• Management & Information Systems Review
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• v.39 no.2
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• pp.39-60
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• 2020

Block chain technology is one of the core elements for realizing the 4^th industrial revolution, and many efforts have been made by government and companies to provide services based on block chain technology. In this study we analyzed the benefits of block chain technology for EVMS and designed EVMS block chain platform with increased data security and work efficiency for project management data, which are important assets in monitoring progress, foreseeing future events, and managing post-completion. We did the case studies on the benefits of block chain technology and then conducted the survey study on security, reliability, and efficiency of block chain technology, targeting 18 block chain experts and project developers. And then, we interviewed EVMS system operator on the compatibility between block chain technology and EVM Systems. The result of the case studies showed that block chain technology can be applied to financial, logistic, medical, and public services to simplify the insurance claim process and to improve reliability by distributing transaction data storage and applying security·encryption features. Also, our research on the characteristics and necessity of block chain technology in EVMS revealed the improvability of security, reliability, and efficiency of management and distribution of EVMS data. Finally, we designed a network model, a block structure, and a consensus algorithm model and combined them to construct a conceptual block chain model for EVM system. This study has the following contribution. First, we reviewed that the block chain technology is suitable for application in the defense sector and proposed a conceptual model. Second, the effect that can be obtained by applying block chain technology to EVMS was derived, and the possibility of improving the existing business process was derived.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.146-154
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• 2019

Recently, a system has been developed and applied to establish and utilize HD maps through R&D. The biggest problem, however, is the lack of a proper HD map update system, which requires the development and adoption of such a system as soon as possible. In addition, in the case of updating HD maps for automated driving, integrity and accuracy of maps are required for safe driving, so an test of these technologies and data quality is required. In April 2018, the Ministry of Land, Infrastructure and Transport implemented a project to 'Develop Technology to Demonstrate and Share the Instant Road Change Detection and Update Technology for automated driving. This paper analyzed the technology for updating map based on the investigation and analysis of relevant technology trends for the development of integrated demonstration and sharing technology of road change rapid detection and updating map technology, and put forward the criteria for road change rapid detection, integrated quality verification of update technology. It is expected that the results of this study will contribute to quality assurance of HD maps that support safety driving for automated vehicles.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.57-69
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• 2023

In a situation where digital transformation using artificial intelligence is active around the world, the growth of domestic AI companies or AI industrial ecosystems is slow. Where a large amount of government funds related to AI are being invested to overcome the difficult economic situation, systematic research on the effect is insufficient. So, this study aimed to examine the policy effectiveness of the government artificial intelligence solution voucher support project for small and medium-sized enterprises (SMEs) using Propensity Score Matching (PSM) and Difference-in-Differences (DID) on the financial performance of beneficiary companies. For empirical analysis, PSM-DID analysis was performed using sales performance since 2019 for 461 companies with a history of voucher support among the AI SMEs data released by the National IT Industry Promotion Agency. As a result of the analysis, the beneficiary companies' asset growth, salary, and R&D expenses increased overall after government support, and no significant contribution could be confirmed in terms of profits. This study suggests that the voucher policy business directly contributed to the company's growth in the short term, but it requires a certain period of time to generate profits.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.117-127
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• 2015

Recently, research and development on satellite payloads are being developed such as the optical sensor, SAR etc. Satellite image for earth observation is being utilized both domestically and abroad. Advanced satellite payload technology has led to the collection and analysis of satellite images relying on the optical sensor. Currently, related organizations such as RDA(the Rural Development Administration) are collectively collaborating to plan a national project to develop a medium-sized satellite based on Korea's domestic technology independently. This paper investigated the cases of the past research on application of satellite images for agriculture and analyzed the technical specifications for satellite payload in each area of such application. Based on the results of the past surveys and consultation studies among local experts in satellite image application, we analyzed the current trends, plans and applications of domestic and overseas R&D in satellite payloads for earth observation in agriculture, and proposed the appropriate technical specifications for developing a future medium-sized satellite for agriculture. The proposed specifications were then incorporated into a simulated satellite to examine its performance to observe the Korean farming areas. The authors anticipate that the findings of this paper will form a useful technical basis for providing the appropriate specifications for developing future medium-sized satellite payloads to be used in agriculture and forestry, and enabling the end users to efficiently utilize the satellite.

• Proceedings of the Korean Society of Laser Processing Conference
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• 1998.11a
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• pp.0-0
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• 1998

-Part I- As market needs become more various, the production of smaller quantities of a wider variety of products becomes increasingly important. In addition, in order to meet demands for more efficient production, long-term unmanned factory operation is prevailing at a remarkable pace. Within this context, laser machines are gaining increasing popularity for use in applications such as cutting and welding metallic and ceramic materials. FANUC supplies four models of $CO_2$ laser oscillators with laser power ranging from 1.5㎾ to 6㎾ on an OEM basis to machine tool builders. However, FANUC has been requested to produce laser oscillators that allow more compact and lower-cost laser machines to be built. To meet such demands, FANUC has developed six models of Slab type YAG laser oscillators with output power ranging from 150W to 2㎾. These oscillators are designed mainly fur cutting and welding sheet metals. The oscillator has an exceptionally superior laser beam quality compared to conventional YAG laser oscillators, thus providing significantly improved machining capability. In addition, the laser beam of the oscillator can be efficiently transmitted through quartz optical fibers, enabling laser machines to be simplified and made more compact. This paper introduces the features of FANUC’s developed Slab type YAG laser oscillators and their applications. - Part II - All-solid-state lasers employing laser diodes (LD) as a source of pumping solid-state laser feature high efficiency, compactness, and high reliability. Thus, they are expected to provide a new generation of processing tools in various fields, especially in automobile and aircraft industries where great hopes are being placed on laser welding technology for steel plates and aluminum materials for which a significant growth in demand is expected. Also, in power plants, it is hoped that reliability and safety will be improved by using the laser welding technology. As in the above, the advent of high-power all-solid-state lasers may not only bring a great technological innovation to existing industry, but also create new industry. This is the background for this project, which has set its sights on the development of high-power, all-solid-state lasers with an average output of over 10㎾, an oscillation efficiency of over 20%, and a laser head volume of below 0.05㎥. FANUC Ltd. is responsible for the research and development of slab type lasers, and TOSHIBA Corp. far rod type lasers. By pumping slab type Nd: YAG crystal and by using quasi-continuous wave (QCW) type LD stacks, FANUC has already obtained an average output power of 1.7㎾, an optical conversion efficiency of 42%, and an electro-optical conversion efficiency of 16%. These conversion efficiencies are the best results the world has ever seen in the field of high-power all-solid-state lasers. TOSHIBA Corp. has also obtained an output power of 1.2㎾, an optical conversion efficiency of 30％, and an electro-optical conversion efficiency of 12%, by pumping the rod type Nd: YAG crystal by continuous wave (CW) type LD stacks. The laser power achieved by TOSHIBA Corp. is also a new world record in the field of rod type all-solid-state lasers. This report provides details of the above results and some information on future development plans.

• Journal of Science and Technology Studies
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• v.5 no.1 s.9
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• pp.55-92
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• 2005

The factors contributing to the formation of an important scientific concept in South Korea and its circulation in the society are the scientific knowledge that had been already formed, matured, and established in the U.S.A, Europe and Japan and has been introduced into Korea, and the institutions that have been formed during the recent modernization in South Korea. The concept of 'genetic information' cannot be an exception in this context. The concept of genetic information is the one that has been extended and intensified by the genomics and bioinformatics formed and matured through the Human Genome Projects from the former concept of inheritance or heredity within the framework of classical and molecular genetics. The purpose of this study was to find out 'how the production structure of genetic information in South Korea has been formed', under the perspective of the conceptual, epistemic, and institutional holisticity or integratedness in the concept and knowledge production structure idealized in Western advanced nations. The discourse of genetic engineering popular in the mid 1980's in South Korea has catalyzed the development of molecular biology. However, the institutional balance that had been established for the biochemistry departments in Natural Science College and Medical College was not formed between the genetic engineering and genetics departments in South Korea. Therefore, they were unable to achieve the more integrative and macro-level disciplinary impact on life sciences, largely due to institutional lack of the capable (human) genetics departments in some leading Korean colleges of Medicine. In genomics, the cutting-edge reprogramming and restructuring of the traditional genetics in the West, South Korea has not invested, even meagerly, in the infrastructure, fund, and research and development (R & D) for the Basic or First Phase of the research trajectory in the Human Genome Project. Without a minimal Basic Phase, the genomics research and development in Korea has been running more or less for the Advanced or Second Phase. Bioinformatics has started developing in Korea under a narrow perspective which regards it as a mere sub-discipline of information technology (IT). Having developed itself in parallel with genomics, bioinformatics contains its own unique logics and contents that can be both directly and indirectly connected to the information science and technology. As a result, bioinformatics reveals a defect in respect of being synergistically integrated into genetics and life sciences in Korea. Owing to the structural problem in the production, genetic information appears to be produced in a fragmented pattern in the Korean society since its fundamental base is weak and thin. A good example of the conceptual and institutional fragmentedness is that 'the genetics of individual identification' is not a normal integrated part of the Korean genetics, but a scientific practice exercised in the departments of legal medicine in a few Medical Colleges. And the environment contributing to the production structure of genetic information in South Korea today comprises 'sangmyung gonghak'(or life engineering) discourse and non-governmental organization movement.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.8-9
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• 2011

On 4 September 2010 an earthquake of magnitude 7.1 on the Richter scale occurred on the Canterbury Plains in the South Island of New Zealand. The Canterbury Plains are an area of extensive groundwater and spring fed surface water systems. Since the September earthquake there have been several thousand aftershocks (Fig. 1), the largest being a 6.3 magnitude quake which occurred close to the centre of Christchurch on 22February 2011. This second quake caused extensive damage to the city of Christchurch including the deaths of 189 people. Both of these quakes had marked hydrological impacts. Water is a vital natural resource for Canterburywith groundwater being extracted for potable supply and both ground and surface water being used extensively for agricultural and horticultural irrigation.The groundwater is of very high quality so that the city of Christchurch (population approx. 400,000) supplies untreated artesian water to the majority of households and businesses. Both earthquakes caused immediate hydrological effects, the most dramatic of which was the liquefaction of sediments and the release of shallow groundwater containing a fine grey silt-sand material. The liquefaction that occurred fitted within the empirical relationship between distance from epicentre and magnitude of quake described by Montgomery et al. (2003). . It appears that liquefaction resulted in development of discontinuities in confining layers. In some cases these appear to have been maintained by artesian pressure and continuing flow, and the springs are continuing to flow even now. In spring-fed streams there was an increase in flow that lasted for several days and in some cases flows remained high for several months afterwards although this could be linked to a very wet winter prior to the September earthquake. Analysis of the slope of baseflow recession for a spring-fed stream before and after the September earthquake shows no change, indicating no substantial change in the aquifer structure that feeds this stream.A complicating factor for consideration of river flows was that in some places the liquefaction of shallow sediments led to lateral spreading of river banks. The lateral spread lessened the channel cross section so water levels rose although the flow might not have risen accordingly. Groundwater level peaks moved both up and down, depending on the location of wells. Groundwater level changes for the two earthquakes were strongly related to the proximity to the epicentre. The February 2011 earthquake resulted in significantly larger groundwater level changes in eastern Christchurch than occurred in September 2010. In a well of similar distance from both epicentres the two events resulted in a similar sized increase in water level but the slightly slower rate of increase and the markedly slower recession recorded in the February event suggests that the well may have been partially blocked by sediment flowing into the well at depth. The effects of the February earthquake were more localised and in the area to the west of Christchurch it was the earlier earthquake that had greater impact. Many of the recorded responses have been compromised, or complicated, by damage or clogging and further inspections will need to be carried out to allow a more definitive interpretation. Nevertheless, it is reasonable to provisionally conclude that there is no clear evidence of significant change in aquifer pressures or properties. The different response of groundwater to earthquakes across the Canterbury Plains is the subject of a new research project about to start that uses the information to improve groundwater characterisation for the region. Montgomery D.R., Greenberg H.M., Smith D.T. (2003) Stream flow response to the Nisqually earthquake. Earth & Planetary Science Letters 209 19-28.

• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.4
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• pp.307-319
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• 2009

Carbon dioxide capture and storage (CCS) technology has been regarded as one of the most possible and practical option to reduce the emission of carbon dioxide ($CO_2$) and consequently to mitigate the climate change. Korean government also have started a 10-year R&D project on $CO_2$ storage in sea-bed geological structure including gas field and deep saline aquifer since 2005. Various relevant researches are carried out to cover the initial survey of suitable geological structure storage site, monitoring of the stored $CO_2$ behavior, basic design of $CO_2$ transport and storage process and the risk assessment and management related to $CO_2$ leakage from engineered and geological processes. Leakage of $CO_2$ to the marine environment can change the chemistry of seawater including the pH and carbonate composition and also influence adversely on the diverse living organisms in ecosystems. Recently, IMO (International Maritime Organization) have developed the risk assessment and management framework for the $CO_2$ sequestration in sub-seabed geological structures (CS-SSGS) and considered the sequestration as a waste management option to mitigate greenhouse gas emissions. This framework for CS-SSGS aims to provide generic guidance to the Contracting Parties to the London Convention and Protocol, in order to characterize the risks to the marine environment from CS-SSGS on a site-specific basis and also to collect the necessary information to develop a management strategy to address uncertainties and any residual risks. The environmental risk assessment (ERA) plan for $CO_2$ storage work should include site selection and characterization, exposure assessment with probable leak scenario, risk assessment from direct and in-direct impact to the living organisms and risk management strategy. Domestic trial of the $CO_2$ capture and sequestration in to the marine geologic formation also should be accomplished through risk management with specified ERA approaches based on the IMO framework. The risk assessment procedure for $CO_2$ marine storage should contain the following components; 1) prediction of leakage probabilities with the reliable leakage scenarios from both engineered and geological part, 2) understanding on physio-chemical fate of $CO_2$ in marine environment especially for the candidate sites, 3) exposure assessment methods for various receptors in marine environments, 4) database production on the toxic effect of $CO_2$ to the ecologically and economically important species, and finally 5) development of surveillance procedures on the environmental changes with adequate monitoring techniques.