• Journal of The Korean Association of Information Education
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• v.14 no.3
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• pp.385-393
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• 2010

Elementary information education is currently provided in accordance with the 2000 ICT educational guidelines. Although the focus of education has shifted from practical use to computer science since 2005, in which way academic education should be led isn't yet clear. The purpose of this study was to examine the impacts of computer science education(CS education) by an education programming tool on school children's awareness of that education. The selected students received education about unplugged, scratch and robot programming, part of the computer science curriculum, in 12 sessions. As a result, there were significant differences between the experimental and control groups in all the variables that included attitude to computer science, interest in that, satisfaction level, self-efficacy and perception of the value of CS education. The findings of the study suggested that in CS education, the improvement of thinking faculty should take precedence over practical use of what's learned, which is expected to heighten the value of that education.

• 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.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.1-10
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modify rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verify the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• Proceedings of the CALSEC Conference
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• 1999.07a
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• pp.277-299
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• 1999

Since Chrysler Motor Co. had experienced the digital development system in the beginning of 1990's, most of leading automobile companies are trying to apply a digital information system for their own business process reengineering based upon concurrent engineering system from product planning phase. This is called as virtual DMU(Digital Mock-Up) system instead of the traditional PMU(Physical Mock-Up) system. By using the virtual prototype, all of the design requirements and system specifications can be checked, changed and optimized more quickly and more efficiently. This paper consists of five chapters for the DMU information system. In the 1$^{st}$ chapter, the principle of digital design system is suggested by using four basic modules such as product design module, process design module, manufacturing system design module and central control module. The basic scheme of DMU is introduced with the benefits of application in the chapter 2. In the chapter 3, a digital design process of new car development is explained with the detailed DMU design and design review processes. In the chapter 4, the practical DMU manufacturing techniques and applications are introduced as CAD/CAM analyses, DPA(Digital Pre-Assembly)reviews for development, production, operation and maintenance phases, digital tolerance analyses and digital factory analyses for assembling line simulation, automated robot welding processes, production jig ＆ fixtures and painting process simulation. Finally, the activities of digital design support; CAS-styling, CAE-engineering and CAT-testing are summarized for design optimization in the chapter 5. As today's automobile manufactures and related business organizations are struggling to compete in the global marketplace, they are concentrating on efficient use of DMU information system to reduce the new car development cost, to have shorten the delivery schedule and to improve product design quality. To meet the demand of those automobile industries on digital information systems, the CALS(Computer aided Acquisition and Logistics Support) and EC(Electronic Commerce)initiative has been focused as a dominant philosophy in defense ＆ commercial industries, specially automobile industries.s.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.197-204
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• 2007

Nowadays, the construction industry is suffering from the decrease of labor productivity caused by the lack of skilled workers and the aging labor forces. The hazardous work conditions and safety problems still exist at the construction sites. The earthwork operation is not the exception. The number of skilled earthwork equipment operators has been rapidly reduced and the equipment needs to be operated in dangerous / hazardous work sites. Thus, through the development of intelligent excavating system, Intelligent Excavating System(I.E.S) research team tries to enhance the safety of work environment, productivity, quality, and payability of the earthwork operation. It is also expected that this research contributes to the development of fundamental construction automation technologies and to the creation a new market sector.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.192-197
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• 2017

In this paper, image filter optimization method based on common sub-expression elimination is proposed for low-power image feature extraction hardware design. Low power and high performance object recognition hardware is essential for industrial robot which is used for factory automation. However, low area Gaussian gradient filter hardware design is required for object recognition hardware. For the hardware complexity reduction, we adopt the symmetric characteristic of the filter coefficients using the transposed form FIR filter hardware architecture. The proposed hardware architecture can be implemented without degradation of the edge detection data quality since the proposed hardware is implemented with original Gaussian gradient filtering algorithm. The expremental result shows the 50% of multiplier savings compared with previous work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1060-1065
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• 2011

In this paper, the proposed method is recognized the hands using color information with input image of the camera. It controls the mouse pointer using recognized hands. In addition, specific commands with the mouse pointer is designed to perform. Most users felt uncomfortable since existing interaction multimedia systems depend on a particular external input devices such as pens and mouse However, the proposed method is to compensate for these shortcomings by hand without the external input devices. In experimental methods, hand areas and backgrounds are separated using color information obtaining image from camera. And coordinates of the mouse pointer is determined using coordinates of the center of a separate hand. The mouse pointer is located in pre-filled area using these coordinates, and the robot will move and execute with the command. In experimental results, the recognition of the proposed method is more accurate but is still sensitive to the change of color of light.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7773-7780
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• 2015

Analysis of existing kettle and its heating system has been the topic for localization technology development. Test pieces are made, polished and etched for existing kettle analysis. Surface of test pieces is observed using SEM, the kettle is verified to be made by deep drawing process from Ferrite-Perlite material. The kettle is also identified to be plated $16{\sim}49{\mu}m$ of thickness with Nickel(16%). Also heat transfer characteristics based on hot wire arrangement is investigated and optimal hot wire system is developed. Developed control system detects overheating and stops the whole system on the long operating time. Developed kettle takes the performance evaluation test for volume expansion and satisfied for standard 'KS G3602'.

• Agribusiness and Information Management
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• v.6 no.1
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• pp.30-36
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• 2014

This study was conducted to determine the major patent and analyze the patent trend of unmanned and automated agricultural production for the open field operation. As a result of conducting a search for patent applications related to these technologies, 1,080 valid patents were selected by evaluating the relevance of the patents and removing noise patents. As a result of the country-based analysis using the selected valid patents, it was found out that the largest number of patent applications were filed in the United States with 541 cases, followed by Japan with 326 cases, the European Union with 128 cases, and Korea with 85 cases. Upon classifying the valid patents into core technology, the path generation and tracking technology accounts for 33% with 353 cases; the implementing control with environmental condition technology accounts for 22% with 236 cases; the robot design technology accounts for 21% with 228 cases; the plant and environment sensing technology accounts for 19% with 206 cases; the yield and quality monitoring technology accounts for 5% with 58 cases. Finally, 10 core patents were selected by performing a patent index evaluation. The United States registered all of the 10 core patents. The results showed that Korea falls behind in the open field-related unmanned and automated agricultural production, compared to other developed agricultural countries.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.364-371
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• 2016

We developed a prediction model of assistance force for the opening/closing of an automobile door depending on the condition of the parking ground. The candidates of the learning models for the operating assistance force were compared to determine the proper force according to the slope and user's force, etc. The reduced experimental model was developed to obtain learning data for the estimation model. The learning algorithm was composed to predict the assistance force to incorporate real assistance force data. Among these algorithms, an Artificial Neural Network (ANN) and Support Vector Machine(SVM) were applied and the adaptability was compared between these models. The SVM provided more adaptability for the learning process of the door assistance force prediction. This paper proposes a system for determining the assistance force to control a door motor to compensate for the deviation of required door force in the slope condition, as needed in the plane condition.