• Korean Journal of Human Ecology
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• v.21 no.5
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• pp.975-988
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• 2012

Although the pattern development for tight-fitting clothing has been carried out using 3D data on humans, the pattern development using 3D scan data obtained for various postures still remains an interesting subject. In this study, we have developed the 2D pattern using the 3D human body reflecting standing and cycling postures. The 3D scan data of a subject was obtained using Cyberware. 2C-AN program(Triangle simplification and the Runge-Kutta method) was used in the system to reduce the 3D scan data points and to make segmented triangular patches in a plane from 3D data. As results, surface distance and area of each body part of standing and cycling postures were also provided for the future application of the functional clothing construction. The area of center piece on the front (c.front) decreased by $106.45cm^2$(-13.08%) and that of lateral piece(s.back) on the back increased by $144.96cm^2$(18.69%) in the patterns of cycling posture. The girth of neck and waist for the cycling posture increased by 0.88cm (3.92%) and 1.56cm(4.40%) respectively, and the that of thigh decreased by 1.01cm(-2.24%). The differences between the area in the 2D pattern obtained from the 3D scan data and that in the 3D scan surface data for standing and cycling postures were very small($-10.34cm^2$(-0.32%) and $-44.33cm^2$(-1.32%)).

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.8
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• pp.1033-1041
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• 2003

Two-phase flow pattern data during horizontal in-tube flow boiling are presented for pure and mixed refrigerants of R134a and Rl23, The flow pattern is observed through tubular sight glasses located at inlet and outlet of the test section, which is made of a stainless steel tube, 2m long with 10mm I.D., 1.5mm wall thickness. The obtained results are compared with the available various correlations for flow pattern. The flow pattern map of Hashizume was in good agreement with the present data except the region of low mass velocity. Weisman flow pattern map was also known to satisfactorily predict data for refrigerants in the region of annular flow. In this study, the flow pattern are simply classified into two groups; stratified(including intermittent, stratified and stratified-wavy) flow and annular flow. The transition quality from stratified to annular flow was obtained by modifying the liquid Froude number.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.196-202
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• 2021

DNA sequencing provides fundamental data in genomics, bioinformatics, biology and many other research areas. With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. Those large volumes of data also require a fast transmission, effective storage, superior functionality and provision of quick access to any record. Data storage costs have a considerable proportion of total cost in the formation and analysis of DNA sequences. In particular, there is a need of highly control of disk storage capacity of DNA sequences but the standard compression techniques unsuccessful to compress these sequences. Several specialized techniques were introduced for this purpose. Therefore, to overcome all these above challenges, lossless compression techniques have become necessary. In this paper, it is described a new DNA compression mechanism of pattern matching extended Compression algorithm that read the input sequence as segments and find the matching pattern and store it in a permanent or temporary table based on number of bases. The remaining unmatched sequence is been converted into the binary form and then it is been grouped into binary bits i.e. of seven bits and gain these bits are been converted into an ASCII form. Finally, the proposed algorithm dynamically calculates the compression ratio. Thus the results show that pattern matching extended Compression algorithm outperforms cutting-edge compressors and proves its efficiency in terms of compression ratio regardless of the file size of the data.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.2
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• pp.167-175
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• 2007

Purpose: The Purpose of this study was to identify for perception and preference on Flexible working pattern of Nurses in hospital. Method: The subjects were 260 nurses enrolled in 11 hospitals located in S and P city. Questionnaire method was utilized for data collection. Data was analyzed by SPSS statistical program. Results: 86.5% of the nurses were working 3 shifts. 70.8% of nurses agreed that they decided to give up nurses because of very irregular working pattern. They want to work 40hrs/weeks, and agree to applying to Flexible working pattern. There was statistically significant between career(F=2.839, p=.039), working place(F=3.086, p=.047), the mind of change of occupation(F=.479, p=.002) and expected life pattern change after applicating for Flexible working pattern. Conclusion: We need to Various Flexible working pattern model. As well as we need to public information about nurses' Flexible working pattern.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.567-574
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• 2013

In this paper, we have proposed an architectural solution for a system for the visualization and modification of large amounts of data. The pattern is based on an asynchronous execution of programmable commands and a reflective approach of an object structure composition. The described pattern provides great flexibility, which helps adopting it easily to custom application needs. We have implemented a system based on the described pattern. The implemented system presents an innovative approach for a dynamic data object initialization and a flexible system for asynchronous interaction with data sources. We believe that this system can help software developers increase the quality and the production speed of their software products.

• The Journal of Korean Medicine
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• v.42 no.1
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• pp.1-11
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• 2021

Objectives: This pilot study aimed to evaluate the agreement between traditional face-to-face Korean medicine (KM) pattern identification and non-face-to-face KM pattern identification using the data from related questionnaires, tongue image, and pulse features in patients with cancer. Methods: From January to June 2020, 16 participants with a cancer diagnosis were recruited at the one Korean medicine hospital. Three experienced Korean medicine doctors independently diagnosed the participants whether they belong to the cold pattern or not, heat pattern or not, deficiency pattern or not, and excess pattern or not. Another researcher collected KM pattern related data using questionnaires including Cold-Heat Pattern Identification (CHPI), tongue image analysis system, and pulse analyzer. Collected KM pattern related data without participants' identifier was provided for the three Korean medicine doctors in random order, and non-face-to-face KM pattern identification was carried out. The kappa value between face-to-face and non-face-to-face pattern identification was calculated. Results: From the face-to-face pattern identification, there were 13/3 cold/non-cold pattern, 4/12 heat/non-heat pattern, 14/2 deficiency/non-deficiency pattern, and 0/16 excess/non-excess pattern participants. In cold/non-cold pattern, kappa value was 0.455 (sensitivity: 0.85, specificity: 0.67, accuracy: 0.81). In heat/non-heat pattern, the kappa value was 0.429 (sensitivity: 0.75, specificity: 0.72, accuracy: 0.75). The kappa value of deficiency/non-deficiency and excess/non-excess pattern was not calculated because of the few participants of non-deficiency, and excess pattern. Conclusions: The agreement between traditional face-to-face pattern identification and non-face-to-face pattern identification seems to be moderate. The non-face-to-face pattern identification using questionnaires, tongue, and pulse features may feasible for the large clinical study.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1031-1040
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• 2004

Electrocardiogram being the recording of the heart's electrical activity provides valuable clinical information about heart's status. Many re-searches have been pursued for heart disease diagnosis using ECG so far. However, electrocardio-graph uses foreign diagnosis algorithm due to inaccuracy of diagnosis results for a heart disease. This paper suggests ECG data collection, data preprocessing and heart disease pattern classification using data mining. This classification technique is the FB(Frequent pattern Bayesian) classifier and is a combination of two data mining problems, naive bayesian and frequent pattern mining. FB uses Product Approximation construction that uses the discovered frequent patterns. Therefore, this method overcomes weakness of naive bayesian which makes the assumption of class conditional independence.

• Fashion & Textile Research Journal
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• v.10 no.5
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• pp.652-659
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• 2008

This study was designed to testify the possibility and devise the method to manipulate the 3D body scan data to produce rounded-belt pattern adaptable to hip-type variation of women in their 20's. The results of this research were as follows : Firstly, based on drop-value distribution of hip and waist girth, 151 subjects were classified into three hip-types; Type 1 (15.23%) was 'cylinder type', showing lowest drop-value, Type 2 (69.54%) was 'average type' and Type3 (15.23%) was 'hourglass type' showing highest drop-value. Secondly, using CAD program, design lines for round shape belt were set on the surface of 3D scan data of representative subject of each type. And divided 3D surfaces were flattened onto the plane by the internal tools of CAD program. The measure, 'lifting value of round belt pattern', implying the level of curve ratio of pattern was higher in back than front. This result might be linked to the fact that the hip part is more protruded than the abdomen part. And the measures also showed highest values in Type 3(hourglass type) and lowest in Type 1(cylinder type), meaning that the pattern of Type 3 showed more rounded shape than that of Type 1. This finding implied that round belt for body type having high drop-value should be shaped more curved. Thirdly, difference ratios of outline length and area between 3D curves(body surface) and 2D plane(pattern) were 4.5% and 1.3%, respectively. This result demonstrated and solidified the feasibility of designing digital garment pattern from 3D body scan data.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.5
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• pp.846-858
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• 2008

This study was designed to propose a method to draft bodice block pattern from 3D body scan data. Subjects were ten elderly women in their 60's, who wear basic size(B: 94cm, W: 82cm) garment. Scanning was done using 3D whole body scanner(WB4, Cyberware). Measurements for 3D data and cross section were attained using Auto CAD, by which a upper bodice pattern for elderly women was drawn on the basis of short measured method. The results are as following: As for most items, no significant differences were shown between measurements from Martin's anthropometry and those from 3D scan data, suggesting measurement from 3D scan data could be used to draft a pattern. The drafting equations acquired were as follows; width of pattern=B/2+5.5, width of waist=W/2+3.5cm, dart amount=8cm. Dart distributions were 23%(B.P.) : 20%(front armpit) : 17%(side seam) : 18%(back armpit) : 15%(back protruded point) : 7% (center back line). Through wearing test using 5-point Likert scale, resultant pattern was evaluated as appropriate for elderly women's pattern to get over 4 point. As a result, it might be said that 3D scanning application is effective for elderly women in that it doesn't take time so much as Martin's anthropometry and that their body shape vary compared with those of young women.