• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.10
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• pp.687-696
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• 2010

In this study, FDD algorithm was developed using the normalized distance method and general pattern classifier method that can be applied to constant air volume air handling unit(CAV AHU) system. The simulation model using TRNSYS and EES was developed in order to obtain characteristic data of CAV AHU system under the normal and the faulty operation. Sensitivity analysis of fault detection was carried out with respect to fault progress. When differential pressure of mixed air filter increased by more than about 105 pascal, FDD algorithm was able to detect the fault. The return air temperature is very important measurement parameter controlling cooling capacity. Therefore, it is important to detect measurement error of the return air temperature. Measurement error of the return air temperature sensor can be detected at below $1.2^{\circ}C$ by FDD algorithm. FDD algorithm developed in this study was found to indicate each failure modes accurately.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.221-228
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• 2020

This study suggests an alternative to the conventional collaborative filtering method for predicting consumer choice, using case-based reasoning. The algorithm of case-based reasoning determines the similarity between the alternative sets that each subject chooses. Case-based reasoning uses the inverse of the normalized Euclidian distance as a similarity measurement. This normalized distance is calculated by the ratio of difference between each attribute level relative to the maximum range between the lowest and highest level. The alternative case-based reasoning based on similarity predicts a target subject's choice by applying the utility values of the subjects most similar to the target subject to calculate the utility of the profiles that the target subject chooses. This approach assumes that subjects who deliberate in a similar alternative set may have similar preferences for each attribute level in decision making. The result shows the similarity between comparable alternatives the consumers consider buying is a significant factor to predict the consumer choice. Also the interaction effect has a positive influence on the predictive accuracy. This implies the consumers who looked into the same alternatives can probably pick up the same product at the end. The suggested alternative requires fewer predictors than conjoint analysis for predicting customer choices.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.1
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• pp.18-26
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• 2008

The invariance relation existing in the non-negative matrix factorization (NMF) is used for constructing robust image hashes in this work. The image is first re-scaled to a fixed size. Low-pass filtering is performed on the luminance component of the re-sized image to produce a normalized matrix. Entries in the normalized matrix are pseudo-randomly re-arranged under the control of a secret key to generate a secondary image. Non-negative matrix factorization is then performed on the secondary image. As the relation between most pairs of adjacent entries in the NMF's coefficient matrix is basically invariant to ordinary image processing, a coarse quantization scheme is devised to compress the extracted features contained in the coefficient matrix. The obtained binary elements are used to form the image hash after being scrambled based on another key. Similarity between hashes is measured by the Hamming distance. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as Gaussian filtering, moderate noise contamination, JPEG compression, re-scaling, and watermark embedding. Hashes of different images have very low collision probability. Tampering to local image areas can be detected by comparing the Hamming distance with a predetermined threshold, indicating the usefulness of the technique in digital forensics.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.10
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• pp.669-678
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• 2008

When operating a complex facility, Fault Detection and Diagnosis (FDD) system is beneficial in equipment management by providing the operator with tools which can help find out a failure of the system. In this research, FDD algorithm was developed using the general pattern classifier method that can be applied to centrifugal chiller system. The simulation model for a centrifugal chiller system was developed in order to obtain characteristic data of turbo chiller system under normal and faulty operation. We tested FDD algorithm of a centrifugal chiller using data from simulation model at full load performance and 60% part load performance. In this research, we presented fault detection method using a normalized distance. Sensitivity analysis of fault detection was carried out with respect to fault progress. FDD algorithm developed in this study was found to indicate each failure modes accurately.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.4
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• pp.473-478
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• 2011

The extent of a rectangular conducting plane for measuring electromagnetic interference is discussed. Mutual coupling between the transmit and receive antennas is negligible, the effects of the ground plane on the normalized site attenuation(NSA) are considered by applying GTD(Geometric theory of diffraction). The calculation was done for the case that measuring distance(d) was 3 m for both horizontal and vertical polarizations. As the result, the size of the rectangular ground plane almost never affects upon NSA for horizontal polarization, but for vertical case, when both width and length of the rectangular plane are several times as long as distance, the effects of the edges are reduced under 1 dB.

• Earthquakes and Structures
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• v.13 no.1
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• pp.59-66
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• 2017

Modern seismic codes rely on performance-based seismic design methodology which requires that the structures withstand inelastic deformation. Many studies have focused on the inelastic deformation ratio evaluation (ratio between the inelastic and elastic maximum lateral displacement demands) for various inelastic spectra. This paper investigates the inelastic response spectra through the ductility demand ${\mu}$, the yield strength reduction factor $R_y$, and the inelastic deformation ratio. They depend on the vibration period T, the post-to-preyield stiffness ratio ${\alpha}$, the peak ground acceleration (PGA), and the normalized yield strength coefficient ${\eta}$ (ratio of yield strength coefficient divided by the PGA). A new inelastic deformation ratio $C_{\eta}$ is defined; it is related to the capacity curve (pushover curve) through the coefficient (${\eta}$) and the ratio (${\alpha}$) that are used as control parameters. A set of 140 real ground motions is selected. The structures are bilinear inelastic single degree of freedom systems (SDOF). The sensitivity of the resulting inelastic deformation ratio mean values is discussed for different levels of normalized yield strength coefficient. The influence of vibration period T, post-to-preyield stiffness ratio ${\alpha}$, normalized yield strength coefficient ${\eta}$, earthquake magnitude, ruptures distance (i.e., to fault rupture) and site conditions is also investigated. A regression analysis leads to simplified expressions of this inelastic deformation ratio. These simplified equations estimate the inelastic deformation ratio for structures, which is a key parameter for design or evaluation. The results show that, for a given level of normalized yield strength coefficient, these inelastic displacement ratios become non sensitive to none of the rupture distance, the earthquake magnitude or the site class. Furthermore, they show that the post-to-preyield stiffness has a negligible effect on the inelastic deformation ratio if the normalized yield strength coefficient is greater than unity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.77-84
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• 2012

Face classification has wide applications in intelligent video surveillance, content retrieval, robot vision, and human-machine interface. Pose and expression changes, and arbitrary illumination are typical problems for face recognition. When the face is captured at a distance, the image quality is often degraded by blurring and noise corruption. This paper investigates the efficacy of multi-classifier decision level fusion for face classification based on the photon-counting linear discriminant analysis with two different cost functions: Euclidean distance and negative normalized correlation. Decision level fusion comprises three stages: cost normalization, cost validation, and fusion rules. First, the costs are normalized into the uniform range and then, candidate costs are selected during validation. Three fusion rules are employed: minimum, average, and majority-voting rules. In the experiments, unfocusing and motion blurs are rendered to simulate the effects of the long distance environments. It will be shown that the decision-level fusion scheme provides better results than the single classifier.

• Journal of computational fluids engineering
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• v.10 no.4 s.31
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• pp.32-38
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• 2005

Present study simulates oscillatory supersonic impinging jet flows using the axisymmetric Navier-Stokes code. To capture the salient features of flow oscillation and overcome the divergence during the initial transient period, several tests have been conducted for the grid and time step sizes. The results also show that the effects of the inlet flow condition at the nozzle exit and turbulence on the oscillatory behavior of supersonic impinging jets are negligible. Frequencies of the surface pressure oscillation obtained by the selected numerical method are in good accord with the measured impinging tones for various cases of nozzle-to-plate distance. Two seemingly different staging behaviors with nozzle-to-plate distance and nozzle pressure variations are found to correlate well if the frequency and distance are normalized by the length of the first shock cell.

• Journal of the Optical Society of Korea
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• v.9 no.1
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• pp.6-12
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• 2005

The perturbation approach is applied to solve the nonlinear Schrodinger equation, and its valid range has been determined by comparing with the results of the split-step Fourier method over a wide range of parameter values. With γ= 2㎞/sup -1/mW/sup -1/, the critical distance for the first order perturbation approach is estimated to be(equation omitted). The critical distance, Z/sub c/, is defined as the distance at which the normalized square deviation compared to the split-step Fourier method reaches 10/sup -3/. Including the second order perturbation will increase Z/sub c/ more than a factor of two, but the increased computation load makes the perturbation approach less attractive. In addition, it is shown mathematically that the perturbation approach is equivalent to the Volterra series approach, which can be used to design a nonlinear equalizer (or compensator). Finally, the perturbation approach is applied to obtain the sinusoidal response of the fiber, and its range of validity has been studied.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.880-886
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• 2016

With lots of information occurring on the Internet, the search engine plays a role in gathering the scattered information on the Internet. Some search engines show not only search result pages including search keyword but also search result numbers of the keyword. The number of keyword searching result provided by the Google search engine can be utilized to identify overall trends for this search word on the internet. This paper is aimed designing and realizing the system which can efficiently manage the number of searching result provided by Google search engine. This paper proposed system operates by Web, and consist of search agent, storage node, and search node, manage keyword and search result, numbers, and executing search. The proposed system make the results such as search keywords, the number of searching, NGD(Normalized Google Distance) that is the distance between two keywords in Google area.