• Journal of Drive and Control
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• v.12 no.2
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• pp.27-33
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• 2015

Excavators are versatile earthmoving equipment that are used in civil engineering, hydraulic engineering, grading and landscaping, pipeline construction and mining. Effective operator training is essential to ensure safe and efficient operating of the machine. The virtual reality excavator based on simulation using conventional large size monitors is limited by the inability to provide a realistic real world training experience. We proposed a flexible observation method with a head tracking system to improve user feeling and sensation when operating a virtual reality excavator. First, an excavation simulator is designed by combining an excavator SimMechanics model and the virtual world. Second, a head mounted display (HMD) device is presented to replace the cumbersome large screens. Moreover, an Inertial Measurement Unit (IMU) sensor is mounted to the HMD for tracking the movement of the operator's head. These signals consequently change the virtual viewpoint of the virtual reality excavator. Simulation results were used to analyze the performance of the proposed system.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.2
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• pp.57-72
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• 2018

In order to extract meaningful information from the excellent farming settlement cases of young farmers published by KNCAF, we studied the key words with text mining and created a word cloud for visualization. First, in the text mining results for the entire sample, the words 'CEO', 'corporate executive', 'think', 'self', 'start', 'mind', and 'effort' are the words with high frequency among the top 50 core words. Their ability to think, judge and push ahead with themselves is a result of showing that they have ability of to be managers or managers. And it is a expression of how they manages to achieve their dream without giving up their dream. The high frequency of words such as "father" and "parent" is due to the high ratio of parents' cooperation and succession. Also 'KNCAF', 'university', 'graduation' and 'study' are the results of their high educational awareness, and 'organic farming' and 'eco-friendly' are the result of the interest in eco-friendly agriculture. In addition, words related to the 6th industry such as 'sales' and 'experience' represent their efforts to revitalize farming and fishing villages. Meanwhile, 'internet', 'blog', 'online', 'SNS', 'ICT', 'composite' and 'smart' were not included in the top 50. However, the fact that these words were extracted without omission shows that young farmers are increasingly interested in the scientificization and high-tech of agriculture and fisheries Next, as a result of grouping the top 50 key words by crop, the words 'facilities' in livestock, vegetables and aquatic crops, the words 'equipment' and 'machine' in food crops were extracted as main words. 'Eco-friendly' and 'organic' appeared in vegetable crops and food crops, and 'organic' appeared in fruit crops. The 'worm' of eco-friendly farming method appeared in the food crops, and the 'certification', which means excellent agricultural and marine products, appeared only in the fishery crops. 'Production', which is related to '6th industry', appeared in all crops, 'processing' and 'distribution' appeared in the fruit crops, and 'experience' appeared in the vegetable crops, food crops and fruit crops. To visualize the extracted words by text mining, we created a word cloud with the entire samples and each crop sample. As a result, we were able to judge the meaning of excellent practices, which are unstructured text, by character size.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.9 no.3
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• pp.102-106
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• 2010

Recently process industries from oil and gas procedures and mining companies to manufactures of chemicals, foods, and beverages has been exploring the USN (Ubiquitous Sensor Networks) technology to improve safety of production processes. However, to apply the USN technology in the large-scale plant industry, reliability and security issues are not fully addressed yet, and the absence of the industrial sensor networking standard causes a compatibility problem with legacy equipment and systems. Although this situation, process industry such as energy plants are looking for the secure wireless plant solution to provide detailed, accurate safety monitoring from previously hard-reach, unaccordable area. In this paper, SPSF (Smart Plant Safety Framework based on Reliable-Secure USN) is suggested to fulfill the requirements of high-risk industrial environments for highly secure, reliable data collection and plant monitoring that is resistant to interference. The SPSF consists of three main layers: 1) Smart Safety Sensing Layer, 2) Smart Safety Network Layers, 3) Plant Network System Layer.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.417-418
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• 2019

4차 산업혁명 시대의 도래로, 제조업 기반의 기업들은 단순히 제품을 가공 또는 조립하여 제품을 판매하는 과거의 공정 행태를 지식화하여 부가가치를 높이는 지능형 생산 체계를 도모하고 있다. 제품을 생산하는데 있어서 현대의 제조기업들은 대부분 관련 장비 또는 설비들에 대한 의존도가 높다. 본 논문에서는 이와 같은 제조 장비를 생산하고 사후관리까지 하는 일련의 데이터들을 수집하고 분석하여 장비의 고장예측부터 신규장비의 기획까지 활용할 수 있는 장비 이력관리 시스템을 제안한다.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.763-772
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• 2021

Drilling Mud Treatment Systems are widely used for Oil Gas drilling mud circulation, horizontal directional drilling mud recycling, geothermal drilling, mining, coal exploration drilling, water well drilling. Degasser is a device used in drilling to remove gasses from drilling fluid which could otherwise form bubbles. For small amounts of entrained gas in a drilling fluid, the degasser can play a major role of removing small bubbles that a liquid film has enveloped and entrapped. As with the desander, its purpose is to remove unwanted solids from the mud system. The smaller cones allow the desilter to efficiently remove smaller diameter drill solids. In this study, a simulation study is conducted on the degasser of the facility in the Mud Treatment System to conduct a performance review on the gas separation in the mud.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.151-159
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• 2017

This study deals with characteristics and risk of a PM based on user survey result, road driving test and data analysis of PM accident. Text mining method is applied to extract PM accident data from Big Data, which are claim data of private insurance company. Road driving test and survey on safety, convenience, noise, overtake ability, steering ability, and climbing ability of PM are performed to evaluate user's safety and convenience considering domestic road condition. As the result of claim data analysis, annual average increase rate of PM accident is 47.4% and average compensation of personal mobility is higher than that of bicycle by maximum 1.5 times. 79.8% of PM accident is self-caused accident due to unskilled driving and age-specific diagnosis rate of driver over 60 is higher than that of under 60. Diagnosis rate of over 60 at lower limb, foot, rib and spine is especially higher than that of under 60. As the result of road driving test and user survey, satisfaction level on safety and convenience of PM is evaluated as close to that of bicycle and satisfaction level of PM is increased after boarding. Overtake ability, steering ability, and climbing ability of PM are evaluated as same or better than that of bicycle but warning equipment to pedestrian or bike such as horn is required because noise level of PM during driving is too low. Finally, user survey result shows that bicycle road is suitable for PM and safety standard, advance-education and insurance are required for PM. It is suggested that drivers' license for PM can be replaced by advance-education. Results of this study can be used to prepare safety measures and legal basis for PM operation.

• Explosives and Blasting
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• v.34 no.3
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• pp.10-16
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• 2016

Recently, transition from open pit to underground mining in limestone mines is an increasing trend in Korea due to environmental issues such as noise, dust and vibrations caused by crushers and equipment. The severe damages in the surrounding rock mass of underground opening caused by explosive blasting may lead to rock fall hazards or casualties. It is well known that variables which mainly affect blast-induced rock falls in underground mining are: blast vibration level, joint orientation and distribution and shape of the cross sections of underground structures. In this study, UDEC program, which is a DEM code, is used to simulate blast vibration-induced rock fall in underground openings. Variation of joint space, joint angle and joint normal stiffness was considered to investigate the effect of joint characteristics on the blast vibration-induced rock fall in underground opening. Finally, jointed rock mass models considering blast-induced damage zone were examined to simulate the critical blast vibration value which may cause rock falls in underground opening.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.1
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• pp.1-8
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• 2018

As the key equipment in deep ocean mining, the slurry pump suffers from wear and blocking problems. In this paper, high-speed photography technique is applied to track the movement rule of single particle of the coarse particle solid-liquid two-phase flow in a double blade slurry pump. The influences of particle diameter and particle density on the pass-through and collision characteristics of particles are analyzed as well. The results show that the average of the passing pump time first decreases and then increases when the particle diameter increases. The average of the passing pump time decreases by 22.7%, when the particle density increases from $1.09g/cm^3$ to $1.75g/cm^3$. Besides, the particle density has great influence on the location where the particle hits the tongue. Most particles of $1.09g/cm^3$ hit the tongue on the left side, while collision location of particles of $1.75g/cm^3$ is mainly on the top and at the right side of the tongue. The research can provide a basis for the optimization design of slurry pump in deep ocean mining system.

• Structural Engineering and Mechanics
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• v.59 no.1
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• pp.37-57
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• 2016

Reservoir geomechanics can play an important role in hydrocarbon recovery mechanism. In $CO_2$-EOR process, reservoir geomechanics analysis is concerned with the simultaneous study of fluid flow and the mechanical response of the reservoir under $CO_2$ injection. Accurate prediction of geomechanical effects during $CO_2$ injection will assist in modeling the Carbon dioxide recovery process and making a better design of process and production equipment. This paper deals with the implementation of a program (FORTRAN 90 interface code), which was developed to couple conventional reservoir (ECLIPSE) and geomechanical (ABAQUS) simulators, using a partial coupling algorithm. A geomechanics reservoir partially coupled approach is presented that allows to iteratively take the impact of geomechanics into account in the fluid flow calculations and therefore performs a better prediction of the process. The proposed approach is illustrated on a realistic field case. The reservoir geomechanics coupled models show that in the case of lower maximum bottom hole injection pressure, the cumulative oil production is more than other scenarios. Moreover at the high injection pressures, the production rates will not change with the injection bottom hole pressure variations. Also the FEM analysis of the reservoir showed that at $CO_2$ injection pressure of 11000 Psi the plastic strain has been occurred in the some parts of the reservoir and the related stress path show a critical behavior.

• STI Policy Review
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• v.8 no.2
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• pp.75-93
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• 2017

Recently, global competition in the manufacturing sector is driving firms in the manufacturing sector to conduct product innovation projects to maintain their competitive edge. The key points of product innovation projects are 1) what the purpose of the project is and 2) what expected results in the target market can be achieved by implementing the innovation. Therefore, this study focuses on the performance of innovation projects with a business viewpoint. In this respect, this study proposes the "achievement rate" of product innovation projects as a measurement of project performance. Then, this study finds the best strategies from various innovation activities to optimize the achievement rate of product innovation projects. There are three major innovation activities for the projects, including three types of R&D activities: Internal, joint and external R&D, and five types of non-R&D activities - acquisition of machines, equipment and software, purchasing external knowledge, job education and training, market research and design. This study applies decision tree modeling, a kind of data-mining methodology, to explore effective innovation activities. This study employs the data from the 'Korean Innovation Survey (KIS) 2014: Manufacturing Sector.' The KIS 2014 gathered information about innovation activities in the manufacturing sector over three years (2011-2013). This study gives some practical implication for managing the activities. First, innovation activities that increased the achievement rate of product diversification projects included a combination of market research, new product design, and job training. Second, our results show that a combination of internal R&D, job training and training, and market research increases the project achievement most for the replacement of outdated products. Third, new market creation or extension of market share indicates that launching replacement products and continuously upgrading products are most important.