• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1356-1362
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• 2015

The location of PV systems in distribution system has been increased as one of countermeasure for global environmental issues. As the operation efficiency of PV systems is getting decreased year by year due to the aging phenomenon and maintenance problems, the optimal algorithm for state diagnosis in PV systems is required in order to improve operation performance in PV systems. The existing output prediction algorithms considering various parameters and conditions of PV modules could have complicated calculation process and then their results may have a possibility of significant prediction error. To solve these problems, this paper proposes an optimal prediction algorithm of PV system by using least square methods of linear regression analysis. And also, this paper presents a performance evaluation algorithm in PV modules based on the proposed optimal prediction algorithm of PV system. The simulation results show that the proposed algorithm is a practical tool of the state diagnosis for performance improvement in PV systems.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.20 no.2
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• pp.24-36
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• 2024

This study analyzed the feasibility of the air source heat pump in residential buildings based on operational performance and carbon emissions. The operational performance and carbon emissions were compared between a gas boiler and an air source heat pump by calculating the annual heating and hot water load based on the 21A and 36A models for actual residential buildings. For the operational performance of the air source heat pump, the lowest (2.3) and highest COP (5.9) were attained during the winter and summer seasons, respectively. The carbon emissions depend on the amount of energy consumed during operations. An air source heat pump consumed 65.10% and 65.4% less energy per year in the 21A and 36A models, respectively compared to the existing gas boiler. Consequently, for air source heat pump carbon emissions were also reduced by 13.3% and 15.1% per year for the 21A and 36A models, respectively. It shows the effectiveness of applying an air source heat pump compared to an existing gas boiler.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.5
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• pp.40-50
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• 2007

One-year-old rooted cuttings of ten poplar clones and one willow clone were planted in a riparian area in Osan. Survival rate, growth performance, biomass, vitality, defoliation, leaf damages by diseases and/or insects and stem borer damage of the poplar and willow clones have been investigated for three growing seasons. Average survival rate of all eleven clones was declined from 80.7% for the first year to 60.7% for the third year. At three years after planting, poplar clones Dorskamp, ST-148 and Eco-28 showed the best survival rate of 80%. For height and DBH growth, the poplar clone Ay-48 and the willow clone 131-25 were the highest 8.3m and 9.5cm, respectively. However, poplar clones 72-30 and 72-31 were lower than those of the other clones. Clones Ay-48 and 131-25 seemed to have strong vitality when compare to the other clones. No serious damages by diseases and insects were found in most clones. Clones Ay-48 and ST-148 were the most tolerant to various diseases and insects. Clone Ay-48 produced the largest biomass for individual and annual total biomass, 22.5kg and 18.7ton $ha^{-1}$, respectively. Clone Dorskamp showed the best adaptability, which was estimated with survival rate, biomass and damages by various diseases and insects in the riparian area and followed by clones Ay-48, 97-19 and Eco-28. As a consequence, the four clones seemed to be the best candidate poplar clones for the establishment of riparian woody buffer.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1448-1456
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• 2022

This paper studies a model to diagnose efficiency reduction of inverter using Multilayer Perceptron(MLP). In this study, two inverter data which started operation at different day was used. A Multilayer Perceptron model was made to predict photovoltaic power data of the latest inverter. As a result of the model's performance test, the Mean Absolute Percentage Error(MAPE) was 4.1034. The verified model was applied to one-year-old and two-year-old data after old inverter starting operation. The predictive power of one-year-old inverter was larger than the observed power by 724.9243 on average. And two-year-old inverter's predictive value was larger than the observed power by 836.4616 on average. The prediction error of two-year-old inverter rose 111.5572 on a year. This error is 0.4% of the total capacity. It was proved that the error is meaningful difference by t-test. The error is predicted value minus actual value. Which means that PV system actually generated less than prediction. Therefore, increasing error is decreasing conversion efficiency of inverter. Finally, conversion efficiency of the inverter decreased by 0.4% over a year using this model.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.78.2-78.2
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• 2003

• Proceedings of the Korean Nuclear Society Conference
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• 2002.05a
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• pp.79.1-79
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• 2002

• Journal of Korean Clinical Health Science
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• v.8 no.2
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• pp.1398-1407
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• 2020

Purpose: The purpose of this study is a technical study to understand the relationship between the recognition and performance of core basic nursing skills of nursing college students who are ahead of clinical practice, and satisfaction with their major. Method: The subjects were 208 second-year students enrolled in the four-year nursing department located in J City and C City. General characteristics, characteristics of clinical practice, and recognition of the importance of core basic nursing skills, performance, and satisfaction with majors were investigated. Descriptive statistics, t-test, analysis of variance, multiple regression analysis and IPA are performed for data analysis Results: The results are follows. The results are follows. First, the performance was lower than that of the core basic nursing skills (p<.001). As a result of comparing the importance recognition and performance of the core basic nursing items, the importance recognition was significantly compared to the performance level in all 20 items. It showed high results. Second, it was found that there was a significant positive correlation (r=.40, p<.01) with major satisfaction in core basic nursing performance. Conclusion: These results highlight the need to develop education. It is necessary to establish a learning strategy through various learning guidance methods and self-directed learning that can improve the performance of items with low performance, although recognized as important through the Core Basic Nursing IPA for nursing students who are about to practice clinical practice. It is suggested to do repeated research applied.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.19 no.3
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• pp.322-333
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• 2012

Purpose: The purpose of this study was to evaluate the effects of a newly developed Introduction to Clinical Nursing (ICN) program on critical thinking skills, communication competence, self-efficacy, and clinical performance self-confidence in nursing students in their third year. Methods: One group pre-test and post-test design was used with three data collection time points (pre-test, post-test1 and post-test2). Participants were 74 third year nursing students approaching their first clinical practicum. The new program included (a) simulated clinical encounters regarding situations of assessing hospitalized patents and caring for patients with oxygenation needs, (b) objective structured clinical examination of skills, (c) lectures, and (e) field trips. Data were analyzed using paired t-tests. Results: After the ICN course, critical thinking skills(significant only between pretest and post-test2), communication competence, and clinical performance self-confidence improved significantly (p<.05). There was no improvement in the self-efficacy total score but there was significant improvement in the subscale, self-regulatory efficacy. Conclusions: The study results indicate that the ICN course may be effective in increasing critical thinking skills, communication competence, and clinical performance self-confidence in nursing students. However, the effect size was very small and modifications of this program should be considered to develop more cost-effective educational programs.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.217-226
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• 2018

According to the Korea Coast Guard's maritime disaster statistics (Korea Coast Guard 2017, Korean Statistical information Service 2018), an average of 2,140 marine accidents occurred every year for the past 6 years and the number of accidents is increasing every year. Among them, maritime accidents of fishing vessels are the most frequent, and recently accidents involving fishing boat and leisure vessels are rapidly increasing as well. In particular, the number of accidents involving leisure vessels increased to about one-third of the accidents of fishing vessels, and emergency rescue requests are increasing every year accordingly. However, the number of crash accidents involving users of small vessels and marine leisure activities are increasing because of the difficulties of installing navigation equipment and electronic navigation charts. Recently, the demand for precise positioning using mobile devices is increasing in the fields of maritime safety, piloting support, and coastal survey. Although various applications of smart devices provide location-based services for users, the measurement results are discontinuous when using the position coordinates of the National Marine Electronics Association (NMEA) calculated by smartphone. Recently, Google announced that they will provide GPS raw data to developers from Android 7.0 Nougat. As a result, developers have an opportunity to receive precise carrier phase and code measurements to make more accurate positioning according to the performance of Android devices. This study analyzed GPS positioning performance using Android devices, and compared and analyzed the positioning performance at sea with high-performance GPS receivers.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.