• Journal of the Korean Geosynthetics Society
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• v.21 no.4
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• pp.1-12
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• 2022

Generally, the plate load test and the field density test are conducted for compaction quality control in earthwork, and then additional analysis. Recently developed that the DCPT (Dynamic Cone Penetration Test) equipment for smart compaction quality control its the system are able to get location and real-time information about worker history management. The IoT-based the DCPT system improved the time-cost in the field compared traditional test, and the functions recording and storage of the DPI (Dynamic Cone Penetration Index) were automated. This paper describes using these DCPT equipment on in-situ and compared to the standards of the DCPT, and the compaction trend had be confirmed with DPI as the field test data. As a result, the DPI of the final compaction decreased by 1.4 times compared to the initial compaction, confirming the increase in the compaction strength of the subgrade compaction layer 10 to 14 cm deep from the surface. A trend of increasing compaction strength was observed. This showed a tendency to increase the compaction strength of the target DPI proposed by MnDOT and the results of the existing plate load test, but there was a difference in the increase rate. Therefore, additional studies are needed on domestic compaction materials and laboratory conditions for target DPI and correlation studies with the plate load tests. If this is reflected, it is suggested that DCPT will be widely used as smart construction equipment in earthworks.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.469-476
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• 2021

The framework plan for the development of an integrated underground space map was established of preventing ground subsidence. The mapping process is expected to be completed to the level of nationwide municipal government standards by end of this year. To facilitate the utilization of the integrated underground space map, paper-based drawings for specialized organizations in underground safety impact assessment have been provided since September 2018, and services for local government officials have been provided in the underground information utilization system since May 2019. However, the map is utilized based on the information at the time of the initial development of the map, without any updates, thereby resulting in a lack of accuracy and latest information. This has led to a decrease in the utilization and reliability of the information. Therefore, in this study, for the underground structures(subway, underground shopping mall, underground passage, underground roadway, underground parking lot, utility tunnel), which are the key components of the integrated underground space map, a standard format for the submission of completed drawings is designed in accordance with Article 42 (2) of the Special Act on Underground Safety Management, which aims at laying the foundation for establishing the updated system of the integrated underground space map. In addition, through the verification of the automatically updated underground structure data based on the standard format, the reliability of the data can be assured. This format is expected to contribute to the improved utilization of the integrated underground space map in the future.

• Journal of Bio-Environment Control
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• v.33 no.2
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• pp.107-113
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• 2024

For efficient soil water management in open fields, the proper use of soil moisture sensors is a prerequisite. Particularly in open-field environments like orchards with extensive root systems, the appropriate positioning of sensors is very important. The present study was conducted to identify the optimal placement of soil moisture sensors by assessing changes in soil water potential across various positions within orchard field soils after installing tensiometers. In apple and Asian pear orchards located in two regions of Korea, nine soil water potential sensors (TEROS 21, METER Group) were installed at distances of 20, 40, and 60 cm from the tree trunk and depths of 10, 20, and 30 cm from the soil surface, and monitored the soil water potential changes over two years. Results indicated that the positions closer to the tree trunk and the soil surface exhibited more pronounced changes in soil water potential. The greatest magnitude of change in soil water potential was observed at a distance of 20 cm and a depth of 10 cm, suggesting this position as the most suitable for soil moisture sensor installation. However, variations in the degree and pattern of changes in soil water potential were noted across sensor positions due to root system growth over time. Therefore, periodic observation and adjustments in sensor placement would be advisable to accurately monitor the soil moisture condition in long-term crops such as fruit trees in open fields.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.113-129
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• 2015

Location branding is a very important income making activity, by giving special meanings to a specific location while producing identity and communal value which are based around the understanding of a place's location branding concept methodology. Many other areas, such as marketing, architecture, and city construction, exert an influence creating an impressive brand image. A place brand which shows great recognition to both native people of S. Korea and foreigners creates significant economic effects. There has been research on creating a strategically and detailed place brand image, and the representative research has been carried out by Anholt who surveyed two million people from 50 different countries. However, the investigation, including survey research, required a great deal of effort from the workforce and required significant expense. As a result, there is a need to make more affordable, objective and effective research methods. The purpose of this paper is to find a way to measure the intensity of the image of the brand objective and at a low cost through text mining purposes. The proposed method extracts the keyword and the factors constructing the location brand image from the related web documents. In this way, we can measure the brand image intensity of the specific location. The performance of the proposed methodology was verified through comparison with Anholt's 50 city image consistency index ranking around the world. Four methods are applied to the test. First, RNADOM method artificially ranks the cities included in the experiment. HUMAN method firstly makes a questionnaire and selects 9 volunteers who are well acquainted with brand management and at the same time cities to evaluate. Then they are requested to rank the cities and compared with the Anholt's evaluation results. TM method applies the proposed method to evaluate the cities with all evaluation criteria. TM-LEARN, which is the extended method of TM, selects significant evaluation items from the items in every criterion. Then the method evaluates the cities with all selected evaluation criteria. RMSE is used to as a metric to compare the evaluation results. Experimental results suggested by this paper's methodology are as follows: Firstly, compared to the evaluation method that targets ordinary people, this method appeared to be more accurate. Secondly, compared to the traditional survey method, the time and the cost are much less because in this research we used automated means. Thirdly, this proposed methodology is very timely because it can be evaluated from time to time. Fourthly, compared to Anholt's method which evaluated only for an already specified city, this proposed methodology is applicable to any location. Finally, this proposed methodology has a relatively high objectivity because our research was conducted based on open source data. As a result, our city image evaluation text mining approach has found validity in terms of accuracy, cost-effectiveness, timeliness, scalability, and reliability. The proposed method provides managers with clear guidelines regarding brand management in public and private sectors. As public sectors such as local officers, the proposed method could be used to formulate strategies and enhance the image of their places in an efficient manner. Rather than conducting heavy questionnaires, the local officers could monitor the current place image very shortly a priori, than may make decisions to go over the formal place image test only if the evaluation results from the proposed method are not ordinary no matter what the results indicate opportunity or threat to the place. Moreover, with co-using the morphological analysis, extracting meaningful facets of place brand from text, sentiment analysis and more with the proposed method, marketing strategy planners or civil engineering professionals may obtain deeper and more abundant insights for better place rand images. In the future, a prototype system will be implemented to show the feasibility of the idea proposed in this paper.

• Journal of the Korea Institute of Building Construction
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• v.9 no.5
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• pp.79-86
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• 2009

In a steel structure, spray-applied fire resistive materials are crucial in preventing structural strength from being weakened in the event of a fire. The quality control of such materials, however, is difficult for manual workers, who can frequently be in short supply. These skilled workers are also very likely to be exposed to environmental hazards. Problems with construction work such as this, which are specifically the difficulty of achieving quality control and the dangerous nature of the work itself, can be solved to some degree by the introduction of automated equipment. It is, however, very difficult to automate the work process, from operation to the selection of a location for the equipment, as the environment of a construction site has not yet been structured to accommodate automation. This is a fundamental study on the possibility of the automation of spray-applied fire resistive coating work. In this study, the linkability of the cutting-edge RTLS to an automation system is reviewed, and a scenario for the automation of spray-applied fire resistive coating work and system composition is presented. The system suggested in this study is still in a conceptual stage, and as such, there are many restrictions still to be resolved. Despite this fact, automation is expected to have good effectiveness in terms of preventing fire from spreading by maintaining a certain level of strength at a high temperature when a fire occurs, as it maintains the thickness of the fire-resistive coating at a specified level, and secures the integrity of the coating with the steel structure, thereby enhancing the fire-resistive performance. It also expected that if future research is conducted in this area in relation to a cutting-edge monitoring TRS, such as the ubiquitous sensor network (USN) and/or building information model (BIM), it will contribute to raising the level of construction automation in Korea, reducing costs through the systematic and efficient management of construction resources, shortening construction periods, and implementing more precise construction

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.333-346
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• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.252-252
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• 2017

Nowadays water shortage is becoming one of the biggest problems in the Korea. Many different methods are developed for conservation of water. Soil water management has become the most indispensable factor for augmenting the crop productivity especially on soybean (Glycine max L.) because of their high susceptibility to both water stress and water logging at various growth stages. The farmers have been using irrigation techniques through manual control which farmers irrigate lands at regular intervals. Automatic irrigation systems are convenient, especially for those who need to travel. If automatic irrigation systems are installed and programmed properly, they can even save you money and help in water conservation. Automatic irrigation systems can be programmed to provide automatic irrigation to the plants which helps in saving money and water and to discharge more precise amounts of water in a targeted area, which promotes water conservation. The objective of this study was to determine the possible effect of automatic irrigation systems based on soil moisture on soybean growth. This experiment was conducted on an upland field with sandy loam soils in Department of Southern Area Crop, NICS, RDA. The study had three different irrigation methods; sprinkle irrigation (SI), surface drip irrigation (SDI) and fountain irrigation (FI). SI was installed at spacing of $7{\times}7m$ and $1.8m^3/hr$ as square for per irrigation plot, a lateral pipe of SDI was laid down to 1.2 m row spacing with $2.3L\;h^{-1}$ discharge rate, the distance between laterals was 20 cm spacing between drippers and FI was laid down in 3m interval as square for per irrigation plot. Soybean (Daewon) cultivar was sown in the June $20^{th}$, 2016, planted in 2 rows of apart in 1.2 m wide rows and distance between hills was 20 cm. All agronomic practices were done as the recommended cultivation. This automatic irrigation system had valves to turn irrigation on/off easily by automated controller, solenoids and moisture sensor which were set the reference level as available soil moisture levels of 30% at 10cm depth. The efficiency of applied irrigation was obtained by dividing the total water stored in the effective root zone to the applied irrigation water. Results showed that seasonal applied irrigation water amounts were $60.4ton\;10a^{-1}$ (SI), $47.3ton\;10a^{-1}$ (SDI) and $92.6 ton\;10a^{-1}$ (FI), respectively. The most significant advantage of SDI system was that water was supplied near the root zone of plants drip by drip. This system saved a large quantity of water by 27.5% and 95.6% compared to SI, FI system. The average soybean yield was significantly affected by different irrigation methods. The soybean yield by different irrigation methods were $309.7kg\;10a^{-1}$ from SDI $282.2kg\;10a^{-1}$ from SI, $289.4kg\;10a^{-1}$ from FI, and $206.3kg\;10a^{-1}$ from control, respectively. SDI resulted in increase of soybean yield by 50.1%, 7.0% 9.8% compared to non-irrigation (control), FI and SI, respectively. Therefore, the automatic irrigation system supplied water only when the soil moisture in the soil went below the reference. Due to the direct transfer of water to the roots water conservation took place and also helped to maintain the moisture to soil ratio at the root zone constant. Thus the system is efficient and compatible to changing environment. The automatic irrigation system provides with several benefits and can operate with less manpower. In conclusion, improving automatic irrigation system can contribute greatly to reducing production costs of crops and making the industry more competitive and sustainable.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.305-316
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• 2011

Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.83-105
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• 2016

Measuring an individual's subjective wellbeing in an accurate, unobtrusive, and cost-effective manner is a core success factor of the wellbeing support system, which is a type of medical IT service. However, measurements with a self-report questionnaire and wearable sensors are cost-intensive and obtrusive when the wellbeing support system should be running in real-time, despite being very accurate. Recently, reasoning the state of subjective wellbeing with conventional sentiment analysis and unstructured data has been proposed as an alternative to resolve the drawbacks of the self-report questionnaire and wearable sensors. However, this approach does not consider contextual polarity, which results in lower measurement accuracy. Moreover, there is no sentimental word net or ontology for the subjective wellbeing area. Hence, this paper proposes a method to extract keywords and their contextual polarity representing the subjective wellbeing state from the unstructured text in online websites in order to improve the reasoning accuracy of the sentiment analysis. The proposed method is as follows. First, a set of general sentimental words is proposed. SentiWordNet was adopted; this is the most widely used dictionary and contains about 100,000 words such as nouns, verbs, adjectives, and adverbs with polarities from -1.0 (extremely negative) to 1.0 (extremely positive). Second, corpora on subjective wellbeing (SWB corpora) were obtained by crawling online text. A survey was conducted to prepare a learning dataset that includes an individual's opinion and the level of self-report wellness, such as stress and depression. The participants were asked to respond with their feelings about online news on two topics. Next, three data sources were extracted from the SWB corpora: demographic information, psychographic information, and the structural characteristics of the text (e.g., the number of words used in the text, simple statistics on the special characters used). These were considered to adjust the level of a specific SWB. Finally, a set of reasoning rules was generated for each wellbeing factor to estimate the SWB of an individual based on the text written by the individual. The experimental results suggested that using contextual polarity for each SWB factor (e.g., stress, depression) significantly improved the estimation accuracy compared to conventional sentiment analysis methods incorporating SentiWordNet. Even though literature is available on Korean sentiment analysis, such studies only used only a limited set of sentimental words. Due to the small number of words, many sentences are overlooked and ignored when estimating the level of sentiment. However, the proposed method can identify multiple sentiment-neutral words as sentiment words in the context of a specific SWB factor. The results also suggest that a specific type of senti-word dictionary containing contextual polarity needs to be constructed along with a dictionary based on common sense such as SenticNet. These efforts will enrich and enlarge the application area of sentic computing. The study is helpful to practitioners and managers of wellness services in that a couple of characteristics of unstructured text have been identified for improving SWB. Consistent with the literature, the results showed that the gender and age affect the SWB state when the individual is exposed to an identical queue from the online text. In addition, the length of the textual response and usage pattern of special characters were found to indicate the individual's SWB. These imply that better SWB measurement should involve collecting the textual structure and the individual's demographic conditions. In the future, the proposed method should be improved by automated identification of the contextual polarity in order to enlarge the vocabulary in a cost-effective manner.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.4
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• pp.409-415
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• 2020

Low-flow mortar injection method grouting technology was selected and the traffic area was preserved as much as possible in order to secure safety for road traffic when the outflow and subsidence of landfill occurred due to ground-water, and etc. In particular, the current existing method was newly improved since there are risks of damage such as hydraulic fracturing at the lower part of the road, spilling of soil particles on steep slopes, and bumps on the road due to excessive injection pressure during construction. This study was carried out at the site of reinforcement work on the road as a maintenance work for the danger zone for collapse of the steep slope of the 00 hill, which was ordered from the 00 city 00 province. The improved low-flow mortar type grouting method adopted a new automated grouting management system and especially, it composites the method for grouting conditions decision by high-pressure pre-grouting test and injection technology by AGS-controlled and studied about grouting effect analysis by using new technology. By applying the improved low-flow mortar type grouting method, it was possible to lay the groundwork for road maintenance work such as the prevention of subsidence of old roads, uneven subsidence of buildings and civil engineering structures, and of soil leakage of ground-water spills. Furthermore, the possibility of application on future grouting work not only for just construction that prevents subsidence of old roads but also for various buildings and civil engineering structures such as railroads, subways, bridges, underground structures, and boulder stone and limestone areas was confirmed.