• The Korean Journal of Archival Studies
• /
• no.44
• /
• pp.51-99
• /
• 2015

The purpose of the archival appraisal has gradually changed from the selection of records to the documentation of the society. In particular, the qualitative and quantitative developments of the current digital technology and web have become the driving force that enables semantic acquisition, rather than physical one. Under these circumstances, the concept of 'documentary heritage' has been re-established internationally, led by UNESCO. Library and Archives Canada (LAC) reflects this trend. LAC has been trying to develop a new appraisal model and an acquisition model at the same time to revive the spirit of total archives, which is the 'Whole-of-society approach'. Features of this approach can be summarized in three main points. First, it is for documentary heritage and the acquisition refers to semantic acquisition, not the physical one. And because the object of management is documentary heritage, the cooperation between documentary heritage institutions has to be a prerequisite condition. Lastly, it cannot only documenting what already happened, it can documenting what is happening in the current society. 'Whole-of-society approach', as an appraisal method, is a way to identify social components based on social theories. The approach, as an acquisition method, is targeting digital recording, which includes 'digitized' heritage and 'born-digital' heritage. And it makes possible to the semantic acquisition of documentary heritage based on the data linking by mapping identified social components as metadata component and establishing them into linked open data. This study pointed out that it is hard to realize documentation of the society based on domestic appraisal system since the purpose is limited to selection. To overcome this limitation, we suggest a guideline applied with 'Whole-of-society approach'.

• Journal of KIISE:Computing Practices and Letters
• /
• v.13 no.7
• /
• pp.433-441
• /
• 2007

The bio-Sensors, which are sensing the vital signs of human bodies, are largely used by the medical equipment. Recently, the sensor network technology, which composes of the sensor interface for small-seize hardware, processor, the wireless communication module and battery in small sized hardware, has been extended to the area of bio-senor network systems due to the advances of the MEMS technology. In this paper we have suggested a design and implementation of a health care information system(called u-EMS) using a bio-sensor network technology that is a combination of the bio-sensor and the sensor network technology. In proposed system, we have used the following vital body sensors such as EKG sensor, the blood pressure sensor, the heart rate sensor, the pulse oximeter sensor and the glucose sensor. We have collected various vital sign data through the sensor network module and processed the data to implement a health care measurement system. Such measured data can be displayed by the wireless terminal(PDA, Cell phone) and the digital-frame display device. Finally, we have conducted a series of tests which considered both patient's vital sign and context-awared information in order to improve the effectiveness of the u-EMS.

• Journal of Life Science
• /
• v.28 no.1
• /
• pp.130-139
• /
• 2018

In ancient times, horse racing was done in ancient European countries in the form of wagon races or mountain races, and wagon racing was adopted as a regular event at the Greek Olympic Games. Thoroughbred horse has been bred since 17th century by intensive selective breeding for its speed, stamina, and racing ability. Then, in the 18th century, horse racing using the Thoroughbred species began to gain popularity among nobles. Since then, horse racing has developed into various forms in various countries and have developed into flat racing, steeplechasing, and harness racing. Thoroughbred racehorse has excellent racing abilities because of powerful selection breeding strategy for 300 years. It is necessary to maintain and maximize horses' ability to race, because horse industries produce enormous economic benefits through breeding, training, and horse racing. Next-generation sequencing (NGS) methods which process large amounts of genomic data have been developed recently. Based on the remarkable development of these genomic analytical techniques, it is now possible to easily carry out animal breeding strategies with superior traits. In order to select breeding racehorse with superior racing traits, the latest genomic analysis techniques have to be introduced. In this paper, we will review the current efforts to improve race performance for racehorses and to examine the research trends of genomic analysis. Finally, we suggest to utilize genomic analysis in Thoroughbred racehorse and Jeju horse, and propose a strategy for selective breeding for Jeju horse, which contributes job creation of Korea.

• Journal of radiological science and technology
• /
• v.40 no.1
• /
• pp.121-126
• /
• 2017

A technique for producing the ear shell for a hearing aid using DICOM (Digital Imaging and Communication in Medicine) image and a 3D printing was studied. It is a new application method, and is an application technique that can improve the safety and infection of hearing aid users and can reduce the production time and process stages. In this study, the effects on the shape surface were examined before and after the printing of the ear shell using a 3D printer based on the values obtained from the raw data of the DICOM images at the volumes of 0.5 mm, 1.0 mm, and 2.0 mm, respectively. Before the printing, relative relationship was compared with respect to the STL (STereoLithography) file structure; and after the printing, the intervals of the layered structure of the ear shell shape surface were compared by magnifying them using a microscope. For the STL file structure, the numbers of triangular vertices, more than five intersecting points, and maximum intersecting points were large in the order of 0.5 mm, 1.0 mm, and 2.0 mm, respectively; and the triangular structure was densely distributed in the order of the bending, angle, and crest regions depending on the sinuosity of the external auditory meatus shape. As for the ear shell shape surface examined by the digital microscope, the interval of the layered structure was thick in the order of 2.0 mm, 1.0 mm, and 0.5 mm. For the STL surface structure mentioned above, the intersecting STL triangular structure was denser as the sinuosity of the 3D ear shell shape became more irregular and the volume of the raw data decreased.

• Journal of Korea Technology Innovation Society
• /
• v.20 no.4
• /
• pp.1192-1211
• /
• 2017

Today, innovation is driven by the challenge of existing paradigms and by cooperating with many other fields as well as their own, and thus the importance of open innovation is emphasized. This study analyzed the effect of open innovation on innovation activities and examined the role of organizational innovation in various innovation activities. For the analysis, Korean Innovation Survey (KIS) data from Science and Technology Policy Institute (STEPI) in 2016 was used. A total of 1,453 manufacturing firms were selected as a sample and logistic regression was performed. As a result, R&D cooperation has a positive effect on product innovation as the most representative means to acquire new knowledge and technology, while R&D cooperation has no relation with process innovation. In the case of organizational innovation, it strengthens positive effects of R&D cooperation on both product innovation and process innovation. Organizational change can be explained to play a positive role in new innovation activities, and then firms will need to consider organizational innovation in relation to R&D cooperation. This study is meaningful in that it analyzes the causal relationship and role in relation to various types of innovation, and will contribute to the firms to smoothly perform innovation activities in the future.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.20 no.6
• /
• pp.1161-1175
• /
• 2018

An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.3
• /
• pp.83-89
• /
• 2023

The clustering technique using RF fingerprint extracts the characteristic signature of the transmitters which are embedded in the transmission waveforms. The output of the RF-Fingerprint feature extraction algorithm for clustering identical DMR(Digital Mobile Radios) is a high-dimensional feature, typically consisting of 512 or more dimensions. While such high-dimensional features may be effective for the classifiers, they are not suitable to be used as inputs for the clustering algorithms. Therefore, this paper proposes a dimension reduction algorithm that effectively reduces the dimensionality of the multidimensional RF-Fingerprint features while maintaining the fingerprinting characteristics of the DMRs. Additionally, it proposes a clustering algorithm that can effectively cluster the reduced dimensions. The proposed clustering algorithm reduces the multi-dimensional RF-Fingerprint features using t-SNE, based on KL Divergence, and performs clustering using Density Peaks Clustering (DPC). The performance analysis of the DMR clustering algorithm uses a dataset of 3000 samples collected from 10 Motorola XiR and 10 Wintech N-Series DMRs. The results of the RF-Fingerprinting-based clustering algorithm showed the formation of 20 clusters, and all performance metrics including Homogeneity, Completeness, and V-measure, demonstrated a performance of 99.4%.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.35 no.6
• /
• pp.146-154
• /
• 2023

In this study, the peak wave period T_p and mean wave period T₀₂ and T_{m-1, 0}, which are major parameters for classifying ocean characteristics, were calculated using water surface elevation data observed from the second west coast oceanographic and meteorological observation tower. In addition, the ratio of abnormal data, correlation analysis, and optimal probability density function were estimated. In the case of T_p among the calculated representative periods, the proportion of abnormal data was 5.73% and 0.67% at each point, and T₀₂ was 4.35% and 0.01%. T_{m-1, 0} was found to be 2.82% and 0.03%. Meanwhile, as a result of analyzing the relationship between T₀₂ and T_p, the relationship was calculated to be 0.53 and 0.63 for each point. The relationship between T_{m-1, 0} and T_p was 1.15 and 1.32, respectively, and T₀₂, T_{m-1, 0} was 1.18 and 1.22. As a result of estimating the optimal probability density function of the calculated representative period, T_p followed the 'Log-normal' and 'Normal' distributions at each point, and T₀₂ was 'Gamma', 'Normal' distribution and T_{m-1, 0} showed that 'Log-normal' and 'Normal' distribution were dominant, respectively. It is decided that these results can be used as basic data for wave analysis conducted on the west coast.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_2
• /
• pp.1635-1650
• /
• 2023

Under global warming, the steadily increasing sea surface temperature (SST) severely impacts marine ecosystems,such as the productivity decrease and change in marine species distribution. Recently, the catch of Todarodes Pacificus, one of South Korea's primary marine resources, has dramatically decreased. In this study, we analyze the marine environment that affects the formation of fishing grounds of Todarodes Pacificus and develop seasonal habitat suitability index (HSI) models based on various satellite data including Geostationary Ocean Color Imager (GOCI) data to continuously manage fisheries resources over Korean exclusive economic zone. About 83% of catches are found within the range of SST of 14.11-26.16℃,sea level height of 0.56-0.82 m, chlorophyll-a concentration of 0.31-1.52 mg m^-3, and primary production of 580.96-1574.13 mg C m^-2 day^-1. The seasonal HSI models are developed using the Arithmetic Mean Model, which showed the best performance. Comparing the developed HSI value with the 2019 catch data, it is confirmed that the HSI model is valid because the fishing grounds are formed in different sea regions by season (East Sea in winter and Yellow Sea in summer) and the high HSI (> 0.6) concurrences to areas with the high catch. In addition, we identified the significant increasing trend in SST over study regions, which is highly related to the formation of fishing grounds of Todarodes Pacificus. We can expect the fishing grounds will be changed by accelerating ocean warming in the future. Continuous HSI monitoring is necessary to manage fisheries' spatial and temporal distribution.

• Journal of Dental Rehabilitation and Applied Science
• /
• v.36 no.4
• /
• pp.254-261
• /
• 2020

Purpose: The purpose of this study was to assess the marginal and internal fit of interim crowns fabricated by two different manufacturing method (subtractive manufacturing technology and additive manufacturing technology). Materials and Methods: Forty study models were fabricated with plasters by making an impression of a master model of the maxillary right first molar for ceramic crown. On each study model, interim crowns (n = 40) were fabricated using three types of 3D printers (Meg-printer 2; Megagen, Zenith U; Dentis, and Zenith D; Dentis) and one type milling machine (imes-icore 450i; imes-icore GmbH). The internal of the interim crowns were filled with silicon and fitted to the study model. Internal scan data was obtained using an intraoral scanner. The fit of interim crowns were evaluated in the margin, absolute margin, axial, cusp, and occlusal area by using the superimposition of 3D scan data (Geomagic control X; 3D Systems). The Kruskal-wallis test, Mann-Whitney U test and Bonferroni correction method were used to compare the results among groups (α = 0.05). Results: There was no significant difference in the absolute marginal discrepancy of the temporary crown manufactured by three 3D printers and one milling machine (P = 0.812). There was a significant difference between the milling machine and the 3D printer in the axial and occlusal area (P < 0.001). The temporary crown with the milling machine showed smaller axial gap and higher occlusal gap than 3D printer. Conclusion: Since the marginal fit of the temporary crown produced by three types of 3D printers were all with in clinically acceptable range (< 120 ㎛), it can be sufficiently used for the fabrication of the temporary crown.