• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.2
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• pp.217-225
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• 2024

Even after the introduction of Global Maritime Distress and Safety System (GMDSS), many maritime accidents occur. A method of transmitting a rescue signal when a person falls into the water from a ship is currently being researched and developed in various ways, but no products have been developed that use frequencies allocated for maritime mobile service. Accordingly, in this study, we designed and produced a man-over-board (MOB) device by applying Group B AMRD technologies, which were adopted through the latest revision of the International Telecommunication Union (ITU). In addition, a receiver and user interface were built to verify the performance of the transmitter, and we confirmed that it can be used in conjunction with existing electronic charts. This MOB device satisfies the general and technical requirements of Group B AMRD using AIS technology and uses integrated components for miniaturization for easy portability in a maritime environment. We expect that it will achieve excellent AIS communication and be essential in rapid response and safety in emergency scenarios.

• Journal of the Health Care and Life Science
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• v.11 no.1
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• pp.67-77
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• 2023

This paper aims as a prior study to cultivate artificial intelligence professionals at the level of colleges in the future by analyzing healthcare services and technologies using artificial intelligence technology. As artificial intelligence technology is recognized as a key engine or core technology in the future that will create national competitiveness and added value, advanced countries are investing a lot of attention and support in developing technologies as well as human resources at the national level. Korea is also promoting national-level R&D manpower training projects such as AI graduate program support projects, and investing heavily in fostering and securing its own artificial intelligence personnel, mainly by large companies, but there is a lack of artificial intelligence experts. This study analyzes the current status of healthcare services and technologies, industries, and artificial intelligence manpower training using artificial intelligence technology, and proposes directions for fostering artificial intelligence personnel at the level of colleges.

• 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.

• Culinary science and hospitality research
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• v.22 no.4
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• pp.24-36
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• 2016

This study investigated the quality characteristics of Haengbyung using dry rice flour added with various amounts (0, 20, 40, 60%) of raw and steamed apricot juice. The moisture contents, color values, pH, texture and sensory evaluation(attribute difference and acceptance) for the samples were tested. The moisture content (p<0.001) and pH(p<0.001) of the Haengbyung significantly decreased with the increase of apricot juice. As for the color of the Haengbyung samples, the higher percentage of the apricot juice showed the lower L-value (p<0.001), and higher a-value(p<0.001) and b-value(p<0.001). Texture profile analysis of Haengbyung samples showed that hardness(p<0.001) and gumminess(p<0.001) increased, while adhesiveness(p<0.001) and cohesiveness(p<0.05) decreased with increasing amounts of apricot juice. An attribute difference test of Haengbyung samples showed that appearance(apricot color(p<0.001) and dryness(p<0.001)), flavor(sour(p<0.001), acerbic (p<0.001), and green fruit(p<0.001)), and taste(sour(p<0.001), acerbic(p<0.001), and astringent(p<0.05) as increased as apricot juice amounts increased. The control and Haengbyung sample with 20% of apricot juice (both raw and steamed) showed the highest acceptance in taste, texture, and overall acceptability in consumer ranking testing.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.27-33
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• 2018

This study was performed to review the domestic and international smart farm service model based on the convergence of agriculture and information & communication technology and derived various factors needed to improve the Korean smart greenhouse. Studies on modelling of crop growth environment in domestic smart farms were limited. And it took a lot of time to build research infrastructure. The cloud-based research platform as an alternative is needed. This platform can provide an infrastructure for comprehensive data storage and analysis as it manages the growth model of cloud-based integrated data, growth environment model, actuators control model, and farm management as well as knowledge-based expert systems and farm dashboard. Therefore, the cloud-based research platform can be applied as to quantify the relationships among various factors, such as the growth environment of crops, productivity, and actuators control. In addition, it will enable researchers to analyze quantitatively the growth environment model of crops, plants, and growth by utilizing big data, machine learning, and artificial intelligences.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.235-243
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• 2002

Ni-base superalloys are used extensively in industry, both in aeroengines and land based turbines. About 60% by weight of most modern gas turbine engine structural components are made of Ni-base superalloys. To satisfy practical demands, the efficiency of gas turbine engines has been steadily and systematically increased by design modifications to handle higher turbine inlet or firing temperatures. However, the increase in operating temperatures has lead to a decrease in the life of components and increase in costs of replacement. Moreover, around 80% of the large frame size industrial/utility gas turbines operating in the world today were installed in the mid-sixties to early seventies and are now 25 to 30 years old. Consequently, there are greater opportunities now to repair and refurbish the older models. Basically, there are two major factors influencing the weldability of the cast alloys: strain-age cracking and liquation cracking. Susceptibility to strain-age cracking is due to the total Ti plus AI content of the alloy; Liquation cracking is due either to the presence of low melting constituents or constitutional liquation of constituents. Though Rene 41 superalloy has 4.5wt.% total Ti and Al content and falls just below the safe limit proposed by Prager et al., controlled grain size and special heat treatments are needed to obtain crack-free welds. Varying heat treatments and filler materials were used in a laboratory study, then the actual welding of service parts was carried out to verity the possibility of crack-tree weld of components fabricated from Rene 41 superalloy. The microstructural observations indicated that there were two kinds of carbides in the FCC matrix. MC carbides were located along the grain boundaries, while M$_{23}$C$_{6}$ carbide was located both inter and intra granularly. Two kinds of filler materials, Rene 41 and Hastelloy X were used to gas tungsten arc weld a patch into the sheet metal, along with varying pre-weld heat treatments. The microstructure, hardness and tensile tests were determined. The service distressed parts were categorized into three classes: with large cracks, with medium cracks and with small or no visible cracks. No significant difference in microstructure among the specimens was observed. Specimens were cut from the corner and the straight edge of the patch repair, away from the corner. The only cracks present were found to be associated with inadequate surface preparation to remove oxidation. Guidelines for oxide removal and the welding procedures developed in the research enabled crack-free welds to be produced.d.

• Korean Journal of Veterinary Service
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• v.36 no.3
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• pp.163-169
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• 2013

Both of avian influenza (AI) and Newcastle disease (ND) can cause mild to severe diease in poultry. In this study, clinical signs, macro, and micro lesions were studied. Eighteen six-week-old SPF chicks were divided into 4 groups (E1, E2, E3 and C1) and housed in different rooms of the isolation facility at CAVAC (Daejeon, Korea). The control group (C1) of 3 chicks was housed separately as uninoculated. Experimental groups (E1, E2 and E3) challenged with H9N2 and/or NDV. E1 group was challenged with 0.1 mL A/Kr/Ck/01310/01 (H9N2) $10^{5.6}$ $EID_{50}$ by intranasal, E2 group was challenged with 0.5 mL Kyojeongwon (KJW) $10^{5.0}{\sim}10^{6.0}$ $ELD_{50}$ by intramuscular, and E3 group was challenged with 0.1 mL A/Kr/Ck/01310/01 $10^{5.6}$ $EID_{50}$ by intranasal and 0.5 mL KJW $10^{5.0}{\sim}10^{6.0}$ $ELD_{50}$ by intramuscular 7 days after H9N2 challenge. In clinical signs and gross findings, E1 group showed 0% mortality, anorexia, and hemorrhage of proventriculus and thymus, E2 group showed 100% mortality within 3~5 days after challenge, anorexia, green diarrhea, hemorrhage of proventriculus, proximal esophagus and thymus, enlargement of kidney, and bronze liver, and E3 group showed 100% mortality within 24~36 hours after NDV challenge, depression, anorexia, green diarrhea, hemorrhage of proventriculus, spleen, and lung, enlargement of kidney, and reduction of thymus size and number. In histopathological examination, E1 group showed depletion and necrosis in bursa of Fabricius, thymus, and spleen, and E2 and E3 group showed severe lymphocyte depletion and necrosis with destruction of lymphoid organ structures. In conclusion, co-infection of H9N2 with ND virus causes acute disease with high mortality than single infection and the pathologic lesions were more severe.

• Korean Journal of Construction Engineering and Management
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• v.10 no.3
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• pp.32-41
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• 2009

In the execution of construction management, such pre-design steps as a planning stage, a basic design stage, and a work design stage are regarded as more important than an actual construction stage. However, the manpower input criterion from the aspect of construction management price standard in the Construction Engineering Management Law does not attach weight to the pre-design stage. In this regard, the aim of this study was to examine the propriety of manpower input in the pre-design stage of construction management and then present an improvement strategy of it. For this, the investigator examined the criterion of service price prescribed in the Construction Engineering Management Law and then comparatively analyzed four sites of construction management services. Study findings are as follows: 1) the actual state of manpower input based on the stepwise average price criterion of construction management service is presented with such steps as the newly established planning step (6.6%), the basic design stage (3.9%$\rightarrow$5.6%), the practical design stage(7.6%$\rightarrow$13.5%), the construction stage (88.5%$\rightarrow$64.0%), and the newly established maintenance stage (10.3%). The average price criterion is classified by total construction expenses and calculated by improved rates and stage; and 2) the three-step criterion of the Construction Engineering Management Law is classified into five stages including the planning stage and the maintenance stage by dividing it with the stepwise construction businesses. Study findings show that the calculation of price criterion in the actual site of construction management services must be operated in a practical and flexible manner and the systematic improvement of stepwise manpower input must be carried out actually.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.765-776
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• 2018

Artificial Intelligence is a rapidly growing technology with the latest developments in computing technology and is considered as one of the next major technologies. Chat-Bot is a system that is designed to respond to user's input according to the rules that are set up in advance and it provides more services through simple and repetitive tasks such as counseling, ordering and others. Accordingly, the study aims to present a model of a celeb-bot using Artificial Intelligence. Celeb-Bot is a combination of Celeb, which are short for Celebrity and Chat-bot. Celeb-Bot provides a Chat-Bot service that allows people to talk to a celebrity. The celeb is the best thing to build a relationship and has the advantages of being accessible to anyone. At the same time, Artificial Intelligence is a technology that can be seen as a person, not a product. Based on this, we believe that Celeb's Characteristic and Chat-bot based on artificial intelligence technologies need to be combined, so variety of products can generate synergy. It is predicted that there will be variety of derivatives that utilize this technology, and it is going to present a celeb-bot model accordingly.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.11-17
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• 2020

In this paper, we propose a method to build a knowledge base based on natural language processing for intelligent battlefield awareness service. The current command and control system manages and utilizes the collected battlefield information and tactical data at a basic level such as registration, storage, and sharing, and information fusion and situation analysis by an analyst is performed. This is an analyst's temporal constraints and cognitive limitations, and generally only one interpretation is drawn, and biased thinking can be reflected. Therefore, it is essential to aware the battlefield situation of the command and control system and to establish the intellignet decision support system. To do this, it is necessary to build a knowledge base specialized in the command and control system and develop intelligent battlefield awareness services based on it. In this paper, among the entity names suggested in the exobrain corpus, which is the private data, the top 250 types of meaningful names were applied and the weapon system entity type was additionally identified to properly represent battlefield information. Based on this, we proposed a way to build a battlefield-aware knowledge base through mention extraction, cross-reference resolution, and relationship extraction.