• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Korean Journal of Ecology and Environment
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• v.49 no.1
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• pp.51-61
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• 2016

This study was carried out to assess the carbon budget of two urban parks and one natural park and to prepare the plan for improving the ecological functions of the park including carbon sink. Net Ecosystem Production (NEP) of those study sites was calculated from the relationship between Net Primary Production (NPP) and soil respiration of each study site. To understand carbon budget of the whole area designated as the park, carbon budget of the urban park was analyzed by classifying the vegetated and the non-vegetated zones. NEP of the Nohae and the Sanggye parks calculated by reflecting areal size that the non-vegetated zones occupy were shown in -1.0 and $0.6\;ton\;C\;ha^{-1}yr^{-1}$, respectively. On the other hand, NEP of Mt. Bulam natural park as a reference site was in $2.3\;ton\;C\;ha^{-1}yr^{-1}$. Based on the result, the Nohae park was assessed as carbon source rather than carbon sink. On the other hand, the Sanggye park was classified as carbon sink but the role was poor compared with natural park. The result is, first of all, due to lower NPP of the vegetation introduced for the parks compared with natural vegetation. The other reason is due to wide arrangement of non-vegetated zone. To solve those problems and thereby to create the urban park with high ecological quality, selection of plant species suitable for the ecological characteristic of the park, their arrangement imitated natural vegetation, and ecological zoning were recommended.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.661-683
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• 2001

There is a rapid increase in the use of digital video information in recent years, it becomes more important to manage video databases efficiently. The development of high speed data network and digital techniques has emerged new multimedia applications such as internet broadcasting, Video On Demand(VOD) combined with video data processing and computer. Video database should be construct for searching fast, efficient video be extract the accurate feature information of video with more massive and more complex characteristics. Video database are essential differences between video databases and traditional databases. These differences lead to interesting new issues in searching of video, data modeling. So, cause us to consider new generation method of database, efficient retrieval method of video. In this paper, We propose the construction and generation method of the video database based on contents which is able to accumulate the meaningful structure of video and the prior production information. And by the proposed the construction and generation method of the video database implemented the video database which can produce the new contents for the internet broadcasting centralized on the video database. For this production, We proposed the video indexing method which integrates the annotation-based retrieval and the content-based retrieval in order to extract and retrieval the feature information of the video data using the relationship between the meaningful structure and the prior production information on the process of the video parsing and extracting the representative key frame. We can improve the performance of the video contents retrieval, because the integrated video indexing method is using the content-based metadata type represented in the low level of video and the annotation-based metadata type impressed in the high level which is difficult to extract the feature information of the video at he same time.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.3
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• pp.329-336
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• 2006

Iron manufacturing process involves production of various by-product including slag, sludge, sintering and EAF(Electric Arc furnace dust). Some of the by-products such as EAF and sintering dust are disposed of as waste due to their high heavy metal contents. It has been notice for many years that the EAF dust also contain about 65% of Fe(0) and Fe(II) and then the possible utilization of the iron. One possibility is to apply the EAF as a lining material in conjunction with clay or HDPE liners, in waste landfill. The probable reaction between the leachate containing toxic elements such as TCE, PCE dioxine and $Cr^{6+}$ is reduction of the toxic materials in corresponding to the oxidation of the reduced iron and therefore diminishing the toxicity of the leachate. It is, however, prerequisite to evaluate the leaching characteristics of the EAF dust before application. Amelioration of the leachate would be archived only when the level of toxic elements in the treated leachate is less than that of in the untreated leachate. Several leaching techniques were selected to cover different conditions and variable environments including time, pH and contact method. The testing methods include availability test, pH-stat test and continuous column test. Cr and Zn are potentially leachable elements among the trace metals. The pH of the EAF dust is highly alkaline, recording around 12 and Zn is unlikely to be leached under the condition. On the contrary Cr is more leachable under alkaline environment. However, the released Cr should be reduced to $Cr^{3+}$ and then removed as $Cr(OH)_3$. Removal of the Cr is observed in the column test and further study on the specific reaction of Cr and EAF dust is underway.

• Proceedings of the Korean Ceranic Society Conference
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• 2005.06a
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• pp.1-112
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• 2005

This report is results of a research on recent R&D trends in electroceramics, mainly focusing on the papers submitted to the organizing committee of the International Conference on Electroceramics 2005 (ICE-2005) which was held at Seoul on 12-15 June 2005. About 380 electroceramics researchers attended at the ICE-2005 from 17 countries including Korea, presenting and discussing their recent results. Therefore, we can easily understand the recent research trends in the field of electroceramics by analyses of the subject and contents of the submitted papers. In addition to the analyses of the papers submitted to the ICE-2005, we also collected some informations about domestic and international research trends to help readers understand this report easily. We analysed the R&D trends on the basis of four main categories, that is, informatics electroceramics, energy and environment ceramics, processing and characterization of electroceramics, and emerging fields of electroceramics. Each main category has several sub-categories again. The informatics ceramics category includes integrated dielectrics and ferroelectrics, oxide and nitride semiconductors, photonic and optoelectronic devices, multilayer electronic ceramics and devices, microwave dielectrics and high frequency devices, and piezoelectric and MEMS applications. The energy and environment ceramics category has four sub-categories, that is, rechargable battery, hydrogen storage, fuel cells, and advanced energy conversion concepts. In the processing and characterization category, there exist domain, strain, and epitaxial dynamics and engineering sub-category, innovative processing and synthesis sub-category, nanostructured materials and nanotechnology sub- category, single crystal growth and characterization sub-category, theory and modeling sub-category. Nanocrystalline electroceramics, electroceramics for smart sensors, and bioceramics sub-categories are included to the emerging fields category. We hope that this report give an opportunity to understand the international research trend, not only to Korean ceramics researchers but also to science and technology policy researchers.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.1
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• pp.68-82
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• 2017

Strengthening surveillance, one of the most important factors in the crime prevention environment of cultural heritages, has difficulty in evaluating and diagnosing the site. For this reasons, surveillance enhancement has been assessed by modelling the shape of cultural heritage, topography, and trees digitally. The purpose of this study is to develop the evaluation method of crime prevention environment for cultural heritage by using the 3D visual exposure index (3DVE) which can quantitatively evaluate the surveillance enhancement in three dimensions. For the study, the evaluation factors were divided into natural, organizational, mechanical, and integrated surveillance. To conduct the analysis, the buildings, terrain, walls, and trees of the study site were modeled in three dimensions and the analysis program was developed by using the Unity 3D. Considering the working area of the person, it is possible to analyze the surveillance point by dividing it into the head and the waist position. In order to verify the feasibility of the 3DVE as the analysis program, we assessed the crime prevention environment by digitally modeling the Donam Seowon(Historic Site No. 383) located in Nonsan. As a result of the study, it was possible to figure out the problems of patrol circulation, the blind spot, and the weak point in natural, mechanical, and organizational surveillance of Donam Seowon. The results of the 3DVE were displayed in 3D drawings, so that the position and object could be identified clearly. Surveillance during the daytime is higher in the order of natural, mechanical, and organizational surveillance, while surveillance during the night is higher in the order of organizational, mechanical, and natural surveillance. The more the position of the work area becomes low, the more it is easy to be shielded, so it is necessary to evaluate the waist position. It is possible to find out and display the blind spot by calculating the surveillance range according to the specification, installation location and height of CCTV. Organizational surveillance, which has been found to be complementary to mechanical surveillance, needs to be analyzed at the vulnerable time when crime might happen. Furthermore, it is note that the analysis of integrated surveillance can be effective in examining security light, CCTV, patrol circulation, and other factors. This study was able to diagnose the crime prevention environment by simulating the actual situation. Based on this study, consecutive researches should be conducted to evaluate and compare alternatives to design the crime prevention environment.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.10
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• pp.916-927
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• 2010

In general water treatment process, the disinfection process by chlorine is used to prevent water borne disease and microbial regrowth in water distribution system. Because chlorines were reacted with organic matter, carcinogens such as disinfection by-products (DBPs) were produced in drinking water. Therefore, a suitable injection of chlorine is need to decrease DBPs. Rechlorination in water pipelines or reservoirs are recently increased to secure the residual chlorine in the end of water pipelines. EPANET 2.0 developed by the U.S. Environmental Protection Agency (EPA) is used to compute the optimal chlorine injection in water treatment plant and to predict the dosage of rechlorination into water distribution system. The bulk decay constant ($k_{bulk}$) was drawn by bottle test and the wall decay constant ($k_{wall}$) was derived from using systermatic analysis method for water quality modeling in target region. In order to predict water quality based on hydraulic analysis model, residual chlorine concentration was forecasted in water distribution system. The formation of DBPs such as trihalomethanes (THMs) was verified with chlorine dosage in lab-scale test. The bulk decay constant ($k_{bulk}$) was rapidly decreased with increasing temperature in the early time. In the case of 25 degrees celsius, the bulk decay constant ($k_{bulk}$) decreased over half after 25 hours later. In this study, there were able to calculate about optimal rechlorine dosage and select on profitable sites in the network map.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Soil and Groundwater Environment
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• v.14 no.3
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• pp.1-13
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• 2009

Alkalinity and total carbon contents were measured by acid neutralizing titration (ANT), back titration (BT), gravitational weighing (GW), non-dispersive infrared-total carbon (NDIR-TC) methods for assessing precision and accuracy of alkalinity and total carbon concentration in $CO_2$-rich water. Artificial $CO_2$-rich water(ACW: pH 6.3, alkalinity 68.8 meq/L, $HCO_3^-$ 2,235 mg/L) was used for comparing the measurements. When alkalinity measured in 0 hr, percent errors of all measurement were 0~12% and coefficient of variation were less than 4%. As the result of post-hoc analysis after repeated measure analysis of variance (RM-AMOVA), the differences between the pair of methods were not significant (within confidence level of 95%), which indicates that the alkalinity measured by any method could be accurate and precise when it measured just in time of sampling. In addition, alkalinity measured by ANT and NDIR-TC were not change after 24 and 48 hours open to atmosphere, which can be explained by conservative nature of alkalinity although $CO_2$ degas from ACW. On the other hand, alkalinity measured by BT and GW increased after 24 and 48 hours open to atmosphere, which was caused by relatively high concentration of measured total carbon and increasing pH. The comparison between geochemical modeling of $CO_2$ degassing and observed data showed that pH of observed ACW was higher than calculated pH. This can be happen when degassed $CO_2$ does not come out from the solution and/or exist in solution as $CO_{2(g)}$ bubble. In that case, $CO_{2(g)}$ bubble doesn't affect the pH and alkalinity. Thus alkalinity measured by ANT and NDIR-TC could not detect the $CO_2$ bubble although measured alkalinity was similar to the calculated alkalinity. Moreover, total carbon measured by ANT and NDIR-TC could be underestimated. Consequently, it is necessary to compare the alkalinity and total carbon data from various kind of methods and interpret very carefully. This study provide technical information of measurement of dissolve $CO_2$ from $CO_2$-rich water which could be natural analogue of geologic sequestration of $CO_2$.

• 한국노년학
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• v.38 no.4
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• pp.1083-1105
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• 2018

The present study sought to capture day-to-day fluctuation of the daily happiness among Korean urban older adults and to examine whether the within person fluctuation of daily happiness is explained by the social and physical activities the older adults experience each day. We also examined whether the within person association between daily social, physical activities and the daily happiness varies by individual characteristics(i.e. gender, age, educational level and health). In addition, we explored the relationships between the level and fluctuation of daily happiness and the level of global happiness. The data was collected by multi-method approach, which includes general survey, daily diary method and collection of physical activity data through the activity monitors. In total, 175 urban older adults participated for seven days of daily diary survey. The data about the number of steps and the time spent on sedentary activities, light intensity physical activities and moderate to vigorous intensity physical activities were also collected during the same period from 16 sub-samples using activity monitors. Hierarchical linear modeling was applied for the analysis. The results were as below. First, the level of happiness of older adults fluctuated during a week, and the patterns of fluctuation varied by the gender and the health. Second, socializing with their children and friends elevated their levels of happiness. Also the impact of contacts with siblings on the level of daily happiness was greater for the unhealthy group compare to the healthy group. Third, older adults were happier on the days when they walked more, but the level of daily happiness decreased on the days when they spent longer time for low intensity physical activities. Lastly, the higher level of daily happiness were related to the higher level of global happiness, but the degree of fluctuation of daily happiness was not related to the level of global happiness. The implications of these results and suggestions for future research are discussed.