• Journal of Digital Convergence
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• v.19 no.2
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• pp.1-12
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• 2021

With the recent 4th Industrial Revolution, the growth and value of big data are continuously increasing, and the government is also actively making efforts to open and utilize public data. However, the situation still does not reach the level of demand for public data use by citizens, At this point, it is necessary to identify research trends in the public data field and seek directions for development. In this study, in order to understand the research trends related to public data, the analysis was performed using topic modeling, which is mainly used in text mining techniques. To this end, we collected papers containing keywords of 'Public data' among domestic and foreign research papers (1,437 domestically, 9,607 overseas) and performed topic modeling based on the LDA algorithm, and compared domestic and foreign public data research trends. After analysis, policy implications were presented. Looking at the time series by topic, research in the fields of 'personal information protection', 'public data management', and 'urban environment' has increased in Korea. Overseas, it was confirmed that research in the fields of 'urban policy', 'cell biology', 'deep learning', and 'cloud·security' is active.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.152-162
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• 2022

This study developed simulation model for predicting the greenhouse interior environment using artificial intelligence machine learning techniques. Various methods have been studied to predict the internal environment of the greenhouse system. But the traditional simulation analysis method has a problem of low precision due to extraneous variables. In order to solve this problem, we developed a model for predicting the temperature inside the greenhouse using machine learning. Machine learning models are developed through data collection, characteristic analysis, and learning, and the accuracy of the model varies greatly depending on parameters and learning methods. Therefore, an optimal model derivation method according to data characteristics is required. As a result of the model development, the model accuracy increased as the parameters of the hidden unit increased. Optimal model was derived from the GRU algorithm and hidden unit 6 (r² = 0.9848 and RMSE = 0.5857℃). Through this study, it was confirmed that it is possible to develop a predictive model for the temperature inside the greenhouse using data outside the greenhouse. In addition, it was confirmed that application and comparative analysis were necessary for various greenhouse data. It is necessary that research for development environmental control system by improving the developed model to the forecasting stage.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.65-82
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• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.57-65
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• 2022

This study simulated the shock wave propagation through the tamping material between explosives and hole wall at blasting works and verified the effect of tamping materials. The Arbitrary Lagrangian-Eulerian(ALE) method was selected to model the mixture of solid (Lagrangian) and fluid (Eulerian). The time series analysis was carried out during blasting process time. Explosives and tamping materials (air or water) were modeled with finite element mesh and the hole wall was assumed as a rigid body that can determine the propagation velocity and shock force hitting the hole wall from starting point (explosives). The numerical simulation results show that the propagation velocity and shock force in case of water were larger than those in case of air. In addition, the real site at blasting work was modeled and simulated. The rock was treated as elasto-plastic material. The results demonstrate that the instantaneous shock force was larger and the demolished block size was smaller in water than in air. On the contrary, the impact in the back side of explosives hole was smaller in water, because considerable amount of shock energy was used to demolish the rock, but the propagation of compression through solid becomes smaller due to the damping effect by rock demolition. Therefore, It can be proven that the water as the tamping media was more profitable than air.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.87-96
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• 2011

Carbon emissions and storages that are strongly related to global warming has have emerged as one of the important issues while many governments and researchers have been interested in climate change and pollution. In this regards, forest biomass estimation is quite importance since forest biomass works as an important medium of the global carbon cycle between the atmosphere and soil. Forest biomass estimation through field survey needs lots of time and labors, and has accessibility issues. Hence, many researchers have focused on the forest biomass approaches based on remotely sensed data. This research comprehensively reviewed forty one international studies using remote sensing data according to five different categories (i.e., location of study area, size of study area, biome, used remote sensing data, and estimation technology). It would be expected that the results of this study can be used for suggesting domestic research directions; domestic research in this field is at the beginning stage in terms of level of technologies and useful materials. As results, 39% out of the reviewed studies used the areas located in North America. 59% out of the researches dealt with small size of the study areas (less than 3,600km2). In case of biome, around 30% of the studies focused on the boreal/taiga areas. Moreover, 35% and 16% of the studies were carried out using Landsat series and Lidar data, respectively. Finally, regression analysis method was most frequently used for forest biomass estimation by 71% out of 41 studies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.457-469
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• 2016

Nakdong river barrage was affected by artificial interference such as construction of port, industrial complex and estuary barrage. This change in Nadong river lead to environmental changes and affected the ability of barrier islands. Therefore, it is decided that the observation of changes in the Nakdong river estuary is very important. In this paper, the topographic change of the Nakdong river barrage observe based on Landsat TM, ETM+ images from 1984 to 2015. In addition, this study tried to conduct a comparative analysis on the area for change of sandy sediment according to tide level. This results could estimate height and volume about sandy sediment accumulated on the lower sand dune. Also, these results are expected to be the basis for prediction of the changing topography of the sand dune. The area of the average change in region 1,2,3 was calculated as 3,015m², 167,550m², 14,596m². This result is expected to be very useful for the continuous observation for sediment changes of Nakdong river.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.533-540
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• 2010

Dam is very important facility in water supply and flood control. Therefore study needs to analyze reservoir capacity accurately to manage Dam efficiently. This study compared time series reservoir capacity using multi-dimensional spatial information to Chungju Dam reservoir and major conclusions are as follows. First, LiDAR and multi beam echo sounder survey were carried out in land zone and water zone of Dam reservoir area. And calibration process was performed to enhance the accuracy of survey data and it could be constructed that multi dimensional spatial information which was clearly satisfied with the standard of tolerance error by validation with ground control points. Reservoir capacity by water level was calculated using triangle irregular network from detailed topographic data that was constructed by linked with airborne LiDAR and multi beam echo sounder data, and curve equation of reservoir capacity was developed through regression analysis in 2008. In the comparison of the reservoir capacity of 2008 with those of 1986 and 1996, the higher water level goes, total reservoir capacity of 2008 showed decrease because of the increase of sediment in reservoir. Also, erosion and sediment area could be analyzed through calculating the reservoir capacity by the range of water level. Especially the range of water level as 130.0~135.0 which is the upper part of average water level, showed the highest erosion characteristics during 1986~2008 and 1996~2008 and it is considered that the erosion of reservoir slant by heavy rainfall is major reason.

• Journal of the Korean Solar Energy Society
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• v.30 no.6
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• pp.73-80
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• 2010

This study was conducted to estimate the relative performance of modules with changed characteristics due to long term exposure to the outdoor environment, with a specially made test device for simultaneous measurement of real time power output from the photovoltaic array, taking into account the inclined panel, direct irradiation, power being generated, temperature as well as the optimal analysis timing. In terminology description, M is an abbreviation of module and Group A, Group B are 10 modules series connection (1~10 of M), (11~20 of M) for each of them respectively. The overall mean voltage difference of M-18 with the lowest power output and M-14 with the highest output is-2.13V and it was identifiable that voltage difference was more concentrated to Group B. In addition, in case of M-2 and M-7, M-8, when compared with M-14, the overall mean voltage difference was -0.92V, -1.56 and -0.91V respectively showing the more concentration to Group A. When the temperature of module went up by $1^{\circ}C$, the mean voltage was reduced by 0.35V. For current, Group A was lower than Group B by-0.022A and the ratio of each group was 49.68% and 50.32% respectively, presumably the module with deteriorated properties were more concentrated to Group A relatively. From the comparison of relations with the comprehensive accumulation, M-2, M-7, M-8, M-16 and M-18 were those with deterioration of performance to the worst, thereby requiring precision examination. In comparative efficiency, M-14 was the most excellent one as 12.19% while M-18 as 10.53% was identified that its efficiency was comparatively rapidly reduced.

• Archives of Plastic Surgery
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• v.34 no.2
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• pp.209-216
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• 2007

Purpose: The ischial area is by far the most common site of pressure sores found in wheel chair bound paraplegic patients, because greatest pressure is exerted from the body on this area in a sitting position. Even after a series of successful pressure sore treatments, the site is very prone to relapse by the simplest ordinary tasks of everyday life. Therefore, it is crucial to preserve the main pedicle during primary surgery. Various surgical procedures employed to treat pressure sores such as myocutaneous flap and perforator flap have been introduced. After introduction of ischial sore treatment using the inferior gluteal artery perforator (IGAP) has been made, the authors experienced favorable clinical results of patients who have undergone IGAP flap procedure in a three year time period. Methods: A total of 17 patients received IGAP flap surgery in our hospital from January 2003 to May 2006, among which 14 of them being males and 3 females. Surgery was performed on the same site again in 6(35%) patients who had originally relapsed after receiving the conventional method of pressure sore surgery. Patients' average age was 49.4(27-71) years old. Most of the patients were paraplegic(11 cases, 65%) and others were either quadriplegic(4 cases, 23%) or ambulatory(2 cases, 12%). Based on hospital records and clinical photographs, we have attempted to assess the feasibility and practicability of the IGAP flap procedure through comparative analysis of several parameters: size of defective area, treatment modalities, occurrence of relapses, complications, and postoperative treatments. Results: The average follow-up duration of 17 subjects was 25.4 months(5-42 months). All flaps survived without any necrosis. Six cases were relapsed cases from conventional surgical procedures. All of them healed well during our follow-up study. Postoperative complications such as wound dehiscence and fistula developed in some subjects, but all were well healed through secondary treatment. A total of 2 cases relapsed after surgery. Conclusion: The inferior gluteal artery perforator flap is an effective method that can be primarily applied in replacement to the conventional ischial pressure sore reconstructive surgery owing to its many advantages: ability to preserve peripheral muscle tissue, numerous possible flap designs, relatively good durability, and the low donor site morbidity rate.