• Knowledge Management Research
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• v.24 no.3
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• pp.217-237
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• 2023

Recently, in the face of successive and unexpected global economic risks, ESG(Environmental, Social, and Governance) management has risen as an essential survival strategy for businesses. Particularly, the supply chain disruptions due to the COVID-19 pandemic have added to the uncertainty of risks, heightening the importance of ESG management in the distribution industry. In this context, the role of blockchain technology in strengthening and managing the connection between the distribution industry and ESG management has become increasingly significant. While there have been extensive proposals for business models that integrate blockchain technology into distribution, few studies have specifically focused on the feasibility and effectiveness of applying blockchain to ESG management in this field. Therefore, this study analyzed the relationship between blockchain and ESG management in the distribution industry by employing association analysis, a text mining technique, on Korean academic research. Through this, the study confirmed the possibility of implementing blockchain in the distribution industry's ESG management and presented keywords to guide future research directions. The findings obtained from this study are expected to be utilized as foundational research for future studies in constructing blockchain-based business models for ESG management in the distribution industry.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.69-78
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• 2010

Spectral modeling synthesis (SMS) has been used as a powerful tool for musical sound modeling. This technique considers a sound as a combination of a deterministic plus a stochastic component. The deterministic component is represented by the series of sinusoids that are described by amplitude, frequency, and phase functions and the stochastic component is represented by a series of magnitude spectrum envelopes that functions as a time varying filter excited by white noise. These representations make it possible for a synthesized sound to attain all the perceptual characteristics of the original sound. However, sometimes considerable phase variations occur in the deterministic component by using the conventional SMS for the complex sound such as whale sounds when the partial frequencies in successive frames differ. This is because it utilizes the calculated phase to synthesize deterministic component of the sound. As a result, it does not provide a good spectrum matching between original and synthesized spectrum in higher frequency region. To overcome this problem, we propose a modified SMS that provides good spectrum matching of original and synthesized sound by calculating complex residual spectrum in frequency domain and utilizing original phase information to synthesize the deterministic component of the sound. Analysis and simulation results for synthesizing whale sounds suggest that the proposed method is comparable to the conventional SMS in both time and frequency domain. However, the proposed method outperforms the SMS in better spectrum matching.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.485-492
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• 2009

The thermal fatigue crack(TFC) is one of the life-limiting mechanisms at the nuclear power plant operating conditions. In order to evaluate the structural integrity, various non-destructive test methods such as radiographic test, ultrasonic test and eddy current are used in the industrial field. However, these methods have restrictions that defect detection is possible after the crack growth. For this reason, acoustic emission testing(AET) is becoming one of powerful inspection methods, because AET has an advantage that possible to monitor the structure continuously. Generally, every mechanism that affects the integrity of the structure or equipment is a source of acoustic emission signal. Therefore the noise filtering is one of the major works to the almost AET researchers. In this study, acoustic emission signal was collected from the pipes which were in the successive thermal fatigue cycles. The data were filtered based on the results from previous experiments. Through the data analysis, the signal characteristics to distinguish the effective signal from the noises for the TFC were proven as the waveform difference. The experiment results provide preliminary information for the acoustic emission technique to the continuous monitoring of the structure failure detection.

• Horticultural Science & Technology
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• v.29 no.2
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• pp.81-86
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• 2011

The effects of girdling on fruit quality and cold resistance of 'Kyoho' grapes were investigated. Girdling treatment was conducted on the trunk at 10 cm above ground with 1 cm width and grapes were harvested at 90 and 110 days after full bloom to compare the fruit quality. First harvesting rate in girdling treatment was higher than that in non-girdling treatment and coloration was also higher in girdled vines at the final harvest. In other words, coloring process of grape was promoted and enhanced by girdling, but this effect of coloring improvement was decreased after successive girdling treatment. Fruit quality showed no difference between the treated and non-treated berries, but fruit cracking rate was lower in girdled treated berries. Girdled trees were weakened and suffered from freezing damage. Especially, most grapevines withered up after being girdled for three consecutive years. Although girdling had effect on improving the berry coloring significantly, the effect wore off with continuous girdling. And it was possible that consecutive girdling leaded to wither and growth suppression especially in grapevines. These adverse effects may make the continuous girdling technique unsuitable in practice for 'Kyoho' grape.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.983-993
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• 2021

Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.444-453
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• 2003

Recently, a great interest of bio-technology(BT) is concentrated and the image analysis technique for electrophoresis gels is highly requested to analyze genetic information or to look for some new bio-activation materials. For this purpose, the location and quantity of each band in a lane should be measured. In most of existing techniques, the approach of peak searching in a profile of a lane is used. But this peak is improper as the representative of a band, because its location does not correspond to that of the brightest pixel or the center of gravity. Also, it is improper to measure band quantity in most of these approaches because various enhancement processes are commonly applied to original images to extract peaks easily. In this paper, we adopt an approach to measure accumulated brightness as a band quantity in each band region, which Is extracted by not using any process of changing relative brightness, and the gravity center of the region is calculated as a band location. Actually, we first extract lanes with an entropy-based threshold calculated on a gel-image histogram. And then, three other methods are proposed and applied to extract bands. In the MER method, peaks and valleys are searched on a vertical search line by which each lane is bisected. And the minimum enclosing rectangle of each band is set between successive two valleys. On the other hand, in the RG-1 method, each band is extracted by using region growing with a peak as a seed, separating overlapped neighbor bands. In the RG-2 method, peaks and valleys are searched on two vertical lines by which each lane is trisected, and the left and right peaks nay be paired up if they seem to belong to the same band, and then each band region is grown up with a peak or both peaks if exist. To compare above three methods, we have measured the location and amount of bands. As a result, the average errors in band location of MER, RG-1, and RG-2 were 6%, 3%, and 1%, respectively, when the lane length is normalized to a unit value. And the average errors in band amount were 8%, 5%, and 2%, respectively, when the sum of band amount is normalized to a unit value. In conclusion, RG-2 was shown to be more reliable in the accuracy of measuring the location and amount of bands.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.30 no.2
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• pp.130-141
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• 2012

This study examines the characteristics of landscape elements and the reappearance techniques of traditional landscape image in Chinatown of the Shanghai Street in Busan, Korea. The subjects of the study are commercial buildings owned by Chinese residents, commercial buildings' naming design and environmental sculptures in the Shanghai Street. The results are as follows: First, the design methods of the front side of commercial buildings were classified into two parts: facede design of buildings and signboard design. The design form of the buildings' facades were classified into five types, there are: emphasis type on Chinese characters' signboard, addition type on decorative signboard, introduction type of traditional patterns, imitation type of traditional architectures and modern architectures' modes. The signs of chinese commercial buildings were observed mostly as having a traditional Chinese font in yellow/white on a red background. It has been found that this style was the most popular method of sign design. Secondly, The commercial buildings' naming design was analyzed into design methods and meanings. Design methods were classified into three types: a combination of meaning and place, a combination of season and atmosphere and tourist attractions. The meaning of the commercial buildings' names was divided into three kinds: the wishes of the prosperity, elegant type and the appropriation of local attractions. Thirdly, the environmental sculptures of Shanghai Street were found to have been influenced by both through out Chinese culture with mixed Korean culture. Finally, as for characteristics of landscape elements, we found three reappearance techniques - addition, replacement, juxtaposition. The technique of addition is added new face to the base map by just two methods - extending and overlapping area. Replacement is created new faces from base map by the action of replacing, it has three types - local replacement, package replacement, successive replacement. Juxtaposition is the fact of two or more things placed together with contrasting effect, it also has three types - the same kind juxtaposition, a different kind juxtaposition, topological juxtaposition. This study is the basic research which is analyzing the landscape design in chinatown. But the research only on Shanghai Street may have some limits in scope. It is considered an necessary study to add, which is about chinatown in other city such as Incheon, Jeonju. Then it is expected that the results of this study can be used for the basic data of the landscape plans, that municipalities are actively progressing their respective development projects of Chinatown.

• Economic and Environmental Geology
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• v.46 no.6
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• pp.485-494
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• 2013

$CO_2$ Monitoring, Mitigation and Verification (MMV) is the essential part in the Carbon Capture and Storage (CCS) project in order to assure the storage permanence economically and environmentally. In large-scale CCS projects in the world, the seismic time-lapse survey is a key technology for monitoring the behavior of injected $CO_2$. In this study, we developed a basic process procedure for 3-D seismic baseline data from the Aquistore project, Estevan, Canada. Major target formations of Aquistore CCS project are the Winnipeg and the Deadwood sandstone formations located between 1,800 and 1,900 ms in traveltime. The analysis of trace energy and similarity attributes of seismic data followed by spectral decomposition are carried out for the characterization of $CO_2$ injection zone. High trace energies are concentrated in the northern part of the survey area at 1,800 ms and in the southern part at 1,850 ms in traveltime. The sandstone dominant regions are well recognized with high reflectivity by the trace energy analysis. Similarity attributes show two structural discontinuities trending the NW-SE direction at the target depth. Spectral decomposition of 5, 20 and 40 Hz frequency contents discriminated the successive E-W depositional events at the center of the research area. Additional noise rejection and stratigraphic interpretation on the baseline data followed by applying appropriate imaging technique will be helpful to investigate the differences between baseline data and multi-vintage monitor data.