• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.143-163
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• 2012

The dominant model of acquiring scholarly contents at academic libraries is so called big deal where libraries subscribe to a bundle of hundreds, if not thousands of journals in a multi-year contract with fixed annual rate increase. The bid deal, started in the mid-1990s, offered a number of advantages for academic libraries and their users. However, escalating prices for these packages have become a serious issue casting doubts about the sustainability of the subscription-based model. At the moment, it appears there is no viable alternative other than pay-per-view method that is being tested at some libraries. Libraries' budget situation will remain a key factor that might change the situation. Open access started in the 2000s as a vehicle to eliminate barriers to publishing and distributing peer-reviewed scholarly journal articles. Open access publishing is witnessing two-digit growth annually. Open access articles now occupy close to 20% of two major citation databases: Scopus and Web of Science. Google Scholar service, debuted in late 2004, is now a popular tool for discovering and accessing scholarly articles from a vast selection of journals around the world. There is a call for taking Google Scholar seriously as a potential replacement of library databases amid concerns regarding the quality of journals indexed, limited search capabilities vis-$\grave{a}$-vis library databases, and monopoly of public goods. Escalating budget problems, rapid growth of open access publishing and the emergence of powerful free tool, such as Google Scholar, need to be taken seriously as these forces might bring disruptive changes to the existing subscription-based model of scholarly contents at academic libraries.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.271-278
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• 2015

Recently, bit data is difficult to easily collect the desired data because big data is collected via the Internet. Big data is higher than the rate at which the data type and the period of time for which data is collected depending on the size of data increases. In particular, since the data of all different by the intended use and the type of data processing accuracy and computational cost is one of the important items. In this paper, we propose data processing method using a dual-chain in a manner to minimize the computational cost of the data when data is correctly extracted at the same time a multi-layered process through the desired number of the user and different kinds of data on the Internet. The proposed scheme is classified into a hierarchical data in accordance with the intended use and method to extract various kinds of data. At this time, multi-processing and tie the data hash with the double chain to enhance the accuracy of the reading. In addition, the proposed method is to organize the data in the hash chain for easy access to the hierarchically classified data and reduced the cost of processing the data. Experimental results, the proposed method is the accuracy of the data on average 7.8% higher than conventional techniques, processing costs were reduced by 4.9% of the data.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.5
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• pp.488-492
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• 2001

To investigate changes of components in salt-fermented big eyed herring, Harengula zunasi sauce during fermentation, various chemical properties were examined at $2\~3$ months intervals during 18 months of fermentation. The hydrolytic degree increased sharply until 5 months of fermentation and showed the gentle increasement after that. On the other hand, the content of total and amino nitrogen increased gradually during 18 months of fermentation, The hypoxanthine and uric acid were the most abundant in ATP related compounds, ranging from $81.7\%\;to\;90.1\%$. After 18 months of fermentation, sauce was rich in free amino acids such as glutamic acid, aspartic acid, alanine, lysine, threonine in that order.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.479-486
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• 2019

The caps foundation method can reduce the load of a building by using the arching effect, but verification of the method is still insufficient. In this paper, a model test was performed to quantitatively prove the load reduction effect by this method. The test was carried out using six conditions according to the size of caps foundation block and the area of the loading plate. The test results show that the earth pressure was the highest at the position closest to the loading point regardless of the size of caps foundation block and the area of the loading plate. At the highest earth pressure position, when the loading plate area was 30 cm × 30 cm, the earth pressure of a small block was reduced by 35.4% on average, and that of a big block was reduced by 39.7% compared to the pressure with no block. When the loading plate area was 60 cm × 60 cm, the earth pressure of the small block was reduced by 33.9% on average, and the earth pressure of the big block was reduced by 42.7%. Therefore, if the caps foundation method is applied, the load will be reduced by more than 33% for a small block and 39% for a big block.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.705-717
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• 2020

Cities in the world are rushing to develop smart cities to create a sustainable and happy city by solving many problems in cities using information and communication technologies such as big data and IoT. However, in Korea's smart cities and smart city certification systems, the focus is on platform-oriented hardware infrastructure, and the information security aspect is first considered to build and authenticate. It is a situation in which a response system for the risk of leakage of big data containing personal information is needed through policy research on the aspect of personal information protection for smart city operation. This paper analyzes the types of personal information in smart cities, problems associated with the construction and operation of smart cities, and the limitations of the current smart city law and personal information protection management system. As a solution, I would like to present a model of a personal information protection management system in the smart city field and propose a plan to strengthen personal information protection through this. Since the management system model of this paper is applied and operated in the national smart city pilot cities, demonstration cities, and CCTV integrated control centers, it is expected that citizens' personal information can be safely managed.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.47 no.4
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• pp.281-289
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• 2011

The purpose of this study is to identify the flow resistance of the bottom trawl net. The bottom trawl net being used in the training ship of Chonnam National University was selected as a full-scale net, and model nets such as 1/10, 1/25 and 1/50 of the actual net were made. Total resistance of the net part, the height of the net mouth and the flow resistance of components of the net such as wing, bag and cod-end part was measured, converted into full-scale and compared. Additionally, the model rule of Tauti (1934), which has been most frequently used in fishing net modeling experiments, was applied to interpret flow resistance and scale effect of model experiment was investigated. Presumed that the flow resistance R is $R=kS{\upsilon}^2$ against the flow velocity of each net ${\upsilon}$, resistance coefficient k was calculated by substituting R, ${\upsilon}$ and S of the net. From the result, it was found that k decreases exponentially when u increases which makes $k=c{\upsilon}^{-m}$. Whereas m of each net is ranged between 0.13-0.16 and there was not significant difference between nets. c does not show big difference in 1/10 and 1/25 model and the value itself was relatively bigger than in 1/50 model. The height of the net mouth of 1/25 and 1/50 model net h decreases exponentially according as ${\upsilon}$ increases to make $h=d{\upsilon}^{-n}$. Whereas d and n values were almost same in two nets. Additionally, when resistance of cod-end, wing and bag part in 1/25 and 1/50 model nets, both nets showed big resistance in bag part when flow is 1m/s as more than 60%. Wing and cod-end part showed almost same value or wing part had little bit larger value. On the other hand, when reviewing the reasons why both models showed difference in 1/50 model while c value against the resistance coefficient k did not show big difference in 1/10 and 1/25 model, it is inferred that the difference occurred not from material difference but from the difference in net size according to scale. It was judged that they are the scale effects concomitant to the model experiments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.72-84
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• 2017

Together with the Big Data of the 4th Industrial Revolution, the traffic information system has been changed to an section detection system by the point detection system. With DTG(Digital Tachograph) data based on Global Navigation Satellite System, the properties of raw data and data according to processing step were examined. We identified the vehicle trajectory, the link travel time of individual vehicle, and the link average travel time which are generated according to the processing step. In this paper, we proposed a application method for traffic management as characteristics of processing data. We selected the historical data considering the data management status of the center and the availability at the present time. We proposed a method to generate the Travel Time Index with historical link average travel time which can be collected all the time with wide range. We propose a method to monitor the traffic congestion using the Travel Time Index, and analyze the case of intersections when the traffic operation method changed. At the same time, the current situation which makes it difficult to fully utilize DTG data are suggested as limitations.

• Korea Journal of Hospital Management
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• v.23 no.1
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• pp.41-50
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• 2018

The purpose of this research is to evaluate Brand Value by using the K-BPI(Korea Brand Power Index) of Korea Management Association which is based on consumer awareness, as well as to identify how Brand Value which is composed of top of awareness, unaided awareness, aided awareness, image, possibility of purchasing, preference, affects on the Market Share perceived by consumers. This research subjects were 10 hospitals with more than 1,000 beds in Seoul and Gyeonggi-do, and survey subjects were 20 or older adults living in the metropolitan area of Korea. Using K-BPI for measuring Brand Value and used calculation of Market Share according to consumer preference model for measuring Market Share. The major results of this research are as follows: First, this research identified that the top 5 hospitals of largest hospitals in metropolitan area measured by using K-BPI and Market Share were same hospitals as Big 4 hospitals of previous research evaluating the comprehensive competitiveness of hospitals and also same as hospitals that appeared recently. Second, Big 5 hospitals ranked first to fifth in both Brand Value and Market Share. To identify the relationship between K-BPI items(top of awareness, unaided awareness, aided awareness, image, availability, preference) and Market Share, multiple linear regression was used by dividing 5 upper and 5 lower group of hospitals per each. The group of 5 upper hospitals had a significant effect on Market Share, with 'top of awareness', 'unaided awareness', 'aided awareness'. The group of 5 lower hospitals had a significant effect on Market Share with 'unaided awareness', 'aided awareness'. The results of this study and hospitals of the first to third hospitals published in the K-BPI press release reported by KMAC in 2017, and the previous studies evaluating the comprehensive competitiveness hospitals, all had one thing in common that Big 4 hospitals ranked high position. This suggests that evaluation of Brand Value also can be a evaluation measure of hospital. A new competitiveness of hospital is expected by managing brand awareness to have a brand competitiveness and by securing intrinsic Market Share of consumer to reach hospital use ultimately.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.81-99
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• 2020

Origin-destination data have been collected and utilized for demand analysis and service design in various fields such as public transportation and traffic operation. As the utilization of big data becomes important, there are increasing needs to store raw origin-destination data for big data analysis. However, it is not practical to store and analyze the raw data for a long period of time since the size of the data increases by the power of the number of the collection points. To overcome this storage limitation and long-period pattern analysis, this study proposes a methodology for compression and origin-destination data analysis with the compressed data. The proposed methodology is applied to public transit data of Sejong and Seoul. We first measure the reconstruction error and the data size for each truncated matrix. Then, to determine a range of principal components for removing random data, we measure the level of the regularity based on covariance coefficients of the demand data reconstructed with each range of principal components. Based on the distribution of the covariance coefficients, we found the range of principal components that covers the regular demand. The ranges are determined as 1~60 and 1~80 for Sejong and Seoul respectively.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.1-6
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• 2018

In smart cities, data from various kinds of sensors are collected and processed to provide smart services to the citizens. Noise information services with noise maps using the collected sensor data from various kinds of ubiquitous sensor networks is one of them. This paper presents a research result which generates three dimensional (3D) noise maps in real-time for smart cities. To make a noise map, we have to converge many informal data which include big image data of geographical Information and massive sensor data. Making such a 3D noise map in real-time requires the processing of the stream data from the ubiquitous sensor networks in real-time and the convergence operation in real-time. They are very challenging works. We developed our own methodology for real-time distributed and parallel processing for it and present it in this paper. Further, we developed our own real-time 3D noise map generation system, with the methodology. The system uses open source softwares for it. Here in this paper, we do introduce one of our systems which uses Apache Storm. We did performance evaluation using the developed system. Cloud computing was used for the performance evaluation experiments. It was confirmed that our system was working properly with good performance and the system can produce the 3D noise maps in real-time. The performance evaluation results are given in this paper, as well.