• 시스템엔지니어링학술지
• /
• 제18권2호
• /
• pp.94-107
• /
• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• 대한통합의학회지
• /
• 제10권3호
• /
• pp.173-184
• /
• 2022

Purpose : The purpose of this study was two-fold: to identify the effect of dental hygienist's self-determination motivation on their job engagement and to analyze the moderating effect of compensation satisfaction that affect the relevance. Methods : Data were collected using a structured self-report questionnaire administered to 260 dental hygienists working in dental hospitals and clinics in Busan, South Korea. These were analyzed using IBM SPSS Statistics version 26.0 and SPSS Process Macro 3.5. A frequency analysis, including the respondents' general characteristics, frequency, percentages, and standard deviations, was performed. A regression analysis was also performed using SPSS Process Macro to verify the moderating effect of compensation satisfaction in the effect of self-determination motivation on job engagement. Results : The self-determination motivation of the dental hygienists had a statistically significant positive effect on their job engagement, which was the dependent variable. Higher intangible compensation satisfaction levels led to a stronger effect of intrinsic motivation but a weaker effect of extrinsic motivation on job engagement. Moreover, higher tangible compensation satisfaction levels strengthened the effect of intrinsic motivation on job engagement. Conclusion : Recently, the demand for oral health care has been increasing, Competition in the dental medical service market warrants, high-quality dental services based on accurate diagnosis and treatment. In this context, dental hygienists' job engagement must be improved. For this purpose, increasing the satisfaction of dental hygienists with self-determination motivation and appropriate compensation is effective. In addition, attention must be paid to the moderating effect of compensation satisfaction on the relationship between intrinsic motivation and job engagement. On the basis of the implications of this study, the results can be used as basic data for improving dental hygienists' welfare system and manpower management.

• 시스템엔지니어링학술지
• /
• 제18권1호
• /
• pp.66-83
• /
• 2022

Artificial Intelligence (AI) is to assumed to be one of next generation technology which determine technological competitiveness and strategic advantage of a certain country. By using the patent data, this study aims to have a comparative analysis of the technological competitiveness of evolving artificial intelligence at different stages of development among the five largest intellectual property offices in the world (IP5). For the analysis data, all AI technology patent data from 1956 to 2019 were utilized according to the classification system presented in the "WIPO 2019 Technology Trend: Artificial Intelligence" report published by the World Intellectual Property Organization (WIPO) in 2019. The results shows that China has already surpassed the United States in terms of the number of patent applications in the field of artificial intelligence technology. However, in the domains of the United States, Europe, Japan, and Korea, the technology competitiveness of the United States is far ahead of China. Interestingly, the rate of increase of Korea's technology competitiveness is also very fast, and it has been shown that the technology strength is ahead of China in non-Chinese domains. The significance of this study can be found in the fact that the temporal and spatial change process of technological competitiveness of significant countries in the field of artificial intelligence technology artificial intelligence was viewed as a macro-framework using the technology index (TS) the differences were compared.

• Journal of Microbiology and Biotechnology
• /
• 제33권1호
• /
• pp.106-113
• /
• 2023

The supply of microbiological risk-free water is essential to keep food safety and public hygiene. And removal, inactivation, and destruction of microorganisms in drinking water are key for ensuring safety in the food industry. Ultraviolet-C (UV-C) irradiation is an attractive method for efficient disinfection of water without generating toxicity and adversely affecting human health. In this study, the disinfection efficiencies of UV-C irradiation on Shigella flexneri (Gram negative) and Listeria monocytogenes (Gram positive) at various concentrations in drinking water were evaluated using a water purifier. Their morphological and physiological characteristics after UV-C irradiation were observed using fluorescence microscopy and flow cytometry combined with live/dead staining. UV-C irradiation (254 nm wavelength, irradiation dose: 40 mJ/cm²) at a water flow velocity of 3.4 L/min showed disinfection ability on both bacteria up to 10⁸ CFU/4 L. And flow cytometric analysis showed different physiological shift between S. flexneri and L. monocytogenes after UV-C irradiation, but no significant shift of morphology in both bacteria. In addition, each bacterium revealed different characteristics with time-course observation after UV-C irradiation: L. monocytogenes dramatically changed its physiological feature and seemed to reach maximum damage at 4 h and then recovered, whereas S. flexneri seemed to gradually die over time. This study revealed that UV-C irradiation of water purifiers is effective in disinfecting microbial contaminants in drinking water and provides basic information on bacterial features/responses after UV-C irradiation.

• 대한전자공학회논문지
• /
• 제23권1호
• /
• pp.10-19
• /
• 1986

This is the last part of the four-part describing the development of a packet-switched computer communication network named the KORNET. In this paper we describe the design and implementation of the packet assembler/dissassembler (PAD) protocol for the asynchronous channel service, and of the network management softwares. The line processing module-B(LPMB) system supporting the asynchronous line includes a PAD protocol, a packet mode DTE/DCE protocol converting to the X.25 protocol, and the asynchronous receiver/transmitter(ART) software. The network management software is operated in master central processing module(MCPM) which includes virtual circuit management (VCM) managing the user channel, the routing management and the high level protocol for communication between the network management center (NMC) and the network node processor(NNP). In this paper, the design, implementation and operation of the softwares for the above service functions will be described in detail.

• International Journal of Knowledge Content Development & Technology
• /
• 제13권1호
• /
• pp.27-41
• /
• 2023

The outbreak of the corona virus diseases (COVID-19) in the late 2019 has affected all facets of educational system including library and information services. Reference services, an important aspect of library services are not exempted from this impact. This study therefore, investigated the impact of COVI\D-19 pandemic on the use of reference services and sources by postgraduate students using Kenneth Dike Library (KDL), University of Ibadan, as a case study. Using descriptive survey of correlational type, the study adopted the use of structured questionnaire to randomly select three hundred (300) postgraduate users of reference sources and services in KDL using online survey monkey. Of the three hundred (300) copies, two hundred and twenty three (223) copies, repre- senting 74.3% were retrieved and used for analysis. Findings revealed that, in spite of COVID-19 pandemic, most postgraduate students used Current Awareness Services (203, 91.0%, mean = 3.19), Reference Sources (202, 90.5%, mean = 3.18) and On-line Public Access Catalogue (195, 87.4%, mean = 3.13); low frequency of bibliotherapy (mean=2.22), Reader's Advisory services (mean=2.30) and inter-library loan (mean=2.13) and that COVID-19 pandemic had high impact on post- graduate students' use of reference services in Kenneth Dike Library, University of Ibadan. Based on the findings, recommendations were made that library management should consider the adoption of virtual reference services (VRS) in addition to the conventional mode of refer- ence services to enhance patronage in the COVID-19 era. The library users should also be trained on how to take advantage of the COVID-19 pandemic to learn new skills in the digital space that will eventually optimize the usage of the library remotely.

• 한국ITS학회 논문지
• /
• 제22권1호
• /
• pp.219-232
• /
• 2023

모빌리티 서비스는 구축 대상 지역의 특성과 여건에 따라 변화할 필요가 있다. 이를 위해서는 해당 지역의 통행행태를 기종점 자료에 반영하여 모빌리티 패턴 및 특성 분석이 요구된다. 그러나 종래의 경우 행정 구역 기반의 존 체계를 기반으로 집계된 기종점 자료를 이용함에 따라 공간적 동질성을 담보하기 어렵기 때문에 신규 모빌리티와 같은 특수 목적성을 보이는 수단에 대한 본연의 통행 특성 분석에 한계가 있다. 이에 본 연구는 기존 존 체계에서 벗어나 데이터 기반의 클러스터링 기법 적용을 통해 설정된 집계 방식을 도출하여 기종점 통행패턴에 대한 공간적 분석을 수행한다. 제안 방법은 대중교통버스 및 택시와 같은 종래의 교통수단 뿐만 아니라 도심형 수요응답형 버스와 같은 신규 모빌리티 서비스에 대한 기종점 데이터 본연의 특징 벡터들을 기반으로 클러스터링을 하여 유사 공간적 특성을 반영한 지역 모빌리티의 이용 특성 분석을 가능하게 한다.

• 자동차안전학회지
• /
• 제14권1호
• /
• pp.26-31
• /
• 2022

Changwon City has the second highest accident rate with 79.6 according to the city bus accident rate. In fact, 250,000 people use the city bus a day in Changwon, The number of accidents is increasing gradually. In addition, a recent fire accident occurred in the engine room of a city bus (CNG) in Changwon, which has gradually expanded the public's anxiety. In the case of business vehicles, the government conducts inspections with a short inspection cycle for the purpose of periodic safety inspections, etc., but it is not in the monitoring stage. In the case of city buses, the operation records are monitored using Digital Tacho Graph (DTG). As such, driving records, methods, etc. are continuously monitored, but inspections are conducted every six months to ascertain the safety and performance of automobiles. It is difficult to identify real-time information on automobile safety. Therefore, in this study, individual automobile management solutions are presented through machine learning techniques of inspection results based on driving records or habits by linking DTG data and Vehicle Inspection Management System (VIMS) data for city buses in Changwon from 2019 to 2020.

• 분석과 대안
• /
• 제3권1호
• /
• pp.29-61
• /
• 2019

Within the discipline of International Relations (IR), the literatures on global governance (GG) and great power management (GPM) at best ignore each other, and at worst treat the other as a rival or enemy. On the one hand, the GPM literature, like both realism in all its forms, and neoliberalism, takes for granted the ongoing, disproportionate influence of the great powers in the management of the international system/society, and does not look much beyond that. On the other hand, the GG literature emphasizes the roles of smaller states, non-state actors and intergovernmental organizations (IGOs), and tends to see great powers more as part of the problem than as part of the solution. This paper argues that the rise to prominence of a non-traditional security agenda, and particularly of human security, has triggered a de facto merger of GPM and GG that the IR literature usually treated as separate and often opposed theories. We use the Ebola crisis of 2014-15 to show how an issue framed as human security brought about a multi-actor response that combined the key elements of GPM and GG. The security framing overrode many of the usual inhibitions between great powers and non-state actors in humanitarian crises, including even the involvement of great power military forces. Through examining broadly the way in which the Ebola crisis is tackled, we argue that in an age of growing human security challenges, GPM and GG are necessarily and fruitfully merging. The role of great powers in this new human security environment is moving away from the simple means and ends of traditional GPM. Now, great powers require the ability to cooperate and coordinate with multiple-level actors to make the GG/GPM nexus more effective and sustainable. In doing so they can both provide crucial resources quickly, and earn respect and status as responsible great powers. IGOs provide legitimation and coordination to the GPM/GG package, and non-state actors (NSAs) provide information, specialist knowledge and personnel, and links into public engagement. In this way, the unique features of the Ebola crisis provide a model for how the merger of GPM and GG might be taken forward on other shared-fate threats facing global international society.

• International Journal of Advanced Culture Technology
• /
• 제10권1호
• /
• pp.274-283
• /
• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.