• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.47-52
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• 2005

Obstructive Sleep Apnea (OSA) is a representative symptom of sleep disorder caused by the obstruction of upper airway. Because OSA causes not only excessive daytime sleepiness and fatigue, hypertension and arrhythmia but also cardiac arrest and sudden death during sleep in the severe case, it is very important to detect the occurrence and the frequency of OSA. OSA is usually diagnosed through the laboratory-based Polysomnography (PSG) which is uncomfortable and expensive. Therefore researches to improve the disadvantages of PSG are needed and studies for the detection of OSA using only one or two parameters are being made as alternatives to PSG. In this paper, we developed an algorithm for the detection of OSA based on Heart Rate Variability (HRV). The proposed method is applied to the ECG data sets provided from PhysioNet which consist of learning set and training set. We extracted features for the detection of OSA such as average and standard deviation of 1 minute R-R interval, power spectrum of R-R interval and S-peak amplitude from data sets. These features are applied to the input of neural network. As a result, we obtained sensitivity of $89.66\%$ and specificity of $95.25\%$. It shows that the features suggested in this study are useful to detect OSA.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.195-209
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• 2003

Spatial-Stochastic Neural Networks Model(SSNNM) is used to estimate long-term streamflow in the parallel reservoir groups. SSNNM employs two kinds of backpropagation algorithms, based on LMBP and BFGS-QNBP separately. SSNNM has three layers, input, hidden, and output layer, in the structure and network configuration consists of 8-8-2 nodes one by one. Nodes in input layer are composed of streamflow, precipitation, pan evaporation, and temperature with the monthly average values collected from Andong and Imha reservoir. But some temporal differences apparently exist in their time series. For the SSNNM training procedure, the training sets in input layer are generated by the PARMA(1,1) stochastic model and they covers insufficient time series. Generated data series are used to train SSNNM and the model parameters, optimal connection weights and biases, are estimated during training procedure. They are applied to evaluate model validation using observed data sets. In this study, the new approaches give outstanding results by the comparison of statistical analysis and hydrographs in the model validation. SSNNM will help to manage and control water distribution and give basic data to develop long-term coupled operation system in parallel reservoir groups of the Upper Nakdong River.

• The Journal of the Petrological Society of Korea
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• v.25 no.3
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• pp.231-240
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• 2016

Three Quaternary faults have been revealed in marine terraces nearby the Homigot and the Gurongpo in the southeastern offshore of Korean Peninsula. The Hajung fault cuts the $4^{th}$ marine terraces and the Guman fault the $2^{nd}$, respectively. The Hajung fault strikes $N55^{\circ}$ to $45^{\circ}W$ and dips $40^{\circ}$ to $45^{\circ}NE$ with reverse-displacement of 180cm vertically. There are four sets of colluvial sediment strata that would be produced by faulting and indicate four times of fault movements during MIS 7 and MIS 5c. The Guman fault site consists of three sets of reverse faults that strike $N80^{\circ}E$ to $N70^{\circ}W$ and dip $25^{\circ}{\sim}35^{\circ}SE$ to $30^{\circ}SW$ with vertical displacement of 9~18 cm. The Guman faulting occurred during 80 ka (MIS 5a) to 71 ka (MIS 4) but it extends only to the lowest bed, the pebble sand bed, lay just on the unconformity, and not to the upper. Considering the attitude of the faults, we inferred that the Hajung fault was activated under the ENE-WSW compression during MIS 7 to MIS 5c and the Guman under N-S trending compression during MIS 5a. Using the OSL age dating results, we reconfirmed that the $2^{nd}$ terrace is correlated to MIS 5a and the $4^{th}$ terraces to MIS 7.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.582-591
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• 2009

The pyramid graph is an interconnection network topology based on regular square mesh and tree structures. In this paper, we adopt a strategy of classification into two disjoint groups of edges in regular square mesh as a base sub-graph constituting of each layer in the pyramid graph. Edge set in the mesh can be divided into two disjoint sub-sets called as NPC(represents candidate edge for neighbor-parent) and SPC(represents candidate edge for shared-parent) whether the parents vertices adjacent to two end vertices of the corresponding edge have a relation of neighbor or shared in the upper layer of pyramid graph. In addition, we also introduce a notion of shrink graph to focus only on the NPC-edges by hiding SPC-edges in the original graph within the shrunk super-vertex on the resulting graph. In this paper, we analyze that the lower and upper bound on the number of NPC-edges in a Hamiltonian cycle constructed on $2^n\times2^n$ mesh is $2^{2n-2}$ and $3*(2^{2n-2}-2^{n-1})$ respectively. By expanding this result into the pyramid graph, we also prove that the maximum number of NPC-edges containable in a Hamiltonian cycle is $4^{n-1}-3*2^{n-1}$-2n+7 in the n-dimensional pyramid.

• Journal of Korean Society of Forest Science
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• v.90 no.2
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• pp.176-183
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• 2001

Loblolly pine (Pinus taeda L.) is the most economically important timber producing species in the southern United States. Much attention has been given to predicting diameter distributions for the solution of multiple-product yield estimates. The three-parameter Weibull diameter distribution yield prediction systems were developed for loblolly pine plantations. A parameter recovery procedure for the Weibull distribution function based on four percentile equations was applied to develop diameter distribution yield prediction models. Four percentiles (0th, 25th, 50th, 95th) of the cumulative diameter distribution were predicted as a function of quadratic mean diameter. Individual tree height prediction equations were developed for the calculation of yields by diameter class. By using individual tree content prediction equations, expected yield by diameter class can be computed. To reduce rounding-off errors, the Weibull cumulative upper bound limit difference procedure applied in this study shows slightly better results compared with upper and lower bound procedure applied in the past studies. To evaluate this system, the predicted diameter distributions were tested against the observed diameter distributions using the Kolmogorov-Smirnov two sample test at the ${\alpha}$=0.05 level to check if any significant differences existed. Statistically, no significant differences were detected based on the data from 516 evaluation data sets. This diameter distribution yield prediction system will be useful in loblolly pine stand structure modeling, in updating forest inventories, and in evaluating investment opportunities.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1183-1193
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• 2010

The pyramid graph is well known in parallel processing as a interconnection network topology based on regular square mesh and tree architectures. The enhanced pyramid graph is an alternative architecture by exchanging mesh into the corresponding torus on the base for upgrading performance than the pyramid. In this paper, we adopt a strategy of classification into two disjoint groups of edges in regular square torus as a basic sub-graph constituting of each layer in the enhanced pyramid graph. Edge set in the torus graph is considered as two disjoint sub-sets called NPC(represents candidate edge for neighbor-parent) and SPC(represents candidate edge for shared-parent) whether the parents vertices adjacent to two end vertices of the corresponding edge have a relation of neighbor or sharing in the upper layer of the enhanced pyramid graph. In addition, we also introduce a notion of shrink graph to focus only on the NPC-edges by hiding SPC-edges within the shrunk super-vertex on the resulting shrink graph. In this paper, we analyze that the lower and upper bounds on the number of NPC-edges in a Hamiltonian cycle constructed on $2^n{\times}2^n$ torus is $2^{2n-2}$ and $3{\cdot}2^{2n-2}$ respectively. By expanding this result into the enhanced pyramid graph, we also prove that the maximum number of NPC-edges containable in a Hamiltonian cycle is $4^{n-1}$-2n+1 in the n-dimensional enhanced pyramid.

• Structural Engineering and Mechanics
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• v.83 no.4
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• pp.495-513
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• 2022

This paper aims to study the fracture mechanism of rocks under the 'u'shape cutters considering the effects of crack (pre-existing crack) distances, crack spacing and crack inclination angles. The effects of loading rates on the rock fragmentation underneath these cutters have been also studied. For this purpose, nine experimental samples with dimensions of 5 cm×10 cm×10 cm consisting of the non-persistent cracks were prepared. The first three specimens' sets had one non-persistent crack (pre-existing crack) with a length of 2 cm and angularity of 0°, 45°, and 90°. The spacing between the crack and the "u" shape cutter was 2 cm. The second three specimens" set had one non-persistent crack with a length of 2 cm and angularity of 0°, 45°, and 90° but the spacing between pre-existing crack and the "u" shape cutter was 4 cm. The third three specimens'set has two non-persistent cracks with lengths of 2 cm and angularity of 0°, 45° and 90°. The spacing between the upper crack and the "u" shape cutter was 2 cm and the spacing between the lower crack and the upper crack was 2 cm. The samples were tested under a loading rate of 0.005 mm/s. concurrent with the experimental investigation. The numerical simulations were performed on the modeled samples with non-persistent cracks using PFC2D. These models were tested under three different loading rates of 0.005 mm/s, 0.01 mm/sec and 0.02 mm/sec. These results show that the crack number, crack spacing, crack angularity, and loading rate has important effects on the crack growth mechanism in the rocks underneath the "u" shape cutters. In addition, the failure modes and the fracture patterns in the experimental tests and numerical simulations are similar to one another showing the validity and accuracy of the current study.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.63-68
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• 2010

Recently, to accelerate the Ubiquitous generation, the input interface of the mobile machinery and tools are actively being researched. In addition with the existing interfaces such as the keyboard and curser (mouse), other subdivisions including the handwriting, voice, vision, and touch are under research for new interfaces. Especially in the case of small-sized mobile machinery and tools, there is a increasing need for an efficient input interface despite the small screens. This is because, additional installment of other devices are strictly limited due to its size. Previous studies on handwriting recognition have generally been based on either two-dimensional images or algorithms which identify handwritten data inserted through vectors. Futhermore, previous studies have only focused on how to enhance the accuracy of the handwriting recognition algorithms. However, a problem arisen is that when an actual handwriting is inserted, the user must select the classification of their characters (e.g Upper or lower case English, Hangul - Korean alphabet, numbers). To solve the given problem, the current study presents a system which distinguishes different languages by analyzing the form/shape of inserted handwritten characters. The proposed technique has treated the handwritten data as sets of vector units. By analyzing the correlation and directivity of each vector units, a more efficient language distinguishing system has been made possible.

• Human Ecology Research
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• v.52 no.1
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• pp.55-62
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• 2014

The purpose of this study is to identify changes in the sleeve patterns of women's jackets from the end of the 19th century to the early 20th century. To meet this purpose, we analyzed nine sets of historic sleeve patterns. The experimental sleeve patterns were selected from the English costume source books that provided women's costume patterns from the 1890s and 1900s. These experimental sleeve patterns were drafted on the basis of the directions given in the source books. The sleeve lengths, widths, and angles of each sleeve pattern were measured. The results of this study showed that the silhouette of the two-piece sleeves of women's jackets in the 1890s had a tight fit; further, they had a sharper elbow curve than that of 1900s' sleeves. The sleeves of the 1890s' women's jackets were 6-11 cm shorter or narrower than the sleeves of the 1900s' jackets. The under-sleeve inseam angle of the 1890s' sleeve was greater than that of the 1900s' sleeve. The outseam angle of the upper sleeve was greater than the under-sleeve angle of the 1900s' sleeve pattern. The elbow curve of the women's jacket sleeve pattern appeared to be a sluggish silhouette. This change happened as the outseam angle of the under sleeve was reduced. This shows that the elbow curve silhouette of the women's jacket sleeves of the 1890s and 1900s has controlled the change in the under-sleeve outseam angle.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.77-93
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• 2020

The literature has reported that hierarchical classification methods generally outperform the flat classification methods for a multi-class document classification problem. Unlike the literature that has constructed a class hierarchy, this paper evaluates the performance of hierarchical and flat classification methods under a situation where the class hierarchy is predefined. We conducted numerical evaluations for two data sets; research papers on climate change adaptation technologies in water sector and 20NewsGroup open data set. The evaluation results show that the hierarchical classification method outperforms the flat classification methods under a certain condition, which differs from the literature. The performance of hierarchical classification method over flat classification method depends on class similarities at levels in the class structure. More importantly, the hierarchical classification method works better when the upper level similarity is less that the lower level similarity.