• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.2
• /
• pp.307-313
• /
• 2022

As the development of renewable energy expands internationally to cope with global warming and climate change, the share of wind power generation has been gradually increasing. Although wind farms can produce electric power for 24 h a day compared to solar power plants, Their interfere with the operation of nearby radars or communication equipment must be analyzed because large-scale wind power turbines are installed. This study analyzed whether a land radio station can receive sufficient signals when a ship sailing outside the offshore wind farm transmits distress signals on the VHF band. Based on the geographic information system digital map around the target area, wind turbine CAD model, and wind farm layout, the area of interest and wind farm were modeled to enable numerical analysis. Among the high frequency analysis techniques suitable for radio wave analysis in a wide area, a dedicated program applying physical optics (PO) and shooting and bouncing ray (SBR) techniques were used. Consequently, the land radio station could receive the electromagnetic field above the threshold of the VHF receiver when a ship outside the offshore wind farm transmitted a distress communication signal. When the line of sight between the ships and the land station are completely blocked, the strength of the received field decreases, but it is still above the threshold. Hence, although a wind farm is a huge complex, a land station can receive the electromagnetic field from the ship's VHF transmitter because the wave length of the VHF band is sufficiently long to have effects such as diffraction or reflection.

• Journal of Korea Water Resources Association
• /
• v.55 no.11
• /
• pp.855-863
• /
• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.869-875
• /
• 2009

Safety is a big issue in the construction sites. For safe and secure management, tracking locations of construction resources such as labors, materials, machineries, vehicles and so on is important. The materials, machineries and vehicles could be controlled by computer, whereas the movement of labors does not have fixed pattern. So, the location and movement of labors need to be monitored continuously for safety. In general, Global Positioning System(GPS) is an opt solution to obtain the location information in outside environments. But it cannot be used for indoor locations as it requires a clear Line-Of-Sight(LOS) to satellites Therefore, indoor location monitoring system could be a convenient alternative for environments such as tunnel and indoor building construction sites. This paper presents a case study to investigate feasibility of Wi-Fi based indoor location monitoring system in construction site. The system is developed by using fingerprint map of gathering Received Signal Strength Indication(RSSI) from each Access Point(AP). The signal information is gathered by Radio Frequency Identification (RFID) tags, which are attached on a helmet of labors to track their locations, and is sent to server computer. Experiments were conducted in a shield tunnel construction site at Guangzhou, China. This study consists of three phases as follows: First, we have a tracking test in entrance area of tunnel construction site. This experiment was performed to find the effective geometry of APs installation. The geometry of APs installation was changed for finding effective locations, and the experiment was performed using one and more tags. Second, APs were separated into two groups, and they were connected with LAN cable in tunnel construction site. The purpose of this experiment was to check the validity of group separating strategy. One group was installed around the entrance and the other one was installed inside the tunnel. Finally, we installed the system inner area of tunnel, boring machine area, and checked the performance with varying conditions (the presence of obstacles such as train, worker, and so on). Accuracy of this study was calculated from the data, which was collected at some known points. Experimental results showed that WiFi-based indoor location system has a level of accuracy of a few meters in tunnel construction site. From the results, it is inferred that the location tracking system can track the approximate location of labors in the construction site. It is able to alert the labors when they are closer to dangerous zones like poisonous region or cave-in..

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.3
• /
• pp.337-352
• /
• 2023

In general, Rainfall-Runoff model parameter set is optimized using the entire data to calculate unique parameter set. However, Korea has a large precipitation deviation according to the season, and it is expected to even worsen due to climate change. Therefore, the need for hydrological data considering seasonal characteristics. In this study, we conducted regional sensitivity analysis(RSA) using the conceptual Rainfall-Runoff model, GR4J aimed at the Soyanggang dam basin, and clustered combining the RSA results with hydrometeorological data using Self-Organizing map(SOM). In order to consider the climate characteristics in parameter estimation, the data was divided based on clustering, and a calibration approach of the Rainfall-Runoff model was developed by comparing the objective functions of the Global Optimization method. The performance of calibration was evaluated by statistical techniques. As a result, it was confirmed that the model performance during the Cold period(November~April) with a relatively low flow rate was improved. This is expected to improve the performance and predictability of the hydrological model for areas that have a large precipitation deviation such as Monsoon climate.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.2
• /
• pp.265-278
• /
• 2022

The global energy paradigm is rapidly changing by centering on carbon neutrality, and wind energy is positioning itself as a leader in renewable energy-based power sources. The success of onshore and offshore wind energy projects focuses on securing the economic feasibility of the project, which depends on securing high-quality wind resources and optimal arrangement of wind turbines. In the process of constructing the wind farm, the optimal arrangement method of wind turbines considering the main wind direction is important, and this is related to minimizing the wake effect caused by the fluid passing through the structure located on the windward side. The accuracy of the predictability of the wake effect is determined by the wake model and modeling technique that can properly simulate it. Therefore, in this paper, using WindSim, a commercial CFD model, the wake diffusion pattern is analyzed through the sensitivity study of each wake model of the proposed onshore wind farm located in the mountainous complex terrain in South Korea, and it is intended to be used as basic research data for wind energy projects in complex terrain in the future.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.6 no.1
• /
• pp.57-66
• /
• 2016

Electronics cultural atlas is a typical methodology for the Digital Humanities. Since electronic cultural atlas could visualize various cultural information based on electronic atlas, that is an information visualization, users are able to make intuitive understanding on specific areas. Therefore, it can be effectively utilized in Area Studies and also helps users to understand comprehensively information on historic event in particular area with time information, because electronic cultural atlas represents a particular subject and time information with geographical information based on map. In other words, electronic cultural atlas may be considered as a specialized system of Digital Humanities for studying the Humanities and Area Studies. In this paper, we design and implement mediterranean electronic cultural atlas(MECA) for researchers of the Mediterranean area that has cultural hybridity formed the exchange of various aspects such as civilization, religion, race and language. In detail, a 'Digital Humanities Research Support System' is constructed to visualize research outcomes related to the Mediterranean area on Electronic Cultural Atlas and to use for researches.

• Korean Journal of Heritage: History & Science
• /
• v.56 no.1
• /
• pp.162-180
• /
• 2023

The World Heritage Committee decided to make "cultural landscapes" a world heritage category in the 16th Session of the UNESCO General Conference. The decision was made from a recognition of the importance of interactions between human beings and the natural environment or between cultural heritage and natural heritage. Many countries have created policies and institutions to protect their own cultural landscapes along with the changing times. Korea, however, has not obviously defined the concepts and categories of its cultural landscapes, but manages policies and institutions based on the concept of a scenic spot, which has some similar meanings. In addition, it even borrows the "list of landscape adjectives," one of the representative methods for managing landscapes, from foreign countries. With this background, this paper suggested how to define cultural landscapes according to the global development flow. It created a list of cultural landscape adjectives by gathering the adjectives that can properly express local cultural landscapes in Korea. In particular, it collected 4,556 articles from a local newspaper by focusing on the case of Shinan-gun, Jeollanam-do, and analyzed key words and adjectives included in them by using big data analysis. The results suggested by this paper, such as the "classification table of cultural landscape types," "list of cultural landscape adjectives" and "network map of nouns/adjectives" can be applied to research on other localities, and furthermore, used as basic data for finding and protecting the characteristics of local cultural landscapes in Korea.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.4
• /
• pp.446-454
• /
• 2023

The impact of climate change on agriculture is substantial, especially as global warming is projected to lead to varying temperature and humidity patterns in the future. These changes pose a higher risk for both crops and livestock, exposing them to environmental stressors under altered climatic conditions. Specifically, as temperatures are expected to rise, the risk of heat stress is assessable through the Temperature-Humidity Index (THI), derived from temperature and relative humidity data. This study involved the comparison of THI collected from 10 Korea Meteorological Administration ASOS stations spanning a 60-year period from 1961 to 2020. Moreover, high-resolution temperature and humidity distribution data from 1981 to 2020 were employed to generate high-resolution TH I distributions, analyzing temporal changes. Additionally, the number of days characterized by heat stress, derived from TH I, was compared over different time periods. Generally, TH I showed an upward trend over the past, albeit with varying rates across different locations. As TH I increased, the frequency of heat stress days also rose, indicating potential future cost increases in the livestock industry due to heat-related challenges. The findings emphasize the feasibility of evaluating heat stress risk in livestock using THI and underscore the need for research analyzing THI under future climate change scenarios.

• Information Systems Review
• /
• v.24 no.1
• /
• pp.1-19
• /
• 2022

Social media-based communication has become crucial part of our personal and official lives. Therefore, it is no surprise that social media sentiment analysis has emerged an important way of detecting potential customers' sentiment trends for all kinds of companies. However, social media sentiment analysis suffers from huge number of sentiment features obtained in the process of conducting the sentiment analysis. In this sense, this study proposes a novel method by using Bayesian Network. In this model MBFS (Markov Blanket-based Feature Selection) is used to reduce the number of sentiment features. To show the validity of our proposed model, we utilized online review data from Yelp, a famous social media about restaurant, bars, beauty salons evaluation and recommendation. We used a number of benchmarking feature selection methods like correlation-based feature selection, information gain, and gain ratio. A number of machine learning classifiers were also used for our validation tasks, like TAN, NBN, Sons & Spouses BN (Bayesian Network), Augmented Markov Blanket. Furthermore, we conducted Bayesian Network-based what-if analysis to see how the knowledge map between target node and related explanatory nodes could yield meaningful glimpse into what is going on in sentiments underlying the target dataset.

• Journal of the Korean earth science society
• /
• v.32 no.7
• /
• pp.832-859
• /
• 2011

The importance of scientific education on accurate oceanic currents and circulation has been increasingly addressed because the currents have played a significant role in climate change and global energy balance. The objectives of this study are to analyze errors of the oceanic current maps in the textbooks, to discuss a variety of error sources, to suggest how to produce a unified oceanic current map of the East Sea for the students. Twenty-seven textbooks based on the 7th National Curriculum were analyzed and quantitatively investigated on the characteristics of the current maps by comparing with both the previous literature and up-to-date scientific knowledge. All the maps in the textbooks with different mappings were converted to digitalized image data with Mercator mapping using geolocation information. Detailed analysis were performed to investigate the patterns of the Tsushima Warm Current (TWC) in the Korea Strait, to examine how closely the nearshore branch of the TWC flows along the Japanese coast, to scrutinize the features of the offshore branch of the TWC south of the subpolar front in the East Sea, to quantitatively investigate the northern range of the northward-propagating East Korea Warm Current and its latitude turning to the east, and lastly to examine the outflow of the TWC near the Tsugaru Strait and the Soya Strait. In addition, the origins, southern limits, and distances from the coast of the Liman Current and the North Korea Cold Current were analyzed. Other erroneous expressions of the currents in the textbooks were presented. These analyses revealed the problems in the present current maps of the textbooks, which might lead the students to misconception. This study also addressed a necessity in a bridge between scientists with up-to-date scientific results and educators who needed educational materials.