• Journal of IKEEE
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• v.23 no.4
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• pp.1415-1422
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• 2019

Background subtraction is the major task of computer vision and image processing to detect changes in video. The best performing background subtraction is computationally expensive that cannot be used in real time in a typical computing environment. The proposed algorithm improves the background subtraction algorithm of the widely used MOG with the image resizing algorithm. The proposed image resizing algorithm is designed to drastically reduce the amount of computation and to utilize local information, which is robust against noise such as camera movement. Experimental results of the proposed algorithm have a classification capability that is close to the state of the art background subtraction method and the processing speed is more than 10 times faster.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.766-772
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• 2015

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3401-3408
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• 2023

In this study, we used the Monte Carlo N-Particle program to simulate the gamma-ray spectra obtained from plastic scintillators holes filled with bismuth nanoparticles. We confirmed that the incorporation of bismuth nanoparticles into a plastic scintillator enhances its performance for gamma-ray spectroscopy using the subtraction method. The subtracted energy spectra obtained from the bismuth-nanoparticle-incorporated and the original plastic scintillator exhibit a distinct energy peak that does not appear in the corresponding original spectra. We varied the diameter and depth of the bismuth-filled holes to determine the optimal hole design for gamma-ray spectroscopy using the subtraction method. We evaluated the energy resolutions of the energy peaks in the gamma-ray spectra to estimate the effects of the bismuth nanoparticles and determine their optimum volume in the plastic scintillator. In addition, we calculated the peak-to-total ratio of the energy spectrum to evaluate the energy measuring limit of the bismuth nanoparticle-containing plastic scintillator using the subtraction method.

• Korean Journal of Optics and Photonics
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• v.14 no.4
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• pp.423-428
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• 2003

In a direct modulated semiconductor laser diode. the structural dependence of current blocking layers was studied in view of the leakage current reduction and the bandwidth expansion. To analyze the leakage current and the parasitic effects, the current-voltage derivation characteristics and the subtraction method were used, respectively. It was shown that the‘inin’type current blocking structure might be the best choice for the purpose of the static and dynamic characteristics.

• School Mathematics
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• v.2 no.2
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• pp.489-508
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• 2000

With the increased use of computational technology, many educators question about spending large amount of class time for dealing with computational algorithms in elementary school math classroom at the expense of more holistic aspects of mathematics such as number sense, spatial sense, problem solving and data management. This paper introduce the new method for learning addition and subtraction so called ‘Mrs. Weill’s Hill’, which is believed as a suitable remedial method for children with mathematical learning disabilities, with perceptual problems, or with limited working memory capacities. This method provides children with external memory strategies by allowing them to solve the addition and subtraction problems in a stage by stage fashion with as many steps as they require. It also gives the child greater flexibility in the solution process and thus helps reduce anxiety.

• Journal of Periodontal and Implant Science
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• v.25 no.1
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• pp.67-75
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• 1995

The progress of periodontal disease and the wound healing process after treatment result in alveolar bone bone change. So, detection of it is very important in the diagnosis and the radiograph of periodontal disease. Various effects have been made to assess the subtle alveolar bone change and digital subtraction radiography (DSR) has been reported to be the best method in evaluating it qualitatively and quantitatively. The present study was performed to estimate the detectable alveolar bone change qualitatively with digital subtraction radiography. For the in vitro study, 10 intraoral standard radiographs were taken from porcine dry mandible which a rectangular cortical bone chip of 0.1mm to 1.0mm thickness with 0.1mm increment was attached on the buccal surface. The radiographs without and with bone plates were reviewed at the same time by 10 observers and requested to detect the presence of cortical bone plates. Digital Subtraction radiograph was reviewed subsequently by using the DSR system(digital converter-256 grey-levels,DT 2851,Data Translation Co., U.S.A;IBM 386 ; CCD camera, FOTOVIX, Tamrom Co., Japan). The detectable thickness of cortical bone plate was O.4mm on the intraoral radiograph and 0.2mm on the subtaction images. For the human study, radiographs were taken from patients by using intraoral film holding device and aluminum reference wedge before and 3 month after bone graft and 1 week after osteoplasty. The grey level change was estimated in the subtraction images and calculated to aluminum equivalent thickness. The grey level of the grafted site was higher that that of healthy controls. Average grey levels of change on healthy controls were O.48mm aluminum equivalent. However, the amount of changes in grafted sites were 1.87mm aluminum thickness equivalent and in the site of osteoplasty were -1.49mm aluminum thickness equivalent. In conclusion, digital subtraction radiography was more effective in detecting as subtle change of alveolar bone than intraoral standard radiography. With the aid of quantitative analysis of digital subtraction radiography, alveolar bone resorption of apposition can be estimated during diagnosis and treatment of periodontally diseased patients.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.102-109
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• 2009

Purpose: Flash 3D (pixon(R) method; 3D OSEM) was developed as a software program to shorten exam time and improve image quality through reconstruction, it is an image processing method that usefully be applied to nuclear medicine tomography. If perfoming brain diamox perfusion scan by reconstructing subtracted images by Flash 3D with shortened image acquisition time, there was a problem that SNR of subtracted image is lower than basal image. To increase SNR of subtracted image, we use LEAP collimators, and we emphasized on sensitivity of vessel dilatation than resolution of brain vessel. In this study, our purpose is to confirm possibility of application of LEAP collimators at brain diamox perfusion tomography, identify proper reconstruction factors by using Flash 3D. Materials and methods: (1) The evaluation of phantom: We used Hoffman 3D Brain Phantom with $^{99m}Tc$. We obtained images by LEAP and LEHR collimators (diamox image) and after 6 hours (the half life of $^{99m}Tc$: 6 hours), we use obtained second image (basal image) by same method. Also, we acquired SNR and ratio of white matters/gray matters of each basal image and subtracted image. (2) The evaluation of patient's image: We quantitatively analyzed patients who were examined by LEAP collimators then was classified as a normal group and who were examined by LEHR collimators then was classified as a normal group from 2008. 05 to 2009. 01. We evaluate the results from phantom by substituting factors. We used one-day protocol and injected $^{99m}Tc$-ECD 925 MBq at both basal image acquisition and diamox image acquisition. Results: (1) The evaluation of phantom: After measuring counts from each detector, at basal image 41~46 kcount, stress image 79~90 kcount, subtraction image 40~47 kcount were detected. LEAP was about 102~113 kcount at basal image, 188~210 kcount at stress image and 94~103 at subtraction image kcount were detected. The SNR of LEHR subtraction image was decreased than LEHR basal image about 37%, the SNR of LEAP subtraction image was decreased than LEAP basal image about 17%. The ratio of gray matter versus white matter is 2.2:1 at LEHR basal image and 1.9:1 at subtraction, and at LEAP basal image was 2.4:1 and subtraction image was 2:1. (2) The evaluation of patient's image: the counts acquired by LEHR collimators are about 40~60 kcounts at basal image, and 80~100 kcount at stress image. It was proper to set FWHM as 7 mm at basal and stress image and 11mm at subtraction image. LEAP was about 80~100 kcount at basal image and 180~200 kcount at stress image. LEAP images could reduce blurring by setting FWHM as 5 mm at basal and stress images and 7 mm at subtraction image. At basal and stress image, LEHR image was superior than LEAP image. But in case of subtraction image like a phantom experiment, it showed rough image because SNR of LEHR image was decreased. On the other hand, in case of subtraction LEAP image was better than LEHR image in SNR and sensitivity. In all LEHR and LEAP collimator images, proper subset and iteration frequency was 8 times. Conclusions: We could archive more clear and high SNR subtraction image by using proper filter with LEAP collimator. In case of applying one day protocol and reconstructing by Flash 3D, we could consider application of LEAP collimator to acquire better subtraction image.

• The Mathematical Education
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• v.59 no.3
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• pp.255-269
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• 2020

In this study, how to instruct the computational estimation of addition and subtraction was considered from the perspective of a 'intended-written-implemented' multi-dimensional curriculum. To this end, the 2015 revised elementary school mathematics curriculum as a intended curriculum and the 2015 revised first~sixth grade textbook as a written curriculum were analyzed with respect to how to instruct the computational estimation of addition and subtraction. As an implemented curriculum, a research study was conducted in relation to the method of instructing teachers about the computational estimation of addition and subtraction. As a result, first, it is necessary to discuss how to develop the ability to estimate and set it as a teaching goal and achievement standard in a separate curriculum to instruct it with learning content. Second, it is necessary to provide an opportunity to learn about various estimation methods by presenting specific activities so that students can learn the estimation itself in a separate operation method. Third, in order to improve the computational estimating ability of addition and subtraction, contents related to the computational estimation need to be included in the achievement criteria, and discussions on the expansion of the areas, and the diversification of the instructing time will be needed.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2E
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• pp.62-68
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• 2003

This paper addresses a novel noise-compensation scheme to solve the mismatch problem between training and testing condition for the automatic speech recognition (ASR) system, specifically in car environment. The conventional spectral subtraction schemes rely on the signal-to-noise ratio (SNR) such that attenuation is imposed on that part of the spectrum that appears to have low SNR, and accentuation is made on that part of high SNR. However, these schemes are based on the postulation that the power spectrum of noise is in general at the lower level in magnitude than that of speech. Therefore, while such postulation is adequate for high SNR environment, it is grossly inadequate for low SNR scenarios such as that of car environment. This paper proposes an efficient spectral subtraction scheme focused specifically to low SNR noisy environment by extracting harmonics distinctively in speech spectrum. Representative experiments confirm the superior performance of the proposed method over conventional methods. The experiments are conducted using car noise-corrupted utterances of Aurora2 corpus.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.4
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• pp.231-234
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• 2013

This paper introduces a mixture of background subtraction technique and K-Means clustering algorithm for removing shadows from video sequences. Lighting conditions cause an issue with segmentation. The proposed method can successfully eradicate artifacts associated with lighting changes such as highlight and reflection, and cast shadows of moving object from segmentation. In this paper, K-Means clustering algorithm is applied to the foreground, which is initially fragmented by background subtraction technique. The estimated shadow region is then superimposed on the background to eliminate the effects that cause redundancy in object detection. Simulation results depict that the proposed approach is capable of removing shadows and reflections from moving objects with an accuracy of more than 95% in every cases considered.