• Journal of Korea Water Resources Association
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• v.52 no.5
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• pp.349-360
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• 2019

The purpose of this study is to evaluate the stream flow and water quality (SS, T-N, and T-P) behavior of Nakdong river basin ($23,609.3km^2$) by simulating the dam and weir operation scenarios using SWAT (Soil and Water Assessment Tool). The operation senarios are the simultaneous release for all dam and weirs (scenario 1), simultaneous release for all weirs (scenario 2), and sequential release for the weirs with one month interval from upstream weirs (scenario 3). Before evaluation, the SWAT was calibrated and validated using 11 years (2005-2015) daily multi-purpose dam inflow at 5 locations (ADD, IHD, HCD, MKD, and MYD), multi-function weir inflow at 7 locations (SHW, GMW, CGW, GJW, DSW, HCW, and HAW), and monthly water quality monitoring data at 6 locations (AD-4, SJ-2, EG, HC, MK-4, and MG). For the two dam inflow and dam storage, the Nash-Sutcliffe efficiency (NSE) was 0.56~0.79, and the coefficient of determination ($R^2$) was 0.68~0.90. For water quality, the $R^2$ of SS, T-N, and T-P was 0.64~0.79, 0.51~0.74, and 0.53~0.72 respectively. For the three scenarios of dam and weir release combination suggested by the ministry of environment, the scenario 1 and 3 operations were improved the stream water quality (for T-N and T-P) within the 3 months since the time of release, but it showed the negative effect for 3 months after compared to scenario 2.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1465-1483
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• 2020

Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• The Journal of Engineering Geology
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• v.29 no.1
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• pp.51-68
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• 2019

This study performs to evaluate adaptability of seashore filtering type seawater-intake which adapts dua1 filter well alternative for direct seawater-intake. This study varies filter condition of seashore free surface aquifer which is composed of sand layer then installs real size dual filter well and single filter well to evaluate water permeability and proper pumping amount according to filter condition. According to result of step aquifer test, it is analysed that 110.3% synergy effect of water permeability coefficient is happened compare to single filter since dual filter well has better improvement. dual filter has higher water permeability coefficient compare to same pumping amount, this means dual filter has more improved water permeability than single filter. According to analysis result of continuous aquifer test, it is evaluated that dual filter well (SD1200) has higher water permeability than single filter well (SS800) by analysis of water permeability coefficient using monitoring well and gauging well, it is also analysed dual filter has 110.7% synergy effect of water permeability coefficient. As a evaluation result of pumping amount according to analysis of water level dropping rate, it is analysed that dual filter well increased 122.8% pumping amount compare to single filter well when water level dropping is 2.0 m. As a result of calculating proper pumping amount using water level dropping rate, it is analysed that dual filter well shows 136.0% higher pumping amount compare to single filter well. It is evaluated that proper pumping amount has 122.8~160% improvement compare to single filter, pumping amount improvement rate is 139.6% compare to averaged single filter. In other words, about 40% water intake efficiency can be improved by just installation of dual filter compare to normal well. Proper pumping amount of dual filter well using inflection point is 2843.3 L/min and it is evaluated that daily seawater intake amount is about $4,100m^3/day$ (${\fallingdotseq}4094.3m^3/day$) in one hole of dual filter well. Since it is possible to intake plenty of water in one hole, higher adaptability is anticipated. In case of intaking seawater using dual filter well, no worries regarding damages on facilities caused by natural disaster such as severe weather or typhoon, improvement of pollution is anticipated due to seashore sand layer acts like filter. Therefore, It can be alternative of environmental issue for existing seawater intake technique, can save maintenance expenses related to installation fee or damages and has excellent adaptability in economic aspect. The result of this study will be utilized as a basic data of site demonstration test for adaptation of riverside filtered water of upcoming dual filter well and this study is also anticipated to present standard of well design and construction related to riverside filter and seashore filter technique.

• Journal of Preventive Medicine and Public Health
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• v.23 no.3 s.31
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• pp.324-337
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• 1990

To assess the effectiveness of the interventions in working environment and personal hygiene for the occupational exposure to the lead, 156 workers (116 exposed subjects and 40 controls) of a newly established battery factory were examined for their blood lead concentration (Pb-B) in every 3 months up to 18 months. Air lead concentration (Pb-A) of the workplaces was also checked for 3 times in 6 months interval from August 1987. Environmental intervention included the local exhaust ventilation and vacuum cleaning of the floor. Intervention of the personal hygiene included the daily change of clothes, compulsory shower after work and hand washing before meal, prohibition of cigarette smoking and food consumption at the work site and wearing mask. Mean Pb-B of the controls was $21.97{\pm}3.36{\mu}g/dl$ at the preemployment examination and slightly increased to $22.75{\pm}3.38{\mu}g/dl$ after 6 months. Mean Pb-B of the workers who were employed before the factory was in operation (Group A) was $20.49{\pm}3.84{\mu}g/dl$ on employment and it was increased to $23.90{\pm}5.30{\mu}g/dl$ after 3 months (p<0.01). Pb-B was increased to $28.84{\pm}5.76{\mu}g/dl$ 6 months after the employment which was 1 month after the initiation of intervention program. It did not increase thereafter and ranged between $26.83{\mu}g/dl\;and\;28.28{\mu}g/dl$ in the subsequent 4 tests. Mean Pb-B of the workers who were employed after the factory had been in operation but before the intervention program was initiated (Group B) was $16.58{\pm}4/53{\mu}g/dl$ before the exposure and it was increased to $28.82{\pm}5.66{\mu}g/dl$(P<0.01) in 3 months later (1 month after the intervention). The values of subsequent 4 tests remained between 26.46 and $28.54{\mu}g/dl$. Mean Pb-B of the workers who were employed after intervention program had been started (Group C) was $19.45{\pm}3.44{\mu}g/dl$ at the preemployment examination and gradually increased to $22.70{\pm}4.55{\mu}g/dl$ after 3 months(P<0.01), $23.68{\pm}4.18{\mu}g/dl$ after 6 months, and $24.42{\pm}3.60{\mu}g/dl$ after 9 months. Work stations were classified into 4 parts according to Pb-A. The Pb-A of part I, the highest areas, were $0.365mg/m^3$, and after the intervention the levels were decreased to $0.216mg/m^3\;and\;0.208mg/m^3$ in follow-up tests. The Pb-A of part II was decreased from $0.232mg/m^3\;to\;0.148mg/m^3,\;and\;0.120mg/m^3$ after the intervention. Pb-A of part III and W was tested only after intervention and the Pb-A of part III were $0.124mg/m^3$ in Jannuary 1988 and $0.081mg/m^3$ in August 1988. The Pb-A of part IV not stationed at one place but moving around, was $0.110mg/m^3$ in August 1988. There was no consistent relationship between Pb-B and Pb-A. Pb-B of the group A and B workers in the part of the highest Pb-A were lower than those of the workers in the parts of lower Pb-A. Pb-B of the workers in the part of the lowest Pb-A incerased more rapidly. Pb-B of group C workers was the highest in part I and the lowest in part IV. These findings suggest that Pb-B is more valid method than Pb-A for monitoring the health of lead workers and intervention in personal hygiene is more effective than environmental intervention.

• Journal of Distribution Science
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• v.8 no.3
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• pp.49-56
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• 2010

At the initial stage of Internet advertising, banner advertising came into fashion. As the Internet developed into a central part of daily lives and the competition in the on-line advertising market was getting fierce, there was not enough space for banner advertising, which rushed to portal sites only. All these factors was responsible for an upsurge in advertising prices. Consequently, the high-cost and low-efficiency problems with banner advertising were raised, which led to an emergence of keyword advertising as a new type of Internet advertising to replace its predecessor. In the beginning of 2000s, when Internet advertising came to be activated, display advertisement including banner advertising dominated the Net. However, display advertising showed signs of gradual decline, and registered minus growth in the year 2009, whereas keyword advertising showed rapid growth and started to outdo display advertising as of the year 2005. Keyword advertising refers to the advertising technique that exposes relevant advertisements on the top of research sites when one searches for a keyword. Instead of exposing advertisements to unspecified individuals like banner advertising, keyword advertising, or targeted advertising technique, shows advertisements only when customers search for a desired keyword so that only highly prospective customers are given a chance to see them. In this context, it is also referred to as search advertising. It is regarded as more aggressive advertising with a high hit rate than previous advertising in that, instead of the seller discovering customers and running an advertisement for them like TV, radios or banner advertising, it exposes advertisements to visiting customers. Keyword advertising makes it possible for a company to seek publicity on line simply by making use of a single word and to achieve a maximum of efficiency at a minimum cost. The strong point of keyword advertising is that customers are allowed to directly contact the products in question through its more efficient advertising when compared to the advertisements of mass media such as TV and radio, etc. The weak point of keyword advertising is that a company should have its advertisement registered on each and every portal site and finds it hard to exercise substantial supervision over its advertisement, there being a possibility of its advertising expenses exceeding its profits. Keyword advertising severs as the most appropriate methods of advertising for the sales and publicity of small and medium enterprises which are in need of a maximum of advertising effect at a low advertising cost. At present, keyword advertising is divided into CPC advertising and CPM advertising. The former is known as the most efficient technique, which is also referred to as advertising based on the meter rate system; A company is supposed to pay for the number of clicks on a searched keyword which users have searched. This is representatively adopted by Overture, Google's Adwords, Naver's Clickchoice, and Daum's Clicks, etc. CPM advertising is dependent upon the flat rate payment system, making a company pay for its advertisement on the basis of the number of exposure, not on the basis of the number of clicks. This method fixes a price for advertisement on the basis of 1,000-time exposure, and is mainly adopted by Naver's Timechoice, Daum's Speciallink, and Nate's Speedup, etc, At present, the CPC method is most frequently adopted. The weak point of the CPC method is that advertising cost can rise through constant clicks from the same IP. If a company makes good use of strategies for maximizing the strong points of keyword advertising and complementing its weak points, it is highly likely to turn its visitors into prospective customers. Accordingly, an advertiser should make an analysis of customers' behavior and approach them in a variety of ways, trying hard to find out what they want. With this in mind, her or she has to put multiple keywords into use when running for ads. When he or she first runs an ad, he or she should first give priority to which keyword to select. The advertiser should consider how many individuals using a search engine will click the keyword in question and how much money he or she has to pay for the advertisement. As the popular keywords that the users of search engines are frequently using are expensive in terms of a unit cost per click, the advertisers without much money for advertising at the initial phrase should pay attention to detailed keywords suitable to their budget. Detailed keywords are also referred to as peripheral keywords or extension keywords, which can be called a combination of major keywords. Most keywords are in the form of texts. The biggest strong point of text-based advertising is that it looks like search results, causing little antipathy to it. But it fails to attract much attention because of the fact that most keyword advertising is in the form of texts. Image-embedded advertising is easy to notice due to images, but it is exposed on the lower part of a web page and regarded as an advertisement, which leads to a low click through rate. However, its strong point is that its prices are lower than those of text-based advertising. If a company owns a logo or a product that is easy enough for people to recognize, the company is well advised to make good use of image-embedded advertising so as to attract Internet users' attention. Advertisers should make an analysis of their logos and examine customers' responses based on the events of sites in question and the composition of products as a vehicle for monitoring their behavior in detail. Besides, keyword advertising allows them to analyze the advertising effects of exposed keywords through the analysis of logos. The logo analysis refers to a close analysis of the current situation of a site by making an analysis of information about visitors on the basis of the analysis of the number of visitors and page view, and that of cookie values. It is in the log files generated through each Web server that a user's IP, used pages, the time when he or she uses it, and cookie values are stored. The log files contain a huge amount of data. As it is almost impossible to make a direct analysis of these log files, one is supposed to make an analysis of them by using solutions for a log analysis. The generic information that can be extracted from tools for each logo analysis includes the number of viewing the total pages, the number of average page view per day, the number of basic page view, the number of page view per visit, the total number of hits, the number of average hits per day, the number of hits per visit, the number of visits, the number of average visits per day, the net number of visitors, average visitors per day, one-time visitors, visitors who have come more than twice, and average using hours, etc. These sites are deemed to be useful for utilizing data for the analysis of the situation and current status of rival companies as well as benchmarking. As keyword advertising exposes advertisements exclusively on search-result pages, competition among advertisers attempting to preoccupy popular keywords is very fierce. Some portal sites keep on giving priority to the existing advertisers, whereas others provide chances to purchase keywords in question to all the advertisers after the advertising contract is over. If an advertiser tries to rely on keywords sensitive to seasons and timeliness in case of sites providing priority to the established advertisers, he or she may as well make a purchase of a vacant place for advertising lest he or she should miss appropriate timing for advertising. However, Naver doesn't provide priority to the existing advertisers as far as all the keyword advertisements are concerned. In this case, one can preoccupy keywords if he or she enters into a contract after confirming the contract period for advertising. This study is designed to take a look at marketing for keyword advertising and to present effective strategies for keyword advertising marketing. At present, the Korean CPC advertising market is virtually monopolized by Overture. Its strong points are that Overture is based on the CPC charging model and that advertisements are registered on the top of the most representative portal sites in Korea. These advantages serve as the most appropriate medium for small and medium enterprises to use. However, the CPC method of Overture has its weak points, too. That is, the CPC method is not the only perfect advertising model among the search advertisements in the on-line market. So it is absolutely necessary that small and medium enterprises including independent shopping malls should complement the weaknesses of the CPC method and make good use of strategies for maximizing its strengths so as to increase their sales and to create a point of contact with customers.