• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.331-341
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• 2014

Internet of Thing(IoT), which is recently talked about with the development of information and communication technology, provides big data to all nodes such as companies and homes, means of transportation etc. by connecting all things with all people through the integrated global network and connecting all actual aspects of economic and social life with Internet of Thing through sensor and software. Defining Internet of Thing, it plays the role of a connector of providing various information required for the decision-making of companies in the cloud computing environment for the Insight usage by collecting and storing Raw Data of the production site through the sensor network and extracting big data in which data is accumulated and Insight through this. In addition, as the industry showing the largest linkage with other root industries among root industries, the mold industry is the core technology for controlling the quality and performance of the final product and realizing the commercialization of new industry such as new growth power industry etc. Recently, awareness on the mold industry is changing from the structure of being labor-intensive, relying on the experience of production workers and repeating modification without the concept of cost to technology-intensive, digitization, high intellectualization due to technology combination according to IT convergence. This study, therefore, is to provide a golden opportunity to increase the direct and indirect expected effects in poor management activities of small businesses by actually implementing and managing the entire process of mold life cycle to information system from mold planning to mass production and preservation by building SME(small and medium-sized enterprises)-type mold life cycle management information system in the cloud computing environment and applying it to the production site.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.747-751
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• 2017

The log has variable informations that are important and necessary to manage a network when accessed to network servers. These informations are used to reduce a cost and efficient manage a network through the meaningful prediction information extraction from the amount of user access. And, the network manager can instantly monitor the status of CPU, memory, disk usage ratio on network using the SNMP. In this paper, firstly, we have accumulated and analysed the 6 network logs and extracted the informations that used to predict the amount of user access. And then, we experimented the prediction simulation with the time series analysis such as moving average method and exponential smoothing. Secondly, we have simulated the usage ration of CPU, memory, and disk using Xian SNMP simulator and extracted the OID for the time series prediction of CPU, memory, and disk usage ration. And then, we presented the visual result of the variable experiments through the Excel and R programming language.

• International Commerce and Information Review
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• v.14 no.2
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• pp.201-225
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• 2012

Developing new technologies and launching new products require a huge sum of money for Research and Development, and there is also market uncertainty. Comparing to advanced countries' companies, Korea's exporting companies have less investment cost in size for R&D and insufficient technology assets accumulated. Therefore, through the open innovation, they should use external technology and enhance the efficiency of the relatively little R&D investment. This paper draws the factors influencing the innovations of Korea's exporting companies, and then it analyses how each innovation influences export performance. First, innovations are devided into two; closed and open innovation. Multiple regression analysis has been done, considering influence factors of innovation such as company's characteristics factors, research's characteristics factors and products characteristics factors to be independent variables, and export performance to be a dependent variable. It shows that firm size and new products launching period have positive effects on each innovation, but research capability and research performance have positive effects only on closed innovation. And open innovation has positive effects on export performance, but closed innovation doesn't have.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.42-47
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• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1689-1690
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• 2006

This study is for implementation of PC based Motor fault diagnosis system. By using harmonics and current signals of the motor, this system diagnoses the motor condition by accumulated harmonic contribution rate. In this proposed system that was composed of 5 parts. A sensor, connection box, evaluation board, device server, and main computer are those. There were two types of sensor, one was harmonic sensor the other was current sensors. The signal was acquired by sensor, and transferred to evaluation board. Second one is connection box. Because the output type of sensor and input type of evaluation board is different, connection box was necessary. Third one was evaluation board. The signal from the sensor was converted to digital signal in evaluation board. And this signal was transferred to device server. Fourth one was device server Device server transferred the data from evaluation board to main computer. And the last one was other parts controlled by main computer. In main computer, there were communication and diagnosis algorithms. The result was derived by main computer. In the result, there were 12 categories and 5 levels of motor conditions. The proposed system had some advantages comparing with stand alone type commercial motor fault diagnosis system. The first, by using remote access it was easier to get the conditions of motor. The second, there was no need to handle the sensors when users measured the motor signals. By this property, no one was necessary at motor location site. The third, this system was less restricted by times and places than commercial stand alone type diagnosis system. Therefore users can operate this system only using the main computer. Once the sensors are installed at the motor, users doesn't need to move to check up the condition of motors. Moreover, if there is ethernet hub, many motors can be not only diagnosed at once but also decreased its cost.

• Journal of Crop Science and Biotechnology
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• v.10 no.2
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• pp.57-63
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• 2007

Due to the strong influence of nitrogen(N) on plant productivity, a vast amount of N fertilizers is used to maximize crop yield. Over-use of N fertilizers leads to severe pollution of the environment, especially the aquatic ecosystem, as well as reducing farmer's income. Growing of N-efficient cultivars is an important prerequisite for integrated nutrient management strategies in both low- and high-input agriculture. Taking maize as a sample crop, this paper reviews the response of plants to low N stress, the physiological processes which may control N-use efficiency in low-N input conditions, and the genetic and molecular biological aspects of N-use efficiency. Since the harvest index(HI) of modern cultivars is quite high, further improvement of these cultivars to adapt to low N soils should aim to increase their capacity to accumulate N at low N levels. To achieve this goal, establishment and maintenance of a large root system during the growth period may be essential. To reduce the cost of N and carbon for root growth, a strong response of lateral root growth to nitrate-rich patches may be desired. Furthermore, a large proportion of N accumulated in roots at early growth stages should be remobilized for grain growth in the late filling stage to increase N-utilization efficiency. Some QTLs and genes related to maize yield as well as root traits have been identified. However, their significance in improving maize NUE at low N inputs in the field need to be elucidated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1907-1917
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• 2010

It is much needed research for ocean scientists to implement a digitizing system that effectively extracts and digitializes sea level records accumulated from the past. The main difficulty of such a system is huge anount of data to be processed. In this paper, we implement a digitizing system to handle such mass-data of sea level records. This system consists of a pre-process step, a digitizing step and a post-process step. In pre-process step, the system adjusts skewnesses of scanned images and normalizes the size of images automatically. Then, it extracts a graph area from images and thins the graph area in digitizing step. Finally, in the post-process step, the system tests the reliability. It is cost-effective and labour-reducing software for scientists not wasting their time to such boring manual digitizing jobs.

• Journal of Information Science Theory and Practice
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• v.7 no.4
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.2
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• pp.101-108
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• 2005

Inertial Navigation System has been used extensively to determine the position, velocity and attitude of the body. An INS is very expensive, however, heavy, power intensive, requires long setting times and the accuracy of the system is degraded as time passed due to the accumulated error. Global Positioning System(GPS) receivers can compensate for the Inertial Navigation System with the ability to provide both absolute position and attitude. This study describes a method to improve both the accuracy of a body positioning and the precision of an attitude determination using GPS antenna array. Existing attitude determination methods using low-cost GPS receivers focused on the relative vectors between the master and the slave antennas. Then the positioning of the master antenna is determined in meter-level because the single point positioning with pseudorange measurements is used. To obtain a better positioning accuracy of the body in this research, a wireless internet is used as an alternative data link for the real-time differential corrections and dual-frequency GPS receivers which is expected to be inexpensive was used. The numerical results show that this system has the centimeter level accuracy in positioning and the degree level accuracy in attitude.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.103-110
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• 2021

Elastomeric bearings composed of flexible rubber materials and steel reinforcement plates are widely used for seismic retrofit of bridges due to their excellent vertical stiffness and flexible lateral stiffness. Especially, it has the advantages of simple construction and low cost. Chloroprene rubber, a type of rubber material, has greater resistance to aging than natural rubber, but its performance is also degraded due to various deterioration factors. Although these aging characteristics are not reflected in the seismic design standards and seismic performance evaluation guidelines, it is reasonable to reflect this when related studies are accumulated. For chloroprene rubber, accelerated heat aging test was performed with variables of heating temperatures and exposure time to analyze shear characteristics. As aging progresses the maximum shear stress and shear strain decrease. Also, the shear stiffness is greatly increased at the same shear strain.