• The Journal of Korean Academic Society of Nursing Education
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• v.25 no.4
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• pp.414-423
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• 2019

Purpose: This study evaluates the effect of behavioral relaxation training on distress and cancer screening intention of patients with upper gastrointestinal endoscopy. Methods: The research was conducted in a non-equivalent control group posttest design. Data were collected from endoscopy subjects in B city from October to November of 2018. Fifteen minutes of behavioral relaxation training were provided to the experimental group (n=40) and traditional relaxation therapy methods were provided to the control group (n=40). Outcome measures were distress and cancer screening intention of patients with upper gastrointestinal endoscopy. Data were analyzed with a ${\chi}^2$-test, independent t-test, Fisher's exact test with SPSS/PC version 23.0. Results: The objective discomfort (t=8.81, p<.001) of the experimental group was lower than that of the control group; there were no significant differences in the subjective discomfort (t=1.73, p=.088). The cancer screening intention (t=-5.85, p<.001) of the experimental group was significantly higher than that of the control group. Conclusion: Behavioral relaxation training was effective in heightening cancer screening intention. Therefore it can be usefully applied to increase cancer screening intention.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.75-80
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• 2013

Background: Breast cancer is the most common cancer diagnosed in females in Sri Lanka and early detection can lead to reduction in morbidity and mortality. Aim: To evaluate selected aspects of breast cancer early detection services implemented through well woman clinics (WWCs) in the Gampaha District. Methods: The study consisted of two components. A retrospective descriptive arm assessed clinical breast examination (CBE) coverage of target age group women (TGW) of 35-59 years in all the WWCs in Gampaha district over 2003-2007. A cross sectional descriptive study additionally assessed quality of breast cancer early detection services. The Lot Quality Assurance Sampling (LQAS) technique was used to decide on the lot size and threshold values, which were computed as twenty and six clinics. Checklists were employed in assessing coverage, physical facilities and clinic activities. Client satisfaction on WWC services was assessed among 200 TGW attending 20 WWCs using an interviewer-administered questionnaire. Results: CBE coverage in the Gampaha district increased only from 1.1-2.2% over 2003-2007. With regard to physical facilities, the number of clinics that were rated substandard varied between 7-18 (35-90%). The items that were lacking included dust bins, notice boards, stationary, furniture and linen, and cleanliness of outside premises and toilets. With regard to clinic activities, punctuality of staff, late commencement of clinics, provision of health education, supervision, CBE and breast self-examination (BSE) were substandard in 7-20 clinics (35-100%). Client satisfaction for WWC services was 45.2% (IQR: 38.7-54.8%) and only 11% had a score of ${\geq}70%$, the cut off set for satisfaction. Conclusions: Breast cancer early detection service coverage in the Gampaha district remained low (2.2%) in 2007, 11 years after commencing WWCs. All 20 clinics were substandard for overall CBE and BSE.

• Women's Health Nursing
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• v.16 no.2
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• pp.126-136
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• 2010

Purpose: This study was done to evaluate factors affecting active early detection behaviors of breast cancer and performance rate of breast self examination (BSE), physical examination and mammography. Methods: The participants were 264 women from an outpatient breast clinic of a university hospital and materials were collected from March 2007 to February 2008 using a structured questionnaire. The data were analyzed using $x^2$ test, logistic analysis. Results: The rate for BSE was 58.3%, for physical examination, 55.3% and for mammography experience, 63.4%. Women with all of these active early detection behaviors accounted for 31.8% of the participants. Various factors such as age, income, marital status, and menopause showed increased significant performance rate. The explanation power of logistic model was 48.5%, and was significant for age, income and health belief. Factors related to high performance rate were being over 40 years of age, high income and high health belief score. Conclusion: Active early detection behaviors were not high in spite of marked increases in breast cancer incidence. Encouragement for women practicing early detection behavior is important, but there is also a need to develop interest and support for the low performance group. More sustained education and public relations are needed to further improve active early detection behavior.

• Fire Science and Engineering
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• v.32 no.3
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• pp.116-122
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• 2018

In Chemical, Biological, Radiological and Nuclear (CBRN) disaster, integrated and optimized equipment package including stretcher, isolation unit, patient monitoring and treatment equipment is essential to achieve proper treatment and prevent secondary contamination. The purpose of this study was to evaluate the efficiency and ease of use of integrated CBRN disaster equipment package for disaster medical response. This study was a randomized crossover study using a manikin simulation for emergency medical technitian (EMT). All participants used the existing devices and prototype of integrated CBRN disaster equipment package alternately. Efficiency was measured by time from vital sign change to detection or treatment application. Ease was use was measured by questionnaires for each patient monitor, stretcher care and isolation unit. 12 EMTs were enrolled. hypoxia-detection time of integrated equipment group was significantly shorter than existing equipment group (4.9 s (3.8-3.9) vs 3.5 s (2.5-3.9), p < 0.05). There was decreasing tendency of ECG change detection and facial mask oxygen supply but no statistical significance was observed. Overall satisfaction of patient monitoring device in integrated equipment group was significantly higher than existing devices (4(3.5-5) vs 3(3-3), p < 0.05). The use of integrated CBRN disaster equipment package shortened the hypoxia detection time and improved usability of vital sign monitor compared to existing devices.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.205-212
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• 2024

This study developed a deep learning model that distinguishes the front (with garnish) and the back (without garnish) surface of the dried semi-finished product (dried bukak) for screening operation before transfter the dried bukak to oil heater using robot's vacuum gripper. For deep learning model training and verification, RGB images for the front and back surfaces of 400 dry bukak that treated by data preproccessing were obtained. YOLO-v5 was used as a base structure of deep learning model. The area, surface information labeling, and data augmentation techniques were applied from the acquired image. Parameters including mAP, mIoU, accumulation, recall, decision, and F1-score were selected to evaluate the performance of the developed YOLO-v5 deep learning model-based surface detection model. The mAP and mIoU on the front surface were 0.98 and 0.96, respectively, and on the back surface, they were 1.00 and 0.95, respectively. The results of binary classification for the two front and back classes were average 98.5%, recall 98.3%, decision 98.6%, and F1-score 98.4%. As a result, the developed model can classify the surface information of the dried bukak using RGB images, and it can be used to develop a robot-automated system for the surface detection process of the dried bukak before deep frying.

• KSBB Journal
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• v.23 no.5
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• pp.398-402
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• 2008

Cyanobacteria havebeen identified as one of the most promising group producing novel biochemically active natural products. Cyanobacteria are a very old group of prokaryotic organisms that produce very diverse secondary metabolites, especially non-ribosomal peptide and polyketide structures. Though many useful natural products have been identified in cyanobacterial biomass, cyanobacteria produce also extracellular proteins related with NRPS/PKS. Detection of unknown secondary metabolites in medium was carried in the present study by a screening of 98 cyanobacterial strains. A degenerated PCR technique as molecular approaches was used for general screening of NRPS/PKS gene in cyanobacteria. A putative PKS gene was detected by DKF/DKR primer in 38 strains (38.8%) and PCR amplicons resulted from a presence of NRPS gene were showed by MTF2/MTR2 primer in 30 strains (30.6%) and by A3/A7 primer in 26 strains (26.5%). HPLC analysis for a detection of natural products was performed in extracts from medium in which cyanobacteria containing putative PKS or NRPS were cultivated. CBT57, CBT62, CBT590 and CBT632 strains were screened for a production of extracellular natural products. 5 pure substances were detected from medium of these cyanobacteria.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.613-631
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• 2013

Cognitive radio (CR) is proposed as a key solution to improve spectral efficiency and overcome the spectrum scarcity. Spectrum sensing is an important task in each CR system with the aim of identifying the spectrum holes and using them for secondary user's (SU) communications. Several conventional methods for spectrum sensing have been proposed such as energy detection, matched filter detection, etc. However, the main limitation of these classical methods is that the CR network is not able to communicate with its own base station during the spectrum sensing period and thus a fraction of the available primary frame cannot be exploited for data transmission. The other limitation in conventional methods is that the SU data frames should be synchronized with the primary network data frames. To overcome the above limitations, here, we propose a spectrum sensing technique based on blind source separation (BSS) that does not need time synchronization between the primary network and the CR. Moreover, by using the proposed technique, the SU can maintain its transmission with the base station even during spectrum sensing and thus higher rates are achieved by the CR network. Simulation results indicate that the proposed method outperforms the accuracy of conventional BSS-based spectrum sensing techniques.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.6
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• pp.453-458
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• 2016

CFRP (Carbon Fiber Reinforced Plastic) and CFRP-metal stacks have recently been widely used in the aerospace and automobile industries. When CFRP is machined by a brittle fracture mechanism, defect generation behaviors are different from those associated with metal cutting. The machining quality is strongly dependent on the properties of CFRP materials. Therefore, process control for CFRP machining is necessary to minimize the defects of differently manufactured CFRPs. In this study, defects in drilling of CFRP substrates with a variety of fiber directions and resin types are compared with respect to thrust force. An experimental study on material interface detection is carried out to investigate its benefits in process control.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.445-449
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• 2005

Various methods to detect the phytoplankton/red tide blooms in the oceanic waters have been developed and tested on satellite ocean color imagery since the last two and half decades, but accurate detection of blooms with these methods remains challenging in optically complex turbid waters, mainly because of the eventual interference of absorbing and scattering properties of dissolved organic and particulate inorganic matters with these methods. The present study introduces a new method called Red tide Index (Rl), providing indices which behave as a good measure of detecting red tide algal blooms in high scattering and absorbing waters of the Korean South Sea and Yellow Sea. The effectiveness of this method in identifying and locating red tides is compared with the standard Ocean Chlorophyll 4 (OC4) bio-optical algorithm applied to SeaWiFS ocean imagery, acquired during two bloom episodes on 27 March 2002 and 28 September 2003. The result revealed that OC4 bio-optical algorithm falsely identifies red tide blooms in areas abundance in colored dissolved organic and particulate inorganic matter constituents associated with coastal areas, estuaries and river mouths, whereas red tide index provides improved capability of detecting, predicting and monitoring of these blooms in both clear and turbid waters.

• Steel and Composite Structures
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• v.14 no.4
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• pp.367-377
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• 2013

Damage in structures often leads to failure. Thus it is very important to monitor structures for the occurrence of damage. When damage happens in a structure the consequence is a change in its modal parameters such as natural frequencies and mode shapes. Artificial Neural Networks (ANNs) are inspired by human biological neurons and have been applied for damage identification with varied success. Natural frequencies of a structure have a strong effect on damage and are applied as effective input parameters used to train the ANN in this study. The applicability of ANNs as a powerful tool for predicting the severity of damage in a model steel girder bridge is examined in this study. The data required for the ANNs which are in the form of natural frequencies were obtained from numerical modal analysis. By incorporating the training data, ANNs are capable of producing outputs in terms of damage severity using the first five natural frequencies. It has been demonstrated that an ANN trained only with natural frequency data can determine the severity of damage with a 6.8% error. The results shows that ANNs trained with numerically obtained samples have a strong potential for structural damage identification.