• Journal of Environmental Impact Assessment
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• v.33 no.1
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• pp.9-17
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• 2024

The purpose of this study is to select and predict optimal heatwave indices for describing and predicting heat-related illnesses. Regression analysis was conducted using Heat-related illness surveillance system data for a number of heat-related illnesses and meteorological data from the Korea Meteorological Administration's Automatic Weather Station (AWS) for the period from 2021 to 2023. Daily average temperature, daily maximum temperature, daily average Wet Bulb Globe Temperature (WBGT), and daily maximum WBGT values were calculated and analyzed. The results indicated that among the four indicators, the daily maximum WBGT showed the highest suitability with an R² value of 0.81 and RMSE of 0.98, with a threshold of 29.94 Celsius. During the entire analysis period, there were a total of 91 days exceeding this threshold, resulting in 339 cases of heat-related illnesses. Predictions of heat-related illness cases from 2021 to 2023 using the regression equation for daily maximum WBGT showed an accuracy with less than 10 cases of error annually, demonstrating a high level of precision. Through continuous research and refinement of data and analysis methods, it is anticipated that this approach could contribute to predicting and mitigating the impact of heatwaves.

• Information Systems Review
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• v.21 no.1
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• pp.23-38
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• 2019

The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.117-129
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• 2015

As the Internet becomes ubiquitous, a large volume of information is posted on the Internet with exponential growth every day. Accordingly, it is not unusual that investors in stock markets gather and compile firm-specific or market-wide information through online searches. Importantly, it becomes easier for investors to acquire value-relevant information for their investment decision with the help of powerful search tools on the Internet. Our study examines whether or not the Internet helps investors assess a firm's value better by using firm-level data over long periods spanning from January 2004 to December 2013. To this end, we construct weekly-based search volume for information technology (IT) services firms on the Internet. We limit our focus to IT firms since they are often equipped with intangible assets and relatively less recognized to the public which makes them hard-to measure. To obtain the information on those firms, investors are more likely to consult the Internet and use the information to appreciate the firms more accurately and eventually improve their investment decisions. Prior studies have shown that changes in search volumes can reflect the various aspects of the complex human behaviors and forecast near-term values of economic indicators, including automobile sales, unemployment claims, and etc. Moreover, search volume of firm names or stock ticker symbols has been used as a direct proxy of individual investors' attention in financial markets since, different from indirect measures such as turnover and extreme returns, they can reveal and quantify the interest of investors in an objective way. Following this line of research, this study aims to gauge whether the information retrieved from the Internet is value relevant in assessing a firm. We also use search volume for analysis but, distinguished from prior studies, explore its impact on return comovements with market returns. Given that a firm's returns tend to comove with market returns excessively when investors are less informed about the firm, we empirically test the value of information by examining the association between Internet searches and the extent to which a firm's returns comove. Our results show that Internet searches are negatively associated with return comovements as expected. When sample is split by the size of firms, the impact of Internet searches on return comovements is shown to be greater for large firms than small ones. Interestingly, we find a greater impact of Internet searches on return comovements for years from 2009 to 2013 than earlier years possibly due to more aggressive and informative exploit of Internet searches in obtaining financial information. We also complement our analyses by examining the association between return volatility and Internet search volumes. If Internet searches capture investors' attention associated with a change in firm-specific fundamentals such as new product releases, stock splits and so on, a firm's return volatility is likely to increase while search results can provide value-relevant information to investors. Our results suggest that in general, an increase in the volume of Internet searches is not positively associated with return volatility. However, we find a positive association between Internet searches and return volatility when the sample is limited to larger firms. A stronger result from larger firms implies that investors still pay less attention to the information obtained from Internet searches for small firms while the information is value relevant in assessing stock values. However, we do find any systematic differences in the magnitude of Internet searches impact on return volatility by time periods. Taken together, our results shed new light on the value of information searched from the Internet in assessing stock values. Given the informational role of the Internet in stock markets, we believe the results would guide investors to exploit Internet search tools to be better informed, as a result improving their investment decisions.

• Journal of Korea Water Resources Association
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• v.53 no.1
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• pp.45-56
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• 2020

This study aims to quantify the uncertainty that can be induced by the objective function when calibrating SWAT parameters using SWAT-CUP. SWAT model was constructed to estimate runoff in Naesenong-cheon, which is the one of mid-watershed in Nakdong River basin, and then automatic calibration was performed using eight objective functions (R², bR², NS, MNS, KGE, PBIAS, RSR, and SSQR). The optimum parameter sets obtained from each objective function showed different ranges, and thus the corresponding hydrologic characteristics of simulated data were also derived differently. This is because each objective function is sensitive to specific hydrologic signatures and evaluates model performance in an unique way. In other words, one objective function might be sensitive to the residual of the extreme value, so that well produce the peak value, whereas ignores the average or low flow residuals. Therefore, the hydrological similarity between the simulated and measured values was evaluated in order to select the optimum objective function. The hydrologic signatures, which include not only the magnitude, but also the ratio of the inclining and declining time in hydrograph, were defined to consider the timing of the flow occurrence, the response of watershed, and the increasing and decreasing trend. The results of evaluation were quantified by scoring method, and hence the optimal objective functions for SWAT parameter calibration were determined as MNS (342.48) and SSQR (346.45) with the highest total scores.

• Archives of design research
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• v.12 no.3
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• pp.179-188
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• 1999

Today when an age of unlimited competition is being ushered in, we are witnessing a Domino phenomenon driving many companies into insolvency due to the control of IMF bailout program and national management crisis. Amid such an extreme vortex, our companies are struggling hared to survive the crisis. As it is, it is very difficult for domestic companies to invest their capitals in the development of new technologies as they did in the past. Particularly, as knowhow or information regarding new technologies or products are databased or computerized enough to allow for its easier sharing or transmission, the conventional competitive edges are being dismissed more and more. Under such circumstances, the industrial design may be the best strategy or means for domestic companies to surmount their management crisis. For an industrial design may help to create a higher added value with a shouter-term investment or effort than other types of research and development efforts. In order to realize such a higher added value of the industrial design with a shorter-term investment, it is required to establish an educational system which can continue to supply the quality design professionals armed with sense of creativity and practical applicability. Only when such an educational system has been established, our companies can afford to advance into the world markets with their unique designs produced by their professional designers. With such a basic conception in mind, this study was aimed at providing for the data useful to establishment of a scientific and systematic industrial design education system or the prerequisite for development of our industrial designs. To this end, the educational system of domestic and foreign college design departments were investigated and analyzed, while researcher's experience at a design department of Yuhan college (hereunder called 'Y' college) were used. Based on the results of investigation and analysis, marketing strategies for design departments are put forwards together with a new pedagogic method of bringing up professional industrial designers through reinforcement of the design department curriculum.

• The Journal of Art Theory & Practice
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• no.14
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• pp.7-32
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• 2012

The exhibition was started in 2010 in the New Acropolis Museum of Athens and embarked a journey since 2011 as a travelling exhibition inside Greece and abroad. The main purpose of the exhibition was to draw attention of the general public to the value of the 'rescue excavation' and of cultural heritage of Greece, by presenting the reconstruction bust of a girl whose skull was found in Kerameikos cemetery of ancient Athens. The new Kerameikos excavation was initiated by the construction of Metropolitan Railway lines in the center of Athens between 1992 to 1998. It revealed a pit of a mass burial where about 150 people were inhumed in a very hasty way without proper funeral rites or offerings. These bodies are identified as the victims of the infamous plague of Athens in the first years of the Peloponnesian War(430-426 BC). The epidemic disease killed almost one third of the city population including Pericles, and brought extreme fear and panic to the Athens society. The traditional funerary rites were totally disrupted, and the social decorum and the morality among the citizens became enfeebled. The plague and the civil war were the decisive factors to end the Golden Age of Democratic Athens. However, the exhibition organizers did not focus on the tragic aspect of this disaster and its casualties. Their main concern was to simplify the scholarly works of archaeological excavation and microchemistry analysis so that the exhibition viewers will easily understand and empathize the living value of the scholarly works of ancient Greek civilization. The centripetal element of the exhibition was the vivid face of an 11 years old ancient girl 'Myrtis', which was carefully reconstructed based on both the scientific data and artistic imagination. Also the set up of the exhibition was structured in order to stimuli cognitive and emotional experience of the visitors who witnessed the rebirth of a vibrant human being from an ancient debris. The museologists' continuous efforts to promote projects of contemporary artists, publications, and school programs related to the exhibition indicate that the ulterior motive of this exhibition is the cultural education of the present and future generation through the intimate experiences of ancient Greek life. Also this is the reason why the various museums that held the travelling exhibition try to make the presentation as a gesture of memorial service for an anonymous Athenian girl who deceased circa 2400 years ago. The pragmatic efforts of Greek scholars and museologists through exhibition show us a way to find a solution to the continuous threat of cultural resources by massive construction projects and land development, and to overcome public indifference to the history and cultural heritage.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.745-760
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• 2021

Prediction of a stock price has been a subject of interest for a long time in financial markets, and thus, many studies have been conducted in various directions. As the efficient market hypothesis introduced in the 1970s acquired supports, it came to be the majority opinion that it was impossible to predict stock prices. However, recent advances in predictive models have led to new attempts to predict the future prices. Here, we summarize past studies on the price prediction by evaluation measures, and predict the direction of stock prices of Samsung Electronics, LG Chem, and NAVER by applying various machine learning models. In addition to widely used technical indicator variables, accounting indicators such as Price Earning Ratio and Price Book-value Ratio and outputs of the hidden Markov Model are used as predictors. From the results of our analysis, we conclude that no models show significantly better accuracy and it is not possible to predict the direction of stock prices with models used. Considering that the models with extra predictors show relatively high test accuracy, we may expect the possibility of a meaningful improvement in prediction accuracy if proper variables that reflect the opinions and sentiments of investors would be utilized.

• Journal of the Korean Geotechnical Society
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• v.25 no.11
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• pp.105-115
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• 2009

The Jeju sand was sampled from the beach in Jeju Island and its basic properties were analyzed. The cementation effect of Jeju coastal sediments was evaluated from in-situ tests such as SPT, CPT, and the Suspension-PS test. It was shown from test results that the Jeju sand has high extreme void ratios due to the angularity of grains and the intra-particle voids of hollow particles, similar to typical calcareous sands. From cone penetration test in the calibration chamber, it was found that the cone resistance($q_c$)-relative density($D_R$)-vertical effective stress(${\sigma}_v'$) relation of Jeju sand almost matches that of high compressible quartz sand. However, the $q_C-D_R-{\sigma}_v'$ correlation suggested for uncemented Jeju sand overestimates the relative density of coastal sediments of Jeju Island due to the cementation effect. From the analysis of the relation of cone resistance, N value, and small strain shear modulus measured in-situ, it seems reasonable to assume that the coastal sediment of Jeju Island is a naturally cemented one.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.239-247
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• 2023

The FIDIC Red Book is an international standard contract condition in which the Employer designs and the Contractor performs the construction. The Engineer of FIDIC Red Book shall agree or determine any matter or Claim in accordance with Sub-Clause 3.7 neutrally, not as an agent of the Employer. This study aimed to derive Key Risk Sub-Clauses out of 49 Sub-Clauses that the Engineer of FIDIC Red Book recently revised in 18 years shall agree or determine according to Sub-Clause 3.7 using the Delphi method. A panel of 35 experts with more than 10 years of experience and expertise in international construction contracts was formed, and through total three Delphi surveys, errors and biases were prevented in the judgment process to improve reliability. As for the research method, 49 Sub-Clauses that engineers shall agree on or determine according to Sub-Clause 3.7 of the FIDIC Red Book were investigated through the analysis of contract conditions. In order to evaluate the probability and impact of contractual risk for each 49 Sub-Clause, the Delphi survey conducted repeatedly a closed-type survey three times on a Likert 10-point scale. The results of the first Delphi survey were delivered during the second survey, and the results of the second survey were delivered to the third survey, which was re-evaluated in the direction of increasing the consensus of experts' opinions. The reliability of the Delphi 3rd survey results was verified with the COV value of the coefficient of variation. The PI Risk Matrix was applied to the average value of risk probability and impact of each of the 49 Sub-Clauses and finally, 9 Key Risk Sub-Clauses that fell within the extreme risk range were derived.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.661-671
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• 2017

The objective of this study was to analyze the flood stage considering the uncertainty caused by the river roughness coefficients and discharge. The methodology of this study involved the GLUE (Generalized Likelihood Uncertainty Estimation) to quantify the uncertainty bounds applying three different storm events. The uncertainty range of the roughness was 0.025~0.040. In case of discharge, the uncertainty stemmed from parameters in stage-discharge rating curve, if h represents stage for discharge Q, which can be written as $Q=A(h-B)^C$. Parameters in rating curve (A, B and C) were estimated by non-linear regression model and assumed by t distribution. The range of parameters in rating curve was 5.138~18.442 for A, -0.524~0.104 for B and 2.427~2.924 for C. By sampling 10,000 parameter sets, Monte Carlo simulations were performed. The simulated stage value was represented by 95% confidence interval. In storm event 1~3, the average bound was 0.39 m, 0.83 m and 0.96 m, respectively. The peak bound was 0.52 m, 1.36 m and 1.75 m, respectively. The recurrence year of each storm event applying the frequency analysis was 1-year, 10-year and 25-year, respectively.