• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.6
• /
• pp.219-225
• /
• 2019

There is a problem with the existing method of selecting the difficulty levels of Hanja characters. Some Hanja characters selected by the existing methods are different from Sino-Korean words used in real life and it is impossible to know how many times the Hanja characters are used. To solve this problem, we measure the difficulty of Hanja characters using the multiple regression analysis with the frequency as the features. Based on the elementary textbooks, FWS and FHU are counted. A questionnaire is written using the two frequencies and stroke together to answer the appropriate timing of learning the Hanja characters and use them as target variables for regression. Use stepwise regression to select the appropriate features and perform multiple linear regression. The R² score of the model was 0.1105 and the RMSE was 0.1105.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.1B
• /
• pp.13-20
• /
• 2011

The spatio-temporal pattern in precipitation is a significant element in defining characteristics of precipitation. In this study, a new scheme on regionalization utilizing temporal information was introduced on the basis of existing approaches that is mainly based on simple moments of data and geographical information. Given the identified spatio-temporal pattern, this study was extended to characterize regional pattern of annual maximum rainfall over Korea. We have used circular statistics to characterize the temporal distribution on the precipitation, and the circular statistics allow us to effectively assess changes in timing of the extreme rainfall in detail. In this study, a modified K-means method was incorporated with derived temporal characteristics of extreme rainfall in order to better characterize hydrologic pattern for regional frequency analysis. The extreme rainfall was reasonably separated into five categories that considered most attributes in both quantitative and temporal changes in extremes. The results showed that the proposed approach is a promising approach for regionalization in term of physical understanding of extreme rainfall.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.100-100
• /
• 2017

FT is one of the major floral activator in plant flowering. FT determines the changing point of time from vegetative stage to reproductive stage. To understand the role of FT homologs in short-day plant soybean, we identified 10 soybean FT homologous genes and named GmFTs. We figured out that 10 GmFT genes were further categorized into three subclades through phylogenetic analysis. Expression analysis of GmFT genes indicated that they might have different functions in photoperiod-dependent soybean flowering. Most of GmFTs, for example, GmFT2a, GmFT2b, GmFT5a and GmFT6 mainly expressed in soybean leaves at short-day condition. However, interestingly GmFT1a and GmFT4 represented opposite expression pattern to other GmFTs. Arabidopsis transgenic plants overexpressing GmFT2a and GmFT5a exhibited extremely early flowering. In contrast, overexpression of GmFT4 delayed flowering of Arabidopsis transgenic plants. The results suggest that GmFT4 has antagonistic role to other GmFTs in soybean flowering. Interestingly, mRNA level of GmFT2a is higher in early flowering soybean accessions than in late flowering ones. Moreover, the highest point of mRNA level of GmFT2a showed the positive correlation with the timing of flowering of soybean accessions. But that of GmFT4 showed opposite pattern. Here, we report that soybean FT homologs might acquire different functions in photoperiod-dependent flowering through the functional diversification during evolution.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.18 no.2
• /
• pp.89-104
• /
• 2015

In order to effectively manage forested areas in South Korea on a national scale, using remotely sensed data is considered most suitable. In this study, utilizing Land coverage maps and Forest type maps of national geographic information instead of collecting field data was tested for conducting supervised classification on SPOT-5 and KOMPSAT-2 imagery focusing on forested areas. Supervised classification were conducted in two ways: analysing a whole area around the study site and/or only forested areas around the study site, using Support Vector Machine. The overall accuracy for the classification on the whole area ranged from 54.9% to 68.9% with kappa coefficients of over 0.4, which meant the supervised classification was in general considered moderate because of sub-classifying forested areas into three categories (i.e. hardwood, conifer, mixed forests). Compared to this, the overall accuracy for forested areas were better for sub-classification of forested areas probably due to less distraction in the classification. To further improve the overall accuracy, it is needed to gain individual imagery rather than mosaic imagery to use more spetral bands and select more suitable conditions such as seasonal timing. It is also necessary to obtain precise and accurate training data for sub-classifying forested areas. This new approach can be considered as a basis of developing an excellent analysis manner for understanding and managing forest landscape.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.10
• /
• pp.2232-2240
• /
• 2015

Recently in the field of Big Data, there is a trend of collecting and reprocessing the existing data such as products having high interest of customers and past purchase details to be utilized for the analysis of transaction propensity of users(product recommendations, sales forecasts, etc). Studies related to the propensity of previous users has limitations on its range of subjects and investigation timing and difficult to make predictions on detailed products with lack of real-time thus there exists difficult disadvantages of introducing appropriate and quick sales strategy against the trend. This paper utilizes the machine learning algorithm application to analyze the transaction propensity of users. As a result of applying the machine learning algorithm, it has demonstrated that various indicators which can be deduced by detailed product were able to be extracted.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.40 no.2
• /
• pp.209-215
• /
• 2020

In order to understand the characteristics of natural droughts, it is very important to interpret the spatio-temporal relationship between different types of droughts. In this study, meteorological and hydrological drought events were defined to account for the overlap between drought duration and spatial extent in three dimensions (i.e., latitude, longitude, and timing). In other words, the spatio-temporal drought propagation characteristics were analyzed based on the drought characteristic factors (duration, area, depth, center). The drought map considering the characteristics of spatio-temporal drought propagation can be used to find the fundamental cause of the hydrological drought which is expected to frequently occur in the future. In addition, the drought map is expected to be useful in preparing an effective drought response plan.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.11
• /
• pp.2446-2452
• /
• 2012

In order to meet the recently enhanced emission standards at home and abroad, it is necessary to develop the CRDI ECU control algorithm that users can adjust fuel injection timing and amount in response to their needs. Therefore, this study developed the simulator for knocking analysis that enables knocking discrimination and engine balance correction applicable to the ECU exclusive to the industrial CRDI engine. The purpose of this study is to provide the driver-oriented diagnostic service that enable drivers to diagnose vehicles directly by developing diagnostic devices for vehicles with ths use of the results of the developed simulator for knocing analysis according to the OBD-II standards. For this purpose, this study aims to improve the fuel efficiency of vehicles by proposing the S/W design method of the OBD-II diagnosis device that can provide real-time communcations with the use of wired system and bluetooth module as a wireless system to send and recevice automobile fault diagnosis signal and sensor output signal, and to suggest an improvement for engine efficiency by minimizing the generation of harmful exhaust gas.

• Journal of Family Resource Management and Policy Review
• /
• v.12 no.1
• /
• pp.57-89
• /
• 2008

Using the data of 'middle-and old-aged people' in the 6th year(2003) of KLIPS(Korea Labor and Income Panel Study), this study compared entirely retired men's income source and amount of income divided by the time of retirement and analyzed the determinants of main income source and amount of income level using Multinomial Logit Analysis and Tobit Analysis. The results of these were as following; First, Entirely retired men has average 1.27 income source and the amount of income from main income source is positioned at 85% of total income. This result indicates the lack of variety to get opportunities of income sources for the living and also means high risk associated with the entirely retired men if he looses the main income source. Second, most of income source of entirely retired men is spouse's earned income or private income transfers, however, if we divide those as timing of retirement and characters of each individual, it is represented that the most of income source is differentiated by the position at labor market during work life and the opportunity for building the wealth, and the possibility of obtaining public pension and public support. Third, the income level depends on what sort of income source the retired men has, this shows that there is not a strong relationship between obtaining a Income source and gaining above the certain level of income.

• The Journal of Korean Academy of Prosthodontics
• /
• v.37 no.4
• /
• pp.531-541
• /
• 1999

The purpose of this study was to compare surface roughness and bone formation around two types of threaded commercially pure titanium implants manufactured by two different companies. The test implants were manufactured by Sumin synthesis dental materials Co. (Avana, Busan, Korea), while the controls were manufactured by Nobel Biocare (MK II, Goteborg, Sweden). To compare bone formation adjacent to newly product implant with $Br{\aa}nemark$ MK II implant, surface roughness was measured by Accurate 1500M and histomorphometric analysis was done. The results were as follows: 1. Measurement of surface roughness showed that Avana implant had a slightly more irregular surface compared with $Br{\aa}nemark$ implant. 2. In the light microscopic studies, no infiltration of inflammatory cells nor the giant cells were observed on both groups. 3. In the light and fluorescent microscopic studies, the amount of osseointegration and the extent and the timing of bone formation were similar. 4. There were no statistically difference between two groups in the average bone to implant con-tacts. Branemark implant; 67% (SD 23%), Avana implant; 70% (SD 16%). Comparing with $Br{\aa}nemark$ implant, Avana implant made of CP grade II titanium showed similar good bone healing, formation and osseointegration.

• Smart Structures and Systems
• /
• v.6 no.3
• /
• pp.197-209
• /
• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.