• Korean Journal of Construction Engineering and Management
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• v.7 no.4 s.32
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• pp.137-145
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• 2006

Calculating non-working days is very important element for the accurate estimation of construction time. And non-working days are largely affected by weather factors such as rainfall, wind velocity, snowfall and temperature. In the case of concrete works, there are lots of referable information for the calculation of non-working days due to the weather factors. However, for the structural steel works, there are very limited information only. Through literature survey and interviews with a few engineers, this paper established the weather factors that affect steel structural works and the impact of those factors. Based on the factors and the expected impact of the factors together with the weather data during the last 15 years in Seoul region gathered from Korea Meteorological Administration, this paper suggests the monthly non-working day of structural steel work due to weather factors. This information can be used for the early estimation of construction time.

• KDI Journal of Economic Policy
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• v.35 no.1
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• pp.63-101
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• 2013

'Venture firms' in Korea are the firms who are certified as 'venture', whose certification types are defined by a law ('Special Law for the Support of Venture Firms'), and therefore encompass not only the venture capital-financed companies, which are usually regarded as ventures in USA and European countries, but also other types of firms such as R&D-intensive firms and the firms with financial guarantee or loans through technology evaluation ('technology finance or loan firms'). This paper examines the differences in the Korean venture firms' growth between the venture certification types. For the empirical analysis, this paper uses the lists of venture-certified firms from 1998 to 2010 which are then linked with their financial data in Korea Enterprises Database (KED). According to the results of empirical analyses, the companies in the 'venture capital-financed firms' type show greater growth rate in sales and the number of regular employees 3 and 5 years after first venture certification than the firms in type of 'technology finance/loan firms'. Moreover, the newly certified companies in 'R&D-intensive firms' type are also showing faster growth than the 'technology finance/loan firms' since 2003 where the venture industry has undergone a consolidation phase after the blast of so-called 'IT venture bubble' in 2001~2002. These results imply that the so-called 'venture firms' in Korea are composed with heterogeneous firm groups with different characteristics and that the companies selected through market mechanism ('venture capital-financed firms') outperforms the companies selected on the basis of policy interests ('technology finance/loan firms') in terms of the growth in sales and employment. On the basis of these findings, this paper suggests that the current venture-support policy should consider the different policy demands of firms across the type of venture certification more actively and that should refocus the objective of policies on facilitating venture capital market rather than emphasizing the nominal increase in the number of venture-certified firms.

• Journal of Intelligence and Information Systems
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• v.16 no.1
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• pp.93-116
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• 2010

Ensemble approach is applied to the detection modeling of illegal cash accommodation (ICA) that is the well-known type of fraudulent usages of credit cards in far east nations and has not been addressed in the academic literatures. The performance of fraud detection model (FDM) suffers from the imbalanced data problem, which can be remedied to some extent using an ensemble of many classifiers. It is generally accepted that ensembles of classifiers produce better accuracy than a single classifier provided there is diversity in the ensemble. Furthermore, recent researches reveal that it may be better to ensemble some selected classifiers instead of all of the classifiers at hand. For the effective detection of ICA, we adopt ensemble size reduction technique that prunes the ensemble of all classifiers using accuracy and diversity measures. The diversity in ensemble manifests itself as disagreement or ambiguity among members. Data imbalance intrinsic to FDM affects our approach for ICA detection in two ways. First, we suggest the training procedure with over-sampling methods to obtain diverse training data sets. Second, we use some variants of accuracy and diversity measures that focus on fraud class. We also dynamically calculate the diversity measure-Forward Addition and Backward Elimination. In our experiments, Neural Networks, Decision Trees and Logit Regressions are the base models as the ensemble members and the performance of homogeneous ensembles are compared with that of heterogeneous ensembles. The experimental results show that the reduced size ensemble is as accurate on average over the data-sets tested as the non-pruned version, which provides benefits in terms of its application efficiency and reduced complexity of the ensemble.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.151-159
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• 2010

This paper presents a research result that was performed to develop a more accurate freeway crash prediction model than existing models. While the existing crash models only focus on developing crash relationships associated with highway geometric conditions found on a short section of a crash site, this research applies a different approach considering the upstream highway geometric conditions as well. Theoretically, crashes occur while motorists are in motion, and particularly at freeways vehicle speed at one specific point is very sensitive to upstream geometric conditions. Therefore, this is a reasonable approach. To form the analysis data base, this research gathers the geometric conditions of the West Seaside Freeway 269.3 km and six years crash data ranging 2003-2008 for these freeway sections. As a result, it is found that crashes fit well into Negative Binomial Distribution, and, based on the developed model, total number of crashes is inversely proportional to highway curve length and radius. Contrarily, crash occurrences are proportional to tangent length. This result is different from existing crash study results, and it seems to be resulted from this research assumption that a crash is influenced greatly by upstream geometric conditions. Also, this research provides the expected effects on crash occurrences of the length of downgrade sections, speed camera placements, and the on- and off- ramp presences. It is expected that this research result is useful for doing more reasonable highway designs and safety audit analysis, and applying the same research approach to national roads and other major roads in urban areas is recommended.

• Knowledge Management Research
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• v.23 no.3
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• pp.129-152
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• 2022

As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.303-314
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• 2022

The persistence analysis of marine physical environment factors is a basic analysis that must precede the use of sea areas as an analysis required in the coastal engineering such as downtime and design. In this study, the persistence analysis was implemented for wind speed and significant wave height data from four observation points of Deokjeokdo, Oeyeondo, Geomundo, and Geojedo among the marine meteorological observation buoys of the Korea Meteorological Administration. The persistence time means the consecutive time of observation data beyond specific level. The threshold wind speed and significant wave height were set in the range of 1~15 m/s and the range of 0.25~3.0 m, respectively. Then, the persistence time was extracted. As a result of the analysis, the persistence time of wind speed and significant wave height decreased rapidly as the reference value increased. The median persistence times under the maximum reference thresholds were assessed as a maximum of 5 hours for wind speed and a maximum of 8 hours for significant wave height. When the reference wind speed and significant wave height were 15 m/s and 3 m, respectively, the persistence time that could occur with a 1% probability were 52 and 56 hours. This study can be expanded to all coastal areas in Korea, and it is expected that various engineering applications by performing a persistence analysis of the metocean data.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.1-16
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• 2024

Alvin Toffler mentioned that it is important for future society to keep pace with synchronization and that time deviations can hinder social development. As we experience the new normal era of untact, we have experienced an increase in non-face-to-face contact and accelerated digital transformation. Amid these rapid changes, we can maintain the need for synchronization or change in space. Therefore, we would like to study what kind of settlements people create and choose. We looked at the metaverse as an object that could indirectly find out about this, and used the content called "Animal Crossing" to collect data related to the spatial form of the metaverse. Sampling utilized a judgment sampling method during non-probability sampling to alleviate differences due to the progress of the game. The collected data was classified according to floor plan and location type and briefly organized through descriptive statistics. After matching each facility by use, data was constructed by setting coordinates for each cluster and listing them. This data was interpreted graphically on the coordinate plane for each cluster, and Euclidean analysis was performed to analyze the relationships between clusters and residential choice using a Euclidean matrix. As a result of the analysis, it could be interpreted that efficiency was pursued by arranging similar functions in close proximity. Nevertheless, when choosing a residence, it was interpreted that the intention was to create a community through arrangement adjacent to residents rather than efficiency or convenience. Due to the differences between the metaverse and the real world, it is expected that there will be limitations in equating it with reality. However, through the space expressed in the virtual world by people who are far away from the constraints of reality, we can indirectly know the wishes that we have not been able to express due to our lack of awareness.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.23-38
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• 2012

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.

• Journal of Bio-Environment Control
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• v.23 no.4
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• pp.293-302
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• 2014

This study was carried out to develop rain shelter which can make an appropriate size and environment for Chinese cabbage rainproof cultivation. Fifty three farms with chinese cabbage rainproof cultivation system have been investigated to set up width and height of rain shelter. Mostly the width of 6m was desired for rain shelter and the height of 1.6m for their eaves, so these values were chosen as the dimensions for rain shelter. After an analysis of their structural safety and installation costs by the specifications of the rafter pipe, Ø$25.4{\times}1.5t$ and 90cm have been set as the size of rafter that such size costs the least. This size is stable with $27m{\cdot}s^{-1}$ of wind velocity and 17cm of snow depth. Therefore it is difficult to apply this dimension to area with higher climate load. In order to sort out such problem, the rain shelter has been designed to avoid damage on frame by opening plastic film to the ridge. Once greenhouse band is loosen by turning the manual switch at the both sides of rain shelter and open button of controller is pushed then switch motor rises up along the guide pipe and plastic film is opened to the ridge. Chinese cabbage can be damaged by insects if rain shelter is opened completely as revealed a field. To prevent this, farmers can install an insect-proof net. Further, the greenhouse can be damaged by typhoon while growing Chinese cabbage therefore the effect of an insect-proof net on structural safety has been analyzed. And then structural safety has been analyzed through using flow-structure interaction method at the wind condition of $40m{\cdot}s^{-1}$. And it assumed that wind applied perpendicular to side of the rain shelter which was covered by insect-proof net. The results indicated that plastic film was directly affected by wind therefore high pressure occurred on the surface. But wind load on insect-proof net was smaller than on plastic film and pressure distribution was also uniform. The results of structural analysis by applying pressure data extracted from flow analysis indicated that the maximum stress occurred at the end of pipe which is the ground part and the value has been 54.6MPa. The allowable stress of pipe in the standard of structural safety must be 215 MPa or more therefore structural safety of this rain shelter is satisfied.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.1
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• pp.62-68
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• 2014

Purpose: After I-131 therapy, SPECT/CT is useful in identifying location of thyroid remnants and metastasis of thyroid cancers. An excessive uptake of thyroid leads to a ringing artifact in the SPECT images. The aim of this study is to investigate and suggest a proper post filters to remove ringing artifact and produce better image quality. Materials and Methods: A low-cost, customized thyroid-mimicking phantom, consisting of an acrylic bottle and a hollow sphere was used for SPECT/CT Discovery (GE Healthcare, USA). It was filled with I-131 solution. The ratio of hollow sphere to background were varied as 50:1, 200:1, 1000:1 and 4000:1. Acquired images were reconstructed by OSEM (2 iterations, 10 subsets) with and without Evolution (resolution recovery correction, GE). Three different post-filters were applied; Butterworth (cut off: 0.38 to 0.58 with intervals of 0.05), Hanning (cut off: 0.8 to 1 with intervals of 0.05) and Gaussian (FWHM: 3 to 5 with intervals of 0.5) filters. Contrast, background variability, air area variability, and full width half maximum (FWHM) were compared. Results: Higher contrasts were obtained from the SPECT images with Evolution than without Evolution. In the case of images without Evolution, image distortion such as star artifact was generated. For all sphere-to-background ratio, the Butterworth filter showed better constrasts and FWHMs than other two filters, but the ringing artifact was still generated in all studies except 50:1 and it was decreased as cutoff value was increased. The ringing artifact didn't appear with Hanning and Gaussian filters at all studies, however constrats and FWHMs with Gaussian was worse than Hanning filter. For the images having ringing artifacts, the background variability and air area variability were increased. Conclusion: In this study, we suggested that it is desirable to use Hanning filter when the ringing artifact is generated and to use Butterworth filter when ringing artifact is not generated in I-131 SPECT.