• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.15-22
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• 2022

In order to improve the accuracy of the deep learning object detection technique, the effect of magnification rate conditions and seasonal factors on detection accuracy in aerial photographs and drone images was analyzed through experiments. Among the deep learning object detection techniques, Mask R-CNN, which shows fast learning speed and high accuracy, was used to detect the vehicle to be detected in pixel units. Through Seoul's aerial photo service, learning images were captured at different screen magnifications, and the accuracy was analyzed by learning each. According to the experimental results, the higher the magnification level, the higher the mAP average to 60%, 67%, and 75%. When the magnification rates of train and test data of the data set were alternately arranged, low magnification data was arranged as train data, and high magnification data was arranged as test data, showing a difference of more than 20% compared to the opposite case. And in the case of drone images with a seasonal difference with a time difference of 4 months, the results of learning the image data at the same period showed high accuracy with an average of 93%, confirming that seasonal differences also affect learning.

• Journal of Advanced Technology Convergence
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• v.2 no.2
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• pp.23-30
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• 2023

This study is a descriptive research study conducted to find out the level of perception of the good death among nursing students and compare sub-factors among the perceptions of a good death. As for the research method, 102 people who explained the purpose of the study and agreed to participate were conveniently recruited. As a research tool, 'Measure of concept of a Good Death' by Schwartz et al. (2003) was translated by Lee (2017), and the research was conducted through online. For data analysis, statistical techniques such as descriptive statistics, frequency analysis, t-test, and one-way ANOVA of the IBM SPSS Statistics 26 program were used. Factors showing average differences in scores for each of the three sub-factors of good death awareness were derived from the experience of clinical practice. The mean of good death (3.13±0.36 points) of nursing students who experienced clinical practice was statistically significantly higher than that of students without clinical practice experience (2.90±0.31 points) (t=3.156, p=.002). In particular, the mean of good death for 'closure' was statistically significantly higher for those with experience in clinical practice (3.46±0.39 points) than those without experience (3.16±0.37 points) (t=3.476, p=.001). Through this study, it was confirmed that nursing students' perception of a good death differed depending on whether or not they were in clinical practice. The results of this study are expected to provide basic data for the establishment of effective educational strategies for the perception of good death in nursing students.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.881-893
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• 2008

The major objective of this study is to investigate the fatigue damage factor evaluation of immovability crossing for railway turnout by the field test and qualitative analysis. From the field test results of the servicing turnout crossing and qualitative analysis with frictional wear which section stiffness decreased, it was evaluated fatigue life of servicing turnout crossing. Most design practices have not taken advantage of the advanced theories in the modern fracture mechanics and finite element analysis due to complexity of analysis as well as the large quantity of vaguely defined parameters in actual designs. This paper considers fatigue problems in turnout crossing using effective analytical and design tools from the field of qualitative constraint reasoning. A set of software modules was developed for fatigue analysis and evaluation, which is easily applicable in engineering practices of designers. The techniques enable the use complex analysis formulations to tackle practical problems with uncertainties, and present the design outcome in two-dimensional design space solution. Appropriate engineering assumptions and judgments in carrying out these procedures, often the most difficult part for practicing engineers, can be partially produced by using qualitative reasoning to define the trends and ranges, interval constraint analysis to derive the controlling parameters, as well as design space to account for practical experience.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.649-659
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• 2006

Recently there has been huge efforts to improve performance in construction process by applying emerging techniques such as the Lean principle and Just-in-time concept. However, little achievement as we expected has come out in reality due to the lack of strategy to set a definite goal of the execution and differences of personal viewpoints on construction productivity. Accordingly, it is the most important to promote the circumstances for the construction process improvement by quantifying the goals of respective unit activity groups. This research explores feasible solutions for the improvement of construction projects performance by combining the six-sigma principle for the generic administrative innovation based on the idea of construction process performance. For this purpose, mutual comparisons of various current approaches are performed in an attempt to establish the advantages in applying six-sigma idea and to provide its fundamental strategy. Furthermore, through a case study with the simulation of applying six-sigma to a unit activity group in construction process, this paper verifies that the overall performance improves as the degree of sigma level gets advanced.

• Smart Media Journal
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• v.12 no.8
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• pp.45-59
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• 2023

Users who want to experience the metaverse for tourism are exposed to strategic planning in space for the purpose of cultural content. In addition, users learn integrated cultural content in the process of proceeding according to the virtual environment. and Along with the meaning of time and space, users will experience space-telling. It is important to induce interest from the beginning of the experience to continue the experience. However, obstacles arise in this process. This is because developers should promote connections with new information to users who do not have sufficient prior knowledge and only have keywords of interest. Therefore, efficient design methods to enhance interest should be studied in advance. But so far, there has been no research on how to systematically design prior organizers to induce interest in virtual space. This study is an interest-inducing design method that occurs in the process of developing the meaning of virtual space and storytelling of cultural content, and can be seen as a basic study using conceptual guidance-based prior organizer education and learning techniques. First, virtual space elements and human behavior theories were considered. Subsequently, five representative examples of previous organizers currently used were explored, and redesigned and proposed based on a conceptual map for information access and delivery purposes. Through this research process, it was possible to confirm that spatial attributes and cognitive interest elements were effectively transmitted to meaningful learning leading to storytelling learning and elements of service design design method through conceptual guidance.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.519-528
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• 2023

The aim of this study was to enhance the flow rate and noise performance of a centrifugal pump in dishwashers by designing an optimized impeller shape through numerical and experimental investigations. To evaluate the performance of the target centrifugal pump, experiment was conducted using a pump performance tester and noise experiment was carried out in a semi-anechoic chamber with microphones and a reflecting wall behind the dishwasher. Through the use of advanced computational fluid dynamics techniques, numerical simulations were performed to analyze the flow and aeroacoustics performance of our target centrifugal pump impeller. To achieve this, numerical simulations were carried out using the Reynolds-Average Navier-Stokes equations and Ffowcs-Willliams and Hawkings equations as governing equations. In order to ensure the validity of numerical methods, a thorough comparison of numerical results with experimental results. After having confirmed the reliability of the current numerical method of this study, the optimization of the target centrifugal pump impeller was conducted. An improvement in flow rate was confirmed numerically, and a manufactured proto-type of the optimized model was used for experimental investigation. Furthermore, it was observed that by applying the fan law, we could effectively reduce noise levels without reducing the flow rate.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.57-62
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• 2023

This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.598-608
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• 2023

To comprehensively grasp the dynamic changes in the coastal terrain and coastal erosion, it is imperative to incorporate temporal and spatial continuity through frequent and continuous monitoring. Recently, there has been a proliferation of research in coastal monitoring using remote sensing, accompanied by advancements in image monitoring and analysis technologies. Remote sensing, typically involves collection of images from aircraft or satellites from a distance, and offers distinct advantages in swiftly and accurately analyzing coastal terrain changes, leading to an escalating trend in its utilization. Remote satellite image-based coastal line detection involves defining measurable coastal lines from satellite images and extracting coastal lines by applying coastal line detection technology. Drawing from the various data sources surveyed in existing literature, this study has comprehensively analyzed encompassing the definition of coastal lines based on satellite images, current status of remote satellite imagery, existing research trends, and evolving landscape of technology for satellite image-based coastal line detection. Based on the results, research directions, on latest trends, practical techniques for ideal coastal line extraction, and enhanced integration with advanced digital monitoring were proposed. To effectively capture the changing trends and erosion levels across the entire Korean Peninsula in future, it is vital to move beyond localized monitoring and establish an active monitoring framework using digital monitoring, such as broad-scale satellite imagery. In light of these results, it is anticipated that the coastal line detection field will expedite the progression of ongoing research practices and analytical technologies.

• Journal of Korean Medicine Rehabilitation
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• v.33 no.4
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• pp.31-44
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• 2023

Objectives The purpose of this study is to check the research trends of pharmacopuncture treatment in nerve entrapment syndrome, identify specific techniques, identify which pharmacopuncture are used, and provide directions for future research. Methods This study was conducted based on the five steps suggested by Arksey and O'Malley. We searched five domestic databases (Research Information Sharing Service, Oriental Medicine Advanced Searching Integrated System, Korean studies Information Service System, Science ON, and KMBASE) and identified studies with key search terms like "nerve entrapment" And "pharmacopuncture" until June 23, 2023. Results Twenty-nine studies were finally selected. among them, 25 papers were non-comparative studies (86.2%). The most common disease was carpal tube syndrome (n=10). All the investigated studies were treated by injecting pharmacopuncture into the pathway of the entraped nerve. The depth of pharmacopuncture injection was mentioned only in 13 studies. As for the pharmacopuncture used, sweet bee venom was 8 studies and bee venom was 6 studies, and about half of the pharmacopuncture manufactured with Bee venom as the main component accounted for. Conclusions This study is a scoping review of the pharmacopuncture treatment for nerve entrapment, which was first conducted in Korea. The treatment is mainly performed on the path way of the entraped nerve. After that, it is necessary to study the standardization of the specific technique method of pharmacopuncture and the uniformity of evaluation criteria.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.597-603
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• 2023

The paradigm of military operations has evolved from platform-centric warfare to network-centric warfare and further to information-centric warfare, driven by advancements in information technology. In recent years, with the development of cutting-edge technologies such as big data, artificial intelligence, and the Internet of Things (IoT), military operations are transitioning towards knowledge-centric warfare (KCW), based on artificial intelligence. Consequently, the military places significant emphasis on integrating advanced information and communication technologies (ICT) to establish reliable C4I (Command, Control, Communication, Computer, Intelligence) systems. This research emphasizes the need to apply data mining techniques to analyze and evaluate various aspects of C4I systems, including enhancing combat capabilities, optimizing utilization in network-based environments, efficiently distributing information flow, facilitating smooth communication, and effectively implementing knowledge sharing. Data mining serves as a fundamental technology in modern big data analysis, and this study utilizes it to analyze real-world cases and propose practical strategies to maximize the efficiency of military command and control systems. The research outcomes are expected to provide valuable insights into the performance of C4I systems and reinforce knowledge-centric warfare in contemporary military operations.