• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Korean Institute of Interior Design Journal
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• v.23 no.3
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• pp.153-163
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• 2014

The eco-friendly elements are important for new construction and renovation and redevelopment of the buildings. The green buildings are related with minimizing environmental pollution and how to live with nature throughout the entire process of demolishing and building. The purpose of this paper is to study on eco-friendly business buildings in the trend of mandatory green building certification system. The analysis of this paper is comparative studies on practices at eleven domestic eco-friendly business buildings through site survey on design framework of green buildings. The design framework of eleven this buildings is six kinds of skills on technical, renewable, ecological, cultural, healthy, social. The eleven this buildings in the new & renewable energy and IT technology of technical sector are satisfied with the framework. But, domestic most advanced eco-friendly business buildings are placed difference between almost the two times on the lower buildings at comparative evaluation. The three of this buildings are gratified rainwater harvesting and waste recycling systems for renewable and recycle. The buildings have an excellent aspects of technology and ecology. The benefits of this buildings are related with future compulsory zero energy house to take technical advantage of renewable energy. However, the buildings reflecting the regional culture types is insufficient. The buildings should be supplemented as follows. This buildings are need to have the social enhancement programs and design for convenient space of community residents, through health and comfort of on workplace. Moreover, this buildings have features of coexisting with human beings and nature friendly with the aim of realizing the sustainable development. The social enhancement programs through regional cultural aspects with ecology are related with individual and community livings in harmony, non-hierarchical communal lifes. The development of the cultural aspects provide for consensus about the local community and creating sustainable communities. Thus, The buildings are to have energy saving, pleasant and healthy living environment and interactive individual and community livings in harmony.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.50-56
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• 2018

The Internet of Things (IoT) and Visible Light Communication (VLC) is opening up new services in lighting industry by integrating sensory network features in addition to standard illumination functionality. In this progressive developments, the next generation lighting devices for smart homes are capable to sense the environmental conditions and transfer the captured data through lights to gateway controller to access remotely. The smart home environmental sensor information's are few kbps only so VLC systems need to built-in with low rate light connectivity to transfer data to the gateway. To provide error free communication, the quality of a received light signal is important to be considered when designing an VLC receiver. Therefore, this paper proposes the design of robust low rate IoL receiver design using NCP302 voltage detector for micro controller to adapt the IoT/IoL front end module for system integration. To evaluate the proposed system performance, the Arduino UNO based IoT/IoL controller designed with lighting, sensors and lights connectivity interfaces. The experimental result shows that the robust interference rejection is feasible on proposed VOL receiver and possible to have an error-free communication up to 10 kbps at a low SNR using OOK modulation.

• Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.103-115
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• 2014

The engineering design process is a creative process, and the designers must repeatedly apply Undo/Redo operations to modify CAD models to explore new solutions. Undo/Redo has become one of most important functions in interactive graphics and CAD systems. Undo/Redo in a collaborative CAD system is also very helpful for collaborative awareness among a group of cooperative designers to eliminate misunderstanding and to recover from design error. However, Undo/Redo in a collaborative CAD system is much more complicated. This is because a single erroneous operation is propagated to other remote sites, and operations are interleaved at different sites. This paper presents a multi-user selective Undo/Redo approach in full distributed collaborative CAD systems. We use site ID and State Vectors to locate the Undo/Redo target at each site. By analyzing the composition of the complex CAD model, a tree-like structure called Feature Combination Hierarchy is presented to describe the decomposition of a CAD model. Based on this structure, the dependency relationship among features is clarified. B-Rep re-evaluation is simplified with the assistance of the Feature Combination Hierarchy. It can be proven that the proposed Undo/Redo approach satisfies the intention preservation and consistency maintenance correctness criteria for collaborative systems.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.313-319
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• 2017

In this paper, we present a design technique that miniaturises the DC-DC converter, a key component in the electric vehicle system, using the advanced material (Ga-N HEMT) in the LLC resonant converter and freely changes the resonant frequency. This design is also proposed to improve the efficiency and temperature characteristics by adding SR Topology in the secondary side output during the operation of power supply. In this experiment, as a consequence of the constructed circuit with the operation of high switching frequency of 200 kHz, the size of LLC and PFC was able to be minimised by 40[%]. Thus, the characteristics of operating temperature demonstrated $60-65^{\circ}C$ without a heat sink, when the temperature was measured at 250W (12V/20A). The features were all due to the advantages of the change of switching frequency, switching circuits implementation, and the maximisation of switching frequency. Based on these design results, we would like to implement more than 1 [kW].

• Korean Institute of Interior Design Journal
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• v.15 no.3 s.56
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• pp.83-91
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• 2006

Our human society is rapidly changing into the world of advanced visual information with the development of image industry, the advent of satellite and terrestrial DMB, and the opening of Ubiquitous era. Like this, we are living in the space of overflowing media contents. Jean Baudrillad anticipated that the influential power of image would dominate our reality in 'Simulation'. Noticing the indication of our time, which is organized by various information media including the mass media, Baudrillad predicted that the 21st century would be an era of symbol and image due to the development of television, computer, and internet. This paper attempts to find the physical and conceptual peculiarities of the space change according to the use of display, by analyzing SF films, where future daily life is a major setting, under the judgement that the exploration of space change is significant. Through findings, it tries to lead the visual expansion, which recognizes display as space itself rather than object of space and changes unmoving space into moving space, and suggest the future space design by using digital space. It suggests case studies, which use digital display in the real space, as a study method and it examines the features, influences, and roles of digital display through investigating literatures and cases. In addition, it attempts to find a correlation of digital display and space by selecting films, which can give the affluent resources of analysis on the digital display among SF films. Therefore, it will come to a conclusion that space change should be dealt with in the space design.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.95-100
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• 2011

Due to rapid growth and development of telecommunication information technology, interest has been amplified regarding ubiquitous network computing and user-oriented service. Also, the rapid development of related technologies has been a big spotlight. Smart phone, with features such as a PC with advanced features is a mobile phone. According to environment and infrastructure development, a variety of mobile-based application software to provide various kinds of information and services has been released. However, most of them are provider-driven information systems and aim to provide large amounts of information simply to an unspecified number of users. Therefore, customized or personalized provision of information and service explained earlier for individual users has been hardly come true. According to background and need, this study wants to design and implement recommendations system for personalization and customization in mobile environments. To acquire more accurate recommendation results, recommendation system shall be composed using the Hybrid Filtering. Effective information recommendation according to user's situation by using user's context-information of purpose and location that are available in mobile devices before running the filtering of the information to improve the quality of recommendations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.989-1002
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• 2018

Grouting for the rock joint is to strengthen the rock strata by infiltrating cement grout materials into the rock joints. Grouting is one of a field of study which is difficult to develop deterministic and quantitative design approach because of multiphase behaviors of grout materials and 3 dimensional features of rock joints. Therefore, GIN (Grouting Intensity Number) can be a good index with appropriate monitoring of pressure and volume of grout. In this paper, we investigate the effects of joint roughness (JRC) and rheology of cement material during the infiltration of cement grout material into rock joint through CFD (computational fluid dynamics) analyses. With rough joint surface and increase of WC ratio, the frictional resistance during the grouting increases. The results have been summarized with polynomial correlations.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.238-245
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• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.