• Environmental and Resource Economics Review
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• v.20 no.4
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• pp.761-796
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• 2011

The purpose of this paper is to derive fuel mix of electricity generating system with the lowest cost considering energy security and climate change mitigations as the target of energy policy. Energy Security Price Index(ESPI), based on the measure of market concentration in fossil fuel market and political risk of exporting countries, is chosen to assess the level of energy security. The methodology of Energy Conservation Supply Curve(CSC) is applied to fuel mix to meet the carbon emission mitigation through increasing the alternatives participation and introduction of new technologies. These also represent an improvement on the level of energy security, having the complementarity between two objectives. The alternative measure for improving energy security is exploration and production(E&P) of fossil fuel for energy sufficiency. Fuel mix of electricity generating system to achieve certain objectives in 2020 can be derived with the lowest cost considering energy security and carbon emission mitigations.

• The KIPS Transactions:PartA
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• v.9A no.1
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• pp.75-82
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• 2002

A robust signal transition density propagation method for a zero delay model is presented to obtain the signal transition density for estimating the power consumption. The power estimation for the zero delay model is a proper criteria for the lower boundary of power consumption. Since the input characteristics are generally unknown at design stage, robust estimation for wide range input characteristics is very important for the power consumption. In this paper, a conventional transition estimation method will be explored. And this exploration will be analyzed with the input/output signal transition behavior and used to propose the robust signal transition density propagation for the power estimation. In order to apply to practical circuits, the reconvergent path, which is crucial to affect the exactness of the power estimation, will be studied and an algorithm to take the reconvergent path into consideration will be presented. In experiment, the proposed methodology shows better robustness, comparable accuracy and elapsed time compared to the conventional methods.

• STI Policy Review
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• v.8 no.2
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• pp.75-93
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• 2017

Recently, global competition in the manufacturing sector is driving firms in the manufacturing sector to conduct product innovation projects to maintain their competitive edge. The key points of product innovation projects are 1) what the purpose of the project is and 2) what expected results in the target market can be achieved by implementing the innovation. Therefore, this study focuses on the performance of innovation projects with a business viewpoint. In this respect, this study proposes the "achievement rate" of product innovation projects as a measurement of project performance. Then, this study finds the best strategies from various innovation activities to optimize the achievement rate of product innovation projects. There are three major innovation activities for the projects, including three types of R&D activities: Internal, joint and external R&D, and five types of non-R&D activities - acquisition of machines, equipment and software, purchasing external knowledge, job education and training, market research and design. This study applies decision tree modeling, a kind of data-mining methodology, to explore effective innovation activities. This study employs the data from the 'Korean Innovation Survey (KIS) 2014: Manufacturing Sector.' The KIS 2014 gathered information about innovation activities in the manufacturing sector over three years (2011-2013). This study gives some practical implication for managing the activities. First, innovation activities that increased the achievement rate of product diversification projects included a combination of market research, new product design, and job training. Second, our results show that a combination of internal R&D, job training and training, and market research increases the project achievement most for the replacement of outdated products. Third, new market creation or extension of market share indicates that launching replacement products and continuously upgrading products are most important.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.145-159
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• 2020

Because of the recent development of information and communication technology, companies are exposed to various media such as blogs, social media, and YouTube. In particular, exposed news affects the company's reputation. So, while positive news can improve corporate value, negative news can lead to financial losses for the company. In this study, we redefine corporate reputation as social responsibility, vision and leadership, financial performance, products and services through existing literature, and conducted an AHP survey with a total of four components to calculate the weight of each factor. As a result of the calculation, the proportion of financial performance was the highest at 0.41, and products and services, vision and leadership, and social responsibility were the lowest. In addition, in order to measure the reputation of a company, it is classified as a component that defines online news using the LDA technique. In addition, through sentiment analysis, an index for each corporate reputation factor was derived, and the reputation index was calculated by combining it with the AHP analysis result, and Spearman ranking correlation analysis was performed to secure the validity of the research results. Therefore, the significance of this study is that the definition and importance of the constituent factors can contribute to the future planning and development direction of the company, and also contribute to the derivation of the corporate reputation index. This study is significant in that a new analysis methodology that applied AHP analysis results to sentiment analysis was suggested.

• Journal of Microbiology and Biotechnology
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• v.32 no.2
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• pp.176-186
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• 2022

Continued fenvalerate use has caused serious environmental pollution and requires large-scale remediation. Dibutyl phthalate (DBP) was discovered in fenvalerate metabolites degraded by Citrobacter freundii CD-9. Coculturing is an effective method for bioremediation, but few studies have analyzed the degradation pathways and potential mechanisms of cocultures. Here, a DBP-degrading strain (BDBP 071) was isolated from soil contaminated with pyrethroid pesticides (PPs) and identified as Stenotrophomonas acidaminiphila. The optimum conditions for DBP degradation were determined by response surface methodology (RSM) analysis to be 30.9 mg/l DBP concentration, pH 7.5, at a culture temperature of 37.2℃. Under the optimized conditions, approximately 88% of DBP was degraded within 48 h and five metabolites were detected. Coculturing C. freundii CD-9 and S. acidaminiphila BDBP 071 promoted fenvalerate degradation. When CD-9 was cultured for 16 h before adding BDBP 071, the strain inoculation ratio was 5:5 (v/v), fenvalerate concentration was 75.0 mg/l, fenvalerate was degraded to 84.37 ± 1.25%, and DBP level was reduced by 5.21 mg/l. In addition, 12 fenvalerate metabolites were identified and a pathway for fenvalerate degradation by the cocultured strains was proposed. These results provide theoretical data for further exploration of the mechanisms used by this coculture system to degrade fenvalerate and DBP, and also offer a promising method for effective bioremediation of PPs and their related metabolites in polluted environments.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.346-356
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• 2022

The jurisprudential legal rules govern the way Muslims react and interact to daily life. This creates a huge stream of questions, that require highly qualified and well-educated individuals, called Muftis. With Muslims representing almost 25% of the planet population, and the scarcity of qualified Muftis, this creates a demand supply problem calling for Automation solutions. This motivates the application of Artificial Intelligence (AI) to solve this problem, which requires a well-designed Question-Answering (QA) system to solve it. In this work, we propose a QA system, based on retrieval augmented generative transformer model for jurisprudential legal question. The main idea in the proposed architecture is the leverage of both state-of-the art transformer models, and the existing knowledge base of legal sources and question-answers. With the sensitivity of the domain in mind, due to its importance in Muslims daily lives, our design balances between exploitation of knowledge bases, and exploration provided by the generative transformer models. We collect a custom data set of 850,000 entries, that includes the question, answer, and category of the question. Our evaluation methodology is based on both quantitative and qualitative methods. We use metrics like BERTScore and METEOR to evaluate the precision and recall of the system. We also provide many qualitative results that show the quality of the generated answers, and how relevant they are to the asked questions.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.127-132
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• 2002

Recent deepwater offshore structures in Gulf of Mexico utilize butt welded tubular joints. Application of welded tubular joint includes tendons, production risers, and steel catenary risers. Fatigue life assessment of these joints becomes more critical because the structures to which they are attached are allowed to undergo cyclic and sometimes large displacements around an anchored position. Estimating the fatigue behavior of these tubular members in the design stage is generally conducted by using S-N curves specified in the codes and standards. Applying the stress concentration factor of the welded structure to S-N approach often results in very conservative assessment because the stress field acting on the tubular has a non-uniform distribution through the thickness. Fracture mechanics and fitness for service (FFS) technology have been applied in the design of the catenary risers. This technology enables the engineer to establish proper requirements on weld quality and inspection acceptance criteria to assure satisfactory structural integrity during its design life. It also provides guidance on proper design curves to be used and a methodology for accounting for the effects of non-uniform stress distribution through the wall thickness. An attempt was made to develop set of S-N curves based on fracture mechanics approach by considering non-uniform stress distribution and a threshold stress intensity factor. Series of S-N curves generated from this approach were compared to the existing S-N curves. For flat plate butt joint, the S-N curve generated from fracture mechanics matches with the IIW class 100 curve when initial crack depth was 0.5 mm (0.02"). Similar comparison with API X′ was made for tubular joint.. These initial crack depths are larger than the limits of inspection by current Non-destructive examination (NDE) means, such as Automatic Ultrasonic Inspection (AUT). Thus a safe approach can be taken by specifying acceptance criteria that are close to limits of sizing capability of the selected NDE method. The comparison illustrates conservatism built into the S-N design curve.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1284-1284
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• 2024

Leveraging large language models and safety accident report data has unique potential for analyzing construction accidents, including the classification of accident types, injured parts, and work processes, using unstructured free text accident scenarios. We previously proposed a novel approach that harnesses the power of fine-tuned Generative Pre-trained Transformer to classify 6 types of construction accidents (caught-in-between, cuts, falls, struck-by, trips, and other) with an accuracy of 82.33%. Furthermore, we proposed a novel methodology, saliency visualization, to discern which words are deemed important by black box models within a sentence associated with construction accidents. It helps understand how individual words in an input sentence affect the final output and seeks to make the model's prediction accuracy more understandable and interpretable for users. This involves deliberately altering the position of words within a sentence to reveal their specific roles in shaping the overall output. However, the validation of saliency visualization results remains insufficient and needs further analysis. In this context, this study aims to qualitatively validate the effectiveness of saliency visualization methods. In the exploration of saliency visualization, the elements with the highest importance scores were qualitatively validated against the construction accident risk factors (e.g., "the 4m pipe," "ear," "to extract staircase") emerging from Construction Safety Management's Integrated Information data scenarios provided by the Ministry of Land, Infrastructure, and Transport, Republic of Korea. Additionally, construction accident precursors (e.g., "grinding," "pipe," "slippery floor") identified from existing literature, which are early indicators or warning signs of potential accidents, were compared with the words with the highest importance scores of saliency visualization. We observed that the words from the saliency visualization are included in the pre-identified accident precursors and risk factors. This study highlights how employing saliency visualization enhances the interpretability of models based on large language processing, providing valuable insights into the underlying causes driving accident predictions.

• Geophysics and Geophysical Exploration
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• v.1 no.1
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• pp.25-30
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• 1998

Time-lapse crosswell seismic data, recorded before and after the cavity filling, showed that the filling increased the velocity at a known cavity zone in an old mine site in Inchon area. The seismic response depicted on the tomogram and in conjunction with the geologic data from drillings imply that the size of the cavity may be either small or filled by debris. In this study, I attempted to evaluate the filling effect by analyzing velocity measured from the time-lapse tomograms. The data acquired by a downhole airgun and 24-channel hydrophone system revealed that there exists measurable amounts of source statics. I presented a methodology to estimate the source statics. The procedure for this method is: 1) examine the source firing-time for each source, and remove the effect of irregular firing time, and 2) estimate the residual statics caused by inaccurate source positioning. This proposed multi-step inversion may reduce high frequency numerical noise and enhance the resolution at the zone of interest. The multi-step inversion with different starting models successfully shows the subtle velocity changes at the small cavity zone. The inversion procedure is: 1) conduct an inversion using regular sized cells, and generate an image of gross velocity structure by applying a 2-D median filter on the resulting tomogram, and 2) construct the starting velocity model by modifying the final velocity model from the first phase. The model was modified so that the zone of interest consists of small-sized grids. The final velocity model developed from the baseline survey was as a starting velocity model on the monitor inversion. Since we expected a velocity change only in the cavity zone, in the monitor inversion, we can significantly reduce the number of model parameters by fixing the model out-side the cavity zone equal to the baseline model.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.167-176
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• 2022

We designed a borehole deviation survey tool applicable for steel-cased holes, K-DEV, and developed a prototype for a depth of 500 m aiming to development of own equipment required to secure deep subsurface characterization technologies. K-DEV is equipped with sensors that provide digital output with verified high performance; moreover, it is also compatible with logging winch systems used in Korea. The K-DEV prototype has a nonmagnetic stainless steel housing with an outer diameter of 48.3 mm, which has been tested in the laboratory for water resistance up to 20 MPa and for durability by running into a 1-km deep borehole. We confirmed the operational stability and data repeatability of the prototype by constantly logging up and down to the depth of 600 m. A high-precision micro-electro-mechanical system (MEMS) gyroscope was used for the K-DEV prototype as the gyro sensor, which is crucial for azimuth determination in cased holes. Additionally, we devised an accurate trajectory survey algorithm by employing Unscented Kalman filtering and data fusion for optimization. The borehole test with K-DEV and a commercial logging tool produced sufficiently similar results. Furthermore, the issue of error accumulation due to drift over time of the MEMS gyro was successfully overcome by compensating with stationary measurements for the same attitude at the wellhead before and after logging, as demonstrated by the nearly identical result to the open hole. We believe that the methodology of K-DEV development and operational stability, as well as the data reliability of the prototype, were confirmed through these test applications.