• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.143-151
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• 2013

NAND flash-based SSDs (Solid State Drive) have advantages of fast input/output performance and low power consumption so that they could be widely used as storages on tablet, desktop PC, smart-phone, and server. But, SSD has the disadvantage of wear-leveling due to increase of the number of writes. In order to improve the lifespan of the SSD, a variety of data deduplication techniques have been introduced. General fixed-size splitting method allocates fixed size of chunk without considering locality of data so that it may execute unnecessary chunking and hash key generation, and variable-size splitting method occurs excessive operation since it compares data byte-by-byte for deduplication. This paper proposes adaptive chunking method based on application locality and file name locality of written data in SSD-based server storage. The proposed method split data into 4KB or 64KB chunks adaptively according to application locality and file name locality of duplicated data so that it can reduce the overhead of chunking and hash key generation and prevent duplicated data writing. The experimental results show that the proposed method can enhance write performance, reduce power consumption and operation time compared to existing variable-size splitting method and fixed size splitting method using 4KB.

• Journal of the Korean Mathematical Society
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• v.54 no.2
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• pp.613-626
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• 2017

For the overdetermined linear system, when both the data matrix and the observed data are contaminated by noise, Total Least Squares method is an appropriate approach. Since an ill-conditioned data matrix with noise causes a large perturbation in the solution, some kind of regularization technique is required to filter out such noise. In this paper, we consider a Dual regularized Total Least Squares problem. Unlike the Tikhonov regularization which constrains the size of the solution, a Dual regularized Total Least Squares problem considers two constraints; one constrains the size of the error in the data matrix, the other constrains the size of the error in the observed data. Our method derives two nonlinear equations to construct the iterative method. However, since the Jacobian matrix of two nonlinear equations is not guaranteed to be nonsingular, we adopt a trust-region based iteration method to obtain the solution.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2401-2408
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• 1997

The measured pulse shapes provided in the given data package demonstrated pulse distortions due to laser speckle. the distorted pulse shapes were carefully analyzed, modeled, and then applied to the DTTL(Digital-data Transition Tracking Loop)[1] bit synchronizer simulator to measure the mean time delay and its delay variation performance. The result showed that the maximum mean time delay variation with the modeled data was 12.5% when window size equals 1. All the data given were located within this modeled boundary and the maximum eman time delay variation was 7% in this case. The mean time delay variation was known to be smaller by reducing the window size [2][5][6]. The mitigated delay variation was 2.5% in the modeled case and 1.4% in the data set given when the windown size equals 0.1. With the digital DTTL insteal of analog DTTL, similar results was obtained.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.6
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• pp.383-391
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• 2011

As we know the effects of cache memory research, instruction and data caches can be separated for higher performance with Harvard CPUs. In this paper, we shows the efficiency of buffer system in the instruction and data flash storage medium. And we analyzed characteristics of the data and instruction flash and evaluated the performance. Finally, we propose the best buffer structure with an optimal block size and buffer size for the instruction and data flash.

• The Journal of Korean Physical Therapy
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• v.32 no.5
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• pp.277-282
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• 2020

Purpose: The main purposes of this study are to identify the degree of effect size and variables related to it, on the effect of physical therapy on shoulder adhesive capsulitis. Methods: This study were collected 8 studies published between 2010.01.01. and 2020.08.01. The Analysis result confirmed 16 effect size data, the random effect model was chosen because of the heterogeneity of the data. Results: First, full case showed the largest mean effect size 3.28 (p<0.001). Second, Size of the effect according to hands on+off intervention the 5.17 (p>0.344). Third, Number of participants showed 15 or more effect size 4.19 (p<0.002). intervention period showed 8 weeks effect size 5.12 (p>0.425). Number of intervention showed 14 or less effect size 3.99 (p>0.061). Publication type showed thesis effect size 4.34 (p<0.003). Finally, 'Trim and Fill' result confirmed that the calibration effect size is 1.71 (p<0.001). Conclusion: We were able to confirm that physical therapy had great effect on shoulders adhesive capsulitis, and that the effect differed according to the methods of intervention, the methods of evaluation.

• Fashion & Textile Research Journal
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• v.15 no.2
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• pp.247-255
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• 2013

This study develops size sections and specifications for females 7-18 years old. The specifications will contribute to the development of precise virtual models that represent basic data for the size alteration of 3D virtual models. A total of 33 items from the $5^{th}$ Size Korea data set were adopted and analyzed. Two representative factors (Obesity and Height Factors) were identified through a factor analysis of the 33 items. Waist circumference and stature were selected as representative variables for Obesity and Height Factors, respectively, and conducted cross tabulations between waist circumference and height for the age groups of 7-12 and 13-18 year-olds. Size sections were developed for the development of 3D models based on the results. A regression analysis then developed size specifications for each section with independent variables of waist circumference and height as well as dependent variables of reference body size. Subsequently, Obesity Factors were better explained by waist circumference and Height Factors were better explained by stature. Finally, size specifications for each section were developed.

• The Journal of Korean Physical Therapy
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• v.32 no.4
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• pp.222-227
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• 2020

Purpose: The primary purposes of this study were to identify the degree of the effect size and the variables related to it on the effects of physical therapy on myofascial pain syndrome. Methods: This study collected 15 studies published between 2008.01.01 and 2019.12.31. The Analysis results confirmed 57 effect size data. The random-effect model was chosen because of the heterogeneity of the data. Results: First, the full case showed the largest mean effect size of 2.03 (p<0.001). Second, the size of the effect, according to the handson intervention, was 2.74 (p<0.003). Third, the VAS showed an effect size of 2.30 (p<0.001). Fourth, the intervention period showed a 1- to 15-day effect size of 2.94 (p<0.001). The number of interventions showed a 6 to 10 effect size of 2.84 (p<0.006). The number of participants showed a 10 or less effect size of 2.66 (p<0.001). Finally, the 'Trim and Fill' result confirmed that the calibration effect size was 0.93 (p<0.001). Conclusion: Physical therapy had a great effect on myofascial pain syndrome in the neck and shoulders, and that the effect differed according to the methods of the intervention and the methods of evaluation.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.155-166
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• 2003

Mobile computing becomes a new issue of researches in computing due to the advances of mobile equipment and the connection with Internet. In mobile environment, there are many constraints such as limited bandwidth, intermittent disconnection, limited battery life, and so on. By these reasons, broadcasting has been generally used to disseminate data efficiently by the mobile applications. This paper proposes an adaptive broadcasting method which logically divides broadcast channel into the periodic broadcast channel and the on-demand broadcast channel and dynamically assigns the bandwidths of both channel. The former disseminates data that are selected based on both the popularity and the size of each datum, the latter disseminates data that are selected based on the requests of mobile clients. When selecting data to be disseminated, the proposed broadcasting method considers the mobility of a mobile client and also considers the size of each datum by using SF(size factor) proposed in this paper. This paper also evaluates the proposed broadcasting method by measuring the energy expenditure of mobile client in experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.49-57
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• 2022

Recently, various uses of artificial intelligence have been made possible through the deep artificial neural network structure of machine learning, demonstrating human-like capabilities. Unfortunately, the deep structure of the artificial neural network has not yet been accurately interpreted. This part is acting as anxiety and rejection of artificial intelligence. Among these problems, we solve the capability part of artificial neural networks. Calculate the size of the artificial neural network structure and calculate the size of data that the artificial neural network can process. The calculation method uses the group method used in mathematics to calculate the size of data and artificial neural networks using an order that can know the structure and size of the group. Through this, it is possible to know the capabilities of artificial neural networks, and to relieve anxiety about artificial intelligence. The size of the data and the deep artificial neural network are calculated and verified through numerical experiments.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.187-190
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• 2007

This study is for analyzing best band in image matching using correlation coefficient of left and right images of stereo image pair, lot red, green, blue band images separated from color aerial photo and gray image converted from the same color aerial photo image. The image matching is applied to construct Digital Elevation Model(DEM) or terrain data. The correlation coefficients and variation by change of pixel patch size are computed from pixel patches of which sizes are $11{\times}11{\sim}101{\times}101$. Consequently, the correlation coefficient in red band image is highest. The lowest is in blue band. Therefore, to construct terrain data using image matching, the red band image is preferable. As the size of pixel patch is growing, the correlation coefficient is increasing. But increasing rate declines from $51{\times}51$ image patch size and above. It is proved that the smaller pixel patch size than $51{\times}51$ is applied to construct terrain data using image matching.