• Transactions of the Korean hydrogen and new energy society
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• v.34 no.6
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• pp.682-688
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• 2023

In this paper, analyzes the type of failure and its effect on the hydrogen fueling nozzle used in hydrogen station. Failure of hydrogen fueling nozzle was analyzed using a qualitative risk assessment method, failure mode and effect analysis. The failure data of hydrogen fueling nozzles installed in domestic hydrogen stations are collected, and the failure types are classified, checked the main components causing the failure. Criticality analysis was derived based on frequency and severity depending on the failure mode performed. A quality function is developed by a performance test evaluation item of the hydrogen fueling nozzle, and the priority order of design characteristics is selected. Through the analysis results, the elements to improve the main components for enhancing the quality and maintenance of the hydrogen fueling nozzle were confirmed.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.435-441
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• 2023

From the mid-to-late 2010s, technology was frequently mentioned in the definition of digital transformation. In the early stages, the private sector started actively using it, and the public sector started to take it seriously. Divided into "providing value and cultural change, the main goals of digital transformation were accomplished, and the ideas of creating new values in social and industrial systems and applying digital technology appeared to be related. Digital transformation, defined as the idea of combining digital solutions to boost competitiveness and add value, necessitates social innovation and cultural shifts at the national level. In order to encourage the digital transformation of the industry, the Industrial Digital Transformation Promotion Act was passed in December 2021. This set the groundwork for a comprehensive and organized approach to facilitating the use of industrial information. We will examine the nature and extent of digital transformation in this study, as well as discover the organizations and regulations that support it. We also want to examine the essential standards and technologies needed to put the digital transformation plan into practice. Lastly, We'll make some conclusions about how this will affect public services' digital transformation.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.75-87
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• 2023

We designed to employ an Artificial Intelligence learning model to predict real estate prices and determine the reasons behind their changes, with the goal of using the results as a guide for policy. Numerous studies have already been conducted in an effort to develop a real estate price prediction model. The price prediction power of conventional time series analysis techniques (such as the widely-used ARIMA and VAR models for univariate time series analysis) and the more recently-discussed LSTM techniques is compared and analyzed in this study in order to forecast real estate prices. There is currently a period of rising volatility in the real estate market as a result of both internal and external factors. Predicting the movement of real estate values during times of heightened volatility is more challenging than it is during times of persistent general trends. According to the real estate market cycle, this study focuses on the three times of extreme volatility. It was established that the LSTM, VAR, and ARIMA models have strong predictive capacity by successfully forecasting the trading price index during a period of unusually high volatility. We explores potential synergies between the hybrid artificial intelligence learning model and the conventional statistical prediction model.

• New & Renewable Energy
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• v.20 no.2
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• pp.26-34
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• 2024

Floating offshore wind turbines (FOWTs) have been developed to overcome large water depths and leverage the abundant wind resource in deep seas. However, wind-wave misalignment can occur depending on the weather conditions, and most megawatt (MW)-class turbines are horizontal-axis wind turbines subjected to yaw errors. Therefore, the power performance and dynamic response of super-large FOWTs exposed simultaneously to these external conditions must be analyzed. In this study, several scenarios combining wind-wave misalignment and yaw error were considered. The IEA 15 MW reference FOWT (v1.1.2) and OpenFAST (v3.4.1) were used to perform numerical simulations. The results show that the power performance was affected more significantly by the yaw error; therefore, the generator power reduction and variability increased significantly. However, the dynamic response was affected more significantly by the wind-wave misalignment increased; thus, the change in the platform 6-DOF and tower loads (top and base) increased significantly. These results can be facilitate improvements to the power performance and structural integrity of FOWTs during the design process.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.286-289
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• 2007

PC 및 서버 급에서 DBMS가 아주 폭넓게 사용되어지고 있으며 그 뿐 아니라 컴퓨팅 파워가 높아짐에 따라서 임베디드 시스템에서도 DBMS가 필요해졌다. 임베디드 시스템에서 DBMS가 충분히 동작할 만큼의 성능을 발휘하게 되었고, 이에 따라 임베디드 시스템에서 동작하는 응용프로그램들도 임베디드 DBMS를 사용하게 되었다. 임베디드 시스템이 점차 플래시 메모리를 사용하는 추세에 맞추어 플래시 기반 임베디드 DBMS 기술 개발이 중요하다. 플래시 메모리의 특성에 맞춘 임베디드 DBMS를 개발하지 않으면, 결과적으로 플래시 메모리의 성능을 저하시키며, 수명도 단축시키는 결과를 초래하게 될 것이다. 특히 임베디드 환경에서는 전기 에너지 자원이 한정되어 있기 때문에 전력 소모를 줄이는 것이 관건이다. 따라서 임베디드 DBMS에서 디스크에서 정의한 비용 모델을 따르는 것은 한계가 있다. 본 논문은 임베디드 DBMS에서 전력 기반 비용 모델을 새롭게 제시하고, 디스크 기반 비용 모델과 비교하여 제시한 비용 모델과의 차이를 보인다.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.205-213
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• 2024

This study uses a large language model (LLM) to identify Aristotle's rhetorical principles (ethos, pathos, and logos) in COVID-19 information on Naver Knowledge-iN, South Korea's leading question-and-answer community. The research analyzed the differences of these rhetorical elements in the most upvoted answers with random answers. A total of 193 answer pairs were randomly selected, with 135 pairs for training and 58 for testing. These answers were then coded in line with the rhetorical principles to refine GPT 3.5-based models. The models achieved F1 scores of .88 (ethos), .81 (pathos), and .69 (logos). Subsequent analysis of 128 new answer pairs revealed that logos, particularly factual information and logical reasoning, was more frequently used in the most upvoted answers than the random answers, whereas there were no differences in ethos and pathos between the answer groups. The results suggest that health information consumers value information including logos while ethos and pathos were not associated with consumers' preference for health information. By utilizing an LLM for the analysis of persuasive content, which has been typically conducted manually with much labor and time, this study not only demonstrates the feasibility of using an LLM for latent content but also contributes to expanding the horizon in the field of AI text extraction.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1532-1537
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• 2024

Time-of-flight (TOF) PET detectors with fast-rise-time scintillators and fast-single photon time resolution silicon photomultiplier (SiPM) have been developed to improve the coincidence timing resolution (CTR) to sub-100 ps. The CTR can be further improved with an optimal bandwidth and minimized electronic noise in the readout circuit and this helps reduce the distortion of the fast signals generated from the TOF-PET detector. The purpose of this study was to develop an ultra-high frequency and fully-differential (UF-FD) readout circuit that minimizes distortion in the fast signals produced using TOF-PET detectors, and suppresses the impact of the electronic noise generated from the detector and front-end readout circuits. The proposed UF-FD readout circuit is composed of two differential amplifiers (time) and a current feedback operational amplifier (energy). The ultra-high frequency differential (7 GHz) amplifiers can reduce the common ground noise in the fully-differential mode and minimize the distortion in the fast signal. The CTR and energy resolution were measured to evaluate the performance of the UF-FD readout circuit. These results were compared with those obtained from a high-frequency and single ended readout circuit. The experiment results indicated that the UF-FD readout circuit proposed in this study could substantially improve the best achievable CTR of TOF-PET detectors.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.752-770
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• 2019

The purpose of this study is to incorporate telemarketing processes to improve telemarketing performance. For this application, we have attempted to mix the model of machine learning to extract potential customers with personalisation techniques to derive recommended products from actual contact. Most of traditional recommendation systems were mainly in ways such as collaborative filtering, which predicts items with a high likelihood of future purchase, based on existing purchase transactions or preferences for products. But, under these systems, new users or items added to the system do not have sufficient information, and generally cause problems such as a cold start that can not obtain satisfactory recommendation items. Also, indiscriminate telemarketing attempts can backfire as they increase the dissatisfaction and fatigue of customers who do not want to be contacted. To this purpose, this study presented a multi-purpose hybrid recommendation algorithm to achieve two goals: to select customers with high possibility of contact, and to recommend products to selected customers. In addition, we used subscription data from telemarketing agency that handles insurance products to derive realistic applicability of the proposed recommendation system. Our proposed recommendation system would certainly solve the cold start and scarcity problem of existing recommendation algorithm by using contents information such as customer master information and telemarketing history. Also. the model could show excellent performance not only in terms of overall performance but also in terms of the recommendation success rate of the unpopular product.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2633-2640
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• 2024

The purpose of this study was to investigate the effect of the reflector, surface treatment, and length of scintillation crystals on the performance of a time-of-flight and depth-of-interaction (TOF-DOI) PET detector with a dual-ended readout and to determine the best reflector and surface treatment. Various types of crystal arrays with three different reflectors (ESR, BaSO₄, and Toray), three different lateral surface treatments (all-polished (AP), all-roughened (AR), and partially roughened (PR, three sides polished, and one side roughened)), and two different lengths (20 and 15 mm) were fabricated. The highest light collection efficiency and best energy resolution were achieved using a crystal with a diffuse reflector (BaSO₄ for AP and Toray for AR). In contrast, the best coincidence timing resolution (CTR) was achieved using an AR crystal with a specular reflector (ESR). The best DOI resolution was achieved using an AR crystal with BaSO₄. Moreover, the results measured with the 20 mm long crystals were similar to those measured with the 15 mm long crystals. Therefore, we concluded that the dual-ended readout PET detector employing the crystal with AR lateral surface treatment and ESR was a good candidate for TOF-DOI PET because it provided excellent CTR and adequate DOI resolution.

• The Journal of Korean Academy of Prosthodontics
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• v.52 no.4
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• pp.338-345
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• 2014

Fabrication of complete denture by Jiro Abe's method was introduced that enhance the retention and stability of denture by sealing around the denture border with mucous membrane to make negative pressure at the inner surface of denture base when swallowing or occlusion. In this case, taking impression and fabricating complete denture by the Jiro Abe's method for an edentulous patient with severe mandibular alveolar bone resorption allowed us to obtain clinically enhance stability of denture and improve satisfaction of patient.