• Journal of Veterinary Science
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• v.21 no.4
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• pp.55.1-55.11
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• 2020

Background: Computed tomography urography (CTU), based on the excretion of contrast medium after its injection, allows visualization of the renal parenchyma and the renal collecting system. Objectives: To determine the optimal contrast medium dose allocation ratio to apply in split-bolus CTU in dogs. Methods: This prospective, experimental, exploratory study used 8 beagles. In 3-phase CTU, unenhanced-, nephrographic-, and excretory-phase images were obtained with a single injection of 600 mg iodine/kg iohexol. In split-bolus CTU, two different contrast medium allocation ratios (30% and 70% for split CTU 1; 50% and 50% for split CTU 2) were used. Unenhanced phase image and a synchronous nephrographic-excretory phase image were acquired. Results: Although the attenuation of the renal parenchyma was significantly lower when using both split CTUs than the 3-phase CTU, based on qualitative evaluation, the visualization score of the renal parenchyma of split CTU 1 was as high as that of the 3-phase CTU, whereas the split CTU 2 score was significantly lower than those of the two others. Artifacts were not apparent, regardless of CTU protocol. The diameter and opacification of the ureter in both split CTUs were not significantly different from those using 3-phase CTU. Conclusions: Split-bolus CTU with a contrast medium allocation ratio of 30% and 70% is feasible for evaluating the urinary system and allows sufficient enhancement of the renal parenchyma and appropriate distention and opacification of the ureter, with similar image quality to 3-phase CTU in healthy dogs. Split-bolus CTU has the advantages of reducing radiation exposure and the number of CT images needed for interpretation.

• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.171-184
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• 2023

Purpose: First, this paper suggests an alternative approach to find optimal portfolio (stocks, bonds and ESG stocks) under the maximizing utility of investors. Second, we include ESG stocks in our optimal portfolio, and compare improvement of welfares in the case with and without ESG stocks in portfolio. Methods: Our main method of analysis follows Brennan et al(2002), designed under the continuous time framework. We assume that the dynamics of stock price follow the Geometric Brownian Motion (GBM) while the short rate have the Vasicek model. For the utility function of investors, we use the Power Utility Function, which commonly used in financial studies. The optimal portfolio and welfares are derived in the partial equilibrium. The parameters are estimated by using Kalman filter and ordinary least square method. Results: During the overall analysis period, the portfolio including ESG, did not show clear welfare improvement. In 2017, it has slightly exceeded this benchmark 1, showing the possibility of improvement, but the ESG stocks we selected have not strongly shown statistically significant welfare improvement results. This paper showed that the factors affecting optimal asset allocation and welfare improvement were different each other. We also found that the proportion of optimal asset allocation was affected by factors such as asset return, volatility, and inverse correlation between stocks and bonds, similar to traditional financial theory. Conclusion: The portfolio with ESG investment did not show significant results in welfare improvement is due to that 1) the KRX ESG Leaders 150 selected in our study is an index based on ESG integrated scores, which are designed to affect stability rather than profitability. And 2) Korea has a short history of ESG investment. During the limited analysis period, the performance of stock-related assets was inferior to bond assets at the time of the interest rate drop.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1076-1088
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• 1997

Data repliciation techniques of distributed database a allocation methods occures to overhead to change together all repkicas for consistency maintenance at updates .In case of data migration horizontal or vertical fragment migration has caused to caused to increase data communication.In this paper we purpose batch proxessing method groups the associated items of table and stores temporary table assciated with file relication and migrations.This method increase the usagility of system buffer in distributed trancsaction processing with a number of data inputs and updates.After all,it improved the perform-ance of distributed transaction system by reducing disk I\O processing time and the cost of data cimmunication among local sites.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3823-3840
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• 2020

Recently, auto-encoder has emerged as the most popular method in convolutional neural network (CNN) based image compression and has achieved impressive performance. In the traditional auto-encoder based image compression model, the encoder simply sends the features of last layer to the decoder, which cannot allocate bits over different spatial regions in an efficient way. Besides, these methods do not fully exploit the contextual information under different receptive fields for better reconstruction performance. In this paper, to solve these issues, a novel auto-encoder model is designed for image compression, which can effectively transmit the hierarchical features of the encoder to the decoder. Specifically, we first propose an adaptive bit-allocation strategy, which can adaptively select an importance channel. Then, we conduct the multiply operation on the generated importance mask and the features of the last layer in our proposed encoder to achieve efficient bit allocation. Moreover, we present an additional novel perceptual loss function for more accurate image details. Extensive experiments demonstrated that the proposed model can achieve significant superiority compared with JPEG and JPEG2000 both in both subjective and objective quality. Besides, our model shows better performance than the state-of-the-art convolutional neural network (CNN)-based image compression methods in terms of PSNR.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1549-1554
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• 2018

Recently the design of railway systems have been performed, based on the analysis of operational conditions and service targets, it is to optimize the effectiveness and efficiency of system operation. Many RAMS requirements have been developed to transform operation conditions into system design characteristics. However, our railway industry has not actived the application of RAMS into system design performance. According to short of RAMS application, many technologies that have been developed are not only applied the existing systems that is operating, but also have not succeed to apply for new systems. In order to design the effective and efficient railway systems that are optimized to operation conditions and service targets, a systems approach and RAMS management are necessary in railway development, operation and maintenance. Therefore, in this study, the RAMS performance requirement design methods are discussed. the allocation methods from system level to each devices of subsystems.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.151-159
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• 2015

This article analyzes English abstracts of the articles published in Journal of the Korean Data & Information Science Society using text mining techniques. At first, term-document matrices are formed by various methods and then visualized by social network analysis. LDA (latent Dirichlet allocation) and CTM (correlated topic model) are also employed in order to extract topics from the abstracts. Performances of the topic models are compared via entropy for several numbers of topics and weighting methods to form term-document matrices.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.11
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• pp.2801-2809
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• 1996

Scheduling problems in real-time systems are known to be NP-hard. the heuristic approaches aregenerally aplied to solve a certain class of systems. One of such cases is to allocate periodic tasks to multiprocessors while the moethod assures the requirement of the deadine constraints of real-time systems. The study on the allocation of periodic taks includes RMNF, RMFF, FFDUF and Next-Fit-M algorithms, which make a set of task grups first and then allocate to processors. This papre proposes the various algorithms which are based on the Next-Fit-M. To analyze the four proposed methods, simulation was carried on, in which the sample tasks are randomly generated with the various time intervals. The proposed algorithms reduce the number of processors compared with the conventional methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.2
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• pp.111-119
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• 2017

This paper presents a method to determine the rear steering angle in integrated chassis control with electronic stability control (ESC) and rear wheel steering (RWS). A control yaw moment needed to stabilize a vehicle should be distributed into the tire forces generated by the ESC and RWS. Weighted pseudo-inverse control allocation (WPCA) is adopted to determine the tire forces. Four methods are proposed to calculate the rear wheel steering angle. To validate the proposed methods, a simulation is performed using a vehicle simulation software package, CarSim. The simulation results show that the proposed method for determining the rear wheel steering angle improves the performance of the integrated chassis control.

• The Journal of Korean Medicine
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• v.30 no.5
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• pp.115-126
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• 2009

Objective: By assessing the quality of methodology and synthesis of results of RCTs (Randomized Controlled Clinical Trials) with herbal acupuncture (pharmacopuncture), we hope to help with administrating herbal acupuncture therapy in clinic and conducting RCT with herbal acupuncture. Methods: Reports of RCT conducted in Korea published in medical journals until February 2009 were collected. We surveyed elementary information of RCTs, evaluated randomization, double-blinding, allocation concealment and put together the results of RCTs by seven clinical topics. Results: 38 RCTs with herbal acupuncture were selected, then adequate methods for randomization and allocation concealment were found in 39% and 5% of studies. Complete double-blinding and a clear accounting of all participants were conducted in 42% and 50% of reports. The synthesis of RCTs revealed that herbal acupuncture was useful and effective on degenerative gonarthritis, omarthralgia on cerebrovascular accident, acute ankle sprain, back sprain, neck sprain, headache, rheumatoid arthritis and tennis elbow, generally. Conclusions: Although further improvement in quality of methodology of RCTs with herbal acupuncture is required, clinical usefulness of herbal acupuncture was shown especially on disorders of musculoskeletal system via RCTs.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.521-526
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• 2017

Data format of Big data is diverse and vast, and its generation speed is very fast, requiring new management and analysis methods, not traditional data processing methods. Textual mining techniques can be used to extract useful information from unstructured text written in human language in online documents on social networks. Identifying trends in the message of politics, economy, and culture left behind in social media is a factor in understanding what topics they are interested in. In this study, text mining was performed on online news related to a given keyword using topic - oriented analysis technique. We use Latent Dirichiet Allocation (LDA) to extract information from web documents and analyze which subjects are interested in a given keyword, and which topics are related to which core values are related.