• Journal of Information Technology Applications and Management
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• v.28 no.1
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• pp.83-93
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• 2021

The purpose of this study was to develop a personalized SMT (smart monitor target) game interface for game users who enjoy airsoft sports as individual purchases of SMT have increased since the advent of the untouched era. For this study, the UX (user experience) of the game interface was designed based on previous research. In particular, the personalized game service was reinforced by adding the CP (command post) of the SMT system that performs the home function of the console game, which was intended to help the user maintain immersed in the game in the personalized space of the SMT. Major design elements for the SMT game interface included layout, color, graphics, buttons, and text, and the interface design was proceeded based on them. After composing a grid with a layout in which the tab function was applied to the interface with a vertical three-segment structure and the outer margin value secured, the military camouflage pattern and texture were applied to the colored tone to perform graphics work. Targets and thumbnails were produced as illustrations using experts to ensure the consistency of the interface, and then function buttons and texts on each page were used concisely for intuitive information delivery. The design sources organized in this way were developed using the Unity engine. In the future, we hope that game user-centered personalized interfaces will continue to develop and provide differentiated services unique to SMT systems in the airsoft gun market.

• Convergence Security Journal
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• v.23 no.4
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• pp.61-70
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• 2023

Clustering is an unsupervised learning method that involves grouping data based on features such as distance metrics, using data without known labels or ground truth values. This method has the advantage of being applicable to various types of data, including images, text, and audio, without the need for labeling. Traditional clustering techniques involve applying dimensionality reduction methods or extracting specific features to perform clustering. However, with the advancement of deep learning models, research on deep clustering techniques using techniques such as autoencoders and generative adversarial networks, which represent input data as latent vectors, has emerged. In this study, we propose a deep clustering technique based on deep learning. In this approach, we use an autoencoder to transform the input data into latent vectors, and then construct a vector space according to the cluster structure and perform k-means clustering. We conducted experiments using the MNIST and Fashion-MNIST datasets in the PyTorch machine learning library as the experimental environment. The model used is a convolutional neural network-based autoencoder model. The experimental results show an accuracy of 89.42% for MNIST and 56.64% for Fashion-MNIST when k is set to 10.

• Cartoon and Animation Studies
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• s.46
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• pp.1-22
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• 2017

The practical learning requires the new paradigm in its content of education and environment along with the rapid development of information communication technology and the expansion of digital content industry. Especially, the animation education, core area of digital content industry, has attempted to improve the content and method of education by focusing on creativity, convergence and practical education. However, education environment in the previous form of computer laboratory has not been reflected the characteristics of animation education. In the light of this, this research would suggests the effective education environment implemented animation job competency and the characteristics of animation production. Firstly, the problem of previous educational environment will be explored through looking at computer rooms of domestic Universities. The characteristics of animation production consisted of Pre-production, Main-production, Post-production and elements of animation job competency will be reviewed by focusing on three phases of production, Pre-production, Main-production and Post-production, and six particular jobs, concept art, modeling & texturing, animating, lighting, VFX and compositing. Secondly, 6 types of space adapted from space syntax, possibly explored the embedded meaning of the structure of space and environment, will be reviewed by focusing on integration, separation and interaction. Thirdly, based on the characteristics of animation production, the element of animation job competency, 6 types of space, analytical tools about animation project education will be deducted, and the case study regarding animation studio, Walt Disney studio, will be processed by focusing on its production environment and spatial composition by focusing on Pre-production, Main-production, Post-production. Fifthly, the effective spatial composition for animation project education will be explored based on the interpretation of literature reviews and case study. In regard to this, the research addresses the spatial composition reflected the characteristics of practical learning and job competency in animation education, which differs from the previous form of standardized education spaces.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.2
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• pp.406-414
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• 2002

A new approach, referred to as a successive zooming genetic algorithm (SZGA), is Proposed for identifying a global solution for continuous optimization problems. In order to improve the local fine-tuning capability of GA, we introduced a new method whereby the search space is zoomed around the design point with the best fitness per 100 generation. Furthermore, the reliability of the optimized solution is determined based on the theory of probability. To demonstrate the superiority of the proposed algorithm, a simple genetic algorithm, micro genetic algorithm, and the proposed algorithm were tested as regards for the minimization of a multiminima function as well as simple functions. The results confirmed that the proposed SZGA significantly improved the ability of the algorithm to identify a precise global minimum. As an example of structural optimization, the SZGA was applied to the optimal location of support points for weight minimization in the radial gate of a dam structure. The proposed algorithm identified a more exact optimum value than the standard genetic algorithms.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.615-618
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• 2011

Living cells generate the cell cycle or apoptosis, depending on the course will be repeated. If an error occurs during this period of life in order to maintain the cells in the peripheral cells find the error portion. These cellular functions were applied to the system to simulate the circuit. Circuit implementation of the present study was constructed the redundant structure in order to found the error quickly. Self-repairing of digital systems as an advanced form of fault-tolerance has been increasingly receiving attention according as digital systems have been more and more complex and speed-up especially for urgent systems or those working on extreme environments such as deep sea and outer space. Simulating the process of cell differentiation algorithm was confirmed by the FPGA on the counter circuit. If an error occurs on the circuit where the error was quickly locate and repair. In this paper, we propose a novel self-repair architecture for fast and robust fault-recovery that can easily apply to real, complex digital systems. These Self-Repairing Algorithms make it possible for the application digital systems to be alive even though in very noisy and extreme environments.

• Steel and Composite Structures
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• v.19 no.6
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• pp.1333-1354
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• 2015

A higher order analytical solution for static analysis of a truncated conical composite sandwich panel subjected to different loading conditions was presented in this paper which was based on a new improved higher order sandwich panel theory. Bending analysis of sandwich structures with flexible cores subjected to concentrated load, uniform distributed load on a patch, harmonic and uniform distributed loads on the top and/or bottom face sheet of the sandwich structure was also investigated. For the first time, bending analysis of truncated conical composite sandwich panels with flexible cores was performed. The governing equations were derived by principle of minimum potential energy. The first order shear deformation theory was used for the composite face sheets and for the core while assuming a polynomial description of the displacement fields. Also, the in-plane hoop stresses of the core were considered. In order to assure accuracy of the present formulations, convergence of the results was examined. Effects of types of boundary conditions, types of applied loads, conical angles and fiber angles on bending analysis of truncated conical composite sandwich panels were studied. As, there is no research on higher order bending analysis of conical sandwich panels with flexible cores, the results were validated by ABAQUS FE code. The present approach can be linked with the standard optimization programs and it can be used in the iteration process of the structural optimization. The proposed approach facilitates investigation of the effect of physical and geometrical parameters on the bending response of sandwich composite structures.

• Journal of the Microelectronics and Packaging Society
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• v.20 no.3
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• pp.59-62
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• 2013

Experimental analyses on the solder joint reliability of plastic ball grid array under harsh random vibration were presented. The chips were assembled on the daisy chained circuit boards for the test samples preparation, half of which were processed for underfill to investigate the underfill effects on the solder failures. Acceptance and qualification levels were applied for the solder failure tests, and the overall controlled RMS of the power spectrum densities of the steps were 22.7 Grms and 32.1 Grms, respectively. It was found that the samples survived without any solder failure during the tests, demonstrating the robustness of the packaging structure for potential avionics and space applications.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.20-28
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• 2015

In this paper, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame with posture variation and camera view point adaptation by employing the non-adaptive random projections that preserve the structure of the image feature space of objects. The existing online tracking algorithms update models with features from recent video frames and the numerous issues remain to be addressed despite on the improvement in tracking. The data-dependent adaptive appearance models often encounter the drift problems because the online algorithms does not get the required amount of data for online learning. So, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame.

• Proceedings of the KIEE Conference
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• 2006.07e
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• pp.19-22
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• 2006

The CMD(Condition Monitoring & Diagnosis) System is used to monitor and analyze the PD(Partial Discharge), Arc, Temperature, Pressure, Gas in Oil and so on for reliability and availability of the substation. Although this system comes into the spotlight as the forecast and management of the failure and fault, there are some problems. For example, the unified standard was not defined, and the effective management of the layed communication network does not performed, limitation of physical space, etc. To resolve above problems, this paper suggests the IEC61850 compatible eCMD system architecture for monitoring and analyzing the CMD factor in substations. The suggested eCMD system consists of CMD-LU(Condition Monitoring & Diagnosis-Local Unit), IED(Intelligent Electronic Device), and engineering centers. The IEC61850 is the international standard that defines communication networks and system in substation.

• Acta Via Serica
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• v.9 no.1
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• pp.139-160
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• 2024

This study delves into the concept of cultural hybridity, using the Great Mosque-Cathedral in Córdoba, Spain as a unique case study. This monumental site stands as a testament to the convergence of Islamic and Christian architecture and ideology, a phenomenon that is often discussed in modern contexts. However, this study takes a step further, examining cultural hybridity across historical epochs to reveal its persistent relevance in shaping social and cultural landscapes. Originally a mosque transformed into a Christian cathedral, the Great Mosque-Cathedral is a prime example of this phenomenon, reflecting continuous cultural, architectural, and ideological exchanges between the two religions. This paper meticulously analyzes how the structure's architectural elements embody these exchanges, such as its ornate mihrab and unique double-arched columns. By integrating theories of hybridity with a detailed architectural and historical analysis, the study argues that the mosque-cathedral is not merely a physical space but a dynamic medium through which cultural negotiations and adaptations are articulated. The findings underscore the complexity of cultural hybridity, challenging simplistic interpretations of cultural exchange and dominance, and highlighting the mosque-cathedral's role in ongoing debates about identity and heritage in contemporary society. This comprehensive examination contributes to academic discussions on hybridity and enhances our understanding of cultural resilience and transformation through architectural spaces.