concepts can properly translate the linguistic rating into numeric expressions, and are thus employed in evaluating the influence of BIM applications as a mathematical process. The rotational fuzzy models are used to represent the membership functions of the performance values and their corresponding weights. Illustrations of the use of this fuzzy BIM performance tree are presented in the study for the uninitiated users. The results of these processes are an evaluation of BIM project performance as highly positive. The quantification of the performance ratings for the individual factors is a significant contributor to this assessment, capable of parsing vernacular language into numerical data for a more accurate and precise use in performance analysis. It is hoped that fuzzy performance trees and fuzzy set analysis can be used as a tool for the quality and risk analysis for other construction techniques in the future. Baldwin's rotational models are used to represent the membership functions of the fuzzy sets. Three scenarios are presented using fuzzy MEAN, AND and OR gates from the lowest to intermediate levels of the tree, and fuzzy SUM gate to relate the intermediate level to the top component of the tree, i.e., BIM application final performance. The use of fuzzy MEAN for lower levels and fuzzy SUM gates to reach the top level suggests the most realistic and accurate results. The methodology (fuzzy performance tree) described in this paper is appropriate to implement in today's construction industry when limited objective data is presented and it is heavily relied on experts' subjective judgment.

• Journal of Environmental Health Sciences
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• v.46 no.4
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• pp.410-422
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• 2020

Objectives: According to the Act on Registration, Evaluation, Etc. of Chemicals, new and existing chemicals must be registered by 2030. In addition, industries need to submit hazard data as an attachment during the registration process. Therefore, we constructed a nationwide chemical database to support small industry by providing hazard data and original sources. During the process, we developed a new standard procedure for minimizing errors and increasing reliability. Methods: We analyzed the categories of errors and the cause of the errors through the verification results of the 2019 project. We present an improved database construction methodology and system. Results: Errors are categorized according to their causative factors into simple, technical, and structural type errors. Simple errors arise simply because of decreased concentration or negligence in following the instructions. Technical errors are caused by a discrepancy between the professional field and the type of data. Structural errors indicate systemic errors such as incomplete forms on the excel database or ambiguity in the guidelines. Lessons from the errors collected in the 2019 project are used to update the procedures for database authorization and technical guidelines. The main update points are as follows; 'supplementation of review process', 'giving regular training to external reviewers', 'giving additional information to authors, like physico-chemical properties of substances, degradability, etc.', 'amendment of excel form', and 'guideline upgrades'. Conclusions: We conducted this study with the aim of improving the accuracy and reliability of the database of hazard information for chemical substances. The new procedures and guidelines are now being used in the 2020 project for construction of a hazard information database for Korea.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.41-61
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• 2004

The purpose of this paper is to construct $\ulcorner$CIDEAR(Cross Impact-DEA-AR)$\lrcorner$ model which evaluates proposed R&D projects considering cross impact among them and selects proper projects to utilize resources efficiently as well as to maximize efficacy of investments. For this purpose, $\ulcorner$CIDEAR$\lrcorner$ model is designed as the following six steps. $\ulcorner$Decision Theory Evaluation Model$\lrcorner$ is for setting and selecting the evaluation items according to the structured procedure of evaluation system. The priority of items is decided at $\ulcorner$AR Decision Model$\lrcorner$$\ulcorner$Cross Impact Estimation Model$\lrcorner$ is for computing the final probability of success and the result is used to revise the evaluation results of $\ulcorner$Decision Theory Evaluation Model$\lrcorner$. $\ulcorner$Resource Performance Analysis Model$\lrcorner$ classifies the proposed R&D projects on the basis of required resources and expected performance. Consequently, the possibility of bias of project selection can be prevented. $\ulcorner$Priority Oder Decision Model$\lrcorner$ is for computing the efficacy of proposed projects. Finally, $\ulcorner$Efficacy-Efficiency Cause Analysis Model$\lrcorner$ analyzes the structure of efficacy and efficiency of the projects. The major findings and significances of this study are summarized as follows: (1) $\ulcorner$CIDEAR$\lrcorner$ model can deal with the affairs of R&D projects having the characteristics of mutual independence as well as mutual dependence in the point of efficacy and efficiency. Hence, it is possible to evaluate and select R&D projects more accurately. (2) It can be possible to raise the possibility of projects success. R&D manager can use the information for project management because the efficacy-efficiency structure of selected projects can be analyzed. (3) We proved the usefulness of the constructed $\ulcorner$CIDEAR$\lrcorner$ model using an case about twenty-one R&D projects of a leading company of electronic industry in Korea.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.1
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• pp.57-73
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• 2021

The purpose of this study is to analyze the diffusion period and productivity of smartwork in an organization. Firms are increasingly interested in smartwork for non contact work and working from home because of the corona 19. The smartwork is a new technology that changes face-to-face work in an organization. It helps the work of individuals and organizations regardless of time and place. The theoretical background describes the complexity, system thinking, diffusion theory, smart work, organizational resistance, and productivity. This study analyzes the diffusion period and productivity of smart work through business simulation techniques. A simulation study progresses four stages. There are problem definition, hypothesis establishment and causal loop diagram, model construction and verification, and policy evaluation. The simulation models contain an individual's resistance variables organizational investment and leadership variables related to the operation of smartwork. The organizational investment variables include organizational culture, legal system, implement systems and technology investment. The individual resistance variables include cognitive, attitude, structure and technological resistance. The leadership includes leadership interest variables and performance linkage variables. The simulation executed the changes of a people number adopting smart work and the organizational productivity monthly. As a result of the simulation, many organization members have accepted the smart work innovation after 20 months. The organizational productivity through smart work showed very high value after 16 months. In scenario analysis, the individuals' awareness and attitude resistance showed very important variables to productivity and a personal change of smart work adoption. Meanwhile, The organizational investment showed that the high driving-force increased not productivity and the low driving-force showed decreased low productivity. Also, leadership variables showed a powerful driver for changing smart work productivity. The implication of the study has suggested extending complexity, diffusion theory and organization resistance theory based on simulation methods.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.6
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• pp.643-648
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• 2013

In this paper, we developed a system which can detect and can alarm about the sailing provocative climate by using a photo. The research on domestic shipbuilding industry and in IT fusion technology is under construction, but a reliable safety device which can alarm a sailor about the circumstances of the fog and rain during ship operation as soon as possible due to the constant state in domestic. In this paper, a compact, for system low-power transceiver and data processing equipment for sensing were developed, also a performance evaluation got accomplished with simulation analysis. In results, it is operating normally at least 32.36[dB] and maximum values f 89.20[dB] in the domestic, and 32.55 to 60.66[dB] in the outdoors.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.27 no.4
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• pp.398-422
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• 2017

Objectives: The major aim of this study is to construct the database of retrospective exposure assessment for crystalline silica through reviews of literatures in South Korea. Methods: Airborne concentrations of crystalline silica were collected using an academic information search engine, Research Information Service System(RISS), operated by the Korea Education & Research Information Service(KERIS). The key words used for the literature search were 'silica', 'crystalline silica', 'cristobalite', 'quartz' and 'tridymite'. A total number of 18 published documents with the information of crystalline silica level in air or bulk samples were selected and used to estimate retrospective exposures to crystalline silica. Weighted arithmetic mean(WAM) calculated across studies was summarized by industry type. Industries were classified according to Korea Standard Industrial Classification(KSIC) using information provided in the literature. Results: A total of 2,131 individual air sampling data measured from 1987 to 2012 were compiled. Compiled individual measurement data consisted of 827 respirable crystalline silica (RCS), 31 total crystalline silica(TCS), 24 crystalline silica(CS), 778 respirable dust(RD) and 471 total dust(TD). Most of RCS measurements(68.9%) were collected from 'cast of metals(KSIC 243)'. Comparing industry types, 'mining coal and lignite(KISC 051)' showed the highest WAM concentration of RCS, $0.14mg/m^3$, followed by $0.11mg/m^3$ of 'manufacture of other non-metallic mineral products(KSIC 239)', $0.108mg/m^3$ of 'manufacture of ceramic ware(KSIC 232)', $0.098mg/m^3$ of 'heavy construction(KSIC 412)' and $0.062mg/m^3$ of 'cast of metals(KSIC 243)'. In terms of crystalline silica contents in airborne dust, 'manufacture of other non-metallic mineral products(KSIC 239)' showed the highest value of 7.3%(wt/wt), followed by 6.8% of 'manufacture of ceramic ware(KSIC 232)', 5.8% of 'mining of iron ores(KSIC 061)', 4.9% of 'cast of metals(KSIC 243)' and 4.5% of 'heavy construction(KSIC 412)'. WAM concentrations of RCS had no consistent trends over time from 1994 ($0.26mg/m^3$) to 2012 ($0.12mg/m^3$). Conclusion: The data set related RCS exposure level by industries can be used to determine not only the possibility of retrospective exposure to RCS, but also to evaluate the level of quantitative retrospective exposure to RCS.

• Journal of Environmental Health Sciences
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• v.36 no.5
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• pp.391-401
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• 2010

A reduction in risk of occupational exposure to chemical hazards within the workplace has been the focus of attention both through industry initiatives and legislation. The aims of this study were to develop an exposure matrix by industry and process, and to apply this matrix to control the risk of occupational exposure to Dichloromethane (DCM). The exposure matrix is a tool to convert information on industry and process into information on occupational risk. The exposure matrix comprised industries and processes involving DCM, based on an exposure database provided by KOSHA (the Korean Occupational Safety and Health Agency), which was gathered from a workplace hazards evaluation program in Korea. The risk assessment of the exposure matrix was performed using Hallmark risk assessment tool. The results of the risk assessment were indicated by a Danger Value (DV) calculated from the combination of hazard rating (HR), duration of use rating (DUR), and risk probability rating (RPR) of exposure to the chemical, and were divided into four control bands which were related to control measures. The applicability of the risk assessment of the exposure matrix was evaluated by a field study, and survey of the employees of the exposure matrix groups. Among 45 industries examined, this study found that greater attention should be paid to two industries: the manufacture of other optical instruments and photographic equipment, and the manufacture of printing ink, and to one process among 47 examined, the packing process in the manufacture of printing ink, because these were regarded as carrying the highest risk. This tool of a risk assessment for the exposure matrix can be applied as a general exposure information system for hazard control, risk quantification, setting the occupational exposure limit, and hazard surveillance. The exposure matrix includes workforce data, and it provides information on the numbers of exposed workers in Korea by agent, occupation, and level of exposure and risk.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.265-290
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• 2022

An economic evaluation was conducted using cost-benefit analysis for an integrated service platform of open access research articles. The data needed for benefit measurement were collected by conducting a series of surveys to service beneficiaries, including 1,313 academic researchers, 49 bio-industry researchers, and 102 researchers in various industries. Cost-benefit analysis and sensitivity analysis were conducted after estimating the total costs for system construction and operations, anticipated direct and indirect benefits. With respect to the cost-benefit analysis limited to direct benefits, the estimated benefit was KRW 82 billion, which is about 14 times of the total costs for eight years of the entire business period. With respect to the cost-benefit analysis for both direct and indirect benefits, BCR was estimated to be about 98.9 and NPV to be KRW 538.8 billion, indicating that economic feasibility of the project was sufficiently secured. The results of this analysis may help securing the investment to the integrated service platform for OA research products, and the benefit estimation model developed in this study would be utilized as an assessment tool during the rest of this project.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.7
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• pp.380-394
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• 2015

This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2014. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of heat and mass transfer, cooling and heating, and air-conditioning, the flow inside building rooms, and smoke control on fire. Research issues dealing with duct and pipe were reduced, but flows inside building rooms, and smoke controls were newly added in thermal and fluid engineering research area. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results for thermal contact resistance measurement of metal interface, a fan coil with an oval-type heat exchanger, fouling characteristics of plate heat exchangers, effect of rib pitch in a two wall divergent channel, semi-empirical analysis in vertical mesoscale tubes, an integrated drying machine, microscale surface wrinkles, brazed plate heat exchangers, numerical analysis in printed circuit heat exchanger. In the area of pool boiling and condensing, non-uniform air flow, PCM applied thermal storage wall system, a new wavy cylindrical shape capsule, and HFC32/HFC152a mixtures on enhanced tubes, were actively studied. In the area of industrial heat exchangers, researches on solar water storage tank, effective design on the inserting part of refrigerator door gasket, impact of different boundary conditions in generating g-function, various construction of SCW type ground heat exchanger and a heat pump for closed cooling water heat recovery were performed. (3) In the field of refrigeration, various studies were carried out in the categories of refrigeration cycle, alternative refrigeration and modelling and controls including energy recoveries from industrial boilers and vehicles, improvement of dehumidification systems, novel defrost systems, fault diagnosis and optimum controls for heat pump systems. It is particularly notable that a substantial number of studies were dedicated for the development of air-conditioning and power recovery systems for electric vehicles in this year. (4) In building mechanical system research fields, seventeen studies were reported for achieving effective design of the mechanical systems, and also for maximizing the energy efficiency of buildings. The topics of the studies included energy performance, HVAC system, ventilation, and renewable energies, piping in the buildings. Proposed designs, performance performance tests using numerical methods and experiments provide useful information and key data which can improve the energy efficiency of the buildings. (5) The field of architectural environment was mostly focused on indoor environment and building energy. The main researches of indoor environment were related to the evaluation of work noise in tunnel construction and the simulation and development of a light-shelf system. The subjects of building energy were worked on the energy saving of office building applied with window blind and phase change material(PCM), a method of existing building energy simulation using energy audit data, the estimation of thermal consumption unit of apartment building and its case studies, dynamic window performance, a writing method of energy consumption report and energy estimation of apartment building using district heating system. The remained studies were related to the improvement of architectural engineering education system for plant engineering industry, estimating cooling and heating degree days for variable base temperature, a prediction method of underground temperature, the comfort control algorithm of car air conditioner, the smoke control performance evaluation of high-rise building, evaluation of thermal energy systems of bio safety laboratory and a development of measuring device of solar heat gain coefficient of fenestration system.