• Korea Journal of Hospital Management
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• v.17 no.4
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• pp.21-31
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• 2012

This is a case study of Gangnam S University Hospital applying a par level transfer system for reagent materials. The purpose of this study is evaluated on the cutting down on inventory expenses and medical service revenue in the point of resource based view. The data was acquired through the financial statement of Gangnam S Hospital for the fiscal year 2008, 2009, 2010 and 2011, and compared with the Korea health industry statistics index for hospital accounts based on the materials in Korea Health Industry Development Institute. The results of the study are as follows. Medical reagent materials expenditure cut down as 305 million won through 2009 fiscal year. Medical profits for the Gangnam S University hospital's income statement in 2011 show well over acquired 3.37 billion won through the enlarged diagnostic test numbers. In conclusion, Gangnam S University Hospital health statistics's index shows very high profits. The results of this study have some limitations in terms of generalization as only one hospital in Seoul. Further studies with relationship inventory performance and enlarged reagent materials are expected in this area.

• Smart Media Journal
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• v.9 no.3
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• pp.80-89
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• 2020

Out - of - distribution (OOD) samples are frequently encountered when deploying a classification model in plenty of real-world machine learning-based applications. Those samples are normally sampling far away from the training distribution, but many classifiers still assign them high reliability to belong to one of the training categories. In this study, we address the problem of removing OOD examples by estimating marginal density estimation using variational autoencoder (VAE). We also investigate other proper methods, such as temperature scaling, Gaussian discrimination analysis, and label smoothing. We use Chonnam National University (CNU) weeds dataset as the in - distribution dataset and CIFAR-10, CalTeach as the OOD datasets. Quantitative results show that the proposed framework can reject the OOD test samples with a suitable threshold.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1057-1070
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• 2021

Case-related news filtering is crucial in legal text mining and divides news into case-related and case-unrelated categories. Because case-related news originates from various fields and has different writing styles, it is difficult to establish complete filtering rules or keywords for data collection. In addition, the labeled corpus for case-related news is sparse; therefore, to train a high-performance classification model, it is necessary to annotate the corpus. To address this challenge, we propose topic-enhanced positive-unlabeled learning, which selects positive and negative samples guided by topics. Specifically, a topic model based on a variational autoencoder (VAE) is trained to extract topics from unlabeled samples. By using these topics in the iterative process of positive-unlabeled (PU) learning, the accuracy of identifying case-related news can be improved. From the experimental results, it can be observed that the F1 value of our method on the test set is 1.8% higher than that of the PU learning baseline model. In addition, our method is more robust with low initial samples and high iterations, and compared with advanced PU learning baselines such as nnPU and I-PU, we obtain a 1.1% higher F1 value, which indicates that our method can effectively identify case-related news.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1261-1270
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• 2022

This study was conducted to investigate the possibility of using gaze entropy to evaluate an operator's situation awareness in an emergency accident situation of a nuclear power plant. Gaze entropy can be an effective measure for evaluating an operator's situation awareness at a nuclear power plant because it can express gaze movement as a single comprehensive number. In order to determine the relationship between situation awareness and gaze entropy for an emergency accident situation of a nuclear power plant, an experiment was conducted to measure situation awareness and gaze entropy using simulators created for emergency accident situations LOCA, SGTR, SLB, and LOV. The experiment was to judge the accident situation of nuclear power plants presented in the simulator. The results showed that situation awareness and Shannon, dwell time, and Markov entropy had a significant negative correlation, while visual attention entropy (VAE) did not show any significant correlation with situation awareness. The results determined that Shannon entropy, dwell time entropy, and Markov entropy could be used as measures to evaluate situation awareness.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.84-89
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• 2023

In recent years, with the breakthrough of Artificial Intelligence (AI) technology in deep learning algorithms such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAE), AI generation technology has rapidly expanded in various sub-sectors in the art field. 2022 as the explosive year of AI-generated art, especially in the creation of AI-generated art creative design, many excellent works have been born, which has improved the work efficiency of art design. This study analyzed the application design characteristics of AI generation technology in two sub fields of artistic creative design of AI painting and AI animation production , and compares the differences between traditional painting and AI painting in the field of painting. Through the research of this paper, the advantages and problems in the process of AI creative design are summarized. Although AI art designs are affected by technical limitations, there are still flaws in artworks and practical problems such as copyright and income, but it provides a strong technical guarantee in the expansion of subdivisions of artistic innovation and technology integration, and has extremely high research value.

• Structural Engineering and Mechanics
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• v.63 no.3
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• pp.317-327
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• 2017

The addition of different types of polymers such as SBR, VAE, Acrylic, etc. in concrete and mortar leads to an increase in compressive, tensile and bond strength and decrease in permeability of polymer modified mortar (PMM) and concrete (PMC). The improvement in properties such as bond strength and impermeability makes PMM/PMC suitable for use as repair/retrofitting and water proofing material. In the present study effect of addition of fluoropolymer on the strength and permeability properties of mortar has been studied. In the cement mortar different percentages viz. 10, 20 and 30 percent of fluoropolymer by weight of cement was added. It has been observed that on addition of fluoropolymer in mortar the workability of mortar increases. In the present study all specimens were cast keeping the workability constant, i.e., flow value $105{\pm}5mm$, by changing the amount of water content in the mortar suitably. The specimens were cured for two different curing conditions. Firstly, these were cured wet for one day and then cured dry for 27 days. Secondly, specimens were cured wet for 7 days and then cured dry for 21 days. It has been observed that compressive strength and split tensile strength of specimens cured wet for 7 days and then cured dry for 21 days is 7-13 percent and 12-15 percent, respectively, higher than specimens cured one day dry and 27 days wet. The sorptivity of fluoropolymer modified mortar decreases by 88.56% and 91% for curing condtion one and two, respectively. However, It has been observed that on addition of 10 percent fluoropolymer both compressive and tensile strength decreases, but with the increase in percentage addition from 10 to 20 and 30 percent both the strengths starts increasing and becomes equal to that of the control specimen at 30 percent for both the curing conditions. It is further observed that percentage decrease in strength for second curing condition is relatively less as compared to the first curing condition. However, for both the curing conditions chloride ion permeability of polymer modified mortar becomes very low.

• The Journal of Korean Physical Therapy
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• v.14 no.1
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• pp.27-37
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• 2002

This is the study of the knee joint injured patients at the orthopaedic surgery clinic where is located in Daejon, who has MCL combine injured ACL reconstruction caused by sport activity and accident during the period from Jan. 2001 to Oct. 2001. By comparing with groups between 7th case of I-group for MCL combined stitch and II-group for ACL reconstruction since 6weeks cast. We have been concluded with that following results. 1. Range of motion for the knee was not limited at 5th case(37%) of I-group, 6th case(42%) of II-group and the cases of Flexion deficit less then 10 -degree were 2nd case(13%) of I-group and II-group 1st case(8%) with no extension deficit more then 5 -degree. 2. The level of activity that tells you whether you are capable of exercise for six month after operation. It han been divided by 3 levels. The case of capable of doing low risk exercise(swimming, cycling, etc.) was 5th case of I-group, the case of capable of doing medium risk exercise(jogging, etc.) was 3rd case of I-group and 4th case of II-group and the case of capable of doing high risk exercise(football, etc.) were 3rd case of I-group and 3rd case of II-group. 3. The timing of the return to their job were average 6.4 weeks for I-group and average 22.9 weeks for II-group(P<.05, statistical difference). 4. There was no statistical difference between I-group and II-group for the timing of the return to their job(P>.05). 5. By using VAS to compare them there was no statistical difference between I-group and II-group of clinical results according to Lysholm scale.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.133-142
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• 2023

The large process plant is currently implementing predictive maintenance technology to transition from the traditional Time-Based Maintenance (TBM) approach to the Condition-Based Maintenance (CBM) approach in order to improve equipment maintenance and productivity. The traditional techniques for predictive maintenance involved managing upper/lower thresholds (Set-Point) of equipment signals or identifying anomalies through control charts. Recently, with the development of techniques for big analysis, machine learning-based AAKR (Auto-Associative Kernel Regression) and deep learning-based VAE (Variation Auto-Encoder) techniques are being actively applied for predictive maintenance. However, this predictive maintenance techniques is only effective during steady-state operation of plant equipment, and it is difficult to apply them during start-up and shutdown periods when rises or falls. In addition, unlike processes such as nuclear and thermal power plants, which operate for hundreds of days after a single start-up, because the pumped power plant involves repeated start-ups and shutdowns 4-5 times a day, it is needed the prediction and alarm algorithm suitable for its characteristics. In this study, we aim to propose an approach to apply the optimal predictive alarm algorithm that is suitable for the characteristics of Pumped Storage Power Plant(PSPP) facilities to the system by analyzing the predictive maintenance techniques used in existing nuclear and coal power plants.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.500-510
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• 2023

Passive sonar signals mainly contain both normal and abnormal signals. The abnormal signals mixed with normal signals are primarily detected using an AutoEncoder (AE) that learns only normal signals. However, existing AEs may perform inaccurate detection by reconstructing distorted normal signals from mixed signal. To address these limitations, we propose an abnormal signal detection model based on a Recurrent Neural Network (RNN) and vector quantization. The proposed model generates a codebook representing the learned latent vectors and detects abnormal signals more accurately through the proposed search process of code vectors. In experiments using publicly available underwater acoustic data, the AE and Variational AutoEncoder (VAE) using the proposed method showed at least a 2.4 % improvement in the detection performance and at least a 9.2 % improvement in the extraction performance for abnormal signals than the existing models.

• Korean journal of applied entomology
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• v.36 no.4
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• pp.351-356
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• 1997

Biological control of forest insect pests, Agelastica coeruleci, Meganola n~elancholia,a nd Glyphodes perspectalis, turfgrass insect pest, Blitoperfhu orientr~lis,v egetable insect pests, Plutella xylostella and Agrotis segetun~ with entomopathogenic fungus, Beciuveria hassinna GY 1 - 17 isolated from rice paddy of Yangsan in the southern part of Korea were investigated. Mortalities of A. coeruleu and P. ~ylo.~rellluar vae were 100% at the rate of 7.0 and 2.0 x 107conidia/ml after 7 and 5 days and those of M. melancholia were 66.7 - 100% at the rate of 0.03875-3.1 X 107conidia/ml. However, G. perspectulis was not affected at the rate of 2.0 x lo7 to X I04conidia/ml. And mortalites of B. orientcilis and A. segetum larvae were 46.7% at 3.7 x 107conidia/ml and 63.3% at 2.5 X 107conidia/ml.