• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.52-55
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• 2004

VMS (virtual manufacturing system) may be defined as a transparent interface/control mechanism to support human decision-making via simulation and monitoring of real operating situation through modeling of all activities in RMS (real manufacturing system). The three main layers in VMS are business process layer, manufacturing execution layer, and facility operation layer, and each layer is represented by a specific software system having its own input modeler module. The current version of these input modelers has been implemented based on its own 'local' framework, and as a result, there are no information sharing mechanism, nor a common user view among them. Proposed in this paper is a unified modeler framework covering the three VMS layers, in which the concept of PPR (product-process-resource) model is employed as a common semantics framework and a 2D graphic network model is used as a syntax framework. For this purpose, abstract class PPRObject and GraphicObject are defined and then a subclass is inherited from the abstract class for each application layer. This feature would make it easier to develop and maintain the individual software systems. For information sharing, XML is used as a common data format.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1551-1564
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• 2016

The high penetration level of inverter-based distributed generation (DG) power plants is challenging the low-voltage ride-through requirements, especially under unbalanced voltage sags. Recently, a flexible injection of both positive- (PS) and negative-sequence (NS) reactive currents has been suggested for the next generation of grid codes. This can enhance the ancillary services for voltage support at the point of common coupling (PCC). In light of this, considering distant grid faults that occur in a mainly inductive grid, this paper proposes a complete voltage support control scheme for the interface inverters of medium or high-rated DG power plants. The first contribution is the development of a reactive current reference generator combining PS and NS, with a feature to increase the PS voltage and simultaneously decrease the NS voltage, to mitigate voltage imbalance. The second contribution is the design of a voltage support control loop with two flexible PCC voltage set points, which can ensure continuous operation within the limits required in grid codes. In addition, a current saturation strategy is also considered for deep voltage sags to avoid overcurrent protection. Finally, simulation and experimental results are presented to validate the effectiveness of the proposed control scheme.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.77-84
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• 2003

Recent advances in remote sensing techniques provide the potential for monitoring soil color as well as soil moisture conditions at the spatial and temporal scales required for detailed local modeling efforts. Soil moisture as well as soil color is a key feature used in the identification and classification of soils. Soil spectral reflectance has a direct relationship with soil color, as well as to other parameters such as soil moisture, soil texture. and organic matter. We evaluate the influence of seven soil properties, soil color and soil moisture, on soil spectral reflectance. This paper presents the results obtained from the ground-truth spectral reflectance measurements in the 300-1100 nm wavelength range for various land surfaces. The results suggest that the reflectance properties of soils are related to soil color, soil texture, and soil moisture. Increasing soil moisture content generally decreases soil reflectance which leads to parallel curves of soil reflectance spectra across the entire shortwave spectrum. We discuss the relationships between the soil reflectance and the Munsell Soil Color Charts which contain standard color chips with colors specified by designations for hue, value, and chroma.

• Korean Journal of Human Ecology
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• v.17 no.4
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• pp.639-648
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• 2008

This study is to examine the meaning of death, the level of death anxiety, and the aspect of death anxiety that the aged have. For this, a quantitative research subjecting 532 of the aged living in local area, Jeollabuk-do was carried out. And among those 532 questionnaires, 10 were subjected for depth interview. The following is a summary of the result from this study. First, the meaning of death for the aged is classified into three classes as positive, neutral and negative meaning. Among these, there were far greater numbers of the aged who put neutral or negative meanings on their death than the positive one. Second, death anxiety of the aged are divided into three factors: 'annihilation anxiety', 'process anxiety', and 'afterdeath anxiety'. The factor that involves death anxiety the most was process anxiety, then afterdeath anxiety, and annihilation anxiety, in the order. Third, as a result of classifying the feature of death anxiety in the aged into the symptoms of death anxiety and the motive of recognizing death anxiety. Death anxiety is classified into the people with symptoms and those without symptoms, and those with certain symptoms are classified into the physical symptoms and the mental symptoms. The motive of recognizing death anxiety appeared when the individual is aged, experiences the death of other people, suffers physical pains, and when there is a mental loneliness.

• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.19-26
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• 2005

The basis function of wavelet transform used in this paper is constructed by using lifting scheme, which is different from general wavelet transform. Lifting scheme is a new biorthogonal wavelet con-structing method, that does not use Fourier transform for constructing its basis function. In this paper, an image compression and reconstruction method using the lifting scheme was proposed. And this method improves data visualization by supporting a partial reconstruction and a local reconstruction. Approx- imations at various resolutions allow extracting various sizes of feature from an image or signal with a small amount of original information. An approximation with small size of scaling coefficients gives a brief outline of features at fast. Image compression and edge detection techniques provide good frame- works for data management and visualization in multimedia database.

• Smart Structures and Systems
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• v.1 no.1
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• pp.63-82
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• 2005

This paper introduces a technology for robust and low maintenance cost sensor network capable to detect accelerations below a micro-g in a wide frequency bandwidth (above 1,000 Hz). Sensor networks with such performance are critical for navigation, seismology, acoustic sensing, and for the health monitoring of civil structures. The approach is based on the fabrication of an array of high sensitivity accelerometers, each utilizing Fabry-Perot cavity with wavelength-dependent reflectivity to allow embedded optical detection and serialization. The unique feature of the approach is that no local power source is required for each individual sensor. Instead one global light source is used, providing an input optical signal which propagates through an optical fiber network from sensor-to-sensor. The information from each sensor is embedded onto the transmitted light as an intrinsic wavelength division multiplexed signal. This optical "rainbow" of data is then assessed providing real-time sensing information from each sensor node in the network. This paper introduces the Fabry-Perot based accelerometer and examines its critical features, including the effects of imperfections and resolution estimates. It then presents serialization techniques for the creation of systems of arrayed sensors and examines the effects of serialization on sensor response. Finally, a fabrication process is proposed to create test structures for the critical components of the device, which are dynamically characterized.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.372-378
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• 2003

Limitations on the linear discriminant analysis (LDA) for face rerognition, such as the loss of generalization and the computational infeasibility, are addressed and illustrated for a small number of samples. The principal component analysis (PCA) followed by the LDA mapping may be an alternative that ran overcome these limitations. We also show that any schemes based on either mappings or template matching are vulnerable to image variations due to rotation, translation, facial expressions, or local illumination conditions. This entails the importance of a proper preprocessing that can compensate for such variations. A simple template matching, when combined with the geometrically correlated feature-based detection as a preprocessing, is shown to outperform mapping techniques in terms of both the accuracy and the robustness to image variations.

• The Journal of Information Systems
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• v.29 no.3
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• pp.119-144
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• 2020

Purpose Real estate usually takes charge of the highest proportion of physical properties which individual, organizations, and government hold and instability of real estate market affects the economic condition seriously for each economic subject. Consequently, practices for predicting the real estate market have attention for various reasons, such as financial investment, administrative convenience, and wealth management. Additionally, development of machine learning algorithms and computing hardware enhances the expectation for more precise and useful prediction models in real estate market. Design/methodology/approach In response to the demand, this paper aims to provide a framework for forecasting the real estate market with machine learning algorithms. The framework consists of demonstrating the prediction efficiency of each machine learning algorithm, interpreting the interior feature effects of prediction model with a state-of-art algorithm, LIME(Local Interpretable Model-agnostic Explanation), and comparing the results in different cities. Findings This research could not only enhance the academic base for information system and real estate fields, but also resolve information asymmetry on real estate market among economic subjects. This research revealed that macroeconomic indicators, real estate-related indicators, and Google Trends search indexes can predict real-estate prices quite well.

• Korean Parent-Child Health Journal
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• v.17 no.1
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• pp.1-7
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• 2014

Purpose: The research was to identify menstrual regularity & mental health-related factors on unmarried women of childbearing age and provide a raw material in terms of setting up health policy. Methods: The KNHANE V-3 (The Fifth Korea National Health and Nutrition Examination Survey) was used and implemented through spss 18.0. Results: In general characteristics, there wasn't any remarkable difference between 20s and 30s. Looking further Mental health-related factors, stress was higher in 30s (p=.010). In 30s of irregularity mensutration women, it was accounted for 12.5% over than 3months experienced. General characteristics varied by menstrual regularity were age (p=.044), education level (p=.035) and in terms of mental health-related factors, they were stress (p=.044), sleeping time (p=.039). Multiple regression analysis was carried out to identify how influential these factors are on menstrual regularity. As a result, age, education level, sleeping time & stress was the most influence factors. Conclusion: The research had some limitations to specify and approach the feature of target in depth through KNHANE V-3. Thus, if the basic analysis regarding the menstrual problem in relation to local society was conducted on the basis of the result of research, it could help developing the promotion of health program and make the application easier.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.25-32
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• 2004

We propose a hierarchical disparity estimation algorithm with edge-preserving energy-based regularization. Initial disparity vectors are obtained from downsampled stereo images using a feature-based region-dividing disparity estimation technique. Dense disparities are estimated from these initial vectors with shape-adaptive windows in full resolution images. Finally, the vector fields are regularized with the minimization of the energy functional which considers both fidelity and smoothness of the fields. The first two steps provide highly reliable disparity vectors, so that local minimum problem can be avoided in regularization step. The proposed algorithm generates accurate disparity map which is smooth inside objects while preserving its discontinuities in boundaries. Experimental results are presented to illustrate the capabilities of the proposed disparity estimation technique.