• KIEAE Journal
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• v.15 no.6
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• pp.69-80
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• 2015

Purpose: Since most simulation programs take the interface that lists up all the input variables representing all the functionalities, users must know where design variables of an Energy Conservation Measure (ECM) are located and also know what values are appropriate. This is why practitioner designers feel frustrated when they attempt to use simulation. The final objective of this study is to provide a building energy modeling guideline for practitioners in various fields such as architectural design and MEP. Method: As the first step of the modeling guideline, this study provides the Level of Detail (LOD) for simulation modeling of primary ECMs considering the design information available in each design phase. It is prepared by literature review, simulation functionality investigation, and field experts' survey. Result: The proposed simulation LOD offers a milestone at each design phases concerning what design variable and attributes need to be developed with how much of details in order to meet the project goal. Also each design team can set up a simulation usecase considering organizational characteristics based on the proposed LOD.

• Language and Information
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• v.16 no.1
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• pp.25-43
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• 2012

This study introduces set-denoting time expressions in Korean, which can be divided into simple and complex types. It was found that while the simple type expressions are easily represented within ISO-TimeML, a time-expression markup language, some complex type set-denoting expressions are not. Therefore, this study analyzes the reason for these difficulties in representing complex type expressions, as well as suggests the introduction of @measure and @interpretation attributes in the TIMEX3 tag. The @measure attribute represents the time interval, and the @interpretation attribute is used to distinguish distributive readings from cumulative readings. Additionally this paper suggests that a mapping between these and other attributes are required in TLINK.

• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.303-319
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• 2015

The objectives of this paper are to measure surface imperviousness using three different classification methods: per-pixel, sub-pixel, and object-oriented classification. They are tested on high-spatial resolution QuickBird data at 2.4 meters (four spectral bands and three principal component bands) as well as a medium-spatial resolution Landsat TM image at 30 meters. To measure impervious surfaces, we selected 30 sample sites with different land uses and residential densities across image representing the city of Phoenix, Arizona, USA. For per-pixel an unsupervised classification is first conducted to provide prior knowledge on the possible candidate spectral classes, and then a supervised classification is performed using the maximum-likelihood rule. For sub-pixel classification, a Linear Spectral Mixture Analysis (LSMA) is used to disentangle land cover information from mixed pixels. For object-oriented classification several different sets of scale parameters and expert decision rules are implemented, including a nearest neighbor classifier. The results from these three methods show that the object-oriented approach (accuracy of 91%) provides more accurate results than those achieved by per-pixel algorithm (accuracy of 67% and 83% using Landsat TM and QuickBird, respectively). It is also clear that sub-pixel algorithm gives more accurate results (accuracy of 87%) in case of intensive and dense urban areas using medium-resolution imagery.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5464-5484
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• 2016

Few samples face recognition has become a highly challenging task due to the limitation of available labeled samples. As two popular paradigms in face image representation, sparse component analysis is highly robust while parts-based paradigm is particularly flexible. In this paper, we propose a probabilistic generative model to incorporate the strengths of the two paradigms for face representation. This model finds a common spatial partition for given images and simultaneously learns a sparse component analysis model for each part of the partition. The two procedures are built into a probabilistic generative model. Then we derive the score function (i.e. feature mapping) from the generative score space. A similarity measure is defined over the derived score function for few samples face recognition. This model is driven by data and specifically good at representing face images. The derived generative score function and similarity measure encode information hidden in the data distribution. To validate the effectiveness of the proposed method, we perform few samples face recognition on two face datasets. The results show its advantages.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.894-903
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• 2019

An approach for collapse risk assessment is proposed to evaluate the vulnerability of electric cabinet in nuclear power plants. The lognormal approaches, namely maximum likelihood estimation and linear regression, are introduced to establish the fragility curves. These two fragility analyses are applied for the numerical models of cabinets considering various boundary conditions, which are expressed by representing restrained and anchored models at the base. The models have been built and verified using the system identification (SI) technique. The fundamental frequency of the electric cabinet is sensitive because of many attached devices. To bypass this complex problem, the average spectral acceleration $S_{\bar{a}}$ in the range of period that cover the first mode period is chosen as an intensity measure on the fragility function. The nonlinear time history analyses for cabinet are conducted using a suite of 40 ground motions. The obtained curves with different approaches are compared, and the variability of risk assessment is evaluated for restrained and anchored models. The fragility curves obtained for anchored model are found to be closer each other, compared to the fragility curves for restrained model. It is also found that the support boundary conditions played a significant role in acceleration response of cabinet.

• Women's Health Nursing
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• v.30 no.3
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• pp.216-225
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• 2024

Purpose: Selection-optimization-compensation (SOC) models have been proposed and applied to various populations to examine successful aging from a multidimensional perspective. This study aimed to develop a scale to measure SOC strategy among late middle-aged women (aged 50 to 64 years) and to test its validity and reliability. Methods: Preliminary items were developed through a literature review and interviews. Overall, 32 preliminary items were confirmed via two rounds of expert content validity analysis and a pilot survey. Data were collected from 299 late middle-aged women and analyzed using IBM SPSS/PC+ version 27.0. Construct validity, criterion validity, and reliability tests were conducted. Results: The SOC strategy scale, reflecting the characteristics of late middle-aged women and developed through exploratory factor analysis, comprised 19 items across four factors: goal-oriented selection, compensation for loss, outcome optimization, and ability-based optimization. The scale explained 66.9% of the variance in total factors, with a Cronbach's α of .95. Statistically significant correlations with the reference scale (r=.30, p<.001) were observed. Conclusion: The developed scale demonstrated high validity and reliability, thus representing a viable instrument for measuring SOC strategy among late middle-aged women. Using this scale to assess the use of SOC approaches in these women can improve our understanding of the aging process and help establish supportive programs for their aging journeys.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.23-51
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• 2003

With the recent expansion of internet shopping mall, the importance of intelligent products recommendation agents has been increasing. for the products recommendation, This paper propose case-based reasoning approach, and developed a case-based bundle products recommendation system which can recommend a set of sea food used in family events. To apply CBR approach to the bundle products recommendation, it requires the following 4R steps : \circled1 Retrieval, \circled2 Reuse, \circled3 Revise, \circled4 Retain. To retrieve similar cases from the case-base efficiently, case representation scheme is most important. This paper used OW(Object Modeling Technique) to represent bundle products recommendation cases, and developed a similarity measure method to search similar cases. To measure similarity, we used weight-sum approach basically. Especially This paper propose the meaning and uses of taxonomies for representing case features.

• International Journal of Human Ecology
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• v.4 no.2
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• pp.55-75
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• 2003

The purpose of this study was to investigate the effect of employment related factors on household savings for precautionary purposes when controlling for financial security and to compare the results between the two different economic periods. A conceptual framework was developed based on the precautionary saving theory, the family stress theory, and previous empirical studies. As a self-insurance, a measure of security funds were developed and used as the dependent variable. Using data on working households in the 1992 and the 1998 Survey of Consumer Finances (SCF), a MLE estimation was conducted on the pooled data. The 1992 and 1998 data were used to reflect periods of economic recession and expansion, respectively. The results suggested that factors representing resources played the most significant role in determining the amount of security funds. Some of the employment related factors, preferences, financial security, and race were also significantly affected the amount of security funds. The results suggested that stable employment conditions were important for households to accumulate security funds. Households with more human resources and financial resources had a larger amount of security funds than those that had less human and financial resources. From the findings, implications for research, policies, and financial educators had been suggested.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.33-38
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• 1996

This paper provides an approach for representing an optimum vector quantizer by a scalar nonlinear gain-plus-additive noise model. The validity and accuracy of this analytic model is confirmed by comparing the calcuated model quantization errors with actual simulation of the optimum Linde-Buzo-Gray(LBG) vector quantizer. Using this model we frm MSE measure of an M-band filter bank codec in terms of the equivalent scalar quantizatin model and find the optimum FIR filter coefficients for each channel in the M-band structure for a given bit rate, given filter length, and given input signal correlation model. Specific design examples are worked out for 4-tap filters in the two-band paraunitary case. These theoretical results are confirmed by extensive Monte Carlo simulation.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.402-410
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• 2017

For many years, researchers in face description area have been representing and recognizing faces based on different methods that include subspace discriminant analysis, statistical learning and non-statistics based approach etc. But still automatic face recognition remains an interesting but challenging problem. This paper presents a novel and efficient face image representation method based on Optimized Local Ternary Pattern (OLTP) texture features. The face image is divided into several regions from which the OLTP texture feature distributions are extracted and concatenated into a feature vector that can act as face descriptor. The recognition is performed using nearest neighbor classification method with Chi-square distance as a similarity measure. Extensive experimental results on Yale B, ORL and AR face databases show that OLTP consistently performs much better than other well recognized texture models for face recognition.