• Journal of Service Research and Studies
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• v.13 no.3
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• pp.20-38
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• 2023

Recently, car sharing has shown the most remarkable growth among sharing economy services. In the process of analyzing the intention to reuse the car sharing service, this study tried to reflect the unique characteristics of the service, which consists of non-face-to-face self-service, such as reservation, approval, handover, inspection, and return of the vehicle. Specifically, in addition to the perceived benefits and the perceived risks, we considered 'information quality' as a platform characteristic and 'self-efficacy' as a personal characteristic. To collect data, an online survey was conducted on adults with experience in car sharing, and a total of 320 responses were used for analysis. As a result of analyzing the structural equation model, it was found that information quality and self-efficacy increased the perceived benefits of services, and the higher the information quality, the higher the self-efficacy. On the other hand, the role of information quality and self-efficacy in lowering perceived risks was insignificant, and the intention to reuse services was more affected by perceived benefits than perceived risks. As a result of further analysis using Process Macro, it was found that the effect of self-efficacy on reuse intention was mediated by perceived benefits. It was analyzed that the indirect effects of information quality on reuse intention through perceived benefits or self-efficacy were all significant. These results suggest that providing timely, sufficient, and easy-to-understand information required by users on the platform improves self-efficacy and increases service reuse intention. In order to increase the number of service users, it is important for service providers not only to provide promotional activities such as offering attractive prices, but also to provide high-quality information so that users can use it more easily.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.147-159
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• 2023

This study is a study to develop a model for measurement and processing of experience data, which is emerging as a core value in quality management of medical services. In the theoretical background, a literature study was conducted on the importance of experience in medical service, measurement and processing of experience data, and realization of patient-centeredness. Based on these literature and theoretical background research results, operational definitions were performed for the following four research variables, and statistical tests were conducted. Hypothesis 1 is the effect of measuring experience data from the perspective of three factors on persona modeling, Hypothesis 2 is the effect of persona modeling on service blueprint visualization, Hypothesis 3 is the effect of service blueprint visualization on realization of patient-centeredness, and Hypothesis 4 is persona modeling This is the effect that modeling has on the realization of patient-centeredness. After data-based testing of factor analysis, reliability analysis, and correlation analysis, all four hypotheses were adopted as a result of verification using regression analysis. In conclusion, in an era where it is difficult to recognize the value of having only good medical staff and medical equipment in hospitals, it was possible to grasp the meaning that what kind of medical service experience is continuously obtained is more important to patients than the effectiveness of medical staff and medical equipment. In the era of the service economy, the core of hospital service competitiveness is providing attractive experiences, which is the real strength of hospitals, so the measurement and processing of experience data, which is the subject of this study, will have an important meaning in realizing patient-centeredness and realizing smart hospitals.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.207-212
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• 2023

Near-infrared (NIR) absorbing dyes have been applied to various applications such as optical filters, biotechnology, energy storage and conversion, coating additive, and traditionally information-storage materials. Because image sensors used in cellphones and digital cameras have sensitivity in the NIR region, the NIR cut-off filter is essential to achieving more clear images. As energy storage and conversion have been important, diverse NIR absorbing materials have been developed to extend the absorption region to the NIR region, and NIR absorbing materials-based research has proceeded to improve device performances. Adding NIR-absorbing dye with a photo-thermal effect to a self-healable coating system has been attractive for future mobility technology, and more effective self-healing properties have been reported. In this report, the chemical structures of representative NIR-absorbing dyes and state of the art research based on NIR-absorbing dyes are introduced.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.238-247
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• 2023

Liquefied petroleum gas (LPG) is an attractive fuel for ships considering its current technology and economic viability. However, safety guidelines for LPG-fueled ships are still under development, and there have been no cases of applying LPG propulsion systems to small and medium-sized ships in Korea. The purpose of this study was to perform an objective risk assessment for the first marine LPG engine system and propose safe operational standards. First, hazard and operability (HAZOP) analysis was used to divide the engine system into five nodes, and 58 hazards were identified. To compensate for the subjectivity of qualitative evaluation using HAZOP analysis, fuzzy set theory was used, and additional risk factors, such as detectability and sensitivity, were included to compare the relative weights of the risk factors using a fuzzy analytical hierarchy process. As a result, among the five risk factors, those with a major impact on risk were determined to be the frequency and severity. Finally, the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) was applied to select the risk rank more precisely by considering the weights of the risk factors. The risk level was divided into 47 groups, and the major hazard during the operation of the engine system was found through the analysis to be gas leakage during maintenance of the LPG supply line. The technique proposed can be applied to various facilities, such as LPG supply systems, and can be utilized as a standard procedure for risk assessment in developing safety standards for LPG-powered ships.

• Korean Journal of Animal Reproduction
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• v.24 no.4
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• pp.429-437
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• 2000

This study investigated the successful introduction of genes of erythropoietin (EPO) and enhanced green fluorescent protein (EGFP) in bovine embryos following nuclear transfer of bovine fetal fibroblasts (bFF), which were transfected by retrovirus vector system. Non-starved bFF were, transferred into perivitelline space of enucleated oocytes. The bFF-oocyte units were accomplished by cell to cell fusion and activated with calcium inophore and 6-dimethylaminopurine. Reconstructed embryos were co-cultured with bovine oviduct epithelial cells in CRlaa medium for 8 days. Out of 187 (EPO) and 210 (EGFP) bovine eggs reconstructed by nuclear transfer, 149 (EPO : 80.0%) and 158 (EGFP : 75.2%) embryos were cleaved, and among them 36 (EPO : 24.2%) and 35 (EGFP : 22.2%) embryos developed to the blastocyst stage. Of these blastocysts, 100% integration of EPO gene in 36 embryos was determined by PCR, and 100% expression of EGFP gene in 35 embryos was observed under the fluorescent microscope. This result indicates that bovine oocytes reconstructed by nuclear transfer of transfected bFF can successfully develop to the blastocyst stage. Furthermore, this novel procedure may be presumably an attractive method efficiently to produce the transgenic cattles.

• Journal of Applied Biological Chemistry
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• v.65 no.1
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• pp.57-62
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• 2022

Excessive activation and aggregation of platelets is a major cause of cardiovascular disease. Therefore, inhibition of platelet activation and aggregation is considered an attractive therapeutic target in preventing and treating cardiovascular diseases. In particular, strong platelet activation and aggregation by collagen secreted from the vascular endothelium are characteristic of vascular diseases. Artesunate is a compound extracted from the plant roots of Artemisia or Scopolia species, and has been reported to be effective in anticancer and Alzheimer's disease fields. However, the effect and mechanism of artesunate on collagen-induced platelet activation and aggregation have not been elucidated. In this study, the effect of artesunate on collagen-induced human platelet aggregation was confirmed and the mechanism of action of artesunate was clarified. Artesunate inhibited the phosphorylation of PI3K/Akt and Mitogen-activated protein kinases, which are phosphoproteins that are known to act in the signal transduction process when platelets are activated. In addition, artesunate decreased TXA₂ production and decreased granule secretion in platelets such as ATP and serotonin release. As a result, artesunate strongly inhibited platelet aggregation induced by collagen, a strong aggregation inducer secreted from vascular endothelial cells, with an IC₅₀ of 106.41 µM. These results suggest that artesunate has value as an effective antithrombotic agent for inhibiting the activation and aggregation of human platelets through vascular injury.

• SUVANNABHUMI
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• v.10 no.2
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• pp.181-213
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• 2018

How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

• Korean Chemical Engineering Research
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• v.61 no.3
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• pp.368-377
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• 2023

Natural Gas Combined Cycle(NGCC) recently receives lots of attention as an attractive form of power plants by virtue of its low carbon emission compared with coal-fired power plant. Nevertheless, it also needs carbon capture process since it is difficult to completely suppress carbon emission even for the NGCC. A simulation study has been performed to optimize operating condition of a carbon capture process using MEA considering low partial pressure of carbon dioxide in NGCC emission gas. For accurate optimization, overall process model including both NGCC and the carbon capture process has been built with a simulation software. Then, optimization in which various performance indices such as carbon dioxide absorption rate, solvent regeneration rate and power loss in the NGCC are simultaneously reflected has been done. Especially, it is noticeable that this study focuses on not only the amount of energy consumption but also the absorption and regeneration performance of carbon capture process. The best result considering all the performance indices has been achieved when the reboiler temperature is 120 ℃ and the reason has been analyzed.