• Knowledge Management Research
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• v.14 no.5
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• pp.1-14
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• 2013

This paper is aimed at investigating the factors to grow the new technology based firm(NTBF), K-MAC. NTBFs need an environment in which novelty is encouraged, employees find work meaningful and controllable, learning is incorporated into work, ideas and process improvements are implemented and a balanced focus of the internal and external to the company is fostered. With collaboration between industry and academia, Lynda Aiman-Smith made an instrument of VIQ(Value Innovation Quotient), which is consist of 9 factors, 33 items. VIQ Results can help the company to develop a better understanding of the organization's culture, and its formal subgroups. That is to identify subcultures in the organization, to diagnose potential problems or inhibitors of innovation, to identify organizational strengths for innovation and set a quantitative baseline. Using the VIQ,K-MAC analysed the subculture of innovation potential capability. K-MAC organized the COP(community of practice) with the young employees' participation and try to solve the real problem in the working place. This paper explained the diverse growing trajectory through the TPM concept and suggest for the future strategy.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.238-245
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• 2013

Gesture recognition has been widely one of the research areas for natural user interface. This paper presents a novel gesture recognition method using tree classification and multiclass SVM(Support Vector Machine). In the learning step, 3D trajectory of human gesture obtained by a Kinect sensor is classified into the tree nodes according to their distributions. The gestures are resampled and we obtain the histogram of the chain code from the normalized data. Then multiclass SVM is applied to the classified gestures in the node. The input gesture classified using the constructed tree is recognized with multiclass SVM.

• Human Ecology Research
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• v.56 no.2
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• pp.157-165
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• 2018

Using data from the Panel Study on Korean Children, this study investigated whether children with high levels of problem behaviors adjusted more poorly on the $1^{st}-grade$ than children with low levels of problem behaviors, and whether there was evidence of intra-individual stability in behavior problems over time. Data were analyzed by use of the Latent Growth Model and group differences analyses. Three findings were noteworthy. First, there was evidence of intra-individual and inter-individual variability in behavior problems between poor- and non-poor household children. Second, children with higher initial levels of internalizing and externalizing behaviors at 4 years had lower school readiness scores at 6 years. Finally, children with lower levels of school readiness at 6 years had lower school adjustment scores in $1^{st}$ grade. The results discuss implications for future research and policies for preschool children. With mediating effect of school readiness, developmental trajectories of child's problem behavior have been found to be predictors of delayed achievements in school. The results show that intervention programs are necessary for children with high levels of problem behavior. This study also showed that children who experienced poverty at home could have more difficulties in school readiness and school adjustment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.11
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• pp.1186-1193
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• 1991

This paper proposed a trajectory controlmethod for a robot manipulator by using neural networks. The total torque for a manipulator is a sum of the linear feedback controller torque and the neural network feedfoward controller torque. The proposed neural network is a multilayer neural network with time delay elements, and learns the inverse dynamics of manipulator by means of PD(propotional denvative)controller error torque. The error backpropagation (BP) learning neural network controller does not directly require manipulator dynamics information. Instead, it learns the information by training and stores the information and connection weights. The control effects of the proposed system are verified by computer simulation.

• Fashion & Textile Research Journal
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• v.25 no.4
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• pp.429-438
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• 2023

In the 21st century fashion industry, the rise of digital environments has transformed it into a dynamic medium, expanding the horizons of media utilization. Consequently, digital fashion film has emerged as a pivotal tool for fashion communication. Functioning as a visual expression medium, fashion film animates fashion concepts into immersive moving images. Proficiency in digital fashion communication has become imperative, considering the attributes of fashion media. Notably, the role of creative directors in ensuring coherent communication across diverse fashion media platforms has gained prominence, underscoring the need for systematic fashion education to nurture specialized talent. This study, therefore, devised a comprehensive curriculum amalgamating fashion communication and practical digital media skills, implemented within fashion major courses. Through this approach, students gained experimental media proficiency and explored innovative approaches to crafting fashion films that eloquently convey fashion narratives. The participants were exposed to the entire spectrum of fashion media production, encompassing digital storytelling, fashion film conceptualization, filming techniques, meticulous editing, and adept utilization of special effects technology. The study's pedagogical strategy, characterized by a focused learning trajectory, garnered significant acclaim. In essence, this study holds significance by formulating a curriculum that nurtures the imaginative and pragmatic aptitudes of fashion majors, immersing them in the dynamic realm of rapidly evolving digital fashion films and their integration with fashion content.

• Structural Engineering and Mechanics
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• v.89 no.2
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• pp.213-223
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• 2024

This paper proposes a composite design of fuzzy adaptive control scheme based on TMD RC structural system and the gain of two-dimensional fuzzy control is controlled by parameters. Monitoring and learning in LMI then produces performance indicators with a weighting matrix as a function of cost. It allows to control the trade-off between the two efficiencies by adjusting the appropriate weighting matrix. The two-dimensional Boost control model is equivalent to the LMI-constrained multi-objective optimization problem under dual performance criteria. By using the proposed intelligent control model, the fuzzy nonlinear criterion is satisfied. Therefore, the data connection can be further extended. Evaluation of controller performance the proposed controller is compared with other control techniques. This ensures good performance of the control routines used for position and trajectory control in the presence of model uncertainties and external influences. Quantitative verification of the effectiveness of monitoring and control. The purpose of this article is to ensure access to adequate, safe and affordable housing and basic services. Therefore, it is assumed that this goal will be achieved in the near future through the continuous development of artificial intelligence and control theory.

• Steel and Composite Structures
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• v.51 no.5
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• pp.473-485
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• 2024

This paper proposes a composite form of fuzzy adaptive control plan based on a robust observer. The fuzzy 2D control gains are regulated by the parameters in the LMIs. Then, control and learning performance indices with weight matrices are constructed as the cost functions, which allows the regulation of the trade-off between the two performance by setting appropriate weight matrices. The design of 2D control gains is equivalent to the LMIs-constrained multi-objective optimization problem under dual performance indices. By using this proposed smart tracking design via fuzzy nonlinear criterion, the data link can be further extended. To evaluate the performance of the controller, the proposed controller was compared with other control technologies. This ensures the execution of the control program used to track position and trajectory in the presence of great model uncertainty and external disturbances. The performance of monitoring and control is verified by quantitative analysis. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.142-148
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• 2014

A descriptor which is suitable for motion analysis by using the motion features of moving objects from the real time image sequence is proposed. To segment moving objects from the background, the background learning is performed. We extract motion trajectories of individual objects by using the sequence of the 1st order moment of moving objects. The center points of each object are managed by linked list. The descriptor includes the 1st order coordinates of moving object belong to neighbor of the pre-defined position in grid pattern, The start frame number which a moving object appeared in the scene and the end frame number which it disappeared. A video retrieval by the proposed descriptor combining global and local feature is more effective than conventional methods which adopt a single feature among global and local features.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.11a
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• pp.139-145
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• 2006

LRE(Liquid propellant Rocket Engine) is one of the important parts to control the trajectory and dynamics of rocket. The purpose of control of LRE is to control the thrust according to requiredthrust profile and control the mixture ratio of propellants fed into gas generator and combustor for constant mixture ratio. It is not easy to control thrust and mixture ratio of propellants since there are co-interferences among the components of LRE. In this study, the dynamic model of LRE was constructed and the dynamic characteristics were analyzed with control system as PID control and PID+Q-ILC(Iterative Learning Control with Quadratic Criterion) control. From the analysis, it could be observed that PID+Q-ILC control logic is more useful than standard PID control system for control of LRE.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.898-902
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• 2012

A descriptor which is suitable for motion analysis by using the motion features of moving objects from the real time image sequence is proposed. To segment moving objects from the background, the background learning is performed. We extract motion trajectories of individual objects by using the sequence of the $1^{st}$ order moment of moving objects. The center points of each object are managed by linked list. The descriptor includes the $1^{st}$ order coordinates of moving object belong to neighbor of the per-defined position in grid pattern, the start frame number which a moving object appeared in the scene and the end frame number which it disappeared. A video retrieval by the proposed descriptor combining global and local feature is more effective than conventional methods which adopt a single feature among global and local features.