• The KSFM Journal of Fluid Machinery
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• v.17 no.6
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• pp.89-94
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• 2014

The 4th generation SFR is being designed with a milestone of construction by 2028. It is important to understand the subchannel flow characteristics in fuel assembly through the experimental investigations and to estimate the calculation uncertainties for insuring the confidence of the design code calculation results. The friction coefficient and the mixing coefficient are selected as primary parameters. The two parameters are related to the flow distribution and diffusion. To identify the flow distribution, an iso-kinetic method was developed based on the previous study. For the mixing parameters, a wire mesh system and a laser induced fluorescence methods were developed in parallel. The measuring systems were adopted on 37 rod bundle test geometry, which was developed based on the Euler number scaling. A scaling method for a design of experimental facility and the experimental identification techniques for the flow distribution and mixing parameters were developed based on the measurement requirement.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.9-14
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• 2010

In this paper, we propose method of correlation coefficients between sensors by statistical analysis that selects optimal sensors in odor recognition system of selective multi-sensors. The proposed sensor decision method obtains odor data from Metal Oxide Semiconductor(MOS) sensor array and then, we decide optimal sensors based on correlation of obtained odors. First of all, we select total number of 16 sensors eliminated sensor of low response and low reaction rate response among similar sensors. We make up DB using 16 sensors from input odor and we select sensor of low correlation after calculated correlation coefficient of each sensor. Selected sensors eliminate similar sensors' response therefore proposed method are able to decide optimal sensors. We applied to floral scent recognition for performance evaluation of proposed sensors decision method. As a result, application of proposed method with floral scent recognition using correlation coefficient obtained recognition rate of 95.67% case of using 16 sensors while applied floral scent recognition system of proposed sensor decision method confirmed recognition rate of 94.67% using six sensors and 96% using only 8 sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.381-404
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• 2022

Forest fires inflict great losses of human lives and serious damages to ecological systems. Hence, numerous fire detection methods have been proposed, one of which is fire detection based on sensors. However, these methods reveal several limitations when applied in large spaces like forests such as high cost, high level of false alarm, limited battery capacity, and other problems. In this research, we propose a novel forest fire detection method based on image processing and correlation coefficient. Firstly, two fire detection conditions are applied in RGB color space to distinguish between fire pixels and the background. Secondly, the image is converted from RGB to YCbCr color space with two fire detection conditions being applied in this color space. Finally, the correlation coefficient is used to distinguish between fires and objects with fire-like colors. Our proposed algorithm is tested and evaluated on eleven fire and non-fire videos collected from the internet and achieves up to 95.87% and 97.89% of F-score and accuracy respectively in performance evaluation.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.885-890
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• 2003

The Core Base Tree (CBT) multicast routing architecture is a multicast routing protocol for the internet. The CBT establishes a single shared tree for a multicast connection. The shared tree Is rooted at a center node called core. The location of the core may affect the cost and performance of the CBT. The core placement method requires the knowledge of the network topology In this Paper, we propose a simple and effective method for selecting the core. This method requires the distance vector information. in addition, we used results that calculated sample correlation coefficient. And then we select suitable routing algorithm according to member's arrangement states in muliticast group. we select core node that have minimum average cost or PIM-SM protocol is selected. The performance of this method is compared with several other methods by extensive simulations (i.e mean delay, maximum delay, and total cost). Our results shows that this method for Selecting Core is very effective.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.271-286
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• 2013

Recently, a pixel-chaotic-shuffling (PCS) method has been proposed by Huang et al. for encrypting color images using multiple chaotic systems like the Henon, the Lorenz, the Chua, and the Rossler systems. All of which have great encryption performance. The authors claimed that their pixel-chaotic-shuffle (PCS) encryption method has high confidential security. However, the security analysis of the PCS method against the chosen-plaintext attack (CPA) and known-plaintext attack (KPA) performed by Solak et al. successfully breaks the PCS encryption scheme without knowing the secret key. In this paper we present an improved shuffling pattern for the plaintext image bits to make the cryptosystem proposed by Huang et al. resistant to chosen-plaintext attack and known-plaintext attack. The modifications in the existing PCS encryption method are proposed to improve its security performance against the potential attacks described above. The Number of Pixel Change Rate (NPCR), Unified Average Changed Intensity (UACI), information entropy, and correlation coefficient analysis are performed to evaluate the statistical performance of the modified PCS method. The simulation analysis reveals that the modified PCS method has better statistical features and is more resistant to attacks than Huang et al.'s PCS method.

• Smart Structures and Systems
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• v.17 no.1
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• pp.73-89
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• 2016

The stress dependence of ultrasonic wave velocity is known as the acoustoelastic effect. This effect is useful for stress monitoring if the acoustoelastic coefficient of a subject medium is known. The acoustoelastic coefficients of metallic materials such as steel have been studied widely. However, the acoustoelastic coefficient of concrete has not been well understood yet. Basic constituents of concrete are water, cement, and aggregates. The mix proportion of those constituents greatly affects many mechanical and physical properties of concrete and so does the acoustoelastic coefficient of concrete. In this study, influence of the water-cement ratio (w/c ratio) and the fine-coarse aggregates ratio (fa/ta ratio) on the acoustoelastic coefficient of concrete was investigated. The w/c and the fa/ta ratios are important parameters in mix design and affect wave behaviors in concrete. Load-controlled uni-axial compression tests were performed on concrete specimens. Ultrasonic wave measurements were also performed during the compression tests. The stretching coda wave interferometry method was used to obtain the relative velocity change of ultrasonic waves with respect to the stress level of the specimens. From the experimental results, it was found that the w/c ratio greatly affects the acoustoelastic coefficient while the fa/ta ratio does not. The acoustoelastic coefficient increased from $0.003073MPa^{-1}$ to $0.005553MPa^{-1}$ when the w/c ratio was increased from 0.4 to 0.5. On the other hand, the acoustoelastic coefficient changed in small from $0.003606MPa^{-1}$ to $0.003801MPa^{-1}$ when the fa/ta ratio was increased from 0.3 to 0.5. Finally, it was also found that the relative velocity change has a linear relationship with the stress level of concrete.

• Journal of the Korean Geotechnical Society
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• v.18 no.4
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• pp.85-93
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• 2002

This study presented a new method for evaluating the coefficient of consolidation by using inflection point method which was based on the fact that time factor, T corresponding to the inflection point of a semi-logarithmic plot of a time curve is fixed and equals to T = 0.405 at 70.03% consolidation. In the proposed method, as the next load increment is applied as soon as the inflection point is confirmed, the time required to identify the inflection point can be shortened. Thus, the coefficient of consolidation may be easily evaluated. The time required to complete the testing using this rapid consolidation method could be as low as 0.5~9 hours compared with 1 or 2 weeks in the case of the conventional consolidation test. For this study, we designed settlement equipment for normalization of test samples. In test results, the factors of consolidation agreed with undisturbed samples results.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.265-270
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• 2011

In this paper, we propose a method for intensity correction using binarization-based region segmentation in 3D stereoscopic images. In the proposed method, 3D stereoscopic right image is segmented using binarizarion. Small regions in the segmented image are eliminated. For each region in right image, a corresponding region in left image is decided through region matching using correlation coefficient. When region-based matching, in order to prevent overlap between regions, we remove a portion of the area closed to the region boundary using morphological filter. The intensity correction in left and right image can be performed through histogram specification between the corresponding regions. Simulation results show the proposed method has the smallest matching error than the conventional method when we generate the right image from the left image using block based motion compensation.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.555-562
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• 2012

This paper presents a hybrid method for improving the recognition performance, which is based on the nonlinear histogram equalization, features extraction, and statistical correlation of images. The nonlinear histogram equalization based on a logistic function is applied to adaptively improve the quality by adjusting the brightness of the image according to its intensity level frequency. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to rapidly and accurately express the similarity between the images. The local features based on independent component analysis(ICA) that is used to calculate the NCC, is also applied to statistically measure the correct similarity in each images. The proposed method has been applied to the problem for recognizing the 30-face images of 40*50 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the preprocessing, or the methods of conventional and adaptively modified histogram equalization, respectively.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.709-713
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• 2009

Recently, a lot of research that applies data acquired from devices such as cameras and RFIDs to context aware services is being performed in the field on Life-Log and the sensor network. A variety of analytical techniques has been proposed to recognize various information from the raw data because video and audio data include a larger volume of information than other sensor data. However, manually watching a huge amount of media data again has been necessary to create supervised data for the update of a class or the addition of a new class because these techniques generally use supervised learning. Therefore, the problem was that applications were able to use only recognition function based on fixed supervised data in most cases. Then, we proposed a method of acquiring supervised data from a video sharing site where users give comments on any video scene because those sites are remarkably popular and, therefore, many comments are generated. In the first step of this method, words with a high utility value are extracted by filtering the comment about the video. Second, the set of feature data in the time series is calculated by applying functions, which extract various feature data, to media data. Finally, our learning system calculates the correlation coefficient by using the above-mentioned two kinds of data, and the correlation coefficient is stored in the DB of the system. Various other applications contain a recognition function that is used to generate collective intelligence based on Web comments, by applying this correlation coefficient to new media data. In addition, flexible recognition that adjusts to a new object becomes possible by regularly acquiring and learning both media data and comments from a video sharing site while reducing work by manual operation. As a result, recognition of not only the name of the seen object but also indirect information, e.g. the impression or the action toward the object, was enabled.