• Journal of the Korean Society of Industry Convergence
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• v.20 no.2
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• pp.105-113
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• 2017

Recently the direct injection diesel engine is the most efficient one available for road vehicles, so this fundamental advantage suggests the compression injection diesel engine are a wise choice for future development efforts. The compression ignition diesel engine, with its bigger compression ratios if compared to the SI engine, offers a higher thermodynamic efficiency, also additionally the diesel engine with its less pumping losses due to the throttled intake charge as in a SI engine has higher fuel economy. But the largest obstacle to the success of this engine is meeting emission standards for Nitric oxides and particulate matter while maintain fuel consumption advantage over currently available engines. Thus its use should be largely promoted, however, diesel engine emits more Nitric oxides and particulate matter than other competing one. There has been a trade-off between PM and NOx, so efforts to reduce NOx have increased PM and vice versa, but trap change this situation and better possibility emerge for treating NOx emission with engine related means, such as injection timing, equivalence ratio, charge composition, and engine speed. The common rail direct injection system is able to adjust the fuel injection timing in a compression ignition engine, so this electronically controlled injection system can reduce the formation of NOx gas without increase in soot. In this study it is designed and used the engine test bed which is installed with turbocharge and intercooler. In addition to equipped using CRDI by controlling injection timing with mapping modulator, it has been tested and analyzed the engine performance, combustion characteristics, and exhaust emission as operating parameters.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.65-73
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• 2019

Recently commercial mixed-reality devices have be launched and a variety of mixed-reality content has produced, but narrow field of view, which appear to be hardware technical limitations, are mentioned as an important issue for hindering immersion and limiting the scope of use. We propose a new innovative system that cooperate multiple beam projectors and a number of mixed reality devices. Using this technology, users can maximize immersion and minimize frustration of narrow viewing angles through 3D object rendering on background of large 2D screens. This system, named BtS (Beyond the Sight), is implemented on a client-server basis and includes the ability to calibrate between devices, share spatial coordinate systems, and synchronize real-time renderings as core modules. In this paper, each configuration module is described in detail and the possibility of its performance and application is shown through the introduction of mixed reality content case created using BtS system.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.159-202
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• 2022

The 'National Research Data Platform' and the 'Bio Research Data Platform' were recently built and each is actively creating an ecosystem. It is built independently based on other metadata standards, which may cause future interoperability issues. The purpose of this study is to propose a basis for metadata interoperability between the two platforms. To this end, the metadata standards of each platform were analyzed, crosswork targets were selected and mapped, and the suitability of the mapped elements was verified through experts in the bio field. And more appropriate mapping elements were recommended to derive metadata elements for datasets and files. Through this, it was possible to confirm the possibility that the metadata of each platform could be semantically linked and the basis for securing interoperability.

• Korean Medical Education Review
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• v.24 no.2
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• pp.128-140
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• 2022

The purpose of this study was to redesign a problem-based learning (PBL) curriculum and compare the differences between the previous and redesigned PBL based on the results of course satisfaction and student assessments. The PBL was redesigned using curriculum design guidelines (including revisions of curriculum objectives, learning components, learning environments, and assessment methods) that were developed based on previous studies and evaluation results. A comparative study was employed using course satisfaction surveys from the previous and redesigned curricula, and a total of 45 students participated. We also compared student assessment results from concept mapping, learning issue reports, modified essay questions, and reflection journals. We identified four key findings. First, we explored the possibility that the redesigned PBL could be implemented by student facilitators without professors as tutors. Second, the redesigned PBL fostered group dynamics that facilitated developing communication skills and collaborative learning through small-group discussions. Third, the new learning elements added in the redesigned PBL made a meaningful contribution to enhancing students' clinical reasoning based on hypothetico-deductive reasoning. Fourth, concept maps in redesigned PBL contained more complex and various nodes and connections, and the levels of the nodes were more appropriate. The implications of this study can provide meaningful preliminary information for redesigning PBL curricula for medical students to develop their essential competencies through PBL.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.248-248
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• 2023

In recent years, the number of landslides in Korea has been increasing due to extreme weather events such as localized heavy rainfall and typhoons. Landslides often occur with debris flows, land subsidence, and earthquakes. They cause significant damage to life and property. 64% of Korea's land area is made up of mountains, the government wanted to predict landslides to reduce damage. In response, the Korea Forest Service has established a 'Landslide Information System' to predict the likelihood of landslides. This system selects a total of 13 landslide factors based on past landslide events. Using the LR technique (Logistic Regression) to predict the possibility of a landslide occurrence and the accuracy is known to be 0.75. However, most of the data used for learning in the current system is on landslides that occurred from 2005 to 2011, and it does not reflect recent typhoons or heavy rain. Therefore, in this study, we will apply a total of six machine learning techniques (KNN, LR, SVM, XGB, RF, GNB) to predict the occurrence of landslides based on the data of Inje, Gangwon-do, which was recently produced by the National Institute of Forest. To predict the occurrence of landslides, it is necessary to process converting landslide events and factors data into a suitable form for machine learning techniques through ArcGIS and Python. In addition, there is a large difference in the number of data between areas where landslides occurred or not. Therefore, the prediction was performed after correcting the unbalanced data using Tomek Links and Near Miss techniques. Moreover, to control unbalanced data, a model that reflects soil properties will use to remove absolute safe areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• Asia Marketing Journal
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• v.15 no.3
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• pp.1-14
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• 2013

Our research brings managerial insights for developing new digital convergence of devices and services. To explain the phenomenon of device and service convergence, we combine two different approaches from separate research fields: a perceptual mapping technique generally used for segmentation in marketing and associative network analysis mobilized to understanding network structure of core and peripheral as well as the information mediating role of nodes in network science. By combining these two approaches, we provide an in-depth analysis of the associations among devices and services by assessing the centrality of device and service nodes in an associative network. This is done by examining the connections between these services and devices as well as investigating the role of mediation in the combined device-service associative network. Our results based on bi-partite network analysis of survey responses from 250 Internet Protocol (IP) television viewers show which device and which service will play the major role in future device and service convergence as well as which characteristics and functionalities have to be incorporated into future convergence. Among the devices, the mobile handset with the betweenness centrality of 0.26 appears to be the device that would lead future device convergence. Among the services, wireless broadband with the betweenness centrality of 0.276 appears to be the service on which future service convergence needs to be developed. This result is quite unexpected, since wireless broadband has a lower penetration rate than other services, such as fixed broadband and cable TV. In addition, we indicate the possibility of converging devices, such as personal digital assistant (PDA) and mobile handset, and services, such as IPTV and mobile Internet, into wireless broadband services in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1345-1352
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• 2023

With the development of virtual reality (VR) and blockchain technology, Metaverse is being used in various fields such as games, education, and social networking. At the same time, shipments of wearable devices such as smartwatches are growing every year, becoming more and more integrated into people's daily lives. This study presents a new possibility of reflecting the user's body signals measured through the combination of the two phenomena in the metaverse character. Various biometric information such as the user's heart rate and amount of exercise collected through the smartwatch are reflected on the character in the metaverse, allowing the user's physical condition to be reflected in the virtual world. Through this, Metaverse is expected to provide a new experience that can be called 'extended reality' beyond simple virtual reality, improve user's satisfaction with Metaverse, and suggest a direction for the development of smartwatches.

• Structural Engineering and Mechanics
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• v.89 no.6
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• pp.617-626
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• 2024

The study investigated the behavior of plain and fibered Ultra-High Performance Concrete (UHPC) beams under varying loading conditions using integrated analysis of the flexure and acoustic emission tests. The loading rate of testing is -0.25 -2 mm/min. It is observed that on increasing loading rate, flexural strength increases, and toughness decreases. The acoustic emission testing revealed that higher loading rates accelerate crack propagation. Fiber effect and matrix cracking are identified as significant contributors to the release of acoustic emission energy, with fiber rupture/failure and matrix cracking showing rate-dependent behavior. Crack classification analysis indicated that the rise angle (RA) value decreased under quasi-static loading. The average frequency (AF) value increased with the loading rate, but this trend reversed under rate-dependent conditions. K-means analysis identified distinct clusters of crack types with unique frequency and duration characteristics at different loading rates. Furthermore, the historic index and signal strength decreased with increasing loading rate after peak capacity, while the severity index increased in the post-peak zone, indicating more severe damage. The sudden rise in the historic index and cumulative signal strength indicates the possibility of several occurrences, such as the emergence of a significant crack, shifts in cracking modes, abrupt failure, or notable fiber debonding/pull-out. Moreover, there is a distinct rise in the number of AE knees corresponding to the increase in loading rate. The crack mapping from acoustic emission testing aligned with observed failure patterns, validating its use in structural health monitoring.