• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.437-445
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• 2018

IMO (International Maritime Organization) has been strengthening the regulations of ship emission gas such as sulfur oxides (SOX), nitrogen oxides (NOX) and carbon dioxides (CO2) to protect the marine environment. Especially, ECA (Emission Control Area) has been set and operated in the USA and US. As a countermeasure against these environmental regulations, the demand for environmentally, friendly and highly efficient vessels has led to a growing interest in technology related research with respect to electric propulsion systems capable of reducing exhaust gas. Container ships were excluded from the application coverage of the electric propulsion systems for reasons of operation at economical speed. However, in the future, the need for electric propulsion system is expected to rise, because it is easy to monitor and control so that it can be an applicate to smart ship which are represented by fourth industrial revolution technology. In this study, research was carried out to design a generator and battery capacity through the load analysis of the 6,800TEU container ship to apply the electric propulsion system of the container ship. A capacity design based on the load analysis has an advantage that the generator can be operated in a high efficiency section through the load distribution control using the battery.

• Korea Trade Review
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• v.48 no.2
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• pp.45-69
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• 2023

The advent of the 4th industrial technology brought about various changes and innovations in the overall industry, but the digitalization of the logistics industry, which involved complicated paperwork processes and various stakeholders, was somewhat behind compared to other industries. However, changes and innovations related to digitalization in the logistics industry began to accelerate due to the impact of COVID-19. This study is to check the digitalization status of container liners accelerated by these changes, analyze the impact of such changes on customer satisfaction and behavioral intention. In this study, a questionnaire survey was conducted for 30 days targeting workers in the logistics industry who had experience using digitalization products of container shipping companies, and a total of 144 questionnaire responses were used to verify hypotheses. To summarize the results of this study, first, it was confirmed that perceived ease of use has a positive (+) effect on perceived usefulness. Second, perceived ease of use was found to have a positive (+) effect on customer satisfaction. Third, it was found that perceived usefulness had a positive (+) effect on customer satisfaction. Fourth, perceived usefulness has a positive (+) effect on behavioral intention. Fifth, it was found that customer satisfaction had a positive (+) effect on behavioral intention. Summarizing the results of the study, it can be summarized that the digitization of regular shipping companies is convenient to use and has a positive effect on customer satisfaction and behavioral intention if it is useful.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.715-720
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• 2023

The military is driving innovative changes such as AI, cloud computing, and drone operation through the Fourth Industrial Revolution. It is expected that such changes will lead to a rapid increase in the demand for information exchange requirements, reaching all lower-ranking soldiers, as networking based on IoT occurs. The flow of such information must ensure efficient information distribution through various infrastructures such as ground networks, stationary satellites, and low-earth orbit small communication satellites, and the demand for information exchange that is distributed through them must be appropriately dispersed. In this study, we redefined the DSCP, which is closely related to QoS (Quality of Service) in information dissemination, into 11 categories and performed research to map each cluster group identified by cluster analysis to the defense "information exchange requirement list" on a one-to-one basis. The purpose of the research is to ensure efficient information dissemination within a multi-layer integrated network (ground network, stationary satellite network, low-earth orbit small communication satellite network) with limited bandwidth by re-establishing QoS policies that prioritize important information exchange requirements so that they are routed in priority. In this paper, we evaluated how well the information exchange requirement lists classified by cluster analysis were assigned to DSCP through M&S, and confirmed that reclassifying DSCP can lead to more efficient information distribution in a network environment with limited bandwidth.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.891-899
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• 2024

The Fourth Industrial Revolution is centered on a personalized demand fulfillment economy and is all about transformation and flexible processing that can deliver what customers want in real time across space and time. This paper implements the construction and operation of a packaging platform that can instantly procure the required packaging products based on real-time orders and evaluates its performance. The components of customer satisfaction are flexible and dependent on the situation which requires efficient management of enterprise operational processes based on an e-SCM platform. An OMS optimized for these conditions plays an important role in maximizing and differentiating the efficiency of a company's operations and improving its cost advantage. OMS is a system of mass customization that provides efficient MOT(Moment of Truth) logistics services to meet the eco-friendly issues of many individual customers and achieve optimized logistics operation goals to enhance repurchase intentions and sustainable business. OMS precisely analyzes the collected data to support information and decision-making related to efficiency, productivity, cost and provide accurate reports. It uses data visualization tools to express data visually and suggests directions for improvement of the operational process through statistics and prediction analysis.

• Archives of design research
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• v.11 no.1
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• pp.161-172
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• 1998

The evolution of computing environments caused various dharges in our society. The change cj instruction media is one of these effects. WWW using network techndogy is regarded as a pov.powerful tool for rerrote instruction. The methods of utilizing network technologies in design instrudion and design process rould be diversified comparing with those of other general instruction. Computer graphics has been regarded as a very use!u design tool for its accuracy and rapidty. Network can help us to do creative work using cornplter graphics. The merits of this technology are sharing resources and rraking it easy to roIlaborate. Recent cxxnputer graphics instruction has some defects in oontents and methods. The oontents have a weak relationship with other industrial design subjects. From above, the purpose of this thesis is to use computer graphics and netv.urk technology for supporting basic design instruction. Virtual gallery using WWW can be a cyberspare v.tlere the evaluation of results and the exchange of information take plare. This tool makes it easier to oomrunicate and oollaborate with dassmates. A casestudy-Composition with basic objectswas exea.rted by individual for distributed asynchronous rmde. The results of this thesis are summarized for four factors. Rrst, it was easy to transform idea. Serond, student-oriented working was performed. Third, interaction among students was activated. Fourth, not only final results, but also midterm results was oonsidered for evaluation. These methods also have problems as rerent instruction methods, but it rould be used as a instruction tool to compensate for existing instruction methods.

• 대한공업교육학회지
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• v.43 no.1
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• pp.158-176
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• 2018

The purpose of this study is to analyze the satisfaction of the manufacturing process and the satisfaction of manufacturing lesson in the lesson of model product manufacturing based on IoT(Internet of Things) for pre-service technology teachers. and we also analyzed 'smart farm' model production manufacturing among various products. The survey questionnaires with 8 questions to investigate satisfaction level of model manufacturing process, difficulties in manufacturing, and the satisfaction level of manufacturing lesson were collected from the 15 pre-service technology teachers and analyzed by using SPSS program. and The results of this study were as follows: First, the lesson satisfaction average level of pre-service technology teachers was high(M=4.22) in model product manufacturing process for the 'smart farm' model making based on the IoT. Second, the average satisfaction level of 'patent search and prior art search report writing education' was as high as 4.07. Therefore, the application of 'prior art search report writing education' showed that it helped to make the product. Third, the best high satisfaction level in the model production manufacturing procedure was 'education of inventive thinking method'(M=4.40). Therefore, the pre-service technology teachers showed that the 'education of inventive thinking methods' was very helpful from the idea design to the optimal selection of idea. The next order of satisfaction level was high(M=4.33) in 'design education and counseling' and 'guidance through selection of professor who guide the production manufacturing in addition to professors who are in charge of lesson'. Because they were helpful in solving the lack of knowledge of pre-service technology teachers. Fourth, satisfaction level with 'the presentation of model making results and exhibitions', 'presentations and participations of external event' was high (M = 4.13). Although the results of interviews with pre-service technology teachers showed that they suffered from lack of knowledge in various technologies, but it was an opportunity to learn things and felt a sense of accomplishment.

• 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.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.27-40
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• 2022

Building self-sustainable rural infrastructure and environment through smart digital agriculture technology innovation is one of the major goals of the Korean agricultural administration as a part of the nation's 4^th industry revolution. To identify areas for improving and effectively investing in the acceleration of rural development, 207 experts in the areas of crop science and smart digital agriculture technology were interviewed for their opinions and suggestions on 22 questions designed to recognize fundamental agricultural issues to be addressed and solutions to advance technology innovation and rural development. Majority of the participants expected smart digital agriculture technologies to resolve major agricultural issues and help build a better rural environment. To overcome technology gaps and resolve issues more effectively, further investment in training new technology experts and building stronger agricultural technology infrastructure is urgent, and persistent and systematic support from agricultural administration appears to be the key for accelerating the process. While the leading global groups of both public and private sectors have advanced their technologies beyond the field application stage, most of the Korean technologies remain at the early pilot stage. Aging population and lack of labor in rural areas, unknown future climate change, and challenges in sustainable rural development are expected to be resolved by smart digital agriculture technologies. Technological innovations by research institutes should be promptly deployed in the crop production field, and farm training systemically organized by local technology centers can accelerate farming revolution. Standardization of equipment and data systems is another key to the success of digitalization of food crop production and food supply chains nationwide.

• 대한공업교육학회지
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• v.38 no.1
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• pp.49-67
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• 2013

The purpose of this study is to analyze the external systems and the units 'problem solving and invention' of the middle school technology and home economics 1 textbooks of the revised 2011 national curriculum in an effort to provide some information on the content system of invention education in technology class, as invention education was provided as part of a regular subject for the first time. The findings of the study were as follows: First, 'Technology and Inventions' chapter of Technology and Home Economics 1 Textbooks occupied 10-18% share, with the subchapter of 'Problem Solving and Invention' unit taking up 6.7-29% of the textbooks. Second, for most textbooks, 'Technological Problem Solving', 'Idea Generation' 'Multi-dimensional Projection Method', 'Expansive Thought-Processing Methodology', 'Converging Thought Methodology' and 'Invention in Everyday Lives' were included as main contents based on the accomplishment criteria presented in education process interpretation documents. Third, the detailed structures were generally made up as follows: Introduction (Broad Chapter Title, Subchapter Table of Contents, Introduction, Subchapter Title, Study Objectives, Open Thinking); Development (Unit Title, Thinking Ahead, Core Terms, Main Text, Study Helper, Activities, Research Exercises, Supplemental Readings, In-depth Study Topics, Technology in Everyday Lives, Reading Topics, Discussion Topics, and Career Helpers); and Summary (Subchapter Summary, Study Summary, Terms Summary, Writing Follow-up, Self Review, Broad Chapter Evaluation). Fourth, based on the analysis of figures included, photographs had the largest share, followed by figures, tables, and graphs. The photos were used to illustrate various inventions, invention methodologies, and exercise activities, while figures were included to depict the contents included in the main text, and the tables to assist to preparation of process diagrams or materials lists. Fifth, based on the analysis of content weights, greater weights were placed on 'Inventions and Thoughts', and 'Invention Experiment Activities,' while 'Understanding Inventions' and 'Invention and Patents' chapters did not have a lot of texts involved. Sixth, based on the analysis of content presentation methods, most textbooks combined figures, tables, illustrations and texts to discuss the topics. Based on the above study results, we suggest the following: First, a consistent education curriculum should be developed over the topic of invention; and second, more precise and systematic analysis of textbooks would need to be performed.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.