• Journal of Korean Academy of Fundamentals of Nursing
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• v.12 no.1
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• pp.21-29
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• 2005

Purpose: The purpose of this study was to identify the frequency with which nursing interventions according to domains and classes, and core nursing interventions of the Nursing Intervention Classification (NIC) were performed by nurses on orthopedic surgery nursing units. Method: For this purpose, the third edition of NIC was used. Of the 486 nursing interventions, 424 were selected at 75% consent by experts. Data were collected from June, 2003 to July, 2003 5 hospitals and 69 nurses(return rate : 95.8%) in Gwang-ju and Chonnam region. 5 point Likert scale describing frequency was used. Results: The most frequently performed domain was 'physiological : basic'($2.97{\pm}.60$), followed by 'health system'($2.65{\pm}.65$) and 'physiological : complex'($2.55{\pm}.46$). The most frequently performed class was 'activity and exercise management'($3.82{\pm}.89$), followed by 'immobility management'($3.64{\pm}.62$), 'skin/wound management'($3.41 {\pm}.60$), 'physical comfort promotion'($3.23{\pm}.68$) and 'thermoregulation'($3.01{\pm}.91$). The most frequently performed nursing intervention was 'medication administration' ($4.96{\pm}.21$), followed by 'medication administration : intravenous'($4.93{\pm}.31$), 'analgesic administration'($4.91{\pm}.51$), 'pain management'($4.87{\pm}.34$) and 'medication administration : intramuscular'($4.78{\pm}.68$). Conclusion: In conclusion, the third edition of NIC was found to be a general and comprehensive classification system for application on orthopedic surgery nursing units. These findings will help in building of a standardized language for orthopedic surgery nursing units and enhance the quality of nursing care.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.263-272
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• 2019

This paper describes the results of bearing capacity using field loading test of pile, in order to extend the applicability of drilled shaft with mid-size, and the results were compared with the prediction results of design bearing capacity by empirical formular. The static load test result showed that the allowable bearing capacity of high pile strength was about 2.4 times higher than that of low pile strength. The dynamic load test result showed that the allowable bearing capacity of high pile strength was about 1.4 times~1.5 times higher than that of low pile strength. The comparison result of allowable bearing capacity between static and dynamic load test showed that the difference of allowable load ranged from 3% to 6% under the same settlement conditions. As a result of comparing the ultimate bearing capacity by load test and design bearing capacity, it was found that the FHWA proposed equation could be more reasonable than the other proposed equation in load sharing ratios of end bearing and skin friction.

• Journal of Yeungnam Medical Science
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• v.15 no.2
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• pp.325-340
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• 1998

A cross-sectional study was conducted to evaluate the relationship between sick building syndrome(SBS) and the environmental factors affecting SBS on 130 underground workers and 60 controls. The study consisted of 1) a review of environmental condition 2) measurement of temperature, $O_2$, $CO_2$, CO, and formaldehyde and 3) a questionnaire survey of symptom prevalence and perception of environmental conditions using indoor Air Quality questionnaire recommended by National Institute for Occupational Safety and Health. Bronchitis and dust allergy were more prevalent in underground workers significantly(p < 0.05). Among the 18 symptoms related to the indoor air pollution, the experience rate of dry, itching or irritated eyes, sore or dry throat, chest tightness, tired or strained eyes and dry or itchy skin symptom was significantly different between the underground workers and controls. The diagnostic criteria of SBS was defined as at least 1 symptom is experienced 1-3 times a week during the last 1 month among 18 indoor air pollution related symptoms which can be relieved by moving out of the underground. Applying the criteria, the mean symptom score was significant higher in underground workers than controls significantly (p < 0.05). These resalts indicated that underground workers are under inappropriate ergonomic and physical condition and inadequate ventilation. Their experience rate of symptoms related to indoor air pollution and prevalence of SBS was significantly higher than controls. To reduce the prevalence of SBS of underground workers, the surveillance system of indoor air quality, restriction of using fuel in underground and legislative regulations for the environment are needed to establish a better indoor air quality. Early detection, treatment and prevention of SBS through medical attention is also needed.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.