• The Journal of Economics, Marketing and Management
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• v.9 no.2
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• pp.11-20
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• 2021

Purpose: The importance of creativity has been emphasized in the transition from industrial society to knowledge-based society. Recently, design thinking has attracted great attention as one of the ways to increase the creativity of the organization. From the perspective of solving urban problems through collaboration between technology and citizens, the active participation of citizens is indispensable for realizing smart cities. Research design, data and methodology: From the perspective of solving urban problems through collaboration between technology and citizens, the active participation of citizens is indispensable for realizing smart cities. Results: Therefore, the purpose of this research was to design a citizen-participation type system and contents using a specific space to realize a smart city. This system utilizes the concept of space as a tool to promote innovation activities with the participation of citizens and makes it easy for users of space to participate based on urban problems derived from living labs and the internal structure and user flow line have been designed. Conclusions: It was been also used voice recognition, artificial intelligence, the Internet of Things, and big data as important technologies for experiencing smart cities. The system and content were designed with an emphasis on allowing citizens to directly recognize and experience smart city technology, especially through space-based information visualization and multi-faceted stimulus elements.

• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.476-482
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• 2020

In this paper, we propose a block-based modularity architecture design method for distributed machine learning. The proposed architecture is a block-type module structure with various machine learning algorithms. It allows free expansion between block-type modules and allows multiple machine learning algorithms to be organically interlocked according to the situation. The architecture enables open data communication using the metadata query protocol. Also, the architecture makes it easy to implement an application service combining various edge computing devices by designing a communication method suitable for surrounding applications. To confirm the interlocking between the proposed block-type modules, we implemented a hardware-based modularity application system.

• Journal of Mechanical Science and Technology
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• v.15 no.8
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• pp.1108-1118
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• 2001

The purpose of this study is to establish a CAD (Computer Aided Design) system for research and development(R&D) of a new product. In the R&D process of a new product, the design objects are frequently redesigned based on the experimental results obtained with prototypes. The CAD/CAE systems (which is based on computer simulation of physical phenomena) are effective in reducing the number of useless prototypes of a new product. These kinds of conventional CAD/CAE systems do not provide a function to reflect the experimental results to the redesign process, however. This paper proposes a methodology to establish the CAD system, which possesses the engineering model of a designed object in the model database, and refines the model on the basis of experimental results of prototype. The blackboard inference model has been applied to infer model refinement and redesign counterplan by using insufficient knowledge of R&D process of new products.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1440-1445
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• 1990

The system with softfware packages for control system design unifying and encompassing rule based control and conventional control based on numerical models were developed. Users who are not familiar with control theory, numerical computing, and artificial intelligence (AI) can perform system analysis, control design and development of AI control system without difficulty.

• Korean Institute of Interior Design Journal
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• no.37
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• pp.136-143
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• 2003

Users' demands on the space are changing in variety. These demands include reasonable space and form, harmonious composition with surroundings and esthetic satisfaction that could be brought by personal tastes and preferences. In addition, models that are introduced from designing process and from various forms tend to lack objective decision making standard. Accordingly it is difficult to find a clear alternative plan and process. In an effort to solve these problems, the objects of this study are; to propose an analysis model of image and space by using image process techniques that are on study in the field of artificial intelligence based on acquisition of digital image and to verify the application possibilities of such analysis model, 'Isovist' on quantitative analysis. The model can be applied with variable analysis model, as digital image process and other analysis model such as 'Isovist' It is possible that further study can complement problems from this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.7-12
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• 2013

This paper proposed the optimal algorithm of grinding system and the method to realize it. The optimal function was proposed in order to design the optimal grinding process. DE(Differential Evolution) algorithm was used to obtain the selective optimal function. The realization of algorithm was implemented by LabView software used widely at industrial field and the proposed algorithm was verified for through computer simulation. The result of the proposed algorithm can be used for the guide line of the grinding process.

• Transactions on Electrical and Electronic Materials
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• v.18 no.3
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• pp.129-135
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• 2017

This paper introduces a design and a simulation of a hybrid active power filter (HAPF) for harmonics reduction given an ideal supply source. The synchronous reference frame method has been used here to identify the reference currents. The proposed HAPF uses a new artificial- intelligence technique called Particle Swarm Optimization (PSO) for tuning the parameters of a proportional and integral controller called PI-PSO. The PI-PSO controller is used to archive optimality for the DC-link voltage of the HAPF-inverter. The hysteresis non-linear current control method is used in this approach to compare the extracted reference and the actual currents in order to generate the pulse gate required for the HAPF. Results obtained by simulations with Matlab/Simuling show that the proposed approach is very flexible and effective for eliminating harmonic currents generated by the non-linear load with the HAPF based PSO tuning.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.131-138
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• 2022

Soft sensors are used to anticipate complicated model parameters using data from classifiers that are comparatively easy to gather. The goal of this study is to use artificial intelligence techniques to design and build soft sensors. The combination of a Long Short-Term Memory (LSTM) network and Grey Wolf Optimization (GWO) is used to create a unique soft sensor. LSTM is developed to tackle linear model with strong nonlinearity and unpredictability of manufacturing applications in the learning approach. GWO is used to accomplish input optimization technique for LSTM in order to reduce the model's inappropriate complication. The newly designed soft sensor originally brought LSTM's superior dynamic modeling with GWO's exact variable selection. The performance of our proposal is demonstrated using simulations on real-world datasets.

• Design & Manufacturing
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• v.17 no.1
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• pp.27-32
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• 2023

In this paper, we intend to predict the mass of the spiral using CAE and machine learning. First, We generated 125 data for the experiment through a complete factor design of 3 factors and 5 levels. Next, the data were derived by performing a molding analysis through CAE, and the machine learning process was performed using a machine learning tool. To select the optimal model among the models learned using the learning data, accuracy was evaluated using RMSE. The evaluation results confirmed that the Support Vector Machine had a good predictive performance. To evaluate the predictive performance of the predictive model, We randomly generated 10 non-overlapping data within the existing injection molding condition level. We compared the CAE and support vector machine results by applying random data. As a result, good performance was confirmed with a MAPE value of 0.48%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.719-722
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• 2021

최근 인공지능의 새로운 기술들이 하루가 다르게 발전하고 있다. 이에 본 연구에서는 인공지능 교육과 글쓰기 교육을 연계하여 초등학생들의 어휘력 향상을 위한 수업을 설계하고자 한다. 그 방법으로는 본 수업에 앞서 어휘 10문제를 테스트하여 실험에 참가하기 전의 어휘력을 점검한다. 그 후 머신러닝 포키즈를 이용하여 여러 감정에 해당되는 단어들을 다양하게 훈련하도록 하였고, 그 후 관련된 어휘 10문제를 다시 테스트 하였다. 실험 결과 실험에 참가하기 전에는 100점 만점에 58.8점으로 나왔으나 훈련 후의 결과는 평균 68점으로 모든 학생의 성적이 좋아지는 결과를 얻을 수 있었다. 어휘력 문항수가 적은 점과 10명의 실험참가자로 일반화할 수 없는 한계가 있다. 향후 초등교재 한권을 선정하여 어휘를 모두 분석한 후 가장 많이 등장하는 어휘를 골라내어 테스트하여 좀 더 통계적으로 의미 있는 분석을 하고자 한다.