• KIPS Transactions on Computer and Communication Systems
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• v.2 no.2
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• pp.83-92
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• 2013

RSA-CRT is a widely used algorithm that provides high performance implementation of the RSA-signature algorithm. Many previous studies on each operation step have been published to verify the physical leakages of RSA-CRT when used in smart devices. This paper proposes SAED (subtraction algorithm analysis on equidistant data), which extracts sensitive information using the event information of the subtraction operation in a reduction algorithm. SAED is an attack method that uses algorithm-dependent power signal changes. An adversary can extract a key using differential power analysis (DPA) of the subtraction operation. This paper indicates the theoretical rationality of SAED, and shows that its results are better than those of other methods. According to our experiments, only 256 power traces are sufficient to acquire one block of data. We verify that this method is more efficient than those proposed in previously published studies.

• Education of Primary School Mathematics
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• v.21 no.4
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• pp.415-430
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• 2018

The purpose of this study was to get reflections on teaching numbers and operations for special education from analyzing lessons for counting, addition and subtraction of natural number with counting board for students with autism. In order to attain these purposes, this study analyzed the lessons for counting, addition and subtraction of natural number to students with autism in 4th and 6th graders in special class at regular elementary school using counting board for one hour per week for 30 weeks. According to the analysis, counting board that reveals the structure of numbers becomes an effective mathematical materials, and using the counting strategy and computation strategy can be an effective method of teaching, and it is possible to teach mathematical communication to students with autism. From this result, this study presented suggestions for teaching counting, addition and subtraction for students with disabilities.

• Journal of Yeungnam Medical Science
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• v.37 no.2
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• pp.90-97
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• 2020

Background: To minimize damage to the ovarian reserve, it is necessary to evaluate the follicular density in the ovarian tissue surrounding endometriosis on preoperative imaging. The purpose of the present study was to evaluate the usefulness of subtraction pelvic magnetic resonance imaging (MRI) to detect ovarian reserve. Methods: A subtracted T1-weighted image (^subT1WI) was obtained by subtracting unenhanced T1WI from contrast-enhanced T1WI (^ceT1WI) with similar parameters in 22 patients with ovarian endometriosis. The signal-to-noise ratio (SNR) in ovarian endometriosis, which was classified into the high signal intensity and iso-to-low signal intensity groups on the T2-weighted image, was compared to that in normal ovarian tissue. To evaluate the effect of contrast enhancement, a standardization map was obtained by dividing ^subT1WI by ^ceT1WI. Results: On visual assessment of 22 patients with ovarian endometriosis, 16 patients showed a high signal intensity, and 6 patients showed an iso-to-low signal intensity on T1WI. Although SNR in endometriosis with a high signal intensity was higher than that with an iso-to-low signal intensity, there was no difference in SNR after the subtraction (13.72±77.55 vs. 63.03±43.90, p=0.126). The area of the affected ovary was smaller than that of the normal ovary (121.10±22.48 vs. 380.51±75.87 ㎟, p=0.002), but the mean number of pixels in the viable remaining tissue of the affected ovary was similar to that of the normal ovary (0.53±0.09 vs. 0.47±0.09, p=0.682). Conclusion: The subtraction technique used with pelvic MRI could reveal the extent of endometrial invasion of the normal ovarian tissue and viable remnant ovarian tissue.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.439-451
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• 2021

We propose a deep learning-based beamformer combined with spectral subtraction for continuous speech recognition operating in noisy environments. Conventional beamforming systems were mostly evaluated by using pre-segmented audio signals which were typically generated by mixing speech and noise continuously on a computer. However, since speech utterances are sparsely uttered along the time axis in real environments, conventional beamforming systems degrade in case when noise-only signals without speech are input. To alleviate this drawback, we combine online beamforming algorithm and spectral subtraction. We construct a Continuous Speech Enhancement (CSE) evaluation set to evaluate the online beamforming algorithm in noisy environments. The evaluation set is built by mixing sparsely-occurring speech utterances of the CHiME3 evaluation set and continuously-played CHiME3 background noise and background music of MUSDB. Using a Kaldi-based toolkit and Google web speech recognizer as a speech recognition back-end, we confirm that the proposed online beamforming algorithm with spectral subtraction shows better performance than the baseline online algorithm.

• Journal of the Korean School Mathematics Society
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• v.25 no.4
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• pp.423-446
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• 2022

This study explores and compares Korean and U.S. elementary preservice teachers' analytic approaches of students' addition and subtraction computational strategies. Twenty-six Korean and twenty U.S. elementary preservice teachers participated in the study. Participants were asked to analyze mathematical approaches and errors from students' addition and subtraction operations. Preservice teachers' written documents were analyzed by applying open coding and inductive coding based on the grounded theory. As a result, the pattern of error analysis and interpretation of students' addition computations were similar for both Korean and U.S. preservice teachers whereas there were some differences in the analysis of students' subtraction computations. Both Korean and U.S. preservice teachers had difficulties identifying students' strategies and errors for a complicated and unconventional computational approach. Results also indicated that preservice teachers' noticing and interpretation of students' strategies and errors were influenced by their K-12 mathematics curriculum and teacher education program. This study suggests implications and future directions for teacher education, more contextualized teacher preparation programs and balanced connection to the K-12 curriculum.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3E
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• pp.3-8
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• 1999

In speech recognition for real-world applications, the performance degradation due to the mismatch introduced between training and testing environments should be overcome. In this paper, to reduce this mismatch, we provide a hybrid method of spectral subtraction and residual noise masking. We also employ multiple model approach to obtain improved robustness over various noise environments. In this approach, multiple model sets are made according to several noise masking levels and then a model set appropriate for the estimated noise level is selected automatically in recognition phase. According to speaker independent isolated word recognition experiments in car noise environments, the proposed method using model sets with only two masking levels reduced average word error rate by 60% in comparison with spectral subtraction method.

• The Journal of the Acoustical Society of Korea
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• v.23 no.4E
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• pp.125-133
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• 2004

In this paper, we propose a critical banded wavelet packet-based spectral subtraction for speech enhancement. Critical banded wavelet packet, which reflects the human auditory system, may lead to minimization of intelligibility loss and quality improvement of the enhanced speech in the spectral domain, when combined with an appropriate spectral subtraction gain function. The proposed method shows better performance than the conventional one in comparative assessments. We also show that, for effective evaluation of enhanced speech, it is essential to consider the characteristics of speech quality measures.

• 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.

• Speech Sciences
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• v.11 no.1
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• pp.7-20
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• 2004

In this paper, we propose a two-step noise compensation algorithm in feature extraction for achieving robust speech recognition. The proposed method frees us from requiring a priori information on noisy environments and is simple to implement. First, in frequency domain, the Harmonics-based Spectral Subtraction (HSS) is applied so that it reduces the additive background noise and makes the shape of harmonics in speech spectrum more pronounced. We then apply a judiciously weighted variance Feature Vector Normalization (FVN) to compensate for both the channel distortion and additive noise. The weighted variance FVN compensates for the variance mismatch in both the speech and the non-speech regions respectively. Representative performance evaluation using Aurora 2 database shows that the proposed method yields 27.18% relative improvement in accuracy under a multi-noise training task and 57.94% relative improvement under a clean training task.

• Journal of Korean Neurosurgical Society
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• v.57 no.6
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• pp.432-435
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• 2015

Moyamoya disease is a unique cerebrovascular disorder characterized by idiopathic progressive stenosis at the terminal portion of the internal carotid artery (ICA) and fine vascular network. The aim of this review is to present the clinical application of quantitative digital subtraction angiography (QDSA) in pediatric moyamoya disease. Using conventional angiographic data and postprocessing software, QDSA provides time-contrast intensity curves and then displays the peak time ($T_{max}$) and area under the curve (AUC). These parameters of QDSA can be used as surrogate markers for the hemodynamic evaluation of disease severity and quantification of postoperative neovascularization in moyamoya disease.