• Korean Medical Education Review
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• 제22권1호
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• pp.32-45
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• 2020

This narrative review introduces global trends in pharmacovigilance (PV) education for healthcare professionals and the status of PV education in Korea. Proactive participation of healthcare professionals, including physicians, pharmacists, and nurses in reporting suspected adverse events is the main driving force for effective operation of the spontaneous adverse event reporting system database, which in turn facilitates early safety signal detection of otherwise unknown suspected adverse events. The World Health Organization recognizes PV education curriculum as a key aspect in promoting awareness of PV and adverse event reporting among healthcare professionals, and multiple studies have demonstrated that PV educational interventions for healthcare professionals have increased overall adverse event reporting. Considering the global trends in PV education, the curriculum in Korean universities still has room for improvement in promoting PV obligation among future healthcare professionals. Further research is needed to develop PV education curriculum. We suggest a three-step project for innovating PV education in Korea to meet the global PV educational standards: a survey to gauge current PV competencies among healthcare professionals, reform of current PV academic curriculum, and evaluation and fine-tuning of the reformed curriculum.

• The Transactions of the Korean Institute of Power Electronics
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• 제6권5호
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• pp.432-437
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• 2001

This paper describes a new developed 3.3KV/4MW class three-level Voltage Source Inverter(VSI), which is equipped with IIMS(Inverter Information Management System) based on the world wide web and with the Virtual operation simulator. The algorithm for motor control is the stator oriented Direct Torque Control(DTC), which works without speed sensor and gives the physically fastest dynamic response. The IIMS have the functions of operation monitoring and data managements. Virtual operation simulator can analyze and tune the system characteristics without main power. Now, this system is under the field test to verify the confidence.

• Journal of Industrial Technology
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• 제25권B호
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• pp.107-114
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• 2005

Digital media was realized by two-dimensional design backup. But, digital medium decides form of architecture, and act as a design tool that can expand area of thinking. With such social change, investigate for digital architecture. And, wish to analyze design process of digital architecture and search the characteristics. Through comparison of digital and analogue, clear up that the digital world had complex and ambivalent attribute. Define digital design process as "Digital continuum" with characteristic of digital architecture and divided in 3-steps of concept - development - representation. Analyzed digital design process of Frank O, Ghery, Peter Eisenman and Greg Lynn on th assumption division. As a result, design concept is starting from three-dimensional thinking instead of existent two-dimensional thinking. And because general work of process was gone by digital media, "mass costomization" was possible. Also, it gave architect new role. Differ with former days, select various variables, should tuning and cording, and emphasize role as coordinator who must select the result. Digital is summoning very radical and epoch-making change in architecture. At center of these change, digital design process asks architect complex thinking and creative concept.

• Lingua Humanitatis
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• 제1권1호
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• pp.141-157
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• 2001

In his discussion of some desirable tuning points in comparative literary studies, Henry H. H. Remark has emphasized the importance of literary approach to other forms of art. Understanding the significance of such a method of comparative literature, the present study focusses on three contemporary Korean poets who have transferred Mark Chagall′s paintings into their poetry: Youngtae Kim, Chunsoo Kim, and Sunghun Lee. They are usually evaluated as surrealist/modernist in our literary circles. In transforming Chagall′s paintings into his poems, Youngtae Kim has incorporated a variety of surrealist mosaic techniques such as montage and collage. The resultant peculiarity of his poetry makes it hard to lay bare the correspondence or similarities between his poetic world and the world of Chagall′s artistry. It is nonetheless possible to see how Kim, as a poet and painter, had interpreted Chagall′s world with a bird′s-eye view of it. Chunsoo Kim′s "Snow Falling on the Village of Chagall" relates specially to one of Chagall′s paintings, "I and My Village." The present study has taken notice of this correlation in sorting out some basic elements of poetic transfiguration. One of the techniques employed in the poem under discussion is that of juxtaposing the Russian village of Chagall and the Korean village the poet visualizes, with the effect of putting two national traditions in contrast. A reading of the poem reveals that it is not so much the result of a detailed analysis of the painting as a revival of its lingering impression as a whole. In Sunghun Lee′s poetry, surrealist techniques are again a hallmark. But his method of transferring the images of the paintings into his poems falls somewhere between those of Youngtae Kim′s and Chunsoo Kim′s: it is akin to the ′bird′s-eye method′ of the former and shares the impressionistic touch with the latter, but at the same time Lee is analytical by disposition and opts for concrete descriptions. ′Love,′ ′farm,′ and ′time′ are the keywords that are brought under discussion in the present study. There is a growing demand in the current international comparative literary studies for broadening the area of comparative literature. This study hopes to be a small contribution to endorsing the importance of comparative approach to fine arts.

• Journal of the Korea Computer Graphics Society
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• 제29권3호
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• pp.117-125
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• 2023

In the development of clothing design through virtual simulation, it is essential to minimize the differences between the virtual and the real world as much as possible. The most critical task to enhance the similarity between virtual and real garments is to find simulation parameters that can closely emulate the physical properties of the actual fabric in use. The simulation parameter optimization process requires manual tuning by experts, demanding high expertise and a significant amount of time. Especially, considerable time is consumed in repeatedly running simulations to check the results of applying the tuned simulation parameters. Recently, to tackle this issue, artificial neural network learning models have been proposed that swiftly estimate the results of drape test simulations, which are predominantly used for parameter tuning. In these earlier studies, relatively simple linear stiffness models were used, and instead of estimating the entirety of the drape mesh, they estimated only a portion of the mesh and interpolated the rest. However, there is still a scarcity of research on non-linear stiffness models, which are commonly used in actual garment design. In this paper, we propose a learning model for estimating the results of drape simulations for non-linear stiffness models. Our learning model estimates the full high-resolution mesh model of drape. To validate the performance of the proposed method, experiments were conducted using three different drape test methods, demonstrating high accuracy in estimation.

• Journal of Korea Multimedia Society
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• 제23권8호
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• pp.953-964
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• 2020

Ever since media contents took over the world, the importance of typography has increased, and the influence of fonts has be n recognized. Nevertheless, the current Hangul font system is very poor and is provided passively, so it is practically impossible to understand and utilize all the shape characteristics of more than six thousand Hangul fonts. In this paper, the characteristics of Hangul font shapes were selected based on the Hangul structure of similar fonts. The stroke element detection training was performed by fine tuning Faster R-CNN Inception v2, one of the deep learning object detection models. We also propose a system that automatically extracts the stroke element characteristics from characters by introducing an automatic extraction algorithm. In comparison to the previous research which showed poor accuracy while using SVM(Support Vector Machine) and Sliding Window Algorithm, the proposed system in this paper has shown the result of 10 % accuracy to properly detect and extract stroke elements from various fonts. In conclusion, if the stroke element characteristics based on the Hangul structural information extracted through the system are used for similar classification, problems such as copyright will be solved in an era when typography's competitiveness becomes stronger, and an automated process will be provided to users for more convenience.

• The Journal of the Korea institute of electronic communication sciences
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• 제17권3호
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• pp.483-490
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• 2022

Malaria is a disease caused by a parasite and it is prevalent in all over the world. The usual method used to recognize malaria cells is a thick and thin blood smears examination methods, but this method requires a lot of manual calculation, so the efficiency and accuracy are very low as well as the lack of pathologists in impoverished country has led to high malaria mortality rates. In this paper, a malaria cell image recognition model using transfer learning is proposed, which consists in the feature extractor, the residual structure and the fully connected layers. When the pre-training parameters of the VGG-19 model are imported to the proposed model, the parameters of some convolutional layers model are frozen and the fine-tuning method is used to fit the data for the model. Also we implement another malaria cell recognition model without residual structure to compare with the proposed model. The simulation results shows that the model using the residual structure gets better performance than the other model without residual structure and the proposed model has the best accuracy of 97.33% compared to other recent papers.

• Archives of design research
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• 제15권1호
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• pp.257-266
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• 2002

Modern Society is tuning to the wide organized social structure with highly varieties. To the cultural aspects in these days of the late-indusoial society, due to the post-modernism. This kind of trend was found in overall fields of studies. Therefore, the post-modernism is to be a kind of a modern spirit ruling over the late 20th century. Post-modernism is a vague expression, that was begun to appear in various artistic intellectual, ideologic trends with a repulsion of modern design after the World War II. The present age as a modern society slews a distinguished mark of undifferentiation disorganization and relaxation, disassembling of social structure. With the study on the background of occurrence, character and philosophy for the post-modernism, the theoretical background of post-modernism could be seen. According to the influence of post-modernism, the minimalism, retro-design, kitsch-design, deconstructionism-design deconstructionism-design, new materia1-design and cyber-design shown on each trend of modern industrial design were studied.

• KIPS Transactions on Software and Data Engineering
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• 제11권4호
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• pp.179-188
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• 2022

There have been many successful researches on a bearing fault diagnosis based on Deep Learning, but there is still a critical issue of the data distribution difference between training data and test data from their different working conditions causing performance degradation in applying those methods to the machines in the field. As a solution, a data adaptation method has been proposed and showed a good result, but each and every approach is strictly limited to a specific applying scenario or presupposition, which makes it still difficult to be used as a real-world application. Therefore, in this study, we have proposed a method that, using a data transformation with MFCCs and a simple CNN architecture, can perform a robust diagnosis on a target domain data without an additional learning or tuning on the model generated from a source domain data and conducted an experiment and analysis on the proposed method with the CWRU bearing dataset, which is one of the representative datasests for bearing fault diagnosis. The experimental results showed that our method achieved an equal performance to those of transfer learning based methods and a better performance by at least 15% compared to that of an input transformation based baseline method.

• KIPS Transactions on Software and Data Engineering
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• 제8권12호
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• pp.491-498
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• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.